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ton
2023-10-05 00:01:27 +07:00
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# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
# flake8: noqa
"""
Here you can find documentation on how to write your own plugin to allow
ImageIO to access a new backend. Plugins are quite object oriented, and
the relevant classes and their interaction are documented here:
.. currentmodule:: imageio
.. autosummary::
:toctree: ../_autosummary
:template: better_class.rst
imageio.core.Format
imageio.core.Request
.. note::
You can always check existing plugins if you want to see examples.
What methods to implement
-------------------------
To implement a new plugin, create a new class that inherits from
:class:`imageio.core.Format`. and implement the following functions:
.. autosummary::
:toctree: ../_autosummary
imageio.core.Format.__init__
imageio.core.Format._can_read
imageio.core.Format._can_write
Further, each format contains up to two nested classes; one for reading and
one for writing. To support reading and/or writing, the respective classes
need to be defined.
For reading, create a nested class that inherits from
``imageio.core.Format.Reader`` and that implements the following functions:
* Implement ``_open(**kwargs)`` to initialize the reader. Deal with the
user-provided keyword arguments here.
* Implement ``_close()`` to clean up.
* Implement ``_get_length()`` to provide a suitable length based on what
the user expects. Can be ``inf`` for streaming data.
* Implement ``_get_data(index)`` to return an array and a meta-data dict.
* Implement ``_get_meta_data(index)`` to return a meta-data dict. If index
is None, it should return the 'global' meta-data.
For writing, create a nested class that inherits from
``imageio.core.Format.Writer`` and implement the following functions:
* Implement ``_open(**kwargs)`` to initialize the writer. Deal with the
user-provided keyword arguments here.
* Implement ``_close()`` to clean up.
* Implement ``_append_data(im, meta)`` to add data (and meta-data).
* Implement ``_set_meta_data(meta)`` to set the global meta-data.
"""
import importlib
import os
import warnings
# v2 imports remove in v3
from .. import formats
# v2 allows formatting plugins by environment variable
# this is done here.
env_plugin_order = os.getenv("IMAGEIO_FORMAT_ORDER", None)
if env_plugin_order is not None: # pragma: no cover
warnings.warn(
"Setting plugin priority through an environment variable is"
" deprecated and will be removed in ImageIO v3. There is no"
" replacement planned for this feature. If you have an"
" active use-case for it, please reach out to us on GitHub.",
DeprecationWarning,
)
formats.sort(*os.getenv("IMAGEIO_FORMAT_ORDER", "").split(","))
# this class replaces plugin module. For details
# see https://stackoverflow.com/questions/2447353/getattr-on-a-module
def __getattr__(name):
"""Lazy-Import Plugins
This function dynamically loads plugins into the imageio.plugin
namespace upon first access. For example, the following snippet will
delay importing freeimage until the second line:
>>> import imageio
>>> imageio.plugins.freeimage.download()
"""
try:
return importlib.import_module(f"imageio.plugins.{name}")
except ImportError:
raise AttributeError(f"module '{__name__}' has no attribute '{name}'") from None

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#!/usr/bin/env python
# This file is distributed under the terms of the 2-clause BSD License.
# Copyright (c) 2017-2018, Almar Klein
"""
Python implementation of the Binary Structured Data Format (BSDF).
BSDF is a binary format for serializing structured (scientific) data.
See http://bsdf.io for more information.
This is the reference implementation, which is relatively relatively
sophisticated, providing e.g. lazy loading of blobs and streamed
reading/writing. A simpler Python implementation is available as
``bsdf_lite.py``.
This module has no dependencies and works on Python 2.7 and 3.4+.
Note: on Legacy Python (Python 2.7), non-Unicode strings are encoded as bytes.
"""
# todo: in 2020, remove six stuff, __future__ and _isidentifier
# todo: in 2020, remove 'utf-8' args to encode/decode; it's faster
from __future__ import absolute_import, division, print_function
import bz2
import hashlib
import logging
import os
import re
import struct
import sys
import types
import zlib
from io import BytesIO
logger = logging.getLogger(__name__)
# Notes on versioning: the major and minor numbers correspond to the
# BSDF format version. The major number if increased when backward
# incompatible changes are introduced. An implementation must raise an
# exception when the file being read has a higher major version. The
# minor number is increased when new backward compatible features are
# introduced. An implementation must display a warning when the file
# being read has a higher minor version. The patch version is increased
# for subsequent releases of the implementation.
VERSION = 2, 1, 2
__version__ = ".".join(str(i) for i in VERSION)
# %% The encoder and decoder implementation
# From six.py
PY3 = sys.version_info[0] >= 3
if PY3:
text_type = str
string_types = str
unicode_types = str
integer_types = int
classtypes = type
else: # pragma: no cover
logging.basicConfig() # avoid "no handlers found" error
text_type = unicode # noqa
string_types = basestring # noqa
unicode_types = unicode # noqa
integer_types = (int, long) # noqa
classtypes = type, types.ClassType
# Shorthands
spack = struct.pack
strunpack = struct.unpack
def lencode(x):
"""Encode an unsigned integer into a variable sized blob of bytes."""
# We could support 16 bit and 32 bit as well, but the gain is low, since
# 9 bytes for collections with over 250 elements is marginal anyway.
if x <= 250:
return spack("<B", x)
# elif x < 65536:
# return spack('<BH', 251, x)
# elif x < 4294967296:
# return spack('<BI', 252, x)
else:
return spack("<BQ", 253, x)
# Include len decoder for completeness; we've inlined it for performance.
def lendecode(f):
"""Decode an unsigned integer from a file."""
n = strunpack("<B", f.read(1))[0]
if n == 253:
n = strunpack("<Q", f.read(8))[0] # noqa
return n
def encode_type_id(b, ext_id):
"""Encode the type identifier, with or without extension id."""
if ext_id is not None:
bb = ext_id.encode("UTF-8")
return b.upper() + lencode(len(bb)) + bb # noqa
else:
return b # noqa
def _isidentifier(s): # pragma: no cover
"""Use of str.isidentifier() for Legacy Python, but slower."""
# http://stackoverflow.com/questions/2544972/
return (
isinstance(s, string_types)
and re.match(r"^\w+$", s, re.UNICODE)
and re.match(r"^[0-9]", s) is None
)
class BsdfSerializer(object):
"""Instances of this class represent a BSDF encoder/decoder.
It acts as a placeholder for a set of extensions and encoding/decoding
options. Use this to predefine extensions and options for high
performance encoding/decoding. For general use, see the functions
`save()`, `encode()`, `load()`, and `decode()`.
This implementation of BSDF supports streaming lists (keep adding
to a list after writing the main file), lazy loading of blobs, and
in-place editing of blobs (for streams opened with a+).
Options for encoding:
* compression (int or str): ``0`` or "no" for no compression (default),
``1`` or "zlib" for Zlib compression (same as zip files and PNG), and
``2`` or "bz2" for Bz2 compression (more compact but slower writing).
Note that some BSDF implementations (e.g. JavaScript) may not support
compression.
* use_checksum (bool): whether to include a checksum with binary blobs.
* float64 (bool): Whether to write floats as 64 bit (default) or 32 bit.
Options for decoding:
* load_streaming (bool): if True, and the final object in the structure was
a stream, will make it available as a stream in the decoded object.
* lazy_blob (bool): if True, bytes are represented as Blob objects that can
be used to lazily access the data, and also overwrite the data if the
file is open in a+ mode.
"""
def __init__(self, extensions=None, **options):
self._extensions = {} # name -> extension
self._extensions_by_cls = {} # cls -> (name, extension.encode)
if extensions is None:
extensions = standard_extensions
for extension in extensions:
self.add_extension(extension)
self._parse_options(**options)
def _parse_options(
self,
compression=0,
use_checksum=False,
float64=True,
load_streaming=False,
lazy_blob=False,
):
# Validate compression
if isinstance(compression, string_types):
m = {"no": 0, "zlib": 1, "bz2": 2}
compression = m.get(compression.lower(), compression)
if compression not in (0, 1, 2):
raise TypeError("Compression must be 0, 1, 2, " '"no", "zlib", or "bz2"')
self._compression = compression
# Other encoding args
self._use_checksum = bool(use_checksum)
self._float64 = bool(float64)
# Decoding args
self._load_streaming = bool(load_streaming)
self._lazy_blob = bool(lazy_blob)
def add_extension(self, extension_class):
"""Add an extension to this serializer instance, which must be
a subclass of Extension. Can be used as a decorator.
"""
# Check class
if not (
isinstance(extension_class, type) and issubclass(extension_class, Extension)
):
raise TypeError("add_extension() expects a Extension class.")
extension = extension_class()
# Get name
name = extension.name
if not isinstance(name, str):
raise TypeError("Extension name must be str.")
if len(name) == 0 or len(name) > 250:
raise NameError(
"Extension names must be nonempty and shorter " "than 251 chars."
)
if name in self._extensions:
logger.warning(
'BSDF warning: overwriting extension "%s", '
"consider removing first" % name
)
# Get classes
cls = extension.cls
if not cls:
clss = []
elif isinstance(cls, (tuple, list)):
clss = cls
else:
clss = [cls]
for cls in clss:
if not isinstance(cls, classtypes):
raise TypeError("Extension classes must be types.")
# Store
for cls in clss:
self._extensions_by_cls[cls] = name, extension.encode
self._extensions[name] = extension
return extension_class
def remove_extension(self, name):
"""Remove a converted by its unique name."""
if not isinstance(name, str):
raise TypeError("Extension name must be str.")
if name in self._extensions:
self._extensions.pop(name)
for cls in list(self._extensions_by_cls.keys()):
if self._extensions_by_cls[cls][0] == name:
self._extensions_by_cls.pop(cls)
def _encode(self, f, value, streams, ext_id):
"""Main encoder function."""
x = encode_type_id
if value is None:
f.write(x(b"v", ext_id)) # V for void
elif value is True:
f.write(x(b"y", ext_id)) # Y for yes
elif value is False:
f.write(x(b"n", ext_id)) # N for no
elif isinstance(value, integer_types):
if -32768 <= value <= 32767:
f.write(x(b"h", ext_id) + spack("h", value)) # H for ...
else:
f.write(x(b"i", ext_id) + spack("<q", value)) # I for int
elif isinstance(value, float):
if self._float64:
f.write(x(b"d", ext_id) + spack("<d", value)) # D for double
else:
f.write(x(b"f", ext_id) + spack("<f", value)) # f for float
elif isinstance(value, unicode_types):
bb = value.encode("UTF-8")
f.write(x(b"s", ext_id) + lencode(len(bb))) # S for str
f.write(bb)
elif isinstance(value, (list, tuple)):
f.write(x(b"l", ext_id) + lencode(len(value))) # L for list
for v in value:
self._encode(f, v, streams, None)
elif isinstance(value, dict):
f.write(x(b"m", ext_id) + lencode(len(value))) # M for mapping
for key, v in value.items():
if PY3:
assert key.isidentifier() # faster
else: # pragma: no cover
assert _isidentifier(key)
# yield ' ' * indent + key
name_b = key.encode("UTF-8")
f.write(lencode(len(name_b)))
f.write(name_b)
self._encode(f, v, streams, None)
elif isinstance(value, bytes):
f.write(x(b"b", ext_id)) # B for blob
blob = Blob(
value, compression=self._compression, use_checksum=self._use_checksum
)
blob._to_file(f) # noqa
elif isinstance(value, Blob):
f.write(x(b"b", ext_id)) # B for blob
value._to_file(f) # noqa
elif isinstance(value, BaseStream):
# Initialize the stream
if value.mode != "w":
raise ValueError("Cannot serialize a read-mode stream.")
elif isinstance(value, ListStream):
f.write(x(b"l", ext_id) + spack("<BQ", 255, 0)) # L for list
else:
raise TypeError("Only ListStream is supported")
# Mark this as *the* stream, and activate the stream.
# The save() function verifies this is the last written object.
if len(streams) > 0:
raise ValueError("Can only have one stream per file.")
streams.append(value)
value._activate(f, self._encode, self._decode) # noqa
else:
if ext_id is not None:
raise ValueError(
"Extension %s wronfully encodes object to another "
"extension object (though it may encode to a list/dict "
"that contains other extension objects)." % ext_id
)
# Try if the value is of a type we know
ex = self._extensions_by_cls.get(value.__class__, None)
# Maybe its a subclass of a type we know
if ex is None:
for name, c in self._extensions.items():
if c.match(self, value):
ex = name, c.encode
break
else:
ex = None
# Success or fail
if ex is not None:
ext_id2, extension_encode = ex
self._encode(f, extension_encode(self, value), streams, ext_id2)
else:
t = (
"Class %r is not a valid base BSDF type, nor is it "
"handled by an extension."
)
raise TypeError(t % value.__class__.__name__)
def _decode(self, f):
"""Main decoder function."""
# Get value
char = f.read(1)
c = char.lower()
# Conversion (uppercase value identifiers signify converted values)
if not char:
raise EOFError()
elif char != c:
n = strunpack("<B", f.read(1))[0]
# if n == 253: n = strunpack('<Q', f.read(8))[0] # noqa - noneed
ext_id = f.read(n).decode("UTF-8")
else:
ext_id = None
if c == b"v":
value = None
elif c == b"y":
value = True
elif c == b"n":
value = False
elif c == b"h":
value = strunpack("<h", f.read(2))[0]
elif c == b"i":
value = strunpack("<q", f.read(8))[0]
elif c == b"f":
value = strunpack("<f", f.read(4))[0]
elif c == b"d":
value = strunpack("<d", f.read(8))[0]
elif c == b"s":
n_s = strunpack("<B", f.read(1))[0]
if n_s == 253:
n_s = strunpack("<Q", f.read(8))[0] # noqa
value = f.read(n_s).decode("UTF-8")
elif c == b"l":
n = strunpack("<B", f.read(1))[0]
if n >= 254:
# Streaming
closed = n == 254
n = strunpack("<Q", f.read(8))[0]
if self._load_streaming:
value = ListStream(n if closed else "r")
value._activate(f, self._encode, self._decode) # noqa
elif closed:
value = [self._decode(f) for i in range(n)]
else:
value = []
try:
while True:
value.append(self._decode(f))
except EOFError:
pass
else:
# Normal
if n == 253:
n = strunpack("<Q", f.read(8))[0] # noqa
value = [self._decode(f) for i in range(n)]
elif c == b"m":
value = dict()
n = strunpack("<B", f.read(1))[0]
if n == 253:
n = strunpack("<Q", f.read(8))[0] # noqa
for i in range(n):
n_name = strunpack("<B", f.read(1))[0]
if n_name == 253:
n_name = strunpack("<Q", f.read(8))[0] # noqa
assert n_name > 0
name = f.read(n_name).decode("UTF-8")
value[name] = self._decode(f)
elif c == b"b":
if self._lazy_blob:
value = Blob((f, True))
else:
blob = Blob((f, False))
value = blob.get_bytes()
else:
raise RuntimeError("Parse error %r" % char)
# Convert value if we have an extension for it
if ext_id is not None:
extension = self._extensions.get(ext_id, None)
if extension is not None:
value = extension.decode(self, value)
else:
logger.warning("BSDF warning: no extension found for %r" % ext_id)
return value
def encode(self, ob):
"""Save the given object to bytes."""
f = BytesIO()
self.save(f, ob)
return f.getvalue()
def save(self, f, ob):
"""Write the given object to the given file object."""
f.write(b"BSDF")
f.write(struct.pack("<B", VERSION[0]))
f.write(struct.pack("<B", VERSION[1]))
# Prepare streaming, this list will have 0 or 1 item at the end
streams = []
self._encode(f, ob, streams, None)
# Verify that stream object was at the end, and add initial elements
if len(streams) > 0:
stream = streams[0]
if stream._start_pos != f.tell():
raise ValueError(
"The stream object must be " "the last object to be encoded."
)
def decode(self, bb):
"""Load the data structure that is BSDF-encoded in the given bytes."""
f = BytesIO(bb)
return self.load(f)
def load(self, f):
"""Load a BSDF-encoded object from the given file object."""
# Check magic string
f4 = f.read(4)
if f4 != b"BSDF":
raise RuntimeError("This does not look like a BSDF file: %r" % f4)
# Check version
major_version = strunpack("<B", f.read(1))[0]
minor_version = strunpack("<B", f.read(1))[0]
file_version = "%i.%i" % (major_version, minor_version)
if major_version != VERSION[0]: # major version should be 2
t = (
"Reading file with different major version (%s) "
"from the implementation (%s)."
)
raise RuntimeError(t % (__version__, file_version))
if minor_version > VERSION[1]: # minor should be < ours
t = (
"BSDF warning: reading file with higher minor version (%s) "
"than the implementation (%s)."
)
logger.warning(t % (__version__, file_version))
return self._decode(f)
# %% Streaming and blob-files
class BaseStream(object):
"""Base class for streams."""
def __init__(self, mode="w"):
self._i = 0
self._count = -1
if isinstance(mode, int):
self._count = mode
mode = "r"
elif mode == "w":
self._count = 0
assert mode in ("r", "w")
self._mode = mode
self._f = None
self._start_pos = 0
def _activate(self, file, encode_func, decode_func):
if self._f is not None: # Associated with another write
raise IOError("Stream object cannot be activated twice?")
self._f = file
self._start_pos = self._f.tell()
self._encode = encode_func
self._decode = decode_func
@property
def mode(self):
"""The mode of this stream: 'r' or 'w'."""
return self._mode
class ListStream(BaseStream):
"""A streamable list object used for writing or reading.
In read mode, it can also be iterated over.
"""
@property
def count(self):
"""The number of elements in the stream (can be -1 for unclosed
streams in read-mode).
"""
return self._count
@property
def index(self):
"""The current index of the element to read/write."""
return self._i
def append(self, item):
"""Append an item to the streaming list. The object is immediately
serialized and written to the underlying file.
"""
# if self._mode != 'w':
# raise IOError('This ListStream is not in write mode.')
if self._count != self._i:
raise IOError("Can only append items to the end of the stream.")
if self._f is None:
raise IOError("List stream is not associated with a file yet.")
if self._f.closed:
raise IOError("Cannot stream to a close file.")
self._encode(self._f, item, [self], None)
self._i += 1
self._count += 1
def close(self, unstream=False):
"""Close the stream, marking the number of written elements. New
elements may still be appended, but they won't be read during decoding.
If ``unstream`` is False, the stream is turned into a regular list
(not streaming).
"""
# if self._mode != 'w':
# raise IOError('This ListStream is not in write mode.')
if self._count != self._i:
raise IOError("Can only close when at the end of the stream.")
if self._f is None:
raise IOError("ListStream is not associated with a file yet.")
if self._f.closed:
raise IOError("Cannot close a stream on a close file.")
i = self._f.tell()
self._f.seek(self._start_pos - 8 - 1)
self._f.write(spack("<B", 253 if unstream else 254))
self._f.write(spack("<Q", self._count))
self._f.seek(i)
def next(self):
"""Read and return the next element in the streaming list.
Raises StopIteration if the stream is exhausted.
"""
if self._mode != "r":
raise IOError("This ListStream in not in read mode.")
if self._f is None:
raise IOError("ListStream is not associated with a file yet.")
if getattr(self._f, "closed", None): # not present on 2.7 http req :/
raise IOError("Cannot read a stream from a close file.")
if self._count >= 0:
if self._i >= self._count:
raise StopIteration()
self._i += 1
return self._decode(self._f)
else:
# This raises EOFError at some point.
try:
res = self._decode(self._f)
self._i += 1
return res
except EOFError:
self._count = self._i
raise StopIteration()
def __iter__(self):
if self._mode != "r":
raise IOError("Cannot iterate: ListStream in not in read mode.")
return self
def __next__(self):
return self.next()
class Blob(object):
"""Object to represent a blob of bytes. When used to write a BSDF file,
it's a wrapper for bytes plus properties such as what compression to apply.
When used to read a BSDF file, it can be used to read the data lazily, and
also modify the data if reading in 'r+' mode and the blob isn't compressed.
"""
# For now, this does not allow re-sizing blobs (within the allocated size)
# but this can be added later.
def __init__(self, bb, compression=0, extra_size=0, use_checksum=False):
if isinstance(bb, bytes):
self._f = None
self.compressed = self._from_bytes(bb, compression)
self.compression = compression
self.allocated_size = self.used_size + extra_size
self.use_checksum = use_checksum
elif isinstance(bb, tuple) and len(bb) == 2 and hasattr(bb[0], "read"):
self._f, allow_seek = bb
self.compressed = None
self._from_file(self._f, allow_seek)
self._modified = False
else:
raise TypeError("Wrong argument to create Blob.")
def _from_bytes(self, value, compression):
"""When used to wrap bytes in a blob."""
if compression == 0:
compressed = value
elif compression == 1:
compressed = zlib.compress(value, 9)
elif compression == 2:
compressed = bz2.compress(value, 9)
else: # pragma: no cover
assert False, "Unknown compression identifier"
self.data_size = len(value)
self.used_size = len(compressed)
return compressed
def _to_file(self, f):
"""Private friend method called by encoder to write a blob to a file."""
# Write sizes - write at least in a size that allows resizing
if self.allocated_size <= 250 and self.compression == 0:
f.write(spack("<B", self.allocated_size))
f.write(spack("<B", self.used_size))
f.write(lencode(self.data_size))
else:
f.write(spack("<BQ", 253, self.allocated_size))
f.write(spack("<BQ", 253, self.used_size))
f.write(spack("<BQ", 253, self.data_size))
# Compression and checksum
f.write(spack("B", self.compression))
if self.use_checksum:
f.write(b"\xff" + hashlib.md5(self.compressed).digest())
else:
f.write(b"\x00")
# Byte alignment (only necessary for uncompressed data)
if self.compression == 0:
alignment = 8 - (f.tell() + 1) % 8 # +1 for the byte to write
f.write(spack("<B", alignment)) # padding for byte alignment
f.write(b"\x00" * alignment)
else:
f.write(spack("<B", 0))
# The actual data and extra space
f.write(self.compressed)
f.write(b"\x00" * (self.allocated_size - self.used_size))
def _from_file(self, f, allow_seek):
"""Used when a blob is read by the decoder."""
# Read blob header data (5 to 42 bytes)
# Size
allocated_size = strunpack("<B", f.read(1))[0]
if allocated_size == 253:
allocated_size = strunpack("<Q", f.read(8))[0] # noqa
used_size = strunpack("<B", f.read(1))[0]
if used_size == 253:
used_size = strunpack("<Q", f.read(8))[0] # noqa
data_size = strunpack("<B", f.read(1))[0]
if data_size == 253:
data_size = strunpack("<Q", f.read(8))[0] # noqa
# Compression and checksum
compression = strunpack("<B", f.read(1))[0]
has_checksum = strunpack("<B", f.read(1))[0]
if has_checksum:
checksum = f.read(16)
# Skip alignment
alignment = strunpack("<B", f.read(1))[0]
f.read(alignment)
# Get or skip data + extra space
if allow_seek:
self.start_pos = f.tell()
self.end_pos = self.start_pos + used_size
f.seek(self.start_pos + allocated_size)
else:
self.start_pos = None
self.end_pos = None
self.compressed = f.read(used_size)
f.read(allocated_size - used_size)
# Store info
self.alignment = alignment
self.compression = compression
self.use_checksum = checksum if has_checksum else None
self.used_size = used_size
self.allocated_size = allocated_size
self.data_size = data_size
def seek(self, p):
"""Seek to the given position (relative to the blob start)."""
if self._f is None:
raise RuntimeError(
"Cannot seek in a blob " "that is not created by the BSDF decoder."
)
if p < 0:
p = self.allocated_size + p
if p < 0 or p > self.allocated_size:
raise IOError("Seek beyond blob boundaries.")
self._f.seek(self.start_pos + p)
def tell(self):
"""Get the current file pointer position (relative to the blob start)."""
if self._f is None:
raise RuntimeError(
"Cannot tell in a blob " "that is not created by the BSDF decoder."
)
return self._f.tell() - self.start_pos
def write(self, bb):
"""Write bytes to the blob."""
if self._f is None:
raise RuntimeError(
"Cannot write in a blob " "that is not created by the BSDF decoder."
)
if self.compression:
raise IOError("Cannot arbitrarily write in compressed blob.")
if self._f.tell() + len(bb) > self.end_pos:
raise IOError("Write beyond blob boundaries.")
self._modified = True
return self._f.write(bb)
def read(self, n):
"""Read n bytes from the blob."""
if self._f is None:
raise RuntimeError(
"Cannot read in a blob " "that is not created by the BSDF decoder."
)
if self.compression:
raise IOError("Cannot arbitrarily read in compressed blob.")
if self._f.tell() + n > self.end_pos:
raise IOError("Read beyond blob boundaries.")
return self._f.read(n)
def get_bytes(self):
"""Get the contents of the blob as bytes."""
if self.compressed is not None:
compressed = self.compressed
else:
i = self._f.tell()
self.seek(0)
compressed = self._f.read(self.used_size)
self._f.seek(i)
if self.compression == 0:
value = compressed
elif self.compression == 1:
value = zlib.decompress(compressed)
elif self.compression == 2:
value = bz2.decompress(compressed)
else: # pragma: no cover
raise RuntimeError("Invalid compression %i" % self.compression)
return value
def update_checksum(self):
"""Reset the blob's checksum if present. Call this after modifying
the data.
"""
# or ... should the presence of a checksum mean that data is proteced?
if self.use_checksum and self._modified:
self.seek(0)
compressed = self._f.read(self.used_size)
self._f.seek(self.start_pos - self.alignment - 1 - 16)
self._f.write(hashlib.md5(compressed).digest())
# %% High-level functions
def encode(ob, extensions=None, **options):
"""Save (BSDF-encode) the given object to bytes.
See `BSDFSerializer` for details on extensions and options.
"""
s = BsdfSerializer(extensions, **options)
return s.encode(ob)
def save(f, ob, extensions=None, **options):
"""Save (BSDF-encode) the given object to the given filename or
file object. See` BSDFSerializer` for details on extensions and options.
"""
s = BsdfSerializer(extensions, **options)
if isinstance(f, string_types):
with open(f, "wb") as fp:
return s.save(fp, ob)
else:
return s.save(f, ob)
def decode(bb, extensions=None, **options):
"""Load a (BSDF-encoded) structure from bytes.
See `BSDFSerializer` for details on extensions and options.
"""
s = BsdfSerializer(extensions, **options)
return s.decode(bb)
def load(f, extensions=None, **options):
"""Load a (BSDF-encoded) structure from the given filename or file object.
See `BSDFSerializer` for details on extensions and options.
"""
s = BsdfSerializer(extensions, **options)
if isinstance(f, string_types):
if f.startswith(("~/", "~\\")): # pragma: no cover
f = os.path.expanduser(f)
with open(f, "rb") as fp:
return s.load(fp)
else:
return s.load(f)
# Aliases for json compat
loads = decode
dumps = encode
# %% Standard extensions
# Defining extensions as a dict would be more compact and feel lighter, but
# that would only allow lambdas, which is too limiting, e.g. for ndarray
# extension.
class Extension(object):
"""Base class to implement BSDF extensions for special data types.
Extension classes are provided to the BSDF serializer, which
instantiates the class. That way, the extension can be somewhat dynamic:
e.g. the NDArrayExtension exposes the ndarray class only when numpy
is imported.
A extension instance must have two attributes. These can be attribiutes of
the class, or of the instance set in ``__init__()``:
* name (str): the name by which encoded values will be identified.
* cls (type): the type (or list of types) to match values with.
This is optional, but it makes the encoder select extensions faster.
Further, it needs 3 methods:
* `match(serializer, value) -> bool`: return whether the extension can
convert the given value. The default is ``isinstance(value, self.cls)``.
* `encode(serializer, value) -> encoded_value`: the function to encode a
value to more basic data types.
* `decode(serializer, encoded_value) -> value`: the function to decode an
encoded value back to its intended representation.
"""
name = ""
cls = ()
def __repr__(self):
return "<BSDF extension %r at 0x%s>" % (self.name, hex(id(self)))
def match(self, s, v):
return isinstance(v, self.cls)
def encode(self, s, v):
raise NotImplementedError()
def decode(self, s, v):
raise NotImplementedError()
class ComplexExtension(Extension):
name = "c"
cls = complex
def encode(self, s, v):
return (v.real, v.imag)
def decode(self, s, v):
return complex(v[0], v[1])
class NDArrayExtension(Extension):
name = "ndarray"
def __init__(self):
if "numpy" in sys.modules:
import numpy as np
self.cls = np.ndarray
def match(self, s, v): # pragma: no cover - e.g. work for nd arrays in JS
return hasattr(v, "shape") and hasattr(v, "dtype") and hasattr(v, "tobytes")
def encode(self, s, v):
return dict(shape=v.shape, dtype=text_type(v.dtype), data=v.tobytes())
def decode(self, s, v):
try:
import numpy as np
except ImportError: # pragma: no cover
return v
a = np.frombuffer(v["data"], dtype=v["dtype"])
a.shape = v["shape"]
return a
standard_extensions = [ComplexExtension, NDArrayExtension]
if __name__ == "__main__":
# Invoke CLI
import bsdf_cli
bsdf_cli.main()

View File

@@ -1,923 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
""" Plugin for reading DICOM files.
"""
# todo: Use pydicom:
# * Note: is not py3k ready yet
# * Allow reading the full meta info
# I think we can more or less replace the SimpleDicomReader with a
# pydicom.Dataset For series, only ned to read the full info from one
# file: speed still high
# * Perhaps allow writing?
import sys
import os
import struct
import logging
import numpy as np
logger = logging.getLogger(__name__)
# Determine endianity of system
sys_is_little_endian = sys.byteorder == "little"
# Define a dictionary that contains the tags that we would like to know
MINIDICT = {
(0x7FE0, 0x0010): ("PixelData", "OB"),
# Date and time
(0x0008, 0x0020): ("StudyDate", "DA"),
(0x0008, 0x0021): ("SeriesDate", "DA"),
(0x0008, 0x0022): ("AcquisitionDate", "DA"),
(0x0008, 0x0023): ("ContentDate", "DA"),
(0x0008, 0x0030): ("StudyTime", "TM"),
(0x0008, 0x0031): ("SeriesTime", "TM"),
(0x0008, 0x0032): ("AcquisitionTime", "TM"),
(0x0008, 0x0033): ("ContentTime", "TM"),
# With what, where, by whom?
(0x0008, 0x0060): ("Modality", "CS"),
(0x0008, 0x0070): ("Manufacturer", "LO"),
(0x0008, 0x0080): ("InstitutionName", "LO"),
# Descriptions
(0x0008, 0x1030): ("StudyDescription", "LO"),
(0x0008, 0x103E): ("SeriesDescription", "LO"),
# UID's
(0x0008, 0x0016): ("SOPClassUID", "UI"),
(0x0008, 0x0018): ("SOPInstanceUID", "UI"),
(0x0020, 0x000D): ("StudyInstanceUID", "UI"),
(0x0020, 0x000E): ("SeriesInstanceUID", "UI"),
(0x0008, 0x0117): ("ContextUID", "UI"),
# Numbers
(0x0020, 0x0011): ("SeriesNumber", "IS"),
(0x0020, 0x0012): ("AcquisitionNumber", "IS"),
(0x0020, 0x0013): ("InstanceNumber", "IS"),
(0x0020, 0x0014): ("IsotopeNumber", "IS"),
(0x0020, 0x0015): ("PhaseNumber", "IS"),
(0x0020, 0x0016): ("IntervalNumber", "IS"),
(0x0020, 0x0017): ("TimeSlotNumber", "IS"),
(0x0020, 0x0018): ("AngleNumber", "IS"),
(0x0020, 0x0019): ("ItemNumber", "IS"),
(0x0020, 0x0020): ("PatientOrientation", "CS"),
(0x0020, 0x0030): ("ImagePosition", "CS"),
(0x0020, 0x0032): ("ImagePositionPatient", "CS"),
(0x0020, 0x0035): ("ImageOrientation", "CS"),
(0x0020, 0x0037): ("ImageOrientationPatient", "CS"),
# Patient information
(0x0010, 0x0010): ("PatientName", "PN"),
(0x0010, 0x0020): ("PatientID", "LO"),
(0x0010, 0x0030): ("PatientBirthDate", "DA"),
(0x0010, 0x0040): ("PatientSex", "CS"),
(0x0010, 0x1010): ("PatientAge", "AS"),
(0x0010, 0x1020): ("PatientSize", "DS"),
(0x0010, 0x1030): ("PatientWeight", "DS"),
# Image specific (required to construct numpy array)
(0x0028, 0x0002): ("SamplesPerPixel", "US"),
(0x0028, 0x0008): ("NumberOfFrames", "IS"),
(0x0028, 0x0100): ("BitsAllocated", "US"),
(0x0028, 0x0101): ("BitsStored", "US"),
(0x0028, 0x0102): ("HighBit", "US"),
(0x0028, 0x0103): ("PixelRepresentation", "US"),
(0x0028, 0x0010): ("Rows", "US"),
(0x0028, 0x0011): ("Columns", "US"),
(0x0028, 0x1052): ("RescaleIntercept", "DS"),
(0x0028, 0x1053): ("RescaleSlope", "DS"),
# Image specific (for the user)
(0x0028, 0x0030): ("PixelSpacing", "DS"),
(0x0018, 0x0088): ("SliceSpacing", "DS"),
}
# Define some special tags:
# See PS 3.5-2008 section 7.5 (p.40)
ItemTag = (0xFFFE, 0xE000) # start of Sequence Item
ItemDelimiterTag = (0xFFFE, 0xE00D) # end of Sequence Item
SequenceDelimiterTag = (0xFFFE, 0xE0DD) # end of Sequence of undefined length
# Define set of groups that we're interested in (so we can quickly skip others)
GROUPS = set([key[0] for key in MINIDICT.keys()])
VRS = set([val[1] for val in MINIDICT.values()])
class NotADicomFile(Exception):
pass
class CompressedDicom(RuntimeError):
pass
class SimpleDicomReader(object):
"""
This class provides reading of pixel data from DICOM files. It is
focussed on getting the pixel data, not the meta info.
To use, first create an instance of this class (giving it
a file object or filename). Next use the info attribute to
get a dict of the meta data. The loading of pixel data is
deferred until get_numpy_array() is called.
Comparison with Pydicom
-----------------------
This code focusses on getting the pixel data out, which allows some
shortcuts, resulting in the code being much smaller.
Since the processing of data elements is much cheaper (it skips a lot
of tags), this code is about 3x faster than pydicom (except for the
deflated DICOM files).
This class does borrow some code (and ideas) from the pydicom
project, and (to the best of our knowledge) has the same limitations
as pydicom with regard to the type of files that it can handle.
Limitations
-----------
For more advanced DICOM processing, please check out pydicom.
* Only a predefined subset of data elements (meta information) is read.
* This is a reader; it can not write DICOM files.
* (just like pydicom) it can handle none of the compressed DICOM
formats except for "Deflated Explicit VR Little Endian"
(1.2.840.10008.1.2.1.99).
"""
def __init__(self, file):
# Open file if filename given
if isinstance(file, str):
self._filename = file
self._file = open(file, "rb")
else:
self._filename = "<unknown file>"
self._file = file
# Init variable to store position and size of pixel data
self._pixel_data_loc = None
# The meta header is always explicit and little endian
self.is_implicit_VR = False
self.is_little_endian = True
self._unpackPrefix = "<"
# Dict to store data elements of interest in
self._info = {}
# VR Conversion
self._converters = {
# Numbers
"US": lambda x: self._unpack("H", x),
"UL": lambda x: self._unpack("L", x),
# Numbers encoded as strings
"DS": lambda x: self._splitValues(x, float, "\\"),
"IS": lambda x: self._splitValues(x, int, "\\"),
# strings
"AS": lambda x: x.decode("ascii", "ignore").strip("\x00"),
"DA": lambda x: x.decode("ascii", "ignore").strip("\x00"),
"TM": lambda x: x.decode("ascii", "ignore").strip("\x00"),
"UI": lambda x: x.decode("ascii", "ignore").strip("\x00"),
"LO": lambda x: x.decode("utf-8", "ignore").strip("\x00").rstrip(),
"CS": lambda x: self._splitValues(x, float, "\\"),
"PN": lambda x: x.decode("utf-8", "ignore").strip("\x00").rstrip(),
}
# Initiate reading
self._read()
@property
def info(self):
return self._info
def _splitValues(self, x, type, splitter):
s = x.decode("ascii").strip("\x00")
try:
if splitter in s:
return tuple([type(v) for v in s.split(splitter) if v.strip()])
else:
return type(s)
except ValueError:
return s
def _unpack(self, fmt, value):
return struct.unpack(self._unpackPrefix + fmt, value)[0]
# Really only so we need minimal changes to _pixel_data_numpy
def __iter__(self):
return iter(self._info.keys())
def __getattr__(self, key):
info = object.__getattribute__(self, "_info")
if key in info:
return info[key]
return object.__getattribute__(self, key) # pragma: no cover
def _read(self):
f = self._file
# Check prefix after peamble
f.seek(128)
if f.read(4) != b"DICM":
raise NotADicomFile("Not a valid DICOM file.")
# Read
self._read_header()
self._read_data_elements()
self._get_shape_and_sampling()
# Close if done, reopen if necessary to read pixel data
if os.path.isfile(self._filename):
self._file.close()
self._file = None
def _readDataElement(self):
f = self._file
# Get group and element
group = self._unpack("H", f.read(2))
element = self._unpack("H", f.read(2))
# Get value length
if self.is_implicit_VR:
vl = self._unpack("I", f.read(4))
else:
vr = f.read(2)
if vr in (b"OB", b"OW", b"SQ", b"UN"):
reserved = f.read(2) # noqa
vl = self._unpack("I", f.read(4))
else:
vl = self._unpack("H", f.read(2))
# Get value
if group == 0x7FE0 and element == 0x0010:
here = f.tell()
self._pixel_data_loc = here, vl
f.seek(here + vl)
return group, element, b"Deferred loading of pixel data"
else:
if vl == 0xFFFFFFFF:
value = self._read_undefined_length_value()
else:
value = f.read(vl)
return group, element, value
def _read_undefined_length_value(self, read_size=128):
"""Copied (in compacted form) from PyDicom
Copyright Darcy Mason.
"""
fp = self._file
# data_start = fp.tell()
search_rewind = 3
bytes_to_find = struct.pack(
self._unpackPrefix + "HH", SequenceDelimiterTag[0], SequenceDelimiterTag[1]
)
found = False
value_chunks = []
while not found:
chunk_start = fp.tell()
bytes_read = fp.read(read_size)
if len(bytes_read) < read_size:
# try again,
# if still don't get required amount, this is last block
new_bytes = fp.read(read_size - len(bytes_read))
bytes_read += new_bytes
if len(bytes_read) < read_size:
raise EOFError(
"End of file reached before sequence " "delimiter found."
)
index = bytes_read.find(bytes_to_find)
if index != -1:
found = True
value_chunks.append(bytes_read[:index])
fp.seek(chunk_start + index + 4) # rewind to end of delimiter
length = fp.read(4)
if length != b"\0\0\0\0":
logger.warning(
"Expected 4 zero bytes after undefined length " "delimiter"
)
else:
fp.seek(fp.tell() - search_rewind) # rewind a bit
# accumulate the bytes read (not including the rewind)
value_chunks.append(bytes_read[:-search_rewind])
# if get here then have found the byte string
return b"".join(value_chunks)
def _read_header(self):
f = self._file
TransferSyntaxUID = None
# Read all elements, store transferSyntax when we encounter it
try:
while True:
fp_save = f.tell()
# Get element
group, element, value = self._readDataElement()
if group == 0x02:
if group == 0x02 and element == 0x10:
TransferSyntaxUID = value.decode("ascii").strip("\x00")
else:
# No more group 2: rewind and break
# (don't trust group length)
f.seek(fp_save)
break
except (EOFError, struct.error): # pragma: no cover
raise RuntimeError("End of file reached while still in header.")
# Handle transfer syntax
self._info["TransferSyntaxUID"] = TransferSyntaxUID
#
if TransferSyntaxUID is None:
# Assume ExplicitVRLittleEndian
is_implicit_VR, is_little_endian = False, True
elif TransferSyntaxUID == "1.2.840.10008.1.2.1":
# ExplicitVRLittleEndian
is_implicit_VR, is_little_endian = False, True
elif TransferSyntaxUID == "1.2.840.10008.1.2.2":
# ExplicitVRBigEndian
is_implicit_VR, is_little_endian = False, False
elif TransferSyntaxUID == "1.2.840.10008.1.2":
# implicit VR little endian
is_implicit_VR, is_little_endian = True, True
elif TransferSyntaxUID == "1.2.840.10008.1.2.1.99":
# DeflatedExplicitVRLittleEndian:
is_implicit_VR, is_little_endian = False, True
self._inflate()
else:
# http://www.dicomlibrary.com/dicom/transfer-syntax/
t, extra_info = TransferSyntaxUID, ""
if "1.2.840.10008.1.2.4.50" <= t < "1.2.840.10008.1.2.4.99":
extra_info = " (JPEG)"
if "1.2.840.10008.1.2.4.90" <= t < "1.2.840.10008.1.2.4.99":
extra_info = " (JPEG 2000)"
if t == "1.2.840.10008.1.2.5":
extra_info = " (RLE)"
if t == "1.2.840.10008.1.2.6.1":
extra_info = " (RFC 2557)"
raise CompressedDicom(
"The dicom reader can only read files with "
"uncompressed image data - not %r%s. You "
"can try using dcmtk or gdcm to convert the "
"image." % (t, extra_info)
)
# From hereon, use implicit/explicit big/little endian
self.is_implicit_VR = is_implicit_VR
self.is_little_endian = is_little_endian
self._unpackPrefix = "><"[is_little_endian]
def _read_data_elements(self):
info = self._info
try:
while True:
# Get element
group, element, value = self._readDataElement()
# Is it a group we are interested in?
if group in GROUPS:
key = (group, element)
name, vr = MINIDICT.get(key, (None, None))
# Is it an element we are interested in?
if name:
# Store value
converter = self._converters.get(vr, lambda x: x)
info[name] = converter(value)
except (EOFError, struct.error):
pass # end of file ...
def get_numpy_array(self):
"""Get numpy arra for this DICOM file, with the correct shape,
and pixel values scaled appropriately.
"""
# Is there pixel data at all?
if "PixelData" not in self:
raise TypeError("No pixel data found in this dataset.")
# Load it now if it was not already loaded
if self._pixel_data_loc and len(self.PixelData) < 100:
# Reopen file?
close_file = False
if self._file is None:
close_file = True
self._file = open(self._filename, "rb")
# Read data
self._file.seek(self._pixel_data_loc[0])
if self._pixel_data_loc[1] == 0xFFFFFFFF:
value = self._read_undefined_length_value()
else:
value = self._file.read(self._pixel_data_loc[1])
# Close file
if close_file:
self._file.close()
self._file = None
# Overwrite
self._info["PixelData"] = value
# Get data
data = self._pixel_data_numpy()
data = self._apply_slope_and_offset(data)
# Remove data again to preserve memory
# Note that the data for the original file is loaded twice ...
self._info["PixelData"] = (
b"Data converted to numpy array, " + b"raw data removed to preserve memory"
)
return data
def _get_shape_and_sampling(self):
"""Get shape and sampling without actuall using the pixel data.
In this way, the user can get an idea what's inside without having
to load it.
"""
# Get shape (in the same way that pydicom does)
if "NumberOfFrames" in self and self.NumberOfFrames > 1:
if self.SamplesPerPixel > 1:
shape = (
self.SamplesPerPixel,
self.NumberOfFrames,
self.Rows,
self.Columns,
)
else:
shape = self.NumberOfFrames, self.Rows, self.Columns
elif "SamplesPerPixel" in self:
if self.SamplesPerPixel > 1:
if self.BitsAllocated == 8:
shape = self.SamplesPerPixel, self.Rows, self.Columns
else:
raise NotImplementedError(
"DICOM plugin only handles "
"SamplesPerPixel > 1 if Bits "
"Allocated = 8"
)
else:
shape = self.Rows, self.Columns
else:
raise RuntimeError(
"DICOM file has no SamplesPerPixel " "(perhaps this is a report?)"
)
# Try getting sampling between pixels
if "PixelSpacing" in self:
sampling = float(self.PixelSpacing[0]), float(self.PixelSpacing[1])
else:
sampling = 1.0, 1.0
if "SliceSpacing" in self:
sampling = (abs(self.SliceSpacing),) + sampling
# Ensure that sampling has as many elements as shape
sampling = (1.0,) * (len(shape) - len(sampling)) + sampling[-len(shape) :]
# Set shape and sampling
self._info["shape"] = shape
self._info["sampling"] = sampling
def _pixel_data_numpy(self):
"""Return a NumPy array of the pixel data."""
# Taken from pydicom
# Copyright (c) 2008-2012 Darcy Mason
if "PixelData" not in self:
raise TypeError("No pixel data found in this dataset.")
# determine the type used for the array
need_byteswap = self.is_little_endian != sys_is_little_endian
# Make NumPy format code, e.g. "uint16", "int32" etc
# from two pieces of info:
# self.PixelRepresentation -- 0 for unsigned, 1 for signed;
# self.BitsAllocated -- 8, 16, or 32
format_str = "%sint%d" % (
("u", "")[self.PixelRepresentation],
self.BitsAllocated,
)
try:
numpy_format = np.dtype(format_str)
except TypeError: # pragma: no cover
raise TypeError(
"Data type not understood by NumPy: format='%s', "
" PixelRepresentation=%d, BitsAllocated=%d"
% (numpy_format, self.PixelRepresentation, self.BitsAllocated)
)
# Have correct Numpy format, so create the NumPy array
arr = np.frombuffer(self.PixelData, numpy_format).copy()
# XXX byte swap - may later handle this in read_file!!?
if need_byteswap:
arr.byteswap(True) # True means swap in-place, don't make new copy
# Note the following reshape operations return a new *view* onto arr,
# but don't copy the data
arr = arr.reshape(*self._info["shape"])
return arr
def _apply_slope_and_offset(self, data):
"""
If RescaleSlope and RescaleIntercept are present in the data,
apply them. The data type of the data is changed if necessary.
"""
# Obtain slope and offset
slope, offset = 1, 0
needFloats, needApplySlopeOffset = False, False
if "RescaleSlope" in self:
needApplySlopeOffset = True
slope = self.RescaleSlope
if "RescaleIntercept" in self:
needApplySlopeOffset = True
offset = self.RescaleIntercept
if int(slope) != slope or int(offset) != offset:
needFloats = True
if not needFloats:
slope, offset = int(slope), int(offset)
# Apply slope and offset
if needApplySlopeOffset:
# Maybe we need to change the datatype?
if data.dtype in [np.float32, np.float64]:
pass
elif needFloats:
data = data.astype(np.float32)
else:
# Determine required range
minReq, maxReq = data.min(), data.max()
minReq = min([minReq, minReq * slope + offset, maxReq * slope + offset])
maxReq = max([maxReq, minReq * slope + offset, maxReq * slope + offset])
# Determine required datatype from that
dtype = None
if minReq < 0:
# Signed integer type
maxReq = max([-minReq, maxReq])
if maxReq < 2**7:
dtype = np.int8
elif maxReq < 2**15:
dtype = np.int16
elif maxReq < 2**31:
dtype = np.int32
else:
dtype = np.float32
else:
# Unsigned integer type
if maxReq < 2**8:
dtype = np.int8
elif maxReq < 2**16:
dtype = np.int16
elif maxReq < 2**32:
dtype = np.int32
else:
dtype = np.float32
# Change datatype
if dtype != data.dtype:
data = data.astype(dtype)
# Apply slope and offset
data *= slope
data += offset
# Done
return data
def _inflate(self):
# Taken from pydicom
# Copyright (c) 2008-2012 Darcy Mason
import zlib
from io import BytesIO
# See PS3.6-2008 A.5 (p 71) -- when written, the entire dataset
# following the file metadata was prepared the normal way,
# then "deflate" compression applied.
# All that is needed here is to decompress and then
# use as normal in a file-like object
zipped = self._file.read()
# -MAX_WBITS part is from comp.lang.python answer:
# groups.google.com/group/comp.lang.python/msg/e95b3b38a71e6799
unzipped = zlib.decompress(zipped, -zlib.MAX_WBITS)
self._file = BytesIO(unzipped) # a file-like object
class DicomSeries(object):
"""DicomSeries
This class represents a serie of dicom files (SimpleDicomReader
objects) that belong together. If these are multiple files, they
represent the slices of a volume (like for CT or MRI).
"""
def __init__(self, suid, progressIndicator):
# Init dataset list and the callback
self._entries = []
# Init props
self._suid = suid
self._info = {}
self._progressIndicator = progressIndicator
def __len__(self):
return len(self._entries)
def __iter__(self):
return iter(self._entries)
def __getitem__(self, index):
return self._entries[index]
@property
def suid(self):
return self._suid
@property
def shape(self):
"""The shape of the data (nz, ny, nx)."""
return self._info["shape"]
@property
def sampling(self):
"""The sampling (voxel distances) of the data (dz, dy, dx)."""
return self._info["sampling"]
@property
def info(self):
"""A dictionary containing the information as present in the
first dicomfile of this serie. None if there are no entries."""
return self._info
@property
def description(self):
"""A description of the dicom series. Used fields are
PatientName, shape of the data, SeriesDescription, and
ImageComments.
"""
info = self.info
# If no info available, return simple description
if not info: # pragma: no cover
return "DicomSeries containing %i images" % len(self)
fields = []
# Give patient name
if "PatientName" in info:
fields.append("" + info["PatientName"])
# Also add dimensions
if self.shape:
tmp = [str(d) for d in self.shape]
fields.append("x".join(tmp))
# Try adding more fields
if "SeriesDescription" in info:
fields.append("'" + info["SeriesDescription"] + "'")
if "ImageComments" in info:
fields.append("'" + info["ImageComments"] + "'")
# Combine
return " ".join(fields)
def __repr__(self):
adr = hex(id(self)).upper()
return "<DicomSeries with %i images at %s>" % (len(self), adr)
def get_numpy_array(self):
"""Get (load) the data that this DicomSeries represents, and return
it as a numpy array. If this serie contains multiple images, the
resulting array is 3D, otherwise it's 2D.
"""
# It's easy if no file or if just a single file
if len(self) == 0:
raise ValueError("Serie does not contain any files.")
elif len(self) == 1:
return self[0].get_numpy_array()
# Check info
if self.info is None:
raise RuntimeError("Cannot return volume if series not finished.")
# Init data (using what the dicom packaged produces as a reference)
slice = self[0].get_numpy_array()
vol = np.zeros(self.shape, dtype=slice.dtype)
vol[0] = slice
# Fill volume
self._progressIndicator.start("loading data", "", len(self))
for z in range(1, len(self)):
vol[z] = self[z].get_numpy_array()
self._progressIndicator.set_progress(z + 1)
self._progressIndicator.finish()
# Done
import gc
gc.collect()
return vol
def _append(self, dcm):
self._entries.append(dcm)
def _sort(self):
self._entries.sort(key=lambda k: k.InstanceNumber)
def _finish(self):
"""
Evaluate the series of dicom files. Together they should make up
a volumetric dataset. This means the files should meet certain
conditions. Also some additional information has to be calculated,
such as the distance between the slices. This method sets the
attributes for "shape", "sampling" and "info".
This method checks:
* that there are no missing files
* that the dimensions of all images match
* that the pixel spacing of all images match
"""
# The datasets list should be sorted by instance number
L = self._entries
if len(L) == 0:
return
elif len(L) == 1:
self._info = L[0].info
return
# Get previous
ds1 = L[0]
# Init measures to calculate average of
distance_sum = 0.0
# Init measures to check (these are in 2D)
dimensions = ds1.Rows, ds1.Columns
# sampling = float(ds1.PixelSpacing[0]), float(ds1.PixelSpacing[1])
sampling = ds1.info["sampling"][:2] # row, column
for index in range(len(L)):
# The first round ds1 and ds2 will be the same, for the
# distance calculation this does not matter
# Get current
ds2 = L[index]
# Get positions
pos1 = float(ds1.ImagePositionPatient[2])
pos2 = float(ds2.ImagePositionPatient[2])
# Update distance_sum to calculate distance later
distance_sum += abs(pos1 - pos2)
# Test measures
dimensions2 = ds2.Rows, ds2.Columns
# sampling2 = float(ds2.PixelSpacing[0]), float(ds2.PixelSpacing[1])
sampling2 = ds2.info["sampling"][:2] # row, column
if dimensions != dimensions2:
# We cannot produce a volume if the dimensions match
raise ValueError("Dimensions of slices does not match.")
if sampling != sampling2:
# We can still produce a volume, but we should notify the user
self._progressIndicator.write("Warn: sampling does not match.")
# Store previous
ds1 = ds2
# Finish calculating average distance
# (Note that there are len(L)-1 distances)
distance_mean = distance_sum / (len(L) - 1)
# Set info dict
self._info = L[0].info.copy()
# Store information that is specific for the serie
self._info["shape"] = (len(L),) + ds2.info["shape"]
self._info["sampling"] = (distance_mean,) + ds2.info["sampling"]
def list_files(files, path):
"""List all files in the directory, recursively."""
for item in os.listdir(path):
item = os.path.join(path, item)
if os.path.isdir(item):
list_files(files, item)
elif os.path.isfile(item):
files.append(item)
def process_directory(request, progressIndicator, readPixelData=False):
"""
Reads dicom files and returns a list of DicomSeries objects, which
contain information about the data, and can be used to load the
image or volume data.
if readPixelData is True, the pixel data of all series is read. By
default the loading of pixeldata is deferred until it is requested
using the DicomSeries.get_pixel_array() method. In general, both
methods should be equally fast.
"""
# Get directory to examine
if os.path.isdir(request.filename):
path = request.filename
elif os.path.isfile(request.filename):
path = os.path.dirname(request.filename)
else: # pragma: no cover - tested earlier
raise ValueError("Dicom plugin needs a valid filename to examine the directory")
# Check files
files = []
list_files(files, path) # Find files recursively
# Gather file data and put in DicomSeries
series = {}
count = 0
progressIndicator.start("examining files", "files", len(files))
for filename in files:
# Show progress (note that we always start with a 0.0)
count += 1
progressIndicator.set_progress(count)
# Skip DICOMDIR files
if filename.count("DICOMDIR"): # pragma: no cover
continue
# Try loading dicom ...
try:
dcm = SimpleDicomReader(filename)
except NotADicomFile:
continue # skip non-dicom file
except Exception as why: # pragma: no cover
progressIndicator.write(str(why))
continue
# Get SUID and register the file with an existing or new series object
try:
suid = dcm.SeriesInstanceUID
except AttributeError: # pragma: no cover
continue # some other kind of dicom file
if suid not in series:
series[suid] = DicomSeries(suid, progressIndicator)
series[suid]._append(dcm)
# Finish progress
# progressIndicator.finish('Found %i series.' % len(series))
# Make a list and sort, so that the order is deterministic
series = list(series.values())
series.sort(key=lambda x: x.suid)
# Split series if necessary
for serie in reversed([serie for serie in series]):
splitSerieIfRequired(serie, series, progressIndicator)
# Finish all series
# progressIndicator.start('analyse series', '', len(series))
series_ = []
for i in range(len(series)):
try:
series[i]._finish()
series_.append(series[i])
except Exception as err: # pragma: no cover
progressIndicator.write(str(err))
pass # Skip serie (probably report-like file without pixels)
# progressIndicator.set_progress(i+1)
progressIndicator.finish("Found %i correct series." % len(series_))
# Done
return series_
def splitSerieIfRequired(serie, series, progressIndicator):
"""
Split the serie in multiple series if this is required. The choice
is based on examing the image position relative to the previous
image. If it differs too much, it is assumed that there is a new
dataset. This can happen for example in unspitted gated CT data.
"""
# Sort the original list and get local name
serie._sort()
L = serie._entries
# Init previous slice
ds1 = L[0]
# Check whether we can do this
if "ImagePositionPatient" not in ds1:
return
# Initialize a list of new lists
L2 = [[ds1]]
# Init slice distance estimate
distance = 0
for index in range(1, len(L)):
# Get current slice
ds2 = L[index]
# Get positions
pos1 = float(ds1.ImagePositionPatient[2])
pos2 = float(ds2.ImagePositionPatient[2])
# Get distances
newDist = abs(pos1 - pos2)
# deltaDist = abs(firstPos-pos2)
# If the distance deviates more than 2x from what we've seen,
# we can agree it's a new dataset.
if distance and newDist > 2.1 * distance:
L2.append([])
distance = 0
else:
# Test missing file
if distance and newDist > 1.5 * distance:
progressIndicator.write(
"Warning: missing file after %r" % ds1._filename
)
distance = newDist
# Add to last list
L2[-1].append(ds2)
# Store previous
ds1 = ds2
# Split if we should
if len(L2) > 1:
# At what position are we now?
i = series.index(serie)
# Create new series
series2insert = []
for L in L2:
newSerie = DicomSeries(serie.suid, progressIndicator)
newSerie._entries = L
series2insert.append(newSerie)
# Insert series and remove self
for newSerie in reversed(series2insert):
series.insert(i, newSerie)
series.remove(serie)

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@@ -1,897 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
# This code was taken from https://github.com/almarklein/visvis/blob/master/vvmovie/images2swf.py
# styletest: ignore E261
"""
Provides a function (write_swf) to store a series of numpy arrays in an
SWF movie, that can be played on a wide range of OS's.
In desperation of wanting to share animated images, and then lacking a good
writer for animated gif or .avi, I decided to look into SWF. This format
is very well documented.
This is a pure python module to create an SWF file that shows a series
of images. The images are stored using the DEFLATE algorithm (same as
PNG and ZIP and which is included in the standard Python distribution).
As this compression algorithm is much more effective than that used in
GIF images, we obtain better quality (24 bit colors + alpha channel)
while still producesing smaller files (a test showed ~75%). Although
SWF also allows for JPEG compression, doing so would probably require
a third party library for the JPEG encoding/decoding, we could
perhaps do this via Pillow or freeimage.
sources and tools:
- SWF on wikipedia
- Adobes "SWF File Format Specification" version 10
(http://www.adobe.com/devnet/swf/pdf/swf_file_format_spec_v10.pdf)
- swftools (swfdump in specific) for debugging
- iwisoft swf2avi can be used to convert swf to avi/mpg/flv with really
good quality, while file size is reduced with factors 20-100.
A good program in my opinion. The free version has the limitation
of a watermark in the upper left corner.
"""
import os
import zlib
import time # noqa
import logging
import numpy as np
logger = logging.getLogger(__name__)
# todo: use Pillow to support reading JPEG images from SWF?
# Base functions and classes
class BitArray:
"""Dynamic array of bits that automatically resizes
with factors of two.
Append bits using .append() or +=
You can reverse bits using .reverse()
"""
def __init__(self, initvalue=None):
self.data = np.zeros((16,), dtype=np.uint8)
self._len = 0
if initvalue is not None:
self.append(initvalue)
def __len__(self):
return self._len # self.data.shape[0]
def __repr__(self):
return self.data[: self._len].tobytes().decode("ascii")
def _checkSize(self):
# check length... grow if necessary
arraylen = self.data.shape[0]
if self._len >= arraylen:
tmp = np.zeros((arraylen * 2,), dtype=np.uint8)
tmp[: self._len] = self.data[: self._len]
self.data = tmp
def __add__(self, value):
self.append(value)
return self
def append(self, bits):
# check input
if isinstance(bits, BitArray):
bits = str(bits)
if isinstance(bits, int): # pragma: no cover - we dont use it
bits = str(bits)
if not isinstance(bits, str): # pragma: no cover
raise ValueError("Append bits as strings or integers!")
# add bits
for bit in bits:
self.data[self._len] = ord(bit)
self._len += 1
self._checkSize()
def reverse(self):
"""In-place reverse."""
tmp = self.data[: self._len].copy()
self.data[: self._len] = tmp[::-1]
def tobytes(self):
"""Convert to bytes. If necessary,
zeros are padded to the end (right side).
"""
bits = str(self)
# determine number of bytes
nbytes = 0
while nbytes * 8 < len(bits):
nbytes += 1
# pad
bits = bits.ljust(nbytes * 8, "0")
# go from bits to bytes
bb = bytes()
for i in range(nbytes):
tmp = int(bits[i * 8 : (i + 1) * 8], 2)
bb += int2uint8(tmp)
# done
return bb
def int2uint32(i):
return int(i).to_bytes(4, "little")
def int2uint16(i):
return int(i).to_bytes(2, "little")
def int2uint8(i):
return int(i).to_bytes(1, "little")
def int2bits(i, n=None):
"""convert int to a string of bits (0's and 1's in a string),
pad to n elements. Convert back using int(ss,2)."""
ii = i
# make bits
bb = BitArray()
while ii > 0:
bb += str(ii % 2)
ii = ii >> 1
bb.reverse()
# justify
if n is not None:
if len(bb) > n: # pragma: no cover
raise ValueError("int2bits fail: len larger than padlength.")
bb = str(bb).rjust(n, "0")
# done
return BitArray(bb)
def bits2int(bb, n=8):
# Init
value = ""
# Get value in bits
for i in range(len(bb)):
b = bb[i : i + 1]
tmp = bin(ord(b))[2:]
# value += tmp.rjust(8,'0')
value = tmp.rjust(8, "0") + value
# Make decimal
return int(value[:n], 2)
def get_type_and_len(bb):
"""bb should be 6 bytes at least
Return (type, length, length_of_full_tag)
"""
# Init
value = ""
# Get first 16 bits
for i in range(2):
b = bb[i : i + 1]
tmp = bin(ord(b))[2:]
# value += tmp.rjust(8,'0')
value = tmp.rjust(8, "0") + value
# Get type and length
type = int(value[:10], 2)
L = int(value[10:], 2)
L2 = L + 2
# Long tag header?
if L == 63: # '111111'
value = ""
for i in range(2, 6):
b = bb[i : i + 1] # becomes a single-byte bytes()
tmp = bin(ord(b))[2:]
# value += tmp.rjust(8,'0')
value = tmp.rjust(8, "0") + value
L = int(value, 2)
L2 = L + 6
# Done
return type, L, L2
def signedint2bits(i, n=None):
"""convert signed int to a string of bits (0's and 1's in a string),
pad to n elements. Negative numbers are stored in 2's complement bit
patterns, thus positive numbers always start with a 0.
"""
# negative number?
ii = i
if i < 0:
# A negative number, -n, is represented as the bitwise opposite of
ii = abs(ii) - 1 # the positive-zero number n-1.
# make bits
bb = BitArray()
while ii > 0:
bb += str(ii % 2)
ii = ii >> 1
bb.reverse()
# justify
bb = "0" + str(bb) # always need the sign bit in front
if n is not None:
if len(bb) > n: # pragma: no cover
raise ValueError("signedint2bits fail: len larger than padlength.")
bb = bb.rjust(n, "0")
# was it negative? (then opposite bits)
if i < 0:
bb = bb.replace("0", "x").replace("1", "0").replace("x", "1")
# done
return BitArray(bb)
def twits2bits(arr):
"""Given a few (signed) numbers, store them
as compactly as possible in the wat specifief by the swf format.
The numbers are multiplied by 20, assuming they
are twits.
Can be used to make the RECT record.
"""
# first determine length using non justified bit strings
maxlen = 1
for i in arr:
tmp = len(signedint2bits(i * 20))
if tmp > maxlen:
maxlen = tmp
# build array
bits = int2bits(maxlen, 5)
for i in arr:
bits += signedint2bits(i * 20, maxlen)
return bits
def floats2bits(arr):
"""Given a few (signed) numbers, convert them to bits,
stored as FB (float bit values). We always use 16.16.
Negative numbers are not (yet) possible, because I don't
know how the're implemented (ambiguity).
"""
bits = int2bits(31, 5) # 32 does not fit in 5 bits!
for i in arr:
if i < 0: # pragma: no cover
raise ValueError("Dit not implement negative floats!")
i1 = int(i)
i2 = i - i1
bits += int2bits(i1, 15)
bits += int2bits(i2 * 2**16, 16)
return bits
# Base Tag
class Tag:
def __init__(self):
self.bytes = bytes()
self.tagtype = -1
def process_tag(self):
"""Implement this to create the tag."""
raise NotImplementedError()
def get_tag(self):
"""Calls processTag and attaches the header."""
self.process_tag()
# tag to binary
bits = int2bits(self.tagtype, 10)
# complete header uint16 thing
bits += "1" * 6 # = 63 = 0x3f
# make uint16
bb = int2uint16(int(str(bits), 2))
# now add 32bit length descriptor
bb += int2uint32(len(self.bytes))
# done, attach and return
bb += self.bytes
return bb
def make_rect_record(self, xmin, xmax, ymin, ymax):
"""Simply uses makeCompactArray to produce
a RECT Record."""
return twits2bits([xmin, xmax, ymin, ymax])
def make_matrix_record(self, scale_xy=None, rot_xy=None, trans_xy=None):
# empty matrix?
if scale_xy is None and rot_xy is None and trans_xy is None:
return "0" * 8
# init
bits = BitArray()
# scale
if scale_xy:
bits += "1"
bits += floats2bits([scale_xy[0], scale_xy[1]])
else:
bits += "0"
# rotation
if rot_xy:
bits += "1"
bits += floats2bits([rot_xy[0], rot_xy[1]])
else:
bits += "0"
# translation (no flag here)
if trans_xy:
bits += twits2bits([trans_xy[0], trans_xy[1]])
else:
bits += twits2bits([0, 0])
# done
return bits
# Control tags
class ControlTag(Tag):
def __init__(self):
Tag.__init__(self)
class FileAttributesTag(ControlTag):
def __init__(self):
ControlTag.__init__(self)
self.tagtype = 69
def process_tag(self):
self.bytes = "\x00".encode("ascii") * (1 + 3)
class ShowFrameTag(ControlTag):
def __init__(self):
ControlTag.__init__(self)
self.tagtype = 1
def process_tag(self):
self.bytes = bytes()
class SetBackgroundTag(ControlTag):
"""Set the color in 0-255, or 0-1 (if floats given)."""
def __init__(self, *rgb):
self.tagtype = 9
if len(rgb) == 1:
rgb = rgb[0]
self.rgb = rgb
def process_tag(self):
bb = bytes()
for i in range(3):
clr = self.rgb[i]
if isinstance(clr, float): # pragma: no cover - not used
clr = clr * 255
bb += int2uint8(clr)
self.bytes = bb
class DoActionTag(Tag):
def __init__(self, action="stop"):
Tag.__init__(self)
self.tagtype = 12
self.actions = [action]
def append(self, action): # pragma: no cover - not used
self.actions.append(action)
def process_tag(self):
bb = bytes()
for action in self.actions:
action = action.lower()
if action == "stop":
bb += "\x07".encode("ascii")
elif action == "play": # pragma: no cover - not used
bb += "\x06".encode("ascii")
else: # pragma: no cover
logger.warning("unkown action: %s" % action)
bb += int2uint8(0)
self.bytes = bb
# Definition tags
class DefinitionTag(Tag):
counter = 0 # to give automatically id's
def __init__(self):
Tag.__init__(self)
DefinitionTag.counter += 1
self.id = DefinitionTag.counter # id in dictionary
class BitmapTag(DefinitionTag):
def __init__(self, im):
DefinitionTag.__init__(self)
self.tagtype = 36 # DefineBitsLossless2
# convert image (note that format is ARGB)
# even a grayscale image is stored in ARGB, nevertheless,
# the fabilous deflate compression will make it that not much
# more data is required for storing (25% or so, and less than 10%
# when storing RGB as ARGB).
if len(im.shape) == 3:
if im.shape[2] in [3, 4]:
tmp = np.ones((im.shape[0], im.shape[1], 4), dtype=np.uint8) * 255
for i in range(3):
tmp[:, :, i + 1] = im[:, :, i]
if im.shape[2] == 4:
tmp[:, :, 0] = im[:, :, 3] # swap channel where alpha is
else: # pragma: no cover
raise ValueError("Invalid shape to be an image.")
elif len(im.shape) == 2:
tmp = np.ones((im.shape[0], im.shape[1], 4), dtype=np.uint8) * 255
for i in range(3):
tmp[:, :, i + 1] = im[:, :]
else: # pragma: no cover
raise ValueError("Invalid shape to be an image.")
# we changed the image to uint8 4 channels.
# now compress!
self._data = zlib.compress(tmp.tobytes(), zlib.DEFLATED)
self.imshape = im.shape
def process_tag(self):
# build tag
bb = bytes()
bb += int2uint16(self.id) # CharacterID
bb += int2uint8(5) # BitmapFormat
bb += int2uint16(self.imshape[1]) # BitmapWidth
bb += int2uint16(self.imshape[0]) # BitmapHeight
bb += self._data # ZlibBitmapData
self.bytes = bb
class PlaceObjectTag(ControlTag):
def __init__(self, depth, idToPlace=None, xy=(0, 0), move=False):
ControlTag.__init__(self)
self.tagtype = 26
self.depth = depth
self.idToPlace = idToPlace
self.xy = xy
self.move = move
def process_tag(self):
# retrieve stuff
depth = self.depth
xy = self.xy
id = self.idToPlace
# build PlaceObject2
bb = bytes()
if self.move:
bb += "\x07".encode("ascii")
else:
# (8 bit flags): 4:matrix, 2:character, 1:move
bb += "\x06".encode("ascii")
bb += int2uint16(depth) # Depth
bb += int2uint16(id) # character id
bb += self.make_matrix_record(trans_xy=xy).tobytes() # MATRIX record
self.bytes = bb
class ShapeTag(DefinitionTag):
def __init__(self, bitmapId, xy, wh):
DefinitionTag.__init__(self)
self.tagtype = 2
self.bitmapId = bitmapId
self.xy = xy
self.wh = wh
def process_tag(self):
"""Returns a defineshape tag. with a bitmap fill"""
bb = bytes()
bb += int2uint16(self.id)
xy, wh = self.xy, self.wh
tmp = self.make_rect_record(xy[0], wh[0], xy[1], wh[1]) # ShapeBounds
bb += tmp.tobytes()
# make SHAPEWITHSTYLE structure
# first entry: FILLSTYLEARRAY with in it a single fill style
bb += int2uint8(1) # FillStyleCount
bb += "\x41".encode("ascii") # FillStyleType (0x41 or 0x43 unsmoothed)
bb += int2uint16(self.bitmapId) # BitmapId
# bb += '\x00' # BitmapMatrix (empty matrix with leftover bits filled)
bb += self.make_matrix_record(scale_xy=(20, 20)).tobytes()
# # first entry: FILLSTYLEARRAY with in it a single fill style
# bb += int2uint8(1) # FillStyleCount
# bb += '\x00' # solid fill
# bb += '\x00\x00\xff' # color
# second entry: LINESTYLEARRAY with a single line style
bb += int2uint8(0) # LineStyleCount
# bb += int2uint16(0*20) # Width
# bb += '\x00\xff\x00' # Color
# third and fourth entry: NumFillBits and NumLineBits (4 bits each)
# I each give them four bits, so 16 styles possible.
bb += "\x44".encode("ascii")
self.bytes = bb
# last entries: SHAPERECORDs ... (individual shape records not aligned)
# STYLECHANGERECORD
bits = BitArray()
bits += self.make_style_change_record(0, 1, moveTo=(self.wh[0], self.wh[1]))
# STRAIGHTEDGERECORD 4x
bits += self.make_straight_edge_record(-self.wh[0], 0)
bits += self.make_straight_edge_record(0, -self.wh[1])
bits += self.make_straight_edge_record(self.wh[0], 0)
bits += self.make_straight_edge_record(0, self.wh[1])
# ENDSHAPRECORD
bits += self.make_end_shape_record()
self.bytes += bits.tobytes()
# done
# self.bytes = bb
def make_style_change_record(self, lineStyle=None, fillStyle=None, moveTo=None):
# first 6 flags
# Note that we use FillStyle1. If we don't flash (at least 8) does not
# recognize the frames properly when importing to library.
bits = BitArray()
bits += "0" # TypeFlag (not an edge record)
bits += "0" # StateNewStyles (only for DefineShape2 and Defineshape3)
if lineStyle:
bits += "1" # StateLineStyle
else:
bits += "0"
if fillStyle:
bits += "1" # StateFillStyle1
else:
bits += "0"
bits += "0" # StateFillStyle0
if moveTo:
bits += "1" # StateMoveTo
else:
bits += "0"
# give information
# todo: nbits for fillStyle and lineStyle is hard coded.
if moveTo:
bits += twits2bits([moveTo[0], moveTo[1]])
if fillStyle:
bits += int2bits(fillStyle, 4)
if lineStyle:
bits += int2bits(lineStyle, 4)
return bits
def make_straight_edge_record(self, *dxdy):
if len(dxdy) == 1:
dxdy = dxdy[0]
# determine required number of bits
xbits = signedint2bits(dxdy[0] * 20)
ybits = signedint2bits(dxdy[1] * 20)
nbits = max([len(xbits), len(ybits)])
bits = BitArray()
bits += "11" # TypeFlag and StraightFlag
bits += int2bits(nbits - 2, 4)
bits += "1" # GeneralLineFlag
bits += signedint2bits(dxdy[0] * 20, nbits)
bits += signedint2bits(dxdy[1] * 20, nbits)
# note: I do not make use of vertical/horizontal only lines...
return bits
def make_end_shape_record(self):
bits = BitArray()
bits += "0" # TypeFlag: no edge
bits += "0" * 5 # EndOfShape
return bits
def read_pixels(bb, i, tagType, L1):
"""With pf's seed after the recordheader, reads the pixeldata."""
# Get info
charId = bb[i : i + 2] # noqa
i += 2
format = ord(bb[i : i + 1])
i += 1
width = bits2int(bb[i : i + 2], 16)
i += 2
height = bits2int(bb[i : i + 2], 16)
i += 2
# If we can, get pixeldata and make numpy array
if format != 5:
logger.warning("Can only read 24bit or 32bit RGB(A) lossless images.")
else:
# Read byte data
offset = 2 + 1 + 2 + 2 # all the info bits
bb2 = bb[i : i + (L1 - offset)]
# Decompress and make numpy array
data = zlib.decompress(bb2)
a = np.frombuffer(data, dtype=np.uint8)
# Set shape
if tagType == 20:
# DefineBitsLossless - RGB data
try:
a.shape = height, width, 3
except Exception:
# Byte align stuff might cause troubles
logger.warning("Cannot read image due to byte alignment")
if tagType == 36:
# DefineBitsLossless2 - ARGB data
a.shape = height, width, 4
# Swap alpha channel to make RGBA
b = a
a = np.zeros_like(a)
a[:, :, 0] = b[:, :, 1]
a[:, :, 1] = b[:, :, 2]
a[:, :, 2] = b[:, :, 3]
a[:, :, 3] = b[:, :, 0]
return a
# Last few functions
# These are the original public functions, we don't use them, but we
# keep it so that in principle this module can be used stand-alone.
def checkImages(images): # pragma: no cover
"""checkImages(images)
Check numpy images and correct intensity range etc.
The same for all movie formats.
"""
# Init results
images2 = []
for im in images:
if isinstance(im, np.ndarray):
# Check and convert dtype
if im.dtype == np.uint8:
images2.append(im) # Ok
elif im.dtype in [np.float32, np.float64]:
theMax = im.max()
if 128 < theMax < 300:
pass # assume 0:255
else:
im = im.copy()
im[im < 0] = 0
im[im > 1] = 1
im *= 255
images2.append(im.astype(np.uint8))
else:
im = im.astype(np.uint8)
images2.append(im)
# Check size
if im.ndim == 2:
pass # ok
elif im.ndim == 3:
if im.shape[2] not in [3, 4]:
raise ValueError("This array can not represent an image.")
else:
raise ValueError("This array can not represent an image.")
else:
raise ValueError("Invalid image type: " + str(type(im)))
# Done
return images2
def build_file(
fp, taglist, nframes=1, framesize=(500, 500), fps=10, version=8
): # pragma: no cover
"""Give the given file (as bytes) a header."""
# compose header
bb = bytes()
bb += "F".encode("ascii") # uncompressed
bb += "WS".encode("ascii") # signature bytes
bb += int2uint8(version) # version
bb += "0000".encode("ascii") # FileLength (leave open for now)
bb += Tag().make_rect_record(0, framesize[0], 0, framesize[1]).tobytes()
bb += int2uint8(0) + int2uint8(fps) # FrameRate
bb += int2uint16(nframes)
fp.write(bb)
# produce all tags
for tag in taglist:
fp.write(tag.get_tag())
# finish with end tag
fp.write("\x00\x00".encode("ascii"))
# set size
sze = fp.tell()
fp.seek(4)
fp.write(int2uint32(sze))
def write_swf(filename, images, duration=0.1, repeat=True): # pragma: no cover
"""Write an swf-file from the specified images. If repeat is False,
the movie is finished with a stop action. Duration may also
be a list with durations for each frame (note that the duration
for each frame is always an integer amount of the minimum duration.)
Images should be a list consisting numpy arrays with values between
0 and 255 for integer types, and between 0 and 1 for float types.
"""
# Check images
images2 = checkImages(images)
# Init
taglist = [FileAttributesTag(), SetBackgroundTag(0, 0, 0)]
# Check duration
if hasattr(duration, "__len__"):
if len(duration) == len(images2):
duration = [d for d in duration]
else:
raise ValueError("len(duration) doesn't match amount of images.")
else:
duration = [duration for im in images2]
# Build delays list
minDuration = float(min(duration))
delays = [round(d / minDuration) for d in duration]
delays = [max(1, int(d)) for d in delays]
# Get FPS
fps = 1.0 / minDuration
# Produce series of tags for each image
# t0 = time.time()
nframes = 0
for im in images2:
bm = BitmapTag(im)
wh = (im.shape[1], im.shape[0])
sh = ShapeTag(bm.id, (0, 0), wh)
po = PlaceObjectTag(1, sh.id, move=nframes > 0)
taglist.extend([bm, sh, po])
for i in range(delays[nframes]):
taglist.append(ShowFrameTag())
nframes += 1
if not repeat:
taglist.append(DoActionTag("stop"))
# Build file
# t1 = time.time()
fp = open(filename, "wb")
try:
build_file(fp, taglist, nframes=nframes, framesize=wh, fps=fps)
except Exception:
raise
finally:
fp.close()
# t2 = time.time()
# logger.warning("Writing SWF took %1.2f and %1.2f seconds" % (t1-t0, t2-t1) )
def read_swf(filename): # pragma: no cover
"""Read all images from an SWF (shockwave flash) file. Returns a list
of numpy arrays.
Limitation: only read the PNG encoded images (not the JPG encoded ones).
"""
# Check whether it exists
if not os.path.isfile(filename):
raise IOError("File not found: " + str(filename))
# Init images
images = []
# Open file and read all
fp = open(filename, "rb")
bb = fp.read()
try:
# Check opening tag
tmp = bb[0:3].decode("ascii", "ignore")
if tmp.upper() == "FWS":
pass # ok
elif tmp.upper() == "CWS":
# Decompress movie
bb = bb[:8] + zlib.decompress(bb[8:])
else:
raise IOError("Not a valid SWF file: " + str(filename))
# Set filepointer at first tag (skipping framesize RECT and two uin16's
i = 8
nbits = bits2int(bb[i : i + 1], 5) # skip FrameSize
nbits = 5 + nbits * 4
Lrect = nbits / 8.0
if Lrect % 1:
Lrect += 1
Lrect = int(Lrect)
i += Lrect + 4
# Iterate over the tags
counter = 0
while True:
counter += 1
# Get tag header
head = bb[i : i + 6]
if not head:
break # Done (we missed end tag)
# Determine type and length
T, L1, L2 = get_type_and_len(head)
if not L2:
logger.warning("Invalid tag length, could not proceed")
break
# logger.warning(T, L2)
# Read image if we can
if T in [20, 36]:
im = read_pixels(bb, i + 6, T, L1)
if im is not None:
images.append(im)
elif T in [6, 21, 35, 90]:
logger.warning("Ignoring JPEG image: cannot read JPEG.")
else:
pass # Not an image tag
# Detect end tag
if T == 0:
break
# Next tag!
i += L2
finally:
fp.close()
# Done
return images
# Backward compatibility; same public names as when this was images2swf.
writeSwf = write_swf
readSwf = read_swf

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@@ -1,324 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
""" Read/Write BSDF files.
Backend Library: internal
The BSDF format enables reading and writing of image data in the
BSDF serialization format. This format allows storage of images, volumes,
and series thereof. Data can be of any numeric data type, and can
optionally be compressed. Each image/volume can have associated
meta data, which can consist of any data type supported by BSDF.
By default, image data is lazily loaded; the actual image data is
not read until it is requested. This allows storing multiple images
in a single file and still have fast access to individual images.
Alternatively, a series of images can be read in streaming mode, reading
images as they are read (e.g. from http).
BSDF is a simple generic binary format. It is easy to extend and there
are standard extension definitions for 2D and 3D image data.
Read more at http://bsdf.io.
Parameters
----------
random_access : bool
Whether individual images in the file can be read in random order.
Defaults to True for normal files, and to False when reading from HTTP.
If False, the file is read in "streaming mode", allowing reading
files as they are read, but without support for "rewinding".
Note that setting this to True when reading from HTTP, the whole file
is read upon opening it (since lazy loading is not possible over HTTP).
compression : int
Use ``0`` or "no" for no compression, ``1`` or "zlib" for Zlib
compression (same as zip files and PNG), and ``2`` or "bz2" for Bz2
compression (more compact but slower). Default 1 (zlib).
Note that some BSDF implementations may not support compression
(e.g. JavaScript).
"""
import numpy as np
from ..core import Format
def get_bsdf_serializer(options):
from . import _bsdf as bsdf
class NDArrayExtension(bsdf.Extension):
"""Copy of BSDF's NDArrayExtension but deal with lazy blobs."""
name = "ndarray"
cls = np.ndarray
def encode(self, s, v):
return dict(shape=v.shape, dtype=str(v.dtype), data=v.tobytes())
def decode(self, s, v):
return v # return as dict, because of lazy blobs, decode in Image
class ImageExtension(bsdf.Extension):
"""We implement two extensions that trigger on the Image classes."""
def encode(self, s, v):
return dict(array=v.array, meta=v.meta)
def decode(self, s, v):
return Image(v["array"], v["meta"])
class Image2DExtension(ImageExtension):
name = "image2d"
cls = Image2D
class Image3DExtension(ImageExtension):
name = "image3d"
cls = Image3D
exts = [NDArrayExtension, Image2DExtension, Image3DExtension]
serializer = bsdf.BsdfSerializer(exts, **options)
return bsdf, serializer
class Image:
"""Class in which we wrap the array and meta data. By using an extension
we can make BSDF trigger on these classes and thus encode the images.
as actual images.
"""
def __init__(self, array, meta):
self.array = array
self.meta = meta
def get_array(self):
if not isinstance(self.array, np.ndarray):
v = self.array
blob = v["data"]
if not isinstance(blob, bytes): # then it's a lazy bsdf.Blob
blob = blob.get_bytes()
self.array = np.frombuffer(blob, dtype=v["dtype"])
self.array.shape = v["shape"]
return self.array
def get_meta(self):
return self.meta
class Image2D(Image):
pass
class Image3D(Image):
pass
class BsdfFormat(Format):
"""The BSDF format enables reading and writing of image data in the
BSDF serialization format. This format allows storage of images, volumes,
and series thereof. Data can be of any numeric data type, and can
optionally be compressed. Each image/volume can have associated
meta data, which can consist of any data type supported by BSDF.
By default, image data is lazily loaded; the actual image data is
not read until it is requested. This allows storing multiple images
in a single file and still have fast access to individual images.
Alternatively, a series of images can be read in streaming mode, reading
images as they are read (e.g. from http).
BSDF is a simple generic binary format. It is easy to extend and there
are standard extension definitions for 2D and 3D image data.
Read more at http://bsdf.io.
Parameters for reading
----------------------
random_access : bool
Whether individual images in the file can be read in random order.
Defaults to True for normal files, and to False when reading from HTTP.
If False, the file is read in "streaming mode", allowing reading
files as they are read, but without support for "rewinding".
Note that setting this to True when reading from HTTP, the whole file
is read upon opening it (since lazy loading is not possible over HTTP).
Parameters for saving
---------------------
compression : {0, 1, 2}
Use ``0`` or "no" for no compression, ``1`` or "zlib" for Zlib
compression (same as zip files and PNG), and ``2`` or "bz2" for Bz2
compression (more compact but slower). Default 1 (zlib).
Note that some BSDF implementations may not support compression
(e.g. JavaScript).
"""
def _can_read(self, request):
if request.mode[1] in (self.modes + "?"):
# if request.extension in self.extensions:
# return True
if request.firstbytes.startswith(b"BSDF"):
return True
def _can_write(self, request):
if request.mode[1] in (self.modes + "?"):
if request.extension in self.extensions:
return True
# -- reader
class Reader(Format.Reader):
def _open(self, random_access=None):
# Validate - we need a BSDF file consisting of a list of images
# The list is typically a stream, but does not have to be.
assert self.request.firstbytes[:4] == b"BSDF", "Not a BSDF file"
# self.request.firstbytes[5:6] == major and minor version
if not (
self.request.firstbytes[6:15] == b"M\x07image2D"
or self.request.firstbytes[6:15] == b"M\x07image3D"
or self.request.firstbytes[6:7] == b"l"
):
pass # Actually, follow a more duck-type approach ...
# raise RuntimeError('BSDF file does not look like an '
# 'image container.')
# Set options. If we think that seeking is allowed, we lazily load
# blobs, and set streaming to False (i.e. the whole file is read,
# but we skip over binary blobs), so that we subsequently allow
# random access to the images.
# If seeking is not allowed (e.g. with a http request), we cannot
# lazily load blobs, but we can still load streaming from the web.
options = {}
if self.request.filename.startswith(("http://", "https://")):
ra = False if random_access is None else bool(random_access)
options["lazy_blob"] = False # Because we cannot seek now
options["load_streaming"] = not ra # Load as a stream?
else:
ra = True if random_access is None else bool(random_access)
options["lazy_blob"] = ra # Don't read data until needed
options["load_streaming"] = not ra
file = self.request.get_file()
bsdf, self._serializer = get_bsdf_serializer(options)
self._stream = self._serializer.load(file)
# Another validation
if (
isinstance(self._stream, dict)
and "meta" in self._stream
and "array" in self._stream
):
self._stream = Image(self._stream["array"], self._stream["meta"])
if not isinstance(self._stream, (Image, list, bsdf.ListStream)):
raise RuntimeError(
"BSDF file does not look seem to have an " "image container."
)
def _close(self):
pass
def _get_length(self):
if isinstance(self._stream, Image):
return 1
elif isinstance(self._stream, list):
return len(self._stream)
elif self._stream.count < 0:
return np.inf
return self._stream.count
def _get_data(self, index):
# Validate
if index < 0 or index >= self.get_length():
raise IndexError(
"Image index %i not in [0 %i]." % (index, self.get_length())
)
# Get Image object
if isinstance(self._stream, Image):
image_ob = self._stream # singleton
elif isinstance(self._stream, list):
# Easy when we have random access
image_ob = self._stream[index]
else:
# For streaming, we need to skip over frames
if index < self._stream.index:
raise IndexError(
"BSDF file is being read in streaming "
"mode, thus does not allow rewinding."
)
while index > self._stream.index:
self._stream.next()
image_ob = self._stream.next() # Can raise StopIteration
# Is this an image?
if (
isinstance(image_ob, dict)
and "meta" in image_ob
and "array" in image_ob
):
image_ob = Image(image_ob["array"], image_ob["meta"])
if isinstance(image_ob, Image):
# Return as array (if we have lazy blobs, they are read now)
return image_ob.get_array(), image_ob.get_meta()
else:
r = repr(image_ob)
r = r if len(r) < 200 else r[:197] + "..."
raise RuntimeError("BSDF file contains non-image " + r)
def _get_meta_data(self, index): # pragma: no cover
return {} # This format does not support global meta data
# -- writer
class Writer(Format.Writer):
def _open(self, compression=1):
options = {"compression": compression}
bsdf, self._serializer = get_bsdf_serializer(options)
if self.request.mode[1] in "iv":
self._stream = None # Singleton image
self._written = False
else:
# Series (stream) of images
file = self.request.get_file()
self._stream = bsdf.ListStream()
self._serializer.save(file, self._stream)
def _close(self):
# We close the stream here, which will mark the number of written
# elements. If we would not close it, the file would be fine, it's
# just that upon reading it would not be known how many items are
# in there.
if self._stream is not None:
self._stream.close(False) # False says "keep this a stream"
def _append_data(self, im, meta):
# Determine dimension
ndim = None
if self.request.mode[1] in "iI":
ndim = 2
elif self.request.mode[1] in "vV":
ndim = 3
else:
ndim = 3 # Make an educated guess
if im.ndim == 2 or (im.ndim == 3 and im.shape[-1] <= 4):
ndim = 2
# Validate shape
assert ndim in (2, 3)
if ndim == 2:
assert im.ndim == 2 or (im.ndim == 3 and im.shape[-1] <= 4)
else:
assert im.ndim == 3 or (im.ndim == 4 and im.shape[-1] <= 4)
# Wrap data and meta data in our special class that will trigger
# the BSDF image2D or image3D extension.
if ndim == 2:
ob = Image2D(im, meta)
else:
ob = Image3D(im, meta)
# Write directly or to stream
if self._stream is None:
assert not self._written, "Cannot write singleton image twice"
self._written = True
file = self.request.get_file()
self._serializer.save(file, ob)
else:
self._stream.append(ob)
def set_meta_data(self, meta): # pragma: no cover
raise RuntimeError("The BSDF format only supports " "per-image meta data.")

View File

@@ -1,333 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
"""Read DICOM files.
Backend Library: internal
A format for reading DICOM images: a common format used to store
medical image data, such as X-ray, CT and MRI.
This format borrows some code (and ideas) from the pydicom project. However,
only a predefined subset of tags are extracted from the file. This allows
for great simplifications allowing us to make a stand-alone reader, and
also results in a much faster read time.
By default, only uncompressed and deflated transfer syntaxes are supported.
If gdcm or dcmtk is installed, these will be used to automatically convert
the data. See https://github.com/malaterre/GDCM/releases for installing GDCM.
This format provides functionality to group images of the same
series together, thus extracting volumes (and multiple volumes).
Using volread will attempt to yield a volume. If multiple volumes
are present, the first one is given. Using mimread will simply yield
all images in the given directory (not taking series into account).
Parameters
----------
progress : {True, False, BaseProgressIndicator}
Whether to show progress when reading from multiple files.
Default True. By passing an object that inherits from
BaseProgressIndicator, the way in which progress is reported
can be costumized.
"""
# todo: Use pydicom:
# * Note: is not py3k ready yet
# * Allow reading the full meta info
# I think we can more or less replace the SimpleDicomReader with a
# pydicom.Dataset For series, only ned to read the full info from one
# file: speed still high
# * Perhaps allow writing?
import os
import sys
import logging
import subprocess
from ..core import Format, BaseProgressIndicator, StdoutProgressIndicator
from ..core import read_n_bytes
_dicom = None # lazily loaded in load_lib()
logger = logging.getLogger(__name__)
def load_lib():
global _dicom
from . import _dicom
return _dicom
# Determine endianity of system
sys_is_little_endian = sys.byteorder == "little"
def get_dcmdjpeg_exe():
fname = "dcmdjpeg" + ".exe" * sys.platform.startswith("win")
for dir in (
"c:\\dcmtk",
"c:\\Program Files",
"c:\\Program Files\\dcmtk",
"c:\\Program Files (x86)\\dcmtk",
):
filename = os.path.join(dir, fname)
if os.path.isfile(filename):
return [filename]
try:
subprocess.check_call([fname, "--version"])
return [fname]
except Exception:
return None
def get_gdcmconv_exe():
fname = "gdcmconv" + ".exe" * sys.platform.startswith("win")
# Maybe it's on the path
try:
subprocess.check_call([fname, "--version"])
return [fname, "--raw"]
except Exception:
pass
# Select directories where it could be
candidates = []
base_dirs = [r"c:\Program Files"]
for base_dir in base_dirs:
if os.path.isdir(base_dir):
for dname in os.listdir(base_dir):
if dname.lower().startswith("gdcm"):
suffix = dname[4:].strip()
candidates.append((suffix, os.path.join(base_dir, dname)))
# Sort, so higher versions are tried earlier
candidates.sort(reverse=True)
# Select executable
filename = None
for _, dirname in candidates:
exe1 = os.path.join(dirname, "gdcmconv.exe")
exe2 = os.path.join(dirname, "bin", "gdcmconv.exe")
if os.path.isfile(exe1):
filename = exe1
break
if os.path.isfile(exe2):
filename = exe2
break
else:
return None
return [filename, "--raw"]
class DicomFormat(Format):
"""See :mod:`imageio.plugins.dicom`"""
def _can_read(self, request):
# If user URI was a directory, we check whether it has a DICOM file
if os.path.isdir(request.filename):
files = os.listdir(request.filename)
for fname in sorted(files): # Sorting make it consistent
filename = os.path.join(request.filename, fname)
if os.path.isfile(filename) and "DICOMDIR" not in fname:
with open(filename, "rb") as f:
first_bytes = read_n_bytes(f, 140)
return first_bytes[128:132] == b"DICM"
else:
return False
# Check
return request.firstbytes[128:132] == b"DICM"
def _can_write(self, request):
# We cannot save yet. May be possible if we will used pydicom as
# a backend.
return False
# --
class Reader(Format.Reader):
_compressed_warning_dirs = set()
def _open(self, progress=True):
if not _dicom:
load_lib()
if os.path.isdir(self.request.filename):
# A dir can be given if the user used the format explicitly
self._info = {}
self._data = None
else:
# Read the given dataset now ...
try:
dcm = _dicom.SimpleDicomReader(self.request.get_file())
except _dicom.CompressedDicom as err:
# We cannot do this on our own. Perhaps with some help ...
cmd = get_gdcmconv_exe()
if not cmd and "JPEG" in str(err):
cmd = get_dcmdjpeg_exe()
if not cmd:
msg = err.args[0].replace("using", "installing")
msg = msg.replace("convert", "auto-convert")
err.args = (msg,)
raise
else:
fname1 = self.request.get_local_filename()
fname2 = fname1 + ".raw"
try:
subprocess.check_call(cmd + [fname1, fname2])
except Exception:
raise err
d = os.path.dirname(fname1)
if d not in self._compressed_warning_dirs:
self._compressed_warning_dirs.add(d)
logger.warning(
"DICOM file contained compressed data. "
+ "Autoconverting with "
+ cmd[0]
+ " (this warning is shown once for each directory)"
)
dcm = _dicom.SimpleDicomReader(fname2)
self._info = dcm._info
self._data = dcm.get_numpy_array()
# Initialize series, list of DicomSeries objects
self._series = None # only created if needed
# Set progress indicator
if isinstance(progress, BaseProgressIndicator):
self._progressIndicator = progress
elif progress is True:
p = StdoutProgressIndicator("Reading DICOM")
self._progressIndicator = p
elif progress in (None, False):
self._progressIndicator = BaseProgressIndicator("Dummy")
else:
raise ValueError("Invalid value for progress.")
def _close(self):
# Clean up
self._info = None
self._data = None
self._series = None
@property
def series(self):
if self._series is None:
pi = self._progressIndicator
self._series = _dicom.process_directory(self.request, pi)
return self._series
def _get_length(self):
if self._data is None:
dcm = self.series[0][0]
self._info = dcm._info
self._data = dcm.get_numpy_array()
nslices = self._data.shape[0] if (self._data.ndim == 3) else 1
if self.request.mode[1] == "i":
# User expects one, but lets be honest about this file
return nslices
elif self.request.mode[1] == "I":
# User expects multiple, if this file has multiple slices, ok.
# Otherwise we have to check the series.
if nslices > 1:
return nslices
else:
return sum([len(serie) for serie in self.series])
elif self.request.mode[1] == "v":
# User expects a volume, if this file has one, ok.
# Otherwise we have to check the series
if nslices > 1:
return 1
else:
return len(self.series) # We assume one volume per series
elif self.request.mode[1] == "V":
# User expects multiple volumes. We have to check the series
return len(self.series) # We assume one volume per series
else:
raise RuntimeError("DICOM plugin should know what to expect.")
def _get_slice_data(self, index):
nslices = self._data.shape[0] if (self._data.ndim == 3) else 1
# Allow index >1 only if this file contains >1
if nslices > 1:
return self._data[index], self._info
elif index == 0:
return self._data, self._info
else:
raise IndexError("Dicom file contains only one slice.")
def _get_data(self, index):
if self._data is None:
dcm = self.series[0][0]
self._info = dcm._info
self._data = dcm.get_numpy_array()
nslices = self._data.shape[0] if (self._data.ndim == 3) else 1
if self.request.mode[1] == "i":
return self._get_slice_data(index)
elif self.request.mode[1] == "I":
# Return slice from volume, or return item from series
if index == 0 and nslices > 1:
return self._data[index], self._info
else:
L = []
for serie in self.series:
L.extend([dcm_ for dcm_ in serie])
return L[index].get_numpy_array(), L[index].info
elif self.request.mode[1] in "vV":
# Return volume or series
if index == 0 and nslices > 1:
return self._data, self._info
else:
return (
self.series[index].get_numpy_array(),
self.series[index].info,
)
# mode is `?` (typically because we are using V3). If there is a
# series (multiple files), index referrs to the element of the
# series and we read volumes. If there is no series, index
# referrs to the slice in the volume we read "flat" images.
elif len(self.series) > 1:
# mode is `?` and there are multiple series. Each series is a ndimage.
return (
self.series[index].get_numpy_array(),
self.series[index].info,
)
else:
# mode is `?` and there is only one series. Each slice is an ndimage.
return self._get_slice_data(index)
def _get_meta_data(self, index):
if self._data is None:
dcm = self.series[0][0]
self._info = dcm._info
self._data = dcm.get_numpy_array()
nslices = self._data.shape[0] if (self._data.ndim == 3) else 1
# Default is the meta data of the given file, or the "first" file.
if index is None:
return self._info
if self.request.mode[1] == "i":
return self._info
elif self.request.mode[1] == "I":
# Return slice from volume, or return item from series
if index == 0 and nslices > 1:
return self._info
else:
L = []
for serie in self.series:
L.extend([dcm_ for dcm_ in serie])
return L[index].info
elif self.request.mode[1] in "vV":
# Return volume or series
if index == 0 and nslices > 1:
return self._info
else:
return self.series[index].info
else: # pragma: no cover
raise ValueError("DICOM plugin should know what to expect.")

View File

@@ -1,145 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
""" Example plugin. You can use this as a template for your own plugin.
"""
import numpy as np
from .. import formats
from ..core import Format
class DummyFormat(Format):
"""The dummy format is an example format that does nothing.
It will never indicate that it can read or write a file. When
explicitly asked to read, it will simply read the bytes. When
explicitly asked to write, it will raise an error.
This documentation is shown when the user does ``help('thisformat')``.
Parameters for reading
----------------------
Specify arguments in numpy doc style here.
Parameters for saving
---------------------
Specify arguments in numpy doc style here.
"""
def _can_read(self, request):
# This method is called when the format manager is searching
# for a format to read a certain image. Return True if this format
# can do it.
#
# The format manager is aware of the extensions and the modes
# that each format can handle. It will first ask all formats
# that *seem* to be able to read it whether they can. If none
# can, it will ask the remaining formats if they can: the
# extension might be missing, and this allows formats to provide
# functionality for certain extensions, while giving preference
# to other plugins.
#
# If a format says it can, it should live up to it. The format
# would ideally check the request.firstbytes and look for a
# header of some kind.
#
# The request object has:
# request.filename: a representation of the source (only for reporting)
# request.firstbytes: the first 256 bytes of the file.
# request.mode[0]: read or write mode
if request.extension in self.extensions:
return True
def _can_write(self, request):
# This method is called when the format manager is searching
# for a format to write a certain image. It will first ask all
# formats that *seem* to be able to write it whether they can.
# If none can, it will ask the remaining formats if they can.
#
# Return True if the format can do it.
# In most cases, this code does suffice:
if request.extension in self.extensions:
return True
# -- reader
class Reader(Format.Reader):
def _open(self, some_option=False, length=1):
# Specify kwargs here. Optionally, the user-specified kwargs
# can also be accessed via the request.kwargs object.
#
# The request object provides two ways to get access to the
# data. Use just one:
# - Use request.get_file() for a file object (preferred)
# - Use request.get_local_filename() for a file on the system
self._fp = self.request.get_file()
self._length = length # passed as an arg in this case for testing
self._data = None
def _close(self):
# Close the reader.
# Note that the request object will close self._fp
pass
def _get_length(self):
# Return the number of images. Can be np.inf
return self._length
def _get_data(self, index):
# Return the data and meta data for the given index
if index >= self._length:
raise IndexError("Image index %i > %i" % (index, self._length))
# Read all bytes
if self._data is None:
self._data = self._fp.read()
# Put in a numpy array
im = np.frombuffer(self._data, "uint8")
im.shape = len(im), 1
# Return array and dummy meta data
return im, {}
def _get_meta_data(self, index):
# Get the meta data for the given index. If index is None, it
# should return the global meta data.
return {} # This format does not support meta data
# -- writer
class Writer(Format.Writer):
def _open(self, flags=0):
# Specify kwargs here. Optionally, the user-specified kwargs
# can also be accessed via the request.kwargs object.
#
# The request object provides two ways to write the data.
# Use just one:
# - Use request.get_file() for a file object (preferred)
# - Use request.get_local_filename() for a file on the system
self._fp = self.request.get_file()
def _close(self):
# Close the reader.
# Note that the request object will close self._fp
pass
def _append_data(self, im, meta):
# Process the given data and meta data.
raise RuntimeError("The dummy format cannot write image data.")
def set_meta_data(self, meta):
# Process the given meta data (global for all images)
# It is not mandatory to support this.
raise RuntimeError("The dummy format cannot write meta data.")
# Register. You register an *instance* of a Format class. Here specify:
format = DummyFormat(
"dummy", # short name
"An example format that does nothing.", # one line descr.
".foobar .nonexistentext", # list of extensions
"iI", # modes, characters in iIvV
)
formats.add_format(format)

View File

@@ -1,95 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
"""Read TIFF from FEI SEM microscopes.
Backend Library: internal
This format is based on :mod:`TIFF <imageio.plugins.tifffile>`, and supports the
same parameters. FEI microscopes append metadata as ASCII text at the end of the
file, which this reader correctly extracts.
Parameters
----------
discard_watermark : bool
If True (default), discard the bottom rows of the image, which
contain no image data, only a watermark with metadata.
watermark_height : int
The height in pixels of the FEI watermark. The default is 70.
See Also
--------
:mod:`imageio.plugins.tifffile`
"""
from .tifffile import TiffFormat
class FEISEMFormat(TiffFormat):
"""See :mod:`imageio.plugins.feisem`"""
def _can_write(self, request):
return False # FEI-SEM only supports reading
class Reader(TiffFormat.Reader):
def _get_data(self, index=0, discard_watermark=True, watermark_height=70):
"""Get image and metadata from given index.
FEI images usually (always?) contain a watermark at the
bottom of the image, 70 pixels high. We discard this by
default as it does not contain any information not present
in the metadata.
"""
im, meta = super(FEISEMFormat.Reader, self)._get_data(index)
if discard_watermark:
im = im[:-watermark_height]
return im, meta
def _get_meta_data(self, index=None):
"""Read the metadata from an FEI SEM TIFF.
This metadata is included as ASCII text at the end of the file.
The index, if provided, is ignored.
Returns
-------
metadata : dict
Dictionary of metadata.
"""
if hasattr(self, "_fei_meta"):
return self._fei_meta
md = {"root": {}}
current_tag = "root"
reading_metadata = False
filename = self.request.get_local_filename()
with open(filename, encoding="utf8", errors="ignore") as fin:
for line in fin:
if not reading_metadata:
if not line.startswith("Date="):
continue
else:
reading_metadata = True
line = line.rstrip()
if line.startswith("["):
current_tag = line.lstrip("[").rstrip("]")
md[current_tag] = {}
else:
if "=" in line: # ignore empty and irrelevant lines
key, val = line.split("=", maxsplit=1)
for tag_type in (int, float):
try:
val = tag_type(val)
except ValueError:
continue
else:
break
md[current_tag][key] = val
if not md["root"] and len(md) == 1:
raise ValueError("Input file %s contains no FEI metadata." % filename)
self._fei_meta = md
return md

View File

@@ -1,729 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
"""Read/Write video using FFMPEG
.. note::
We are in the process of (slowly) replacing this plugin with a new one that
is based on `pyav <https://pyav.org/docs/stable/>`_. It is faster and more
flexible than the plugin documented here. Check the :mod:`pyav
plugin's documentation <imageio.plugins.pyav>` for more information about
this plugin.
Backend Library: https://github.com/imageio/imageio-ffmpeg
.. note::
To use this plugin you have to install its backend::
pip install imageio[ffmpeg]
The ffmpeg format provides reading and writing for a wide range of movie formats
such as .avi, .mpeg, .mp4, etc. as well as the ability to read streams from
webcams and USB cameras. It is based on ffmpeg and is inspired by/based `moviepy
<https://github.com/Zulko/moviepy/>`_ by Zulko.
Parameters for reading
----------------------
fps : scalar
The number of frames per second to read the data at. Default None (i.e.
read at the file's own fps). One can use this for files with a
variable fps, or in cases where imageio is unable to correctly detect
the fps. In case of trouble opening camera streams, it may help to set an
explicit fps value matching a framerate supported by the camera.
loop : bool
If True, the video will rewind as soon as a frame is requested
beyond the last frame. Otherwise, IndexError is raised. Default False.
Setting this to True will internally call ``count_frames()``,
and set the reader's length to that value instead of inf.
size : str | tuple
The frame size (i.e. resolution) to read the images, e.g.
(100, 100) or "640x480". For camera streams, this allows setting
the capture resolution. For normal video data, ffmpeg will
rescale the data.
dtype : str | type
The dtype for the output arrays. Determines the bit-depth that
is requested from ffmpeg. Supported dtypes: uint8, uint16.
Default: uint8.
pixelformat : str
The pixel format for the camera to use (e.g. "yuyv422" or
"gray"). The camera needs to support the format in order for
this to take effect. Note that the images produced by this
reader are always RGB.
input_params : list
List additional arguments to ffmpeg for input file options.
(Can also be provided as ``ffmpeg_params`` for backwards compatibility)
Example ffmpeg arguments to use aggressive error handling:
['-err_detect', 'aggressive']
output_params : list
List additional arguments to ffmpeg for output file options (i.e. the
stream being read by imageio).
print_info : bool
Print information about the video file as reported by ffmpeg.
Parameters for writing
----------------------
fps : scalar
The number of frames per second. Default 10.
codec : str
the video codec to use. Default 'libx264', which represents the
widely available mpeg4. Except when saving .wmv files, then the
defaults is 'msmpeg4' which is more commonly supported for windows
quality : float | None
Video output quality. Default is 5. Uses variable bit rate. Highest
quality is 10, lowest is 0. Set to None to prevent variable bitrate
flags to FFMPEG so you can manually specify them using output_params
instead. Specifying a fixed bitrate using 'bitrate' disables this
parameter.
bitrate : int | None
Set a constant bitrate for the video encoding. Default is None causing
'quality' parameter to be used instead. Better quality videos with
smaller file sizes will result from using the 'quality' variable
bitrate parameter rather than specifiying a fixed bitrate with this
parameter.
pixelformat: str
The output video pixel format. Default is 'yuv420p' which most widely
supported by video players.
input_params : list
List additional arguments to ffmpeg for input file options (i.e. the
stream that imageio provides).
output_params : list
List additional arguments to ffmpeg for output file options.
(Can also be provided as ``ffmpeg_params`` for backwards compatibility)
Example ffmpeg arguments to use only intra frames and set aspect ratio:
['-intra', '-aspect', '16:9']
ffmpeg_log_level: str
Sets ffmpeg output log level. Default is "warning".
Values can be "quiet", "panic", "fatal", "error", "warning", "info"
"verbose", or "debug". Also prints the FFMPEG command being used by
imageio if "info", "verbose", or "debug".
macro_block_size: int
Size constraint for video. Width and height, must be divisible by this
number. If not divisible by this number imageio will tell ffmpeg to
scale the image up to the next closest size
divisible by this number. Most codecs are compatible with a macroblock
size of 16 (default), some can go smaller (4, 8). To disable this
automatic feature set it to None or 1, however be warned many players
can't decode videos that are odd in size and some codecs will produce
poor results or fail. See https://en.wikipedia.org/wiki/Macroblock.
audio_path : str | None
Audio path of any audio that needs to be written. Defaults to nothing,
so no audio will be written. Please note, when writing shorter video
than the original, ffmpeg will not truncate the audio track; it
will maintain its original length and be longer than the video.
audio_codec : str | None
The audio codec to use. Defaults to nothing, but if an audio_path has
been provided ffmpeg will attempt to set a default codec.
Notes
-----
If you are using anaconda and ``anaconda/ffmpeg`` you will not be able to
encode/decode H.264 (likely due to licensing concerns). If you need this
format on anaconda install ``conda-forge/ffmpeg`` instead.
You can use the ``IMAGEIO_FFMPEG_EXE`` environment variable to force using a
specific ffmpeg executable.
To get the number of frames before having read them all, you can use the
``reader.count_frames()`` method (the reader will then use
``imageio_ffmpeg.count_frames_and_secs()`` to get the exact number of frames,
note that this operation can take a few seconds on large files). Alternatively,
the number of frames can be estimated from the fps and duration in the meta data
(though these values themselves are not always present/reliable).
"""
import re
import sys
import time
import logging
import platform
import threading
import subprocess as sp
import imageio_ffmpeg
import numpy as np
from ..core import Format, image_as_uint
logger = logging.getLogger(__name__)
# Get camera format
if sys.platform.startswith("win"):
CAM_FORMAT = "dshow" # dshow or vfwcap
elif sys.platform.startswith("linux"):
CAM_FORMAT = "video4linux2"
elif sys.platform.startswith("darwin"):
CAM_FORMAT = "avfoundation"
else: # pragma: no cover
CAM_FORMAT = "unknown-cam-format"
def download(directory=None, force_download=False): # pragma: no cover
raise RuntimeError(
"imageio.ffmpeg.download() has been deprecated. "
"Use 'pip install imageio-ffmpeg' instead.'"
)
# For backwards compatibility - we dont use this ourselves
def get_exe(): # pragma: no cover
"""Wrapper for imageio_ffmpeg.get_ffmpeg_exe()"""
return imageio_ffmpeg.get_ffmpeg_exe()
class FfmpegFormat(Format):
"""Read/Write ImageResources using FFMPEG.
See :mod:`imageio.plugins.ffmpeg`
"""
def _can_read(self, request):
# Read from video stream?
# Note that we could write the _video flag here, but a user might
# select this format explicitly (and this code is not run)
if re.match(r"<video(\d+)>", request.filename):
return True
# Read from file that we know?
if request.extension in self.extensions:
return True
def _can_write(self, request):
if request.extension in self.extensions:
return True
# --
class Reader(Format.Reader):
_frame_catcher = None
_read_gen = None
def _get_cam_inputname(self, index):
if sys.platform.startswith("linux"):
return "/dev/" + self.request._video[1:-1]
elif sys.platform.startswith("win"):
# Ask ffmpeg for list of dshow device names
ffmpeg_api = imageio_ffmpeg
cmd = [
ffmpeg_api.get_ffmpeg_exe(),
"-list_devices",
"true",
"-f",
CAM_FORMAT,
"-i",
"dummy",
]
# Set `shell=True` in sp.run to prevent popup of a command
# line window in frozen applications. Note: this would be a
# security vulnerability if user-input goes into the cmd.
# Note that the ffmpeg process returns with exit code 1 when
# using `-list_devices` (or `-list_options`), even if the
# command is successful, so we set `check=False` explicitly.
completed_process = sp.run(
cmd,
stdout=sp.PIPE,
stderr=sp.PIPE,
encoding="utf-8",
shell=True,
check=False,
)
# Return device name at index
try:
name = parse_device_names(completed_process.stderr)[index]
except IndexError:
raise IndexError("No ffdshow camera at index %i." % index)
return "video=%s" % name
elif sys.platform.startswith("darwin"):
# Appears that newer ffmpeg builds don't support -list-devices
# on OS X. But you can directly open the camera by index.
name = str(index)
return name
else: # pragma: no cover
return "??"
def _open(
self,
loop=False,
size=None,
dtype=None,
pixelformat=None,
print_info=False,
ffmpeg_params=None,
input_params=None,
output_params=None,
fps=None,
):
# Get generator functions
self._ffmpeg_api = imageio_ffmpeg
# Process input args
self._arg_loop = bool(loop)
if size is None:
self._arg_size = None
elif isinstance(size, tuple):
self._arg_size = "%ix%i" % size
elif isinstance(size, str) and "x" in size:
self._arg_size = size
else:
raise ValueError('FFMPEG size must be tuple of "NxM"')
if pixelformat is None:
pass
elif not isinstance(pixelformat, str):
raise ValueError("FFMPEG pixelformat must be str")
if dtype is None:
self._dtype = np.dtype("uint8")
else:
self._dtype = np.dtype(dtype)
allowed_dtypes = ["uint8", "uint16"]
if self._dtype.name not in allowed_dtypes:
raise ValueError(
"dtype must be one of: {}".format(", ".join(allowed_dtypes))
)
self._arg_pixelformat = pixelformat
self._arg_input_params = input_params or []
self._arg_output_params = output_params or []
self._arg_input_params += ffmpeg_params or [] # backward compat
# Write "_video"_arg - indicating webcam support
self.request._video = None
regex_match = re.match(r"<video(\d+)>", self.request.filename)
if regex_match:
self.request._video = self.request.filename
# Get local filename
if self.request._video:
index = int(regex_match.group(1))
self._filename = self._get_cam_inputname(index)
else:
self._filename = self.request.get_local_filename()
# When passed to ffmpeg on command line, carets need to be escaped.
self._filename = self._filename.replace("^", "^^")
# Determine pixel format and depth
self._depth = 3
if self._dtype.name == "uint8":
self._pix_fmt = "rgb24"
self._bytes_per_channel = 1
else:
self._pix_fmt = "rgb48le"
self._bytes_per_channel = 2
# Initialize parameters
self._pos = -1
self._meta = {"plugin": "ffmpeg"}
self._lastread = None
# Calculating this from fps and duration is not accurate,
# and calculating it exactly with ffmpeg_api.count_frames_and_secs
# takes too long to do for each video. But we need it for looping.
self._nframes = float("inf")
if self._arg_loop and not self.request._video:
self._nframes = self.count_frames()
self._meta["nframes"] = self._nframes
# Specify input framerate? (only on macOS)
# Ideally we'd get the supported framerate from the metadata, but we get the
# metadata when we boot ffmpeg ... maybe we could refactor this so we can
# get the metadata beforehand, but for now we'll just give it 2 tries on MacOS,
# one with fps 30 and one with fps 15.
need_input_fps = need_output_fps = False
if self.request._video and platform.system().lower() == "darwin":
if "-framerate" not in str(self._arg_input_params):
need_input_fps = True
if not self.request.kwargs.get("fps", None):
need_output_fps = True
if need_input_fps:
self._arg_input_params.extend(["-framerate", str(float(30))])
if need_output_fps:
self._arg_output_params.extend(["-r", str(float(30))])
# Start ffmpeg subprocess and get meta information
try:
self._initialize()
except IndexError:
# Specify input framerate again, this time different.
if need_input_fps:
self._arg_input_params[-1] = str(float(15))
self._initialize()
else:
raise
# For cameras, create thread that keeps reading the images
if self.request._video:
self._frame_catcher = FrameCatcher(self._read_gen)
# For reference - but disabled, because it is inaccurate
# if self._meta["nframes"] == float("inf"):
# if self._meta.get("fps", 0) > 0:
# if self._meta.get("duration", 0) > 0:
# n = round(self._meta["duration"] * self._meta["fps"])
# self._meta["nframes"] = int(n)
def _close(self):
# First close the frame catcher, because we cannot close the gen
# if the frame catcher thread is using it
if self._frame_catcher is not None:
self._frame_catcher.stop_me()
self._frame_catcher = None
if self._read_gen is not None:
self._read_gen.close()
self._read_gen = None
def count_frames(self):
"""Count the number of frames. Note that this can take a few
seconds for large files. Also note that it counts the number
of frames in the original video and does not take a given fps
into account.
"""
# This would have been nice, but this does not work :(
# oargs = []
# if self.request.kwargs.get("fps", None):
# fps = float(self.request.kwargs["fps"])
# oargs += ["-r", "%.02f" % fps]
cf = self._ffmpeg_api.count_frames_and_secs
return cf(self._filename)[0]
def _get_length(self):
return self._nframes # only not inf if loop is True
def _get_data(self, index):
"""Reads a frame at index. Note for coders: getting an
arbitrary frame in the video with ffmpeg can be painfully
slow if some decoding has to be done. This function tries
to avoid fectching arbitrary frames whenever possible, by
moving between adjacent frames."""
# Modulo index (for looping)
if self._arg_loop and self._nframes < float("inf"):
index %= self._nframes
if index == self._pos:
return self._lastread, dict(new=False)
elif index < 0:
raise IndexError("Frame index must be >= 0")
elif index >= self._nframes:
raise IndexError("Reached end of video")
else:
if (index < self._pos) or (index > self._pos + 100):
self._initialize(index)
else:
self._skip_frames(index - self._pos - 1)
result, is_new = self._read_frame()
self._pos = index
return result, dict(new=is_new)
def _get_meta_data(self, index):
return self._meta
def _initialize(self, index=0):
# Close the current generator, and thereby terminate its subprocess
if self._read_gen is not None:
self._read_gen.close()
iargs = []
oargs = []
# Create input args
iargs += self._arg_input_params
if self.request._video:
iargs += ["-f", CAM_FORMAT]
if self._arg_pixelformat:
iargs += ["-pix_fmt", self._arg_pixelformat]
if self._arg_size:
iargs += ["-s", self._arg_size]
elif index > 0: # re-initialize / seek
# Note: only works if we initialized earlier, and now have meta
# Some info here: https://trac.ffmpeg.org/wiki/Seeking
# There are two ways to seek, one before -i (input_params) and
# after (output_params). The former is fast, because it uses
# keyframes, the latter is slow but accurate. According to
# the article above, the fast method should also be accurate
# from ffmpeg version 2.1, however in version 4.1 our tests
# start failing again. Not sure why, but we can solve this
# by combining slow and fast. Seek the long stretch using
# the fast method, and seek the last 10s the slow way.
starttime = index / self._meta["fps"]
seek_slow = min(10, starttime)
seek_fast = starttime - seek_slow
# We used to have this epsilon earlier, when we did not use
# the slow seek. I don't think we need it anymore.
# epsilon = -1 / self._meta["fps"] * 0.1
iargs += ["-ss", "%.06f" % (seek_fast)]
oargs += ["-ss", "%.06f" % (seek_slow)]
# Output args, for writing to pipe
if self._arg_size:
oargs += ["-s", self._arg_size]
if self.request.kwargs.get("fps", None):
fps = float(self.request.kwargs["fps"])
oargs += ["-r", "%.02f" % fps]
oargs += self._arg_output_params
# Get pixelformat and bytes per pixel
pix_fmt = self._pix_fmt
bpp = self._depth * self._bytes_per_channel
# Create generator
rf = self._ffmpeg_api.read_frames
self._read_gen = rf(
self._filename, pix_fmt, bpp, input_params=iargs, output_params=oargs
)
# Read meta data. This start the generator (and ffmpeg subprocess)
if self.request._video:
# With cameras, catch error and turn into IndexError
try:
meta = self._read_gen.__next__()
except IOError as err:
err_text = str(err)
if "darwin" in sys.platform:
if "Unknown input format: 'avfoundation'" in err_text:
err_text += (
"Try installing FFMPEG using "
"home brew to get a version with "
"support for cameras."
)
raise IndexError(
"No (working) camera at {}.\n\n{}".format(
self.request._video, err_text
)
)
else:
self._meta.update(meta)
elif index == 0:
self._meta.update(self._read_gen.__next__())
else:
self._read_gen.__next__() # we already have meta data
def _skip_frames(self, n=1):
"""Reads and throws away n frames"""
for i in range(n):
self._read_gen.__next__()
self._pos += n
def _read_frame(self):
# Read and convert to numpy array
w, h = self._meta["size"]
framesize = w * h * self._depth * self._bytes_per_channel
# t0 = time.time()
# Read frame
if self._frame_catcher: # pragma: no cover - camera thing
s, is_new = self._frame_catcher.get_frame()
else:
s = self._read_gen.__next__()
is_new = True
# Check
if len(s) != framesize:
raise RuntimeError(
"Frame is %i bytes, but expected %i." % (len(s), framesize)
)
result = np.frombuffer(s, dtype=self._dtype).copy()
result = result.reshape((h, w, self._depth))
# t1 = time.time()
# print('etime', t1-t0)
# Store and return
self._lastread = result
return result, is_new
# --
class Writer(Format.Writer):
_write_gen = None
def _open(
self,
fps=10,
codec="libx264",
bitrate=None,
pixelformat="yuv420p",
ffmpeg_params=None,
input_params=None,
output_params=None,
ffmpeg_log_level="quiet",
quality=5,
macro_block_size=16,
audio_path=None,
audio_codec=None,
):
self._ffmpeg_api = imageio_ffmpeg
self._filename = self.request.get_local_filename()
self._pix_fmt = None
self._depth = None
self._size = None
def _close(self):
if self._write_gen is not None:
self._write_gen.close()
self._write_gen = None
def _append_data(self, im, meta):
# Get props of image
h, w = im.shape[:2]
size = w, h
depth = 1 if im.ndim == 2 else im.shape[2]
# Ensure that image is in uint8
im = image_as_uint(im, bitdepth=8)
# To be written efficiently, ie. without creating an immutable
# buffer, by calling im.tobytes() the array must be contiguous.
if not im.flags.c_contiguous:
# checkign the flag is a micro optimization.
# the image will be a numpy subclass. See discussion
# https://github.com/numpy/numpy/issues/11804
im = np.ascontiguousarray(im)
# Set size and initialize if not initialized yet
if self._size is None:
map = {1: "gray", 2: "gray8a", 3: "rgb24", 4: "rgba"}
self._pix_fmt = map.get(depth, None)
if self._pix_fmt is None:
raise ValueError("Image must have 1, 2, 3 or 4 channels")
self._size = size
self._depth = depth
self._initialize()
# Check size of image
if size != self._size:
raise ValueError("All images in a movie should have same size")
if depth != self._depth:
raise ValueError(
"All images in a movie should have same " "number of channels"
)
assert self._write_gen is not None # Check status
# Write. Yes, we can send the data in as a numpy array
self._write_gen.send(im)
def set_meta_data(self, meta):
raise RuntimeError(
"The ffmpeg format does not support setting " "meta data."
)
def _initialize(self):
# Close existing generator
if self._write_gen is not None:
self._write_gen.close()
# Get parameters
# Use None to let imageio-ffmpeg (or ffmpeg) select good results
fps = self.request.kwargs.get("fps", 10)
codec = self.request.kwargs.get("codec", None)
bitrate = self.request.kwargs.get("bitrate", None)
quality = self.request.kwargs.get("quality", None)
input_params = self.request.kwargs.get("input_params") or []
output_params = self.request.kwargs.get("output_params") or []
output_params += self.request.kwargs.get("ffmpeg_params") or []
pixelformat = self.request.kwargs.get("pixelformat", None)
macro_block_size = self.request.kwargs.get("macro_block_size", 16)
ffmpeg_log_level = self.request.kwargs.get("ffmpeg_log_level", None)
audio_path = self.request.kwargs.get("audio_path", None)
audio_codec = self.request.kwargs.get("audio_codec", None)
macro_block_size = macro_block_size or 1 # None -> 1
# Create generator
self._write_gen = self._ffmpeg_api.write_frames(
self._filename,
self._size,
pix_fmt_in=self._pix_fmt,
pix_fmt_out=pixelformat,
fps=fps,
quality=quality,
bitrate=bitrate,
codec=codec,
macro_block_size=macro_block_size,
ffmpeg_log_level=ffmpeg_log_level,
input_params=input_params,
output_params=output_params,
audio_path=audio_path,
audio_codec=audio_codec,
)
# Seed the generator (this is where the ffmpeg subprocess starts)
self._write_gen.send(None)
class FrameCatcher(threading.Thread):
"""Thread to keep reading the frame data from stdout. This is
useful when streaming from a webcam. Otherwise, if the user code
does not grab frames fast enough, the buffer will fill up, leading
to lag, and ffmpeg can also stall (experienced on Linux). The
get_frame() method always returns the last available image.
"""
def __init__(self, gen):
self._gen = gen
self._frame = None
self._frame_is_new = False
self._lock = threading.RLock()
threading.Thread.__init__(self)
self.daemon = True # do not let this thread hold up Python shutdown
self._should_stop = False
self.start()
def stop_me(self):
self._should_stop = True
while self.is_alive():
time.sleep(0.001)
def get_frame(self):
while self._frame is None: # pragma: no cover - an init thing
time.sleep(0.001)
with self._lock:
is_new = self._frame_is_new
self._frame_is_new = False # reset
return self._frame, is_new
def run(self):
# This runs in the worker thread
try:
while not self._should_stop:
time.sleep(0) # give control to other threads
frame = self._gen.__next__()
with self._lock:
self._frame = frame
self._frame_is_new = True
except (StopIteration, EOFError):
pass
def parse_device_names(ffmpeg_output):
"""Parse the output of the ffmpeg -list-devices command"""
# Collect device names - get [friendly_name, alt_name] of each
device_names = []
in_video_devices = False
for line in ffmpeg_output.splitlines():
if line.startswith("[dshow"):
logger.debug(line)
line = line.split("]", 1)[1].strip()
if in_video_devices and line.startswith('"'):
friendly_name = line[1:-1]
device_names.append([friendly_name, ""])
elif in_video_devices and line.lower().startswith("alternative name"):
alt_name = line.split(" name ", 1)[1].strip()[1:-1]
if sys.platform.startswith("win"):
alt_name = alt_name.replace("&", "^&") # Tested to work
else:
alt_name = alt_name.replace("&", "\\&") # Does this work?
device_names[-1][-1] = alt_name
elif "video devices" in line:
in_video_devices = True
elif "devices" in line:
# set False for subsequent "devices" sections
in_video_devices = False
# Post-process, see #441
# prefer friendly names, use alt name if two cams have same friendly name
device_names2 = []
for friendly_name, alt_name in device_names:
if friendly_name not in device_names2:
device_names2.append(friendly_name)
elif alt_name:
device_names2.append(alt_name)
else:
device_names2.append(friendly_name) # duplicate, but not much we can do
return device_names2

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@@ -1,126 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
"""Read FITS files.
Backend Library: `Astropy <https://www.astropy.org/>`_
.. note::
To use this plugin you have to install its backend::
pip install imageio[fits]
Flexible Image Transport System (FITS) is an open standard defining a
digital file format useful for storage, transmission and processing of
scientific and other images. FITS is the most commonly used digital
file format in astronomy.
Parameters
----------
cache : bool
If the file name is a URL, `~astropy.utils.data.download_file` is used
to open the file. This specifies whether or not to save the file
locally in Astropy's download cache (default: `True`).
uint : bool
Interpret signed integer data where ``BZERO`` is the
central value and ``BSCALE == 1`` as unsigned integer
data. For example, ``int16`` data with ``BZERO = 32768``
and ``BSCALE = 1`` would be treated as ``uint16`` data.
Note, for backward compatibility, the kwarg **uint16** may
be used instead. The kwarg was renamed when support was
added for integers of any size.
ignore_missing_end : bool
Do not issue an exception when opening a file that is
missing an ``END`` card in the last header.
checksum : bool or str
If `True`, verifies that both ``DATASUM`` and
``CHECKSUM`` card values (when present in the HDU header)
match the header and data of all HDU's in the file. Updates to a
file that already has a checksum will preserve and update the
existing checksums unless this argument is given a value of
'remove', in which case the CHECKSUM and DATASUM values are not
checked, and are removed when saving changes to the file.
disable_image_compression : bool, optional
If `True`, treats compressed image HDU's like normal
binary table HDU's.
do_not_scale_image_data : bool
If `True`, image data is not scaled using BSCALE/BZERO values
when read.
ignore_blank : bool
If `True`, the BLANK keyword is ignored if present.
scale_back : bool
If `True`, when saving changes to a file that contained scaled
image data, restore the data to the original type and reapply the
original BSCALE/BZERO values. This could lead to loss of accuracy
if scaling back to integer values after performing floating point
operations on the data.
"""
from ..core import Format
_fits = None # lazily loaded
def load_lib():
global _fits
try:
from astropy.io import fits as _fits
except ImportError:
raise ImportError(
"The FITS format relies on the astropy package."
"Please refer to http://www.astropy.org/ "
"for further instructions."
)
return _fits
class FitsFormat(Format):
"""See :mod:`imageio.plugins.fits`"""
def _can_read(self, request):
# We return True if ext matches, because this is the only plugin
# that can. If astropy is not installed, a useful error follows.
return request.extension in self.extensions
def _can_write(self, request):
# No write support
return False
# -- reader
class Reader(Format.Reader):
def _open(self, cache=False, **kwargs):
if not _fits:
load_lib()
hdulist = _fits.open(self.request.get_file(), cache=cache, **kwargs)
self._index = []
allowed_hdu_types = (_fits.ImageHDU, _fits.PrimaryHDU, _fits.CompImageHDU)
for n, hdu in zip(range(len(hdulist)), hdulist):
if isinstance(hdu, allowed_hdu_types):
# Ignore (primary) header units with no data (use '.size'
# rather than '.data' to avoid actually loading the image):
if hdu.size > 0:
self._index.append(n)
self._hdulist = hdulist
def _close(self):
self._hdulist.close()
def _get_length(self):
return len(self._index)
def _get_data(self, index):
# Get data
if index < 0 or index >= len(self._index):
raise IndexError("Index out of range while reading from fits")
im = self._hdulist[self._index[index]].data
# Return array and empty meta data
return im, {}
def _get_meta_data(self, index):
# Get the meta data for the given index
raise RuntimeError("The fits format does not support meta data.")

View File

@@ -1,404 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
"""Read/Write images using FreeImage.
Backend Library: `FreeImage <https://freeimage.sourceforge.io/>`_
.. note::
To use this plugin you have to install its backend::
imageio_download_bin freeimage
or you can download the backend using the function::
imageio.plugins.freeimage.download()
Each Freeimage format has the ``flags`` keyword argument. See the `Freeimage
documentation <https://freeimage.sourceforge.io/>`_ for more information.
Parameters
----------
flags : int
A freeimage-specific option. In most cases we provide explicit
parameters for influencing image reading.
"""
import numpy as np
from ..core import Format, image_as_uint
from ..core.request import RETURN_BYTES
from ._freeimage import FNAME_PER_PLATFORM, IO_FLAGS, download, fi # noqa
# todo: support files with only meta data
class FreeimageFormat(Format):
"""See :mod:`imageio.plugins.freeimage`"""
_modes = "i"
def __init__(self, name, description, extensions=None, modes=None, *, fif=None):
super().__init__(name, description, extensions=extensions, modes=modes)
self._fif = fif
@property
def fif(self):
return self._fif # Set when format is created
def _can_read(self, request):
# Ask freeimage if it can read it, maybe ext missing
if fi.has_lib():
if not hasattr(request, "_fif"):
try:
request._fif = fi.getFIF(request.filename, "r", request.firstbytes)
except Exception: # pragma: no cover
request._fif = -1
if request._fif == self.fif:
return True
elif request._fif == 7 and self.fif == 14:
# PPM gets identified as PBM and PPM can read PBM
# see: https://github.com/imageio/imageio/issues/677
return True
def _can_write(self, request):
# Ask freeimage, because we are not aware of all formats
if fi.has_lib():
if not hasattr(request, "_fif"):
try:
request._fif = fi.getFIF(request.filename, "w")
except ValueError: # pragma: no cover
if request.raw_uri == RETURN_BYTES:
request._fif = self.fif
else:
request._fif = -1
if request._fif is self.fif:
return True
# --
class Reader(Format.Reader):
def _get_length(self):
return 1
def _open(self, flags=0):
self._bm = fi.create_bitmap(self.request.filename, self.format.fif, flags)
self._bm.load_from_filename(self.request.get_local_filename())
def _close(self):
self._bm.close()
def _get_data(self, index):
if index != 0:
raise IndexError("This format only supports singleton images.")
return self._bm.get_image_data(), self._bm.get_meta_data()
def _get_meta_data(self, index):
if not (index is None or index == 0):
raise IndexError()
return self._bm.get_meta_data()
# --
class Writer(Format.Writer):
def _open(self, flags=0):
self._flags = flags # Store flags for later use
self._bm = None
self._is_set = False # To prevent appending more than one image
self._meta = {}
def _close(self):
# Set global meta data
self._bm.set_meta_data(self._meta)
# Write and close
self._bm.save_to_filename(self.request.get_local_filename())
self._bm.close()
def _append_data(self, im, meta):
# Check if set
if not self._is_set:
self._is_set = True
else:
raise RuntimeError(
"Singleton image; " "can only append image data once."
)
# Pop unit dimension for grayscale images
if im.ndim == 3 and im.shape[-1] == 1:
im = im[:, :, 0]
# Lazy instantaion of the bitmap, we need image data
if self._bm is None:
self._bm = fi.create_bitmap(
self.request.filename, self.format.fif, self._flags
)
self._bm.allocate(im)
# Set data
self._bm.set_image_data(im)
# There is no distinction between global and per-image meta data
# for singleton images
self._meta = meta
def _set_meta_data(self, meta):
self._meta = meta
# Special plugins
# todo: there is also FIF_LOAD_NOPIXELS,
# but perhaps that should be used with get_meta_data.
class FreeimageBmpFormat(FreeimageFormat):
"""A BMP format based on the Freeimage library.
This format supports grayscale, RGB and RGBA images.
The freeimage plugin requires a `freeimage` binary. If this binary
not available on the system, it can be downloaded manually from
<https://github.com/imageio/imageio-binaries> by either
- the command line script ``imageio_download_bin freeimage``
- the Python method ``imageio.plugins.freeimage.download()``
Parameters for saving
---------------------
compression : bool
Whether to compress the bitmap using RLE when saving. Default False.
It seems this does not always work, but who cares, you should use
PNG anyway.
"""
class Writer(FreeimageFormat.Writer):
def _open(self, flags=0, compression=False):
# Build flags from kwargs
flags = int(flags)
if compression:
flags |= IO_FLAGS.BMP_SAVE_RLE
else:
flags |= IO_FLAGS.BMP_DEFAULT
# Act as usual, but with modified flags
return FreeimageFormat.Writer._open(self, flags)
def _append_data(self, im, meta):
im = image_as_uint(im, bitdepth=8)
return FreeimageFormat.Writer._append_data(self, im, meta)
class FreeimagePngFormat(FreeimageFormat):
"""A PNG format based on the Freeimage library.
This format supports grayscale, RGB and RGBA images.
The freeimage plugin requires a `freeimage` binary. If this binary
not available on the system, it can be downloaded manually from
<https://github.com/imageio/imageio-binaries> by either
- the command line script ``imageio_download_bin freeimage``
- the Python method ``imageio.plugins.freeimage.download()``
Parameters for reading
----------------------
ignoregamma : bool
Avoid gamma correction. Default True.
Parameters for saving
---------------------
compression : {0, 1, 6, 9}
The compression factor. Higher factors result in more
compression at the cost of speed. Note that PNG compression is
always lossless. Default 9.
quantize : int
If specified, turn the given RGB or RGBA image in a paletted image
for more efficient storage. The value should be between 2 and 256.
If the value of 0 the image is not quantized.
interlaced : bool
Save using Adam7 interlacing. Default False.
"""
class Reader(FreeimageFormat.Reader):
def _open(self, flags=0, ignoregamma=True):
# Build flags from kwargs
flags = int(flags)
if ignoregamma:
flags |= IO_FLAGS.PNG_IGNOREGAMMA
# Enter as usual, with modified flags
return FreeimageFormat.Reader._open(self, flags)
# --
class Writer(FreeimageFormat.Writer):
def _open(self, flags=0, compression=9, quantize=0, interlaced=False):
compression_map = {
0: IO_FLAGS.PNG_Z_NO_COMPRESSION,
1: IO_FLAGS.PNG_Z_BEST_SPEED,
6: IO_FLAGS.PNG_Z_DEFAULT_COMPRESSION,
9: IO_FLAGS.PNG_Z_BEST_COMPRESSION,
}
# Build flags from kwargs
flags = int(flags)
if interlaced:
flags |= IO_FLAGS.PNG_INTERLACED
try:
flags |= compression_map[compression]
except KeyError:
raise ValueError("Png compression must be 0, 1, 6, or 9.")
# Act as usual, but with modified flags
return FreeimageFormat.Writer._open(self, flags)
def _append_data(self, im, meta):
if str(im.dtype) == "uint16":
im = image_as_uint(im, bitdepth=16)
else:
im = image_as_uint(im, bitdepth=8)
FreeimageFormat.Writer._append_data(self, im, meta)
# Quantize?
q = int(self.request.kwargs.get("quantize", False))
if not q:
pass
elif not (im.ndim == 3 and im.shape[-1] == 3):
raise ValueError("Can only quantize RGB images")
elif q < 2 or q > 256:
raise ValueError("PNG quantize param must be 2..256")
else:
bm = self._bm.quantize(0, q)
self._bm.close()
self._bm = bm
class FreeimageJpegFormat(FreeimageFormat):
"""A JPEG format based on the Freeimage library.
This format supports grayscale and RGB images.
The freeimage plugin requires a `freeimage` binary. If this binary
not available on the system, it can be downloaded manually from
<https://github.com/imageio/imageio-binaries> by either
- the command line script ``imageio_download_bin freeimage``
- the Python method ``imageio.plugins.freeimage.download()``
Parameters for reading
----------------------
exifrotate : bool
Automatically rotate the image according to the exif flag.
Default True. If 2 is given, do the rotation in Python instead
of freeimage.
quickread : bool
Read the image more quickly, at the expense of quality.
Default False.
Parameters for saving
---------------------
quality : scalar
The compression factor of the saved image (1..100), higher
numbers result in higher quality but larger file size. Default 75.
progressive : bool
Save as a progressive JPEG file (e.g. for images on the web).
Default False.
optimize : bool
On saving, compute optimal Huffman coding tables (can reduce a
few percent of file size). Default False.
baseline : bool
Save basic JPEG, without metadata or any markers. Default False.
"""
class Reader(FreeimageFormat.Reader):
def _open(self, flags=0, exifrotate=True, quickread=False):
# Build flags from kwargs
flags = int(flags)
if exifrotate and exifrotate != 2:
flags |= IO_FLAGS.JPEG_EXIFROTATE
if not quickread:
flags |= IO_FLAGS.JPEG_ACCURATE
# Enter as usual, with modified flags
return FreeimageFormat.Reader._open(self, flags)
def _get_data(self, index):
im, meta = FreeimageFormat.Reader._get_data(self, index)
im = self._rotate(im, meta)
return im, meta
def _rotate(self, im, meta):
"""Use Orientation information from EXIF meta data to
orient the image correctly. Freeimage is also supposed to
support that, and I am pretty sure it once did, but now it
does not, so let's just do it in Python.
Edit: and now it works again, just leave in place as a fallback.
"""
if self.request.kwargs.get("exifrotate", None) == 2:
try:
ori = meta["EXIF_MAIN"]["Orientation"]
except KeyError: # pragma: no cover
pass # Orientation not available
else: # pragma: no cover - we cannot touch all cases
# www.impulseadventure.com/photo/exif-orientation.html
if ori in [1, 2]:
pass
if ori in [3, 4]:
im = np.rot90(im, 2)
if ori in [5, 6]:
im = np.rot90(im, 3)
if ori in [7, 8]:
im = np.rot90(im)
if ori in [2, 4, 5, 7]: # Flipped cases (rare)
im = np.fliplr(im)
return im
# --
class Writer(FreeimageFormat.Writer):
def _open(
self, flags=0, quality=75, progressive=False, optimize=False, baseline=False
):
# Test quality
quality = int(quality)
if quality < 1 or quality > 100:
raise ValueError("JPEG quality should be between 1 and 100.")
# Build flags from kwargs
flags = int(flags)
flags |= quality
if progressive:
flags |= IO_FLAGS.JPEG_PROGRESSIVE
if optimize:
flags |= IO_FLAGS.JPEG_OPTIMIZE
if baseline:
flags |= IO_FLAGS.JPEG_BASELINE
# Act as usual, but with modified flags
return FreeimageFormat.Writer._open(self, flags)
def _append_data(self, im, meta):
if im.ndim == 3 and im.shape[-1] == 4:
raise IOError("JPEG does not support alpha channel.")
im = image_as_uint(im, bitdepth=8)
return FreeimageFormat.Writer._append_data(self, im, meta)
class FreeimagePnmFormat(FreeimageFormat):
"""A PNM format based on the Freeimage library.
This format supports single bit (PBM), grayscale (PGM) and RGB (PPM)
images, even with ASCII or binary coding.
The freeimage plugin requires a `freeimage` binary. If this binary
not available on the system, it can be downloaded manually from
<https://github.com/imageio/imageio-binaries> by either
- the command line script ``imageio_download_bin freeimage``
- the Python method ``imageio.plugins.freeimage.download()``
Parameters for saving
---------------------
use_ascii : bool
Save with ASCII coding. Default True.
"""
class Writer(FreeimageFormat.Writer):
def _open(self, flags=0, use_ascii=True):
# Build flags from kwargs
flags = int(flags)
if use_ascii:
flags |= IO_FLAGS.PNM_SAVE_ASCII
# Act as usual, but with modified flags
return FreeimageFormat.Writer._open(self, flags)

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@@ -1,316 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
"""Plugin for multi-image freeimafe formats, like animated GIF and ico.
"""
import logging
import numpy as np
from ..core import Format, image_as_uint
from ._freeimage import fi, IO_FLAGS
from .freeimage import FreeimageFormat
logger = logging.getLogger(__name__)
class FreeimageMulti(FreeimageFormat):
"""Base class for freeimage formats that support multiple images."""
_modes = "iI"
_fif = -1
class Reader(Format.Reader):
def _open(self, flags=0):
flags = int(flags)
# Create bitmap
self._bm = fi.create_multipage_bitmap(
self.request.filename, self.format.fif, flags
)
self._bm.load_from_filename(self.request.get_local_filename())
def _close(self):
self._bm.close()
def _get_length(self):
return len(self._bm)
def _get_data(self, index):
sub = self._bm.get_page(index)
try:
return sub.get_image_data(), sub.get_meta_data()
finally:
sub.close()
def _get_meta_data(self, index):
index = index or 0
if index < 0 or index >= len(self._bm):
raise IndexError()
sub = self._bm.get_page(index)
try:
return sub.get_meta_data()
finally:
sub.close()
# --
class Writer(FreeimageFormat.Writer):
def _open(self, flags=0):
# Set flags
self._flags = flags = int(flags)
# Instantiate multi-page bitmap
self._bm = fi.create_multipage_bitmap(
self.request.filename, self.format.fif, flags
)
self._bm.save_to_filename(self.request.get_local_filename())
def _close(self):
# Close bitmap
self._bm.close()
def _append_data(self, im, meta):
# Prepare data
if im.ndim == 3 and im.shape[-1] == 1:
im = im[:, :, 0]
im = image_as_uint(im, bitdepth=8)
# Create sub bitmap
sub1 = fi.create_bitmap(self._bm._filename, self.format.fif)
# Let subclass add data to bitmap, optionally return new
sub2 = self._append_bitmap(im, meta, sub1)
# Add
self._bm.append_bitmap(sub2)
sub2.close()
if sub1 is not sub2:
sub1.close()
def _append_bitmap(self, im, meta, bitmap):
# Set data
bitmap.allocate(im)
bitmap.set_image_data(im)
bitmap.set_meta_data(meta)
# Return that same bitmap
return bitmap
def _set_meta_data(self, meta):
pass # ignore global meta data
class MngFormat(FreeimageMulti):
"""An Mng format based on the Freeimage library.
Read only. Seems broken.
"""
_fif = 6
def _can_write(self, request): # pragma: no cover
return False
class IcoFormat(FreeimageMulti):
"""An ICO format based on the Freeimage library.
This format supports grayscale, RGB and RGBA images.
The freeimage plugin requires a `freeimage` binary. If this binary
is not available on the system, it can be downloaded by either
- the command line script ``imageio_download_bin freeimage``
- the Python method ``imageio.plugins.freeimage.download()``
Parameters for reading
----------------------
makealpha : bool
Convert to 32-bit and create an alpha channel from the AND-
mask when loading. Default False. Note that this returns wrong
results if the image was already RGBA.
"""
_fif = 1
class Reader(FreeimageMulti.Reader):
def _open(self, flags=0, makealpha=False):
# Build flags from kwargs
flags = int(flags)
if makealpha:
flags |= IO_FLAGS.ICO_MAKEALPHA
return FreeimageMulti.Reader._open(self, flags)
class GifFormat(FreeimageMulti):
"""A format for reading and writing static and animated GIF, based
on the Freeimage library.
Images read with this format are always RGBA. Currently,
the alpha channel is ignored when saving RGB images with this
format.
The freeimage plugin requires a `freeimage` binary. If this binary
is not available on the system, it can be downloaded by either
- the command line script ``imageio_download_bin freeimage``
- the Python method ``imageio.plugins.freeimage.download()``
Parameters for reading
----------------------
playback : bool
'Play' the GIF to generate each frame (as 32bpp) instead of
returning raw frame data when loading. Default True.
Parameters for saving
---------------------
loop : int
The number of iterations. Default 0 (meaning loop indefinitely)
duration : {float, list}
The duration (in seconds) of each frame. Either specify one value
that is used for all frames, or one value for each frame.
Note that in the GIF format the duration/delay is expressed in
hundredths of a second, which limits the precision of the duration.
fps : float
The number of frames per second. If duration is not given, the
duration for each frame is set to 1/fps. Default 10.
palettesize : int
The number of colors to quantize the image to. Is rounded to
the nearest power of two. Default 256.
quantizer : {'wu', 'nq'}
The quantization algorithm:
* wu - Wu, Xiaolin, Efficient Statistical Computations for
Optimal Color Quantization
* nq (neuqant) - Dekker A. H., Kohonen neural networks for
optimal color quantization
subrectangles : bool
If True, will try and optimize the GIF by storing only the
rectangular parts of each frame that change with respect to the
previous. Unfortunately, this option seems currently broken
because FreeImage does not handle DisposalMethod correctly.
Default False.
"""
_fif = 25
class Reader(FreeimageMulti.Reader):
def _open(self, flags=0, playback=True):
# Build flags from kwargs
flags = int(flags)
if playback:
flags |= IO_FLAGS.GIF_PLAYBACK
FreeimageMulti.Reader._open(self, flags)
def _get_data(self, index):
im, meta = FreeimageMulti.Reader._get_data(self, index)
# im = im[:, :, :3] # Drop alpha channel
return im, meta
# -- writer
class Writer(FreeimageMulti.Writer):
# todo: subrectangles
# todo: global palette
def _open(
self,
flags=0,
loop=0,
duration=None,
fps=10,
palettesize=256,
quantizer="Wu",
subrectangles=False,
):
# Check palettesize
if palettesize < 2 or palettesize > 256:
raise ValueError("GIF quantize param must be 2..256")
if palettesize not in [2, 4, 8, 16, 32, 64, 128, 256]:
palettesize = 2 ** int(np.log2(128) + 0.999)
logger.warning(
"Warning: palettesize (%r) modified to a factor of "
"two between 2-256." % palettesize
)
self._palettesize = palettesize
# Check quantizer
self._quantizer = {"wu": 0, "nq": 1}.get(quantizer.lower(), None)
if self._quantizer is None:
raise ValueError('Invalid quantizer, must be "wu" or "nq".')
# Check frametime
if duration is None:
self._frametime = [int(1000 / float(fps) + 0.5)]
elif isinstance(duration, list):
self._frametime = [int(1000 * d) for d in duration]
elif isinstance(duration, (float, int)):
self._frametime = [int(1000 * duration)]
else:
raise ValueError("Invalid value for duration: %r" % duration)
# Check subrectangles
self._subrectangles = bool(subrectangles)
self._prev_im = None
# Init
FreeimageMulti.Writer._open(self, flags)
# Set global meta data
self._meta = {}
self._meta["ANIMATION"] = {
# 'GlobalPalette': np.array([0]).astype(np.uint8),
"Loop": np.array([loop]).astype(np.uint32),
# 'LogicalWidth': np.array([x]).astype(np.uint16),
# 'LogicalHeight': np.array([x]).astype(np.uint16),
}
def _append_bitmap(self, im, meta, bitmap):
# Prepare meta data
meta = meta.copy()
meta_a = meta["ANIMATION"] = {}
# If this is the first frame, assign it our "global" meta data
if len(self._bm) == 0:
meta.update(self._meta)
meta_a = meta["ANIMATION"]
# Set frame time
index = len(self._bm)
if index < len(self._frametime):
ft = self._frametime[index]
else:
ft = self._frametime[-1]
meta_a["FrameTime"] = np.array([ft]).astype(np.uint32)
# Check array
if im.ndim == 3 and im.shape[-1] == 4:
im = im[:, :, :3]
# Process subrectangles
im_uncropped = im
if self._subrectangles and self._prev_im is not None:
im, xy = self._get_sub_rectangles(self._prev_im, im)
meta_a["DisposalMethod"] = np.array([1]).astype(np.uint8)
meta_a["FrameLeft"] = np.array([xy[0]]).astype(np.uint16)
meta_a["FrameTop"] = np.array([xy[1]]).astype(np.uint16)
self._prev_im = im_uncropped
# Set image data
sub2 = sub1 = bitmap
sub1.allocate(im)
sub1.set_image_data(im)
# Quantize it if its RGB
if im.ndim == 3 and im.shape[-1] == 3:
sub2 = sub1.quantize(self._quantizer, self._palettesize)
# Set meta data and return
sub2.set_meta_data(meta)
return sub2
def _get_sub_rectangles(self, prev, im):
"""
Calculate the minimal rectangles that need updating each frame.
Returns a two-element tuple containing the cropped images and a
list of x-y positions.
"""
# Get difference, sum over colors
diff = np.abs(im - prev)
if diff.ndim == 3:
diff = diff.sum(2)
# Get begin and end for both dimensions
X = np.argwhere(diff.sum(0))
Y = np.argwhere(diff.sum(1))
# Get rect coordinates
if X.size and Y.size:
x0, x1 = int(X[0]), int(X[-1]) + 1
y0, y1 = int(Y[0]), int(Y[-1]) + 1
else: # No change ... make it minimal
x0, x1 = 0, 2
y0, y1 = 0, 2
# Cut out and return
return im[y0:y1, x0:x1], (x0, y0)

View File

@@ -1,71 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
""" Read GDAL files.
Backend: `GDAL <https://gdal.org/>`_
.. note::
To use this plugin you have to install its backend::
pip install imageio[gdal]
Parameters
----------
none
"""
from ..core import Format, has_module
_gdal = None # lazily loaded in load_lib()
def load_lib():
global _gdal
try:
import osgeo.gdal as _gdal
except ImportError:
raise ImportError(
"The GDAL format relies on the GDAL package."
"Please refer to http://www.gdal.org/"
"for further instructions."
)
return _gdal
GDAL_FORMATS = (".tiff", " .tif", ".img", ".ecw", ".jpg", ".jpeg")
class GdalFormat(Format):
"""See :mod:`imageio.plugins.gdal`"""
def _can_read(self, request):
if request.extension in (".ecw",):
return True
if has_module("osgeo.gdal"):
return request.extension in self.extensions
def _can_write(self, request):
return False
# --
class Reader(Format.Reader):
def _open(self):
if not _gdal:
load_lib()
self._ds = _gdal.Open(self.request.get_local_filename())
def _close(self):
del self._ds
def _get_length(self):
return 1
def _get_data(self, index):
if index != 0:
raise IndexError("Gdal file contains only one dataset")
return self._ds.ReadAsArray(), self._get_meta_data(index)
def _get_meta_data(self, index):
return self._ds.GetMetadata()

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@@ -1,105 +0,0 @@
"""
PIL-based formats to take screenshots and grab from the clipboard.
"""
import threading
import numpy as np
from ..core import Format
class BaseGrabFormat(Format):
"""Base format for grab formats."""
_pillow_imported = False
_ImageGrab = None
def __init__(self, *args, **kwargs):
super(BaseGrabFormat, self).__init__(*args, **kwargs)
self._lock = threading.RLock()
def _can_write(self, request):
return False
def _init_pillow(self):
with self._lock:
if not self._pillow_imported:
self._pillow_imported = True # more like tried to import
import PIL
if not hasattr(PIL, "__version__"): # pragma: no cover
raise ImportError("Imageio Pillow requires " "Pillow, not PIL!")
try:
from PIL import ImageGrab
except ImportError:
return None
self._ImageGrab = ImageGrab
return self._ImageGrab
class Reader(Format.Reader):
def _open(self):
pass
def _close(self):
pass
def _get_data(self, index):
return self.format._get_data(index)
class ScreenGrabFormat(BaseGrabFormat):
"""The ScreenGrabFormat provided a means to grab screenshots using
the uri of "<screen>".
This functionality is provided via Pillow. Note that "<screen>" is
only supported on Windows and OS X.
Parameters for reading
----------------------
No parameters.
"""
def _can_read(self, request):
if request.filename != "<screen>":
return False
return bool(self._init_pillow())
def _get_data(self, index):
ImageGrab = self._init_pillow()
assert ImageGrab
pil_im = ImageGrab.grab()
assert pil_im is not None
im = np.asarray(pil_im)
return im, {}
class ClipboardGrabFormat(BaseGrabFormat):
"""The ClipboardGrabFormat provided a means to grab image data from
the clipboard, using the uri "<clipboard>"
This functionality is provided via Pillow. Note that "<clipboard>" is
only supported on Windows.
Parameters for reading
----------------------
No parameters.
"""
def _can_read(self, request):
if request.filename != "<clipboard>":
return False
return bool(self._init_pillow())
def _get_data(self, index):
ImageGrab = self._init_pillow()
assert ImageGrab
pil_im = ImageGrab.grabclipboard()
if pil_im is None:
raise RuntimeError(
"There seems to be no image data on the " "clipboard now."
)
im = np.asarray(pil_im)
return im, {}

View File

@@ -1,714 +0,0 @@
# -*- coding: utf-8 -*-
# Copyright (c) 2018, imageio contributors
# imageio is distributed under the terms of the (new) BSD License.
#
""" Read LFR files (Lytro Illum).
Backend: internal
Plugin to read Lytro Illum .lfr and .raw files as produced
by the Lytro Illum light field camera. It is actually a collection
of plugins, each supporting slightly different keyword arguments
Parameters
----------
meta_only : bool
Whether to only read the metadata.
include_thumbnail : bool
(only for lytro-lfr and lytro-lfp)
Whether to include an image thumbnail in the metadata.
"""
#
#
# This code is based on work by
# David Uhlig and his lfr_reader
# (https://www.iiit.kit.edu/uhlig.php)
# Donald Dansereau and his Matlab LF Toolbox
# (http://dgd.vision/Tools/LFToolbox/)
# and Behnam Esfahbod and his Python LFP-Reader
# (https://github.com/behnam/python-lfp-reader/)
import os
import json
import struct
import logging
import numpy as np
from ..core import Format
from ..v2 import imread
logger = logging.getLogger(__name__)
# Sensor size of Lytro Illum resp. Lytro F01 light field camera sensor
LYTRO_ILLUM_IMAGE_SIZE = (5368, 7728)
LYTRO_F01_IMAGE_SIZE = (3280, 3280)
# Parameter of lfr file format
HEADER_LENGTH = 12
SIZE_LENGTH = 4 # = 16 - header_length
SHA1_LENGTH = 45 # = len("sha1-") + (160 / 4)
PADDING_LENGTH = 35 # = (4*16) - header_length - size_length - sha1_length
DATA_CHUNKS_ILLUM = 11
DATA_CHUNKS_F01 = 3
class LytroFormat(Format):
"""Base class for Lytro format.
The subclasses LytroLfrFormat, LytroLfpFormat, LytroIllumRawFormat and
LytroF01RawFormat implement the Lytro-LFR, Lytro-LFP and Lytro-RAW format
for the Illum and original F01 camera respectively.
Writing is not supported.
"""
# Only single images are supported.
_modes = "i"
def _can_write(self, request):
# Writing of Lytro files is not supported
return False
# -- writer
class Writer(Format.Writer):
def _open(self, flags=0):
self._fp = self.request.get_file()
def _close(self):
# Close the reader.
# Note that the request object will close self._fp
pass
def _append_data(self, im, meta):
# Process the given data and meta data.
raise RuntimeError("The lytro format cannot write image data.")
def _set_meta_data(self, meta):
# Process the given meta data (global for all images)
# It is not mandatory to support this.
raise RuntimeError("The lytro format cannot write meta data.")
class LytroIllumRawFormat(LytroFormat):
"""This is the Lytro Illum RAW format.
The raw format is a 10bit image format as used by the Lytro Illum
light field camera. The format will read the specified raw file and will
try to load a .txt or .json file with the associated meta data.
This format does not support writing.
Parameters for reading
----------------------
meta_only : bool
Whether to only read the metadata.
"""
def _can_read(self, request):
# Check if mode and extensions are supported by the format
if request.extension in (".raw",):
return True
@staticmethod
def rearrange_bits(array):
# Do bit rearrangement for the 10-bit lytro raw format
# Normalize output to 1.0 as float64
t0 = array[0::5]
t1 = array[1::5]
t2 = array[2::5]
t3 = array[3::5]
lsb = array[4::5]
t0 = np.left_shift(t0, 2) + np.bitwise_and(lsb, 3)
t1 = np.left_shift(t1, 2) + np.right_shift(np.bitwise_and(lsb, 12), 2)
t2 = np.left_shift(t2, 2) + np.right_shift(np.bitwise_and(lsb, 48), 4)
t3 = np.left_shift(t3, 2) + np.right_shift(np.bitwise_and(lsb, 192), 6)
image = np.zeros(LYTRO_ILLUM_IMAGE_SIZE, dtype=np.uint16)
image[:, 0::4] = t0.reshape(
(LYTRO_ILLUM_IMAGE_SIZE[0], LYTRO_ILLUM_IMAGE_SIZE[1] // 4)
)
image[:, 1::4] = t1.reshape(
(LYTRO_ILLUM_IMAGE_SIZE[0], LYTRO_ILLUM_IMAGE_SIZE[1] // 4)
)
image[:, 2::4] = t2.reshape(
(LYTRO_ILLUM_IMAGE_SIZE[0], LYTRO_ILLUM_IMAGE_SIZE[1] // 4)
)
image[:, 3::4] = t3.reshape(
(LYTRO_ILLUM_IMAGE_SIZE[0], LYTRO_ILLUM_IMAGE_SIZE[1] // 4)
)
# Normalize data to 1.0 as 64-bit float.
# Division is by 1023 as the Lytro Illum saves 10-bit raw data.
return np.divide(image, 1023.0).astype(np.float64)
# -- reader
class Reader(Format.Reader):
def _open(self, meta_only=False):
self._file = self.request.get_file()
self._data = None
self._meta_only = meta_only
def _close(self):
# Close the reader.
# Note that the request object will close self._file
del self._data
def _get_length(self):
# Return the number of images.
return 1
def _get_data(self, index):
# Return the data and meta data for the given index
if index not in [0, "None"]:
raise IndexError("Lytro file contains only one dataset")
if not self._meta_only:
# Read all bytes
if self._data is None:
self._data = self._file.read()
# Read bytes from string and convert to uint16
raw = np.frombuffer(self._data, dtype=np.uint8).astype(np.uint16)
# Rearrange bits
img = LytroIllumRawFormat.rearrange_bits(raw)
else:
# Return empty image
img = np.array([])
# Return image and meta data
return img, self._get_meta_data(index=0)
def _get_meta_data(self, index):
# Get the meta data for the given index. If index is None, it
# should return the global meta data.
if index not in [0, None]:
raise IndexError("Lytro meta data file contains only one dataset")
# Try to read meta data from meta data file corresponding
# to the raw data file, extension in [.txt, .TXT, .json, .JSON]
filename_base = os.path.splitext(self.request.get_local_filename())[0]
meta_data = None
for ext in [".txt", ".TXT", ".json", ".JSON"]:
if os.path.isfile(filename_base + ext):
meta_data = json.load(open(filename_base + ext))
if meta_data is not None:
return meta_data
else:
logger.warning("No metadata file found for provided raw file.")
return {}
class LytroLfrFormat(LytroFormat):
"""This is the Lytro Illum LFR format.
The lfr is a image and meta data container format as used by the
Lytro Illum light field camera.
The format will read the specified lfr file.
This format does not support writing.
Parameters for reading
----------------------
meta_only : bool
Whether to only read the metadata.
include_thumbnail : bool
Whether to include an image thumbnail in the metadata.
"""
def _can_read(self, request):
# Check if mode and extensions are supported by the format
if request.extension in (".lfr",):
return True
# -- reader
class Reader(Format.Reader):
def _open(self, meta_only=False, include_thumbnail=True):
self._file = self.request.get_file()
self._data = None
self._chunks = {}
self.metadata = {}
self._content = None
self._meta_only = meta_only
self._include_thumbnail = include_thumbnail
self._find_header()
self._find_chunks()
self._find_meta()
try:
# Get sha1 dict and check if it is in dictionary of data chunks
chunk_dict = self._content["frames"][0]["frame"]
if (
chunk_dict["metadataRef"] in self._chunks
and chunk_dict["imageRef"] in self._chunks
and chunk_dict["privateMetadataRef"] in self._chunks
):
if not self._meta_only:
# Read raw image data byte buffer
data_pos, size = self._chunks[chunk_dict["imageRef"]]
self._file.seek(data_pos, 0)
self.raw_image_data = self._file.read(size)
# Read meta data
data_pos, size = self._chunks[chunk_dict["metadataRef"]]
self._file.seek(data_pos, 0)
metadata = self._file.read(size)
# Add metadata to meta data dict
self.metadata["metadata"] = json.loads(metadata.decode("ASCII"))
# Read private metadata
data_pos, size = self._chunks[chunk_dict["privateMetadataRef"]]
self._file.seek(data_pos, 0)
serial_numbers = self._file.read(size)
self.serial_numbers = json.loads(serial_numbers.decode("ASCII"))
# Add private metadata to meta data dict
self.metadata["privateMetadata"] = self.serial_numbers
# Read image preview thumbnail
if self._include_thumbnail:
chunk_dict = self._content["thumbnails"][0]
if chunk_dict["imageRef"] in self._chunks:
# Read thumbnail image from thumbnail chunk
data_pos, size = self._chunks[chunk_dict["imageRef"]]
self._file.seek(data_pos, 0)
# Read binary data, read image as jpeg
thumbnail_data = self._file.read(size)
thumbnail_img = imread(thumbnail_data, format="jpeg")
thumbnail_height = chunk_dict["height"]
thumbnail_width = chunk_dict["width"]
# Add thumbnail to metadata
self.metadata["thumbnail"] = {
"image": thumbnail_img,
"height": thumbnail_height,
"width": thumbnail_width,
}
except KeyError:
raise RuntimeError("The specified file is not a valid LFR file.")
def _close(self):
# Close the reader.
# Note that the request object will close self._file
del self._data
def _get_length(self):
# Return the number of images. Can be np.inf
return 1
def _find_header(self):
"""
Checks if file has correct header and skip it.
"""
file_header = b"\x89LFP\x0D\x0A\x1A\x0A\x00\x00\x00\x01"
# Read and check header of file
header = self._file.read(HEADER_LENGTH)
if header != file_header:
raise RuntimeError("The LFR file header is invalid.")
# Read first bytes to skip header
self._file.read(SIZE_LENGTH)
def _find_chunks(self):
"""
Gets start position and size of data chunks in file.
"""
chunk_header = b"\x89LFC\x0D\x0A\x1A\x0A\x00\x00\x00\x00"
for i in range(0, DATA_CHUNKS_ILLUM):
data_pos, size, sha1 = self._get_chunk(chunk_header)
self._chunks[sha1] = (data_pos, size)
def _find_meta(self):
"""
Gets a data chunk that contains information over content
of other data chunks.
"""
meta_header = b"\x89LFM\x0D\x0A\x1A\x0A\x00\x00\x00\x00"
data_pos, size, sha1 = self._get_chunk(meta_header)
# Get content
self._file.seek(data_pos, 0)
data = self._file.read(size)
self._content = json.loads(data.decode("ASCII"))
def _get_chunk(self, header):
"""
Checks if chunk has correct header and skips it.
Finds start position and length of next chunk and reads
sha1-string that identifies the following data chunk.
Parameters
----------
header : bytes
Byte string that identifies start of chunk.
Returns
-------
data_pos : int
Start position of data chunk in file.
size : int
Size of data chunk.
sha1 : str
Sha1 value of chunk.
"""
# Read and check header of chunk
header_chunk = self._file.read(HEADER_LENGTH)
if header_chunk != header:
raise RuntimeError("The LFR chunk header is invalid.")
data_pos = None
sha1 = None
# Read size
size = struct.unpack(">i", self._file.read(SIZE_LENGTH))[0]
if size > 0:
# Read sha1
sha1 = str(self._file.read(SHA1_LENGTH).decode("ASCII"))
# Skip fixed null chars
self._file.read(PADDING_LENGTH)
# Find start of data and skip data
data_pos = self._file.tell()
self._file.seek(size, 1)
# Skip extra null chars
ch = self._file.read(1)
while ch == b"\0":
ch = self._file.read(1)
self._file.seek(-1, 1)
return data_pos, size, sha1
def _get_data(self, index):
# Return the data and meta data for the given index
if index not in [0, None]:
raise IndexError("Lytro lfr file contains only one dataset")
if not self._meta_only:
# Read bytes from string and convert to uint16
raw = np.frombuffer(self.raw_image_data, dtype=np.uint8).astype(
np.uint16
)
im = LytroIllumRawFormat.rearrange_bits(raw)
else:
im = np.array([])
# Return array and dummy meta data
return im, self.metadata
def _get_meta_data(self, index):
# Get the meta data for the given index. If index is None,
# it returns the global meta data.
if index not in [0, None]:
raise IndexError("Lytro meta data file contains only one dataset")
return self.metadata
class LytroF01RawFormat(LytroFormat):
"""This is the Lytro RAW format for the original F01 Lytro camera.
The raw format is a 12bit image format as used by the Lytro F01
light field camera. The format will read the specified raw file and will
try to load a .txt or .json file with the associated meta data.
This format does not support writing.
Parameters for reading
----------------------
meta_only : bool
Whether to only read the metadata.
"""
def _can_read(self, request):
# Check if mode and extensions are supported by the format
if request.extension in (".raw",):
return True
@staticmethod
def rearrange_bits(array):
# Do bit rearrangement for the 12-bit lytro raw format
# Normalize output to 1.0 as float64
t0 = array[0::3]
t1 = array[1::3]
t2 = array[2::3]
a0 = np.left_shift(t0, 4) + np.right_shift(np.bitwise_and(t1, 240), 4)
a1 = np.left_shift(np.bitwise_and(t1, 15), 8) + t2
image = np.zeros(LYTRO_F01_IMAGE_SIZE, dtype=np.uint16)
image[:, 0::2] = a0.reshape(
(LYTRO_F01_IMAGE_SIZE[0], LYTRO_F01_IMAGE_SIZE[1] // 2)
)
image[:, 1::2] = a1.reshape(
(LYTRO_F01_IMAGE_SIZE[0], LYTRO_F01_IMAGE_SIZE[1] // 2)
)
# Normalize data to 1.0 as 64-bit float.
# Division is by 4095 as the Lytro F01 saves 12-bit raw data.
return np.divide(image, 4095.0).astype(np.float64)
# -- reader
class Reader(Format.Reader):
def _open(self, meta_only=False):
self._file = self.request.get_file()
self._data = None
self._meta_only = meta_only
def _close(self):
# Close the reader.
# Note that the request object will close self._file
del self._data
def _get_length(self):
# Return the number of images.
return 1
def _get_data(self, index):
# Return the data and meta data for the given index
if index not in [0, "None"]:
raise IndexError("Lytro file contains only one dataset")
if not self._meta_only:
# Read all bytes
if self._data is None:
self._data = self._file.read()
# Read bytes from string and convert to uint16
raw = np.frombuffer(self._data, dtype=np.uint8).astype(np.uint16)
# Rearrange bits
img = LytroF01RawFormat.rearrange_bits(raw)
else:
img = np.array([])
# Return image and meta data
return img, self._get_meta_data(index=0)
def _get_meta_data(self, index):
# Get the meta data for the given index. If index is None, it
# should return the global meta data.
if index not in [0, None]:
raise IndexError("Lytro meta data file contains only one dataset")
# Try to read meta data from meta data file corresponding
# to the raw data file, extension in [.txt, .TXT, .json, .JSON]
filename_base = os.path.splitext(self.request.get_local_filename())[0]
meta_data = None
for ext in [".txt", ".TXT", ".json", ".JSON"]:
if os.path.isfile(filename_base + ext):
meta_data = json.load(open(filename_base + ext))
if meta_data is not None:
return meta_data
else:
logger.warning("No metadata file found for provided raw file.")
return {}
class LytroLfpFormat(LytroFormat):
"""This is the Lytro Illum LFP format.
The lfp is a image and meta data container format as used by the
Lytro F01 light field camera.
The format will read the specified lfp file.
This format does not support writing.
Parameters for reading
----------------------
meta_only : bool
Whether to only read the metadata.
include_thumbnail : bool
Whether to include an image thumbnail in the metadata.
"""
def _can_read(self, request):
# Check if mode and extensions are supported by the format
if request.extension in (".lfp",):
return True
# -- reader
class Reader(Format.Reader):
def _open(self, meta_only=False):
self._file = self.request.get_file()
self._data = None
self._chunks = {}
self.metadata = {}
self._content = None
self._meta_only = meta_only
self._find_header()
self._find_meta()
self._find_chunks()
try:
# Get sha1 dict and check if it is in dictionary of data chunks
chunk_dict = self._content["picture"]["frameArray"][0]["frame"]
if (
chunk_dict["metadataRef"] in self._chunks
and chunk_dict["imageRef"] in self._chunks
and chunk_dict["privateMetadataRef"] in self._chunks
):
if not self._meta_only:
# Read raw image data byte buffer
data_pos, size = self._chunks[chunk_dict["imageRef"]]
self._file.seek(data_pos, 0)
self.raw_image_data = self._file.read(size)
# Read meta data
data_pos, size = self._chunks[chunk_dict["metadataRef"]]
self._file.seek(data_pos, 0)
metadata = self._file.read(size)
# Add metadata to meta data dict
self.metadata["metadata"] = json.loads(metadata.decode("ASCII"))
# Read private metadata
data_pos, size = self._chunks[chunk_dict["privateMetadataRef"]]
self._file.seek(data_pos, 0)
serial_numbers = self._file.read(size)
self.serial_numbers = json.loads(serial_numbers.decode("ASCII"))
# Add private metadata to meta data dict
self.metadata["privateMetadata"] = self.serial_numbers
except KeyError:
raise RuntimeError("The specified file is not a valid LFP file.")
def _close(self):
# Close the reader.
# Note that the request object will close self._file
del self._data
def _get_length(self):
# Return the number of images. Can be np.inf
return 1
def _find_header(self):
"""
Checks if file has correct header and skip it.
"""
file_header = b"\x89LFP\x0D\x0A\x1A\x0A\x00\x00\x00\x01"
# Read and check header of file
header = self._file.read(HEADER_LENGTH)
if header != file_header:
raise RuntimeError("The LFP file header is invalid.")
# Read first bytes to skip header
self._file.read(SIZE_LENGTH)
def _find_chunks(self):
"""
Gets start position and size of data chunks in file.
"""
chunk_header = b"\x89LFC\x0D\x0A\x1A\x0A\x00\x00\x00\x00"
for i in range(0, DATA_CHUNKS_F01):
data_pos, size, sha1 = self._get_chunk(chunk_header)
self._chunks[sha1] = (data_pos, size)
def _find_meta(self):
"""
Gets a data chunk that contains information over content
of other data chunks.
"""
meta_header = b"\x89LFM\x0D\x0A\x1A\x0A\x00\x00\x00\x00"
data_pos, size, sha1 = self._get_chunk(meta_header)
# Get content
self._file.seek(data_pos, 0)
data = self._file.read(size)
self._content = json.loads(data.decode("ASCII"))
data = self._file.read(5) # Skip 5
def _get_chunk(self, header):
"""
Checks if chunk has correct header and skips it.
Finds start position and length of next chunk and reads
sha1-string that identifies the following data chunk.
Parameters
----------
header : bytes
Byte string that identifies start of chunk.
Returns
-------
data_pos : int
Start position of data chunk in file.
size : int
Size of data chunk.
sha1 : str
Sha1 value of chunk.
"""
# Read and check header of chunk
header_chunk = self._file.read(HEADER_LENGTH)
if header_chunk != header:
raise RuntimeError("The LFP chunk header is invalid.")
data_pos = None
sha1 = None
# Read size
size = struct.unpack(">i", self._file.read(SIZE_LENGTH))[0]
if size > 0:
# Read sha1
sha1 = str(self._file.read(SHA1_LENGTH).decode("ASCII"))
# Skip fixed null chars
self._file.read(PADDING_LENGTH)
# Find start of data and skip data
data_pos = self._file.tell()
self._file.seek(size, 1)
# Skip extra null chars
ch = self._file.read(1)
while ch == b"\0":
ch = self._file.read(1)
self._file.seek(-1, 1)
return data_pos, size, sha1
def _get_data(self, index):
# Return the data and meta data for the given index
if index not in [0, None]:
raise IndexError("Lytro lfp file contains only one dataset")
if not self._meta_only:
# Read bytes from string and convert to uint16
raw = np.frombuffer(self.raw_image_data, dtype=np.uint8).astype(
np.uint16
)
im = LytroF01RawFormat.rearrange_bits(raw)
else:
im = np.array([])
# Return array and dummy meta data
return im, self.metadata
def _get_meta_data(self, index):
# Get the meta data for the given index. If index is None,
# it returns the global meta data.
if index not in [0, None]:
raise IndexError("Lytro meta data file contains only one dataset")
return self.metadata

View File

@@ -1,85 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
"""Read/Write NPZ files.
Backend: `Numpy <https://numpy.org/doc/stable/reference/generated/numpy.savez.html>`_
NPZ is a file format by numpy that provides storage of array data using gzip
compression. This imageio plugin supports data of any shape, and also supports
multiple images per file. However, the npz format does not provide streaming;
all data is read/written at once. Further, there is no support for meta data.
See the BSDF format for a similar (but more fully featured) format.
Parameters
----------
None
Notes
-----
This format is not available on Pypy.
"""
import numpy as np
from ..core import Format
class NpzFormat(Format):
"""See :mod:`imageio.plugins.npz`"""
def _can_read(self, request):
# We support any kind of image data
return request.extension in self.extensions
def _can_write(self, request):
# We support any kind of image data
return request.extension in self.extensions
# -- reader
class Reader(Format.Reader):
def _open(self):
# Load npz file, which provides another file like object
self._npz = np.load(self.request.get_file())
assert isinstance(self._npz, np.lib.npyio.NpzFile)
# Get list of names, ordered by name, but smarter
self._names = sorted(self._npz.files, key=lambda x: x.split("_")[-1])
def _close(self):
self._npz.close()
def _get_length(self):
return len(self._names)
def _get_data(self, index):
# Get data
if index < 0 or index >= len(self._names):
raise IndexError("Index out of range while reading from nzp")
im = self._npz[self._names[index]]
# Return array and empty meta data
return im, {}
def _get_meta_data(self, index):
# Get the meta data for the given index
raise RuntimeError("The npz format does not support meta data.")
# -- writer
class Writer(Format.Writer):
def _open(self):
# Npz is not such a great format. We cannot stream to the file.
# So we remember all images and write them to file at the end.
self._images = []
def _close(self):
# Write everything
np.savez_compressed(self.request.get_file(), *self._images)
def _append_data(self, im, meta):
self._images.append(im) # discart meta data
def set_meta_data(self, meta):
raise RuntimeError("The npz format does not support meta data.")

View File

@@ -1,314 +0,0 @@
"""Read/Write images using OpenCV.
Backend Library: `OpenCV <https://opencv.org/>`_
This plugin wraps OpenCV (also known as ``cv2``), a popular image processing
library. Currently, it exposes OpenCVs image reading capability (no video or GIF
support yet); however, this may be added in future releases.
Methods
-------
.. note::
Check the respective function for a list of supported kwargs and their
documentation.
.. autosummary::
:toctree:
OpenCVPlugin.read
OpenCVPlugin.iter
OpenCVPlugin.write
OpenCVPlugin.properties
OpenCVPlugin.metadata
Pixel Formats (Colorspaces)
---------------------------
OpenCV is known to process images in BGR; however, most of the python ecosystem
(in particular matplotlib and other pydata libraries) use the RGB. As such,
images are converted to RGB, RGBA, or grayscale (where applicable) by default.
"""
import warnings
from pathlib import Path
from typing import Any, Dict, List, Optional, Union
import cv2
import numpy as np
from ..core import Request
from ..core.request import URI_BYTES, InitializationError, IOMode
from ..core.v3_plugin_api import ImageProperties, PluginV3
from ..typing import ArrayLike
class OpenCVPlugin(PluginV3):
def __init__(self, request: Request) -> None:
super().__init__(request)
self.file_handle = request.get_local_filename()
if request._uri_type is URI_BYTES:
self.filename = "<bytes>"
else:
self.filename = request.raw_uri
mode = request.mode.io_mode
if mode == IOMode.read and not cv2.haveImageReader(self.file_handle):
raise InitializationError(f"OpenCV can't read `{self.filename}`.")
elif mode == IOMode.write and not cv2.haveImageWriter(self.file_handle):
raise InitializationError(f"OpenCV can't write to `{self.filename}`.")
def read(
self,
*,
index: int = None,
colorspace: Union[int, str] = None,
flags: int = cv2.IMREAD_COLOR,
) -> np.ndarray:
"""Read an image from the ImageResource.
Parameters
----------
index : int, Ellipsis
If int, read the index-th image from the ImageResource. If ``...``,
read all images from the ImageResource and stack them along a new,
prepended, batch dimension. If None (default), use ``index=0`` if
the image contains exactly one image and ``index=...`` otherwise.
colorspace : str, int
The colorspace to convert into after loading and before returning
the image. If None (default) keep grayscale images as is, convert
images with an alpha channel to ``RGBA`` and all other images to
``RGB``. If int, interpret ``colorspace`` as one of OpenCVs
`conversion flags
<https://docs.opencv.org/4.x/d8/d01/group__imgproc__color__conversions.html>`_
and use it for conversion. If str, convert the image into the given
colorspace. Possible string values are: ``"RGB"``, ``"BGR"``,
``"RGBA"``, ``"BGRA"``, ``"GRAY"``, ``"HSV"``, or ``"LAB"``.
flags : int
The OpenCV flag(s) to pass to the reader. Refer to the `OpenCV docs
<https://docs.opencv.org/4.x/d4/da8/group__imgcodecs.html#ga288b8b3da0892bd651fce07b3bbd3a56>`_
for details.
Returns
-------
ndimage : np.ndarray
The decoded image as a numpy array.
"""
if index is None:
n_images = cv2.imcount(self.file_handle, flags)
index = 0 if n_images == 1 else ...
if index is ...:
retval, img = cv2.imreadmulti(self.file_handle, flags=flags)
is_batch = True
else:
retval, img = cv2.imreadmulti(self.file_handle, index, 1, flags=flags)
is_batch = False
if retval is False:
raise ValueError(f"Could not read index `{index}` from `{self.filename}`.")
if img[0].ndim == 2:
in_colorspace = "GRAY"
out_colorspace = colorspace or "GRAY"
elif img[0].shape[-1] == 4:
in_colorspace = "BGRA"
out_colorspace = colorspace or "RGBA"
else:
in_colorspace = "BGR"
out_colorspace = colorspace or "RGB"
if isinstance(colorspace, int):
cvt_space = colorspace
elif in_colorspace == out_colorspace.upper():
cvt_space = None
else:
out_colorspace = out_colorspace.upper()
cvt_space = getattr(cv2, f"COLOR_{in_colorspace}2{out_colorspace}")
if cvt_space is not None:
img = np.stack([cv2.cvtColor(x, cvt_space) for x in img])
else:
img = np.stack(img)
return img if is_batch else img[0]
def iter(
self,
colorspace: Union[int, str] = None,
flags: int = cv2.IMREAD_COLOR,
) -> np.ndarray:
"""Yield images from the ImageResource.
Parameters
----------
colorspace : str, int
The colorspace to convert into after loading and before returning
the image. If None (default) keep grayscale images as is, convert
images with an alpha channel to ``RGBA`` and all other images to
``RGB``. If int, interpret ``colorspace`` as one of OpenCVs
`conversion flags
<https://docs.opencv.org/4.x/d8/d01/group__imgproc__color__conversions.html>`_
and use it for conversion. If str, convert the image into the given
colorspace. Possible string values are: ``"RGB"``, ``"BGR"``,
``"RGBA"``, ``"BGRA"``, ``"GRAY"``, ``"HSV"``, or ``"LAB"``.
flags : int
The OpenCV flag(s) to pass to the reader. Refer to the `OpenCV docs
<https://docs.opencv.org/4.x/d4/da8/group__imgcodecs.html#ga288b8b3da0892bd651fce07b3bbd3a56>`_
for details.
Yields
------
ndimage : np.ndarray
The decoded image as a numpy array.
"""
for idx in range(cv2.imcount(self.file_handle)):
yield self.read(index=idx, flags=flags, colorspace=colorspace)
def write(
self,
ndimage: Union[ArrayLike, List[ArrayLike]],
is_batch: bool = False,
params: List[int] = None,
) -> Optional[bytes]:
"""Save an ndimage in the ImageResource.
Parameters
----------
ndimage : ArrayLike, List[ArrayLike]
The image data that will be written to the file. It is either a
single image, a batch of images, or a list of images.
is_batch : bool
If True, the provided ndimage is a batch of images. If False (default), the
provided ndimage is a single image. If the provided ndimage is a list of images,
this parameter has no effect.
params : List[int]
A list of parameters that will be passed to OpenCVs imwrite or
imwritemulti functions. Possible values are documented in the
`OpenCV documentation
<https://docs.opencv.org/4.x/d4/da8/group__imgcodecs.html#gabbc7ef1aa2edfaa87772f1202d67e0ce>`_.
Returns
-------
encoded_image : bytes, None
If the ImageResource is ``"<bytes>"`` the call to write returns the
encoded image as a bytes string. Otherwise it returns None.
"""
if isinstance(ndimage, list):
ndimage = np.stack(ndimage, axis=0)
elif not is_batch:
ndimage = ndimage[None, ...]
if ndimage[0].ndim == 2:
n_channels = 1
else:
n_channels = ndimage[0].shape[-1]
if n_channels == 1:
ndimage_cv2 = [x for x in ndimage]
elif n_channels == 4:
ndimage_cv2 = [cv2.cvtColor(x, cv2.COLOR_RGBA2BGRA) for x in ndimage]
else:
ndimage_cv2 = [cv2.cvtColor(x, cv2.COLOR_RGB2BGR) for x in ndimage]
retval = cv2.imwritemulti(self.file_handle, ndimage_cv2, params)
if retval is False:
# not sure what scenario would trigger this, but
# it can occur theoretically.
raise IOError("OpenCV failed to write.") # pragma: no cover
if self.request._uri_type == URI_BYTES:
return Path(self.file_handle).read_bytes()
def properties(
self,
index: int = None,
colorspace: Union[int, str] = None,
flags: int = cv2.IMREAD_COLOR,
) -> ImageProperties:
"""Standardized image metadata.
Parameters
----------
index : int, Ellipsis
If int, get the properties of the index-th image in the
ImageResource. If ``...``, get the properties of the image stack
that contains all images. If None (default), use ``index=0`` if the
image contains exactly one image and ``index=...`` otherwise.
colorspace : str, int
The colorspace to convert into after loading and before returning
the image. If None (default) keep grayscale images as is, convert
images with an alpha channel to ``RGBA`` and all other images to
``RGB``. If int, interpret ``colorspace`` as one of OpenCVs
`conversion flags
<https://docs.opencv.org/4.x/d8/d01/group__imgproc__color__conversions.html>`_
and use it for conversion. If str, convert the image into the given
colorspace. Possible string values are: ``"RGB"``, ``"BGR"``,
``"RGBA"``, ``"BGRA"``, ``"GRAY"``, ``"HSV"``, or ``"LAB"``.
flags : int
The OpenCV flag(s) to pass to the reader. Refer to the `OpenCV docs
<https://docs.opencv.org/4.x/d4/da8/group__imgcodecs.html#ga288b8b3da0892bd651fce07b3bbd3a56>`_
for details.
Returns
-------
props : ImageProperties
A dataclass filled with standardized image metadata.
Notes
-----
Reading properties with OpenCV involves decoding pixel data, because
OpenCV doesn't provide a direct way to access metadata.
"""
if index is None:
n_images = cv2.imcount(self.file_handle, flags)
is_batch = n_images > 1
elif index is Ellipsis:
n_images = cv2.imcount(self.file_handle, flags)
is_batch = True
else:
is_batch = False
# unfortunately, OpenCV doesn't allow reading shape without reading pixel data
if is_batch:
img = self.read(index=0, flags=flags, colorspace=colorspace)
return ImageProperties(
shape=(n_images, *img.shape),
dtype=img.dtype,
n_images=n_images,
is_batch=True,
)
img = self.read(index=index, flags=flags, colorspace=colorspace)
return ImageProperties(shape=img.shape, dtype=img.dtype, is_batch=False)
def metadata(
self, index: int = None, exclude_applied: bool = True
) -> Dict[str, Any]:
"""Format-specific metadata.
.. warning::
OpenCV does not support reading metadata. When called, this function
will raise a ``NotImplementedError``.
Parameters
----------
index : int
This parameter has no effect.
exclude_applied : bool
This parameter has no effect.
"""
warnings.warn("OpenCV does not support reading metadata.", UserWarning)
return dict()

View File

@@ -1,477 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
""" Read/Write images using Pillow/PIL.
Backend Library: `Pillow <https://pillow.readthedocs.io/en/stable/>`_
Plugin that wraps the the Pillow library. Pillow is a friendly fork of PIL
(Python Image Library) and supports reading and writing of common formats (jpg,
png, gif, tiff, ...). For, the complete list of features and supported formats
please refer to pillows official docs (see the Backend Library link).
Parameters
----------
request : Request
A request object representing the resource to be operated on.
Methods
-------
.. autosummary::
:toctree: _plugins/pillow
PillowPlugin.read
PillowPlugin.write
PillowPlugin.iter
PillowPlugin.get_meta
"""
from io import BytesIO
from typing import Callable, Optional, Dict, Any, Tuple, cast, Iterator, Union, List
import numpy as np
from PIL import Image, UnidentifiedImageError, ImageSequence, ExifTags # type: ignore
from ..core.request import Request, IOMode, InitializationError, URI_BYTES
from ..core.v3_plugin_api import PluginV3, ImageProperties
import warnings
from ..typing import ArrayLike
def _exif_orientation_transform(orientation: int, mode: str) -> Callable:
# get transformation that transforms an image from a
# given EXIF orientation into the standard orientation
# -1 if the mode has color channel, 0 otherwise
axis = -2 if Image.getmodebands(mode) > 1 else -1
EXIF_ORIENTATION = {
1: lambda x: x,
2: lambda x: np.flip(x, axis=axis),
3: lambda x: np.rot90(x, k=2),
4: lambda x: np.flip(x, axis=axis - 1),
5: lambda x: np.flip(np.rot90(x, k=3), axis=axis),
6: lambda x: np.rot90(x, k=1),
7: lambda x: np.flip(np.rot90(x, k=1), axis=axis),
8: lambda x: np.rot90(x, k=3),
}
return EXIF_ORIENTATION[orientation]
class PillowPlugin(PluginV3):
def __init__(self, request: Request) -> None:
"""Instantiate a new Pillow Plugin Object
Parameters
----------
request : {Request}
A request object representing the resource to be operated on.
"""
super().__init__(request)
self._image: Image = None
if request.mode.io_mode == IOMode.read:
try:
with Image.open(request.get_file()):
# Check if it is generally possible to read the image.
# This will not read any data and merely try to find a
# compatible pillow plugin (ref: the pillow docs).
pass
except UnidentifiedImageError:
if request._uri_type == URI_BYTES:
raise InitializationError(
"Pillow can not read the provided bytes."
) from None
else:
raise InitializationError(
f"Pillow can not read {request.raw_uri}."
) from None
self._image = Image.open(self._request.get_file())
else:
extension = self.request.extension or self.request.format_hint
if extension is None:
warnings.warn(
"Can't determine file format to write as. You _must_"
" set `format` during write or the call will fail. Use "
"`extension` to supress this warning. ",
UserWarning,
)
return
tirage = [Image.preinit, Image.init]
for format_loader in tirage:
format_loader()
if extension in Image.registered_extensions().keys():
return
raise InitializationError(
f"Pillow can not write `{extension}` files."
) from None
def close(self) -> None:
if self._image:
self._image.close()
self._request.finish()
def read(
self, *, index=None, mode=None, rotate=False, apply_gamma=False, as_gray=None
) -> np.ndarray:
"""
Parses the given URI and creates a ndarray from it.
Parameters
----------
index : int
If the ImageResource contains multiple ndimages, and index is an
integer, select the index-th ndimage from among them and return it.
If index is an ellipsis (...), read all ndimages in the file and
stack them along a new batch dimension and return them. If index is
None, this plugin reads the first image of the file (index=0) unless
the image is a GIF or APNG, in which case all images are read
(index=...).
mode : str
Convert the image to the given mode before returning it. If None,
the mode will be left unchanged. Possible modes can be found at:
https://pillow.readthedocs.io/en/stable/handbook/concepts.html#modes
rotate : bool
If set to ``True`` and the image contains an EXIF orientation tag,
apply the orientation before returning the ndimage.
apply_gamma : bool
If ``True`` and the image contains metadata about gamma, apply gamma
correction to the image.
as_gray : bool
Deprecated. Exists to raise a constructive error message.
Returns
-------
ndimage : ndarray
A numpy array containing the loaded image data
Notes
-----
If you read a paletted image (e.g. GIF) then the plugin will apply the
palette by default. Should you wish to read the palette indices of each
pixel use ``mode="P"``. The coresponding color pallete can be found in
the image's metadata using the ``palette`` key when metadata is
extracted using the ``exclude_applied=False`` kwarg. The latter is
needed, as palettes are applied by default and hence excluded by default
to keep metadata and pixel data consistent.
"""
if as_gray is not None:
raise TypeError(
"The keyword `as_gray` is no longer supported."
"Use `mode='L'` instead."
)
if index is None:
if self._image.format == "GIF":
index = Ellipsis
elif self._image.custom_mimetype == "image/apng":
index = Ellipsis
else:
index = 0
if isinstance(index, int):
# will raise IO error if index >= number of frames in image
self._image.seek(index)
image = self._apply_transforms(self._image, mode, rotate, apply_gamma)
return image
else:
iterator = self.iter(mode=mode, rotate=rotate, apply_gamma=apply_gamma)
image = np.stack([im for im in iterator], axis=0)
return image
def iter(
self, *, mode: str = None, rotate: bool = False, apply_gamma: bool = False
) -> Iterator[np.ndarray]:
"""
Iterate over all ndimages/frames in the URI
Parameters
----------
mode : {str, None}
Convert the image to the given mode before returning it. If None,
the mode will be left unchanged. Possible modes can be found at:
https://pillow.readthedocs.io/en/stable/handbook/concepts.html#modes
rotate : {bool}
If set to ``True`` and the image contains an EXIF orientation tag,
apply the orientation before returning the ndimage.
apply_gamma : {bool}
If ``True`` and the image contains metadata about gamma, apply gamma
correction to the image.
"""
for im in ImageSequence.Iterator(self._image):
yield self._apply_transforms(im, mode, rotate, apply_gamma)
def _apply_transforms(self, image, mode, rotate, apply_gamma) -> np.ndarray:
if mode is not None:
image = image.convert(mode)
elif image.mode == "P":
# adjust for pillow9 changes
# see: https://github.com/python-pillow/Pillow/issues/5929
image = image.convert(image.palette.mode)
image = np.asarray(image)
meta = self.metadata(index=self._image.tell(), exclude_applied=False)
if rotate and "Orientation" in meta:
transformation = _exif_orientation_transform(
meta["Orientation"], self._image.mode
)
image = transformation(image)
if apply_gamma and "gamma" in meta:
gamma = float(meta["gamma"])
scale = float(65536 if image.dtype == np.uint16 else 255)
gain = 1.0
image = ((image / scale) ** gamma) * scale * gain + 0.4999
image = np.round(image).astype(np.uint8)
return image
def write(
self,
ndimage: Union[ArrayLike, List[ArrayLike]],
*,
mode: str = None,
format: str = None,
is_batch: bool = None,
**kwargs,
) -> Optional[bytes]:
"""
Write an ndimage to the URI specified in path.
If the URI points to a file on the current host and the file does not
yet exist it will be created. If the file exists already, it will be
appended if possible; otherwise, it will be replaced.
If necessary, the image is broken down along the leading dimension to
fit into individual frames of the chosen format. If the format doesn't
support multiple frames, and IOError is raised.
Parameters
----------
image : ndarray or list
The ndimage to write. If a list is given each element is expected to
be an ndimage.
mode : str
Specify the image's color format. If None (default), the mode is
inferred from the array's shape and dtype. Possible modes can be
found at:
https://pillow.readthedocs.io/en/stable/handbook/concepts.html#modes
format : str
Optional format override. If omitted, the format to use is
determined from the filename extension. If a file object was used
instead of a filename, this parameter must always be used.
is_batch : bool
Explicitly tell the writer that ``image`` is a batch of images
(True) or not (False). If None, the writer will guess this from the
provided ``mode`` or ``image.shape``. While the latter often works,
it may cause problems for small images due to aliasing of spatial
and color-channel axes.
kwargs : ...
Extra arguments to pass to pillow. If a writer doesn't recognise an
option, it is silently ignored. The available options are described
in pillow's `image format documentation
<https://pillow.readthedocs.io/en/stable/handbook/image-file-formats.html>`_
for each writer.
Notes
-----
When writing batches of very narrow (2-4 pixels wide) gray images set
the ``mode`` explicitly to avoid the batch being identified as a colored
image.
"""
if "fps" in kwargs:
raise TypeError(
"The keyword `fps` is no longer supported. Use `duration`"
"(in ms) instead, e.g. `fps=50` == `duration=20` (1000 * 1/50)."
)
extension = self.request.extension or self.request.format_hint
save_args = {
"format": format or Image.registered_extensions()[extension],
}
if isinstance(ndimage, list):
ndimage = np.stack(ndimage, axis=0)
is_batch = True
else:
ndimage = np.asarray(ndimage)
# check if ndimage is a batch of frames/pages (e.g. for writing GIF)
# if mode is given, use it; otherwise fall back to image.ndim only
if is_batch is not None:
pass
elif mode is not None:
is_batch = (
ndimage.ndim > 3 if Image.getmodebands(mode) > 1 else ndimage.ndim > 2
)
elif ndimage.ndim == 2:
is_batch = False
elif ndimage.ndim == 3 and ndimage.shape[-1] == 1:
raise ValueError("Can't write images with one color channel.")
elif ndimage.ndim == 3 and ndimage.shape[-1] in [2, 3, 4]:
# Note: this makes a channel-last assumption
is_batch = False
else:
is_batch = True
if not is_batch:
ndimage = ndimage[None, ...]
pil_frames = list()
for frame in ndimage:
pil_frame = Image.fromarray(frame, mode=mode)
if "bits" in kwargs:
pil_frame = pil_frame.quantize(colors=2 ** kwargs["bits"])
pil_frames.append(pil_frame)
primary_image, other_images = pil_frames[0], pil_frames[1:]
if is_batch:
save_args["save_all"] = True
save_args["append_images"] = other_images
save_args.update(kwargs)
primary_image.save(self._request.get_file(), **save_args)
if self._request._uri_type == URI_BYTES:
file = cast(BytesIO, self._request.get_file())
return file.getvalue()
return None
def get_meta(self, *, index=0) -> Dict[str, Any]:
return self.metadata(index=index, exclude_applied=False)
def metadata(
self, index: int = None, exclude_applied: bool = True
) -> Dict[str, Any]:
"""Read ndimage metadata.
Parameters
----------
index : {integer, None}
If the ImageResource contains multiple ndimages, and index is an
integer, select the index-th ndimage from among them and return its
metadata. If index is an ellipsis (...), read and return global
metadata. If index is None, this plugin reads metadata from the
first image of the file (index=0) unless the image is a GIF or APNG,
in which case global metadata is read (index=...).
exclude_applied : bool
If True, exclude metadata fields that are applied to the image while
reading. For example, if the binary data contains a rotation flag,
the image is rotated by default and the rotation flag is excluded
from the metadata to avoid confusion.
Returns
-------
metadata : dict
A dictionary of format-specific metadata.
"""
if index is None:
if self._image.format == "GIF":
index = Ellipsis
elif self._image.custom_mimetype == "image/apng":
index = Ellipsis
else:
index = 0
if isinstance(index, int) and self._image.tell() != index:
self._image.seek(index)
metadata = self._image.info.copy()
metadata["mode"] = self._image.mode
metadata["shape"] = self._image.size
if self._image.mode == "P" and not exclude_applied:
metadata["palette"] = np.asarray(tuple(self._image.palette.colors.keys()))
if self._image.getexif():
exif_data = {
ExifTags.TAGS.get(key, "unknown"): value
for key, value in dict(self._image.getexif()).items()
}
exif_data.pop("unknown", None)
metadata.update(exif_data)
if exclude_applied:
metadata.pop("Orientation", None)
return metadata
def properties(self, index: int = None) -> ImageProperties:
"""Standardized ndimage metadata
Parameters
----------
index : int
If the ImageResource contains multiple ndimages, and index is an
integer, select the index-th ndimage from among them and return its
properties. If index is an ellipsis (...), read and return the
properties of all ndimages in the file stacked along a new batch
dimension. If index is None, this plugin reads and returns the
properties of the first image (index=0) unless the image is a GIF or
APNG, in which case it reads and returns the properties all images
(index=...).
Returns
-------
properties : ImageProperties
A dataclass filled with standardized image metadata.
Notes
-----
This does not decode pixel data and is fast for large images.
"""
if index is None:
if self._image.format == "GIF":
index = Ellipsis
elif self._image.custom_mimetype == "image/apng":
index = Ellipsis
else:
index = 0
if index is Ellipsis:
self._image.seek(0)
else:
self._image.seek(index)
if self._image.mode == "P":
# mode of palette images is determined by their palette
mode = self._image.palette.mode
else:
mode = self._image.mode
width: int = self._image.width
height: int = self._image.height
shape: Tuple[int, ...] = (height, width)
n_frames: int = self._image.n_frames
if index is ...:
shape = (n_frames, *shape)
dummy = np.asarray(Image.new(mode, (1, 1)))
pil_shape: Tuple[int, ...] = dummy.shape
if len(pil_shape) > 2:
shape = (*shape, *pil_shape[2:])
return ImageProperties(
shape=shape,
dtype=dummy.dtype,
n_images=n_frames if index is Ellipsis else None,
is_batch=index is Ellipsis,
)

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# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
""" Read/Write images using pillow/PIL (legacy).
Backend Library: `Pillow <https://pillow.readthedocs.io/en/stable/>`_
Pillow is a friendly fork of PIL (Python Image Library) and supports
reading and writing of common formats (jpg, png, gif, tiff, ...). While
these docs provide an overview of some of its features, pillow is
constantly improving. Hence, the complete list of features can be found
in pillows official docs (see the Backend Library link).
Parameters for Reading
----------------------
pilmode : str
(Available for all formates except GIF-PIL)
From the Pillow documentation:
* 'L' (8-bit pixels, grayscale)
* 'P' (8-bit pixels, mapped to any other mode using a color palette)
* 'RGB' (3x8-bit pixels, true color)
* 'RGBA' (4x8-bit pixels, true color with transparency mask)
* 'CMYK' (4x8-bit pixels, color separation)
* 'YCbCr' (3x8-bit pixels, color video format)
* 'I' (32-bit signed integer pixels)
* 'F' (32-bit floating point pixels)
PIL also provides limited support for a few special modes, including
'LA' ('L' with alpha), 'RGBX' (true color with padding) and 'RGBa'
(true color with premultiplied alpha).
When translating a color image to grayscale (mode 'L', 'I' or 'F'),
the library uses the ITU-R 601-2 luma transform::
L = R * 299/1000 + G * 587/1000 + B * 114/1000
as_gray : bool
(Available for all formates except GIF-PIL)
If True, the image is converted using mode 'F'. When `mode` is
not None and `as_gray` is True, the image is first converted
according to `mode`, and the result is then "flattened" using
mode 'F'.
ignoregamma : bool
(Only available in PNG-PIL)
Avoid gamma correction. Default True.
exifrotate : bool
(Only available in JPEG-PIL)
Automatically rotate the image according to exif flag. Default True.
Parameters for saving
---------------------
optimize : bool
(Only available in PNG-PIL)
If present and true, instructs the PNG writer to make the output file
as small as possible. This includes extra processing in order to find
optimal encoder settings.
transparency:
(Only available in PNG-PIL)
This option controls what color image to mark as transparent.
dpi: tuple of two scalars
(Only available in PNG-PIL)
The desired dpi in each direction.
pnginfo: PIL.PngImagePlugin.PngInfo
(Only available in PNG-PIL)
Object containing text tags.
compress_level: int
(Only available in PNG-PIL)
ZLIB compression level, a number between 0 and 9: 1 gives best speed,
9 gives best compression, 0 gives no compression at all. Default is 9.
When ``optimize`` option is True ``compress_level`` has no effect
(it is set to 9 regardless of a value passed).
compression: int
(Only available in PNG-PIL)
Compatibility with the freeimage PNG format. If given, it overrides
compress_level.
icc_profile:
(Only available in PNG-PIL)
The ICC Profile to include in the saved file.
bits (experimental): int
(Only available in PNG-PIL)
This option controls how many bits to store. If omitted,
the PNG writer uses 8 bits (256 colors).
quantize:
(Only available in PNG-PIL)
Compatibility with the freeimage PNG format. If given, it overrides
bits. In this case, given as a number between 1-256.
dictionary (experimental): dict
(Only available in PNG-PIL)
Set the ZLIB encoder dictionary.
prefer_uint8: bool
(Only available in PNG-PIL)
Let the PNG writer truncate uint16 image arrays to uint8 if their values fall
within the range [0, 255]. Defaults to true for legacy compatibility, however
it is recommended to set this to false to avoid unexpected behavior when
saving e.g. weakly saturated images.
quality : scalar
(Only available in JPEG-PIL)
The compression factor of the saved image (1..100), higher
numbers result in higher quality but larger file size. Default 75.
progressive : bool
(Only available in JPEG-PIL)
Save as a progressive JPEG file (e.g. for images on the web).
Default False.
optimize : bool
(Only available in JPEG-PIL)
On saving, compute optimal Huffman coding tables (can reduce a few
percent of file size). Default False.
dpi : tuple of int
(Only available in JPEG-PIL)
The pixel density, ``(x,y)``.
icc_profile : object
(Only available in JPEG-PIL)
If present and true, the image is stored with the provided ICC profile.
If this parameter is not provided, the image will be saved with no
profile attached.
exif : dict
(Only available in JPEG-PIL)
If present, the image will be stored with the provided raw EXIF data.
subsampling : str
(Only available in JPEG-PIL)
Sets the subsampling for the encoder. See Pillow docs for details.
qtables : object
(Only available in JPEG-PIL)
Set the qtables for the encoder. See Pillow docs for details.
quality_mode : str
(Only available in JPEG2000-PIL)
Either `"rates"` or `"dB"` depending on the units you want to use to
specify image quality.
quality : float
(Only available in JPEG2000-PIL)
Approximate size reduction (if quality mode is `rates`) or a signal to noise ratio
in decibels (if quality mode is `dB`).
loop : int
(Only available in GIF-PIL)
The number of iterations. Default 0 (meaning loop indefinitely).
duration : {float, list}
(Only available in GIF-PIL)
The duration (in seconds) of each frame. Either specify one value
that is used for all frames, or one value for each frame.
Note that in the GIF format the duration/delay is expressed in
hundredths of a second, which limits the precision of the duration.
fps : float
(Only available in GIF-PIL)
The number of frames per second. If duration is not given, the
duration for each frame is set to 1/fps. Default 10.
palettesize : int
(Only available in GIF-PIL)
The number of colors to quantize the image to. Is rounded to
the nearest power of two. Default 256.
subrectangles : bool
(Only available in GIF-PIL)
If True, will try and optimize the GIF by storing only the
rectangular parts of each frame that change with respect to the
previous. Default False.
Notes
-----
To enable JPEG 2000 support, you need to build and install the OpenJPEG library,
version 2.0.0 or higher, before building the Python Imaging Library. Windows
users can install the OpenJPEG binaries available on the OpenJPEG website, but
must add them to their PATH in order to use PIL (if you fail to do this, you
will get errors about not being able to load the ``_imaging`` DLL).
GIF images read with this plugin are always RGBA. The alpha channel is ignored
when saving RGB images.
"""
import logging
import threading
import numpy as np
from ..core import Format, image_as_uint
from ..core.request import URI_FILE, URI_BYTES
logger = logging.getLogger(__name__)
# todo: Pillow ImageGrab module supports grabbing the screen on Win and OSX.
GENERIC_DOCS = """
Parameters for reading
----------------------
pilmode : str
From the Pillow documentation:
* 'L' (8-bit pixels, grayscale)
* 'P' (8-bit pixels, mapped to any other mode using a color palette)
* 'RGB' (3x8-bit pixels, true color)
* 'RGBA' (4x8-bit pixels, true color with transparency mask)
* 'CMYK' (4x8-bit pixels, color separation)
* 'YCbCr' (3x8-bit pixels, color video format)
* 'I' (32-bit signed integer pixels)
* 'F' (32-bit floating point pixels)
PIL also provides limited support for a few special modes, including
'LA' ('L' with alpha), 'RGBX' (true color with padding) and 'RGBa'
(true color with premultiplied alpha).
When translating a color image to grayscale (mode 'L', 'I' or 'F'),
the library uses the ITU-R 601-2 luma transform::
L = R * 299/1000 + G * 587/1000 + B * 114/1000
as_gray : bool
If True, the image is converted using mode 'F'. When `mode` is
not None and `as_gray` is True, the image is first converted
according to `mode`, and the result is then "flattened" using
mode 'F'.
"""
class PillowFormat(Format):
"""
Base format class for Pillow formats.
"""
_pillow_imported = False
_Image = None
_modes = "i"
_description = ""
def __init__(self, *args, plugin_id: str = None, **kwargs):
super(PillowFormat, self).__init__(*args, **kwargs)
# Used to synchronize _init_pillow(), see #244
self._lock = threading.RLock()
self._plugin_id = plugin_id
@property
def plugin_id(self):
"""The PIL plugin id."""
return self._plugin_id # Set when format is created
def _init_pillow(self):
with self._lock:
if not self._pillow_imported:
self._pillow_imported = True # more like tried to import
import PIL
if not hasattr(PIL, "__version__"): # pragma: no cover
raise ImportError(
"Imageio Pillow plugin requires " "Pillow, not PIL!"
)
from PIL import Image
self._Image = Image
elif self._Image is None: # pragma: no cover
raise RuntimeError("Imageio Pillow plugin requires " "Pillow lib.")
Image = self._Image
if self.plugin_id in ("PNG", "JPEG", "BMP", "GIF", "PPM"):
Image.preinit()
else:
Image.init()
return Image
def _can_read(self, request):
Image = self._init_pillow()
if self.plugin_id in Image.OPEN:
factory, accept = Image.OPEN[self.plugin_id]
if accept:
if request.firstbytes and accept(request.firstbytes):
return True
def _can_write(self, request):
Image = self._init_pillow()
if request.extension in self.extensions or request._uri_type in [
URI_FILE,
URI_BYTES,
]:
if self.plugin_id in Image.SAVE:
return True
class Reader(Format.Reader):
def _open(self, pilmode=None, as_gray=False):
Image = self.format._init_pillow()
try:
factory, accept = Image.OPEN[self.format.plugin_id]
except KeyError:
raise RuntimeError("Format %s cannot read images." % self.format.name)
self._fp = self._get_file()
self._im = factory(self._fp, "")
if hasattr(Image, "_decompression_bomb_check"):
Image._decompression_bomb_check(self._im.size)
# Save the raw mode used by the palette for a BMP because it may not be the number of channels
# When the data is read, imageio hands the palette to PIL to handle and clears the rawmode argument
# However, there is a bug in PIL with handling animated GIFs with a different color palette on each frame.
# This issue is resolved by using the raw palette data but the rawmode information is now lost. So we
# store the raw mode for later use
if self._im.palette and self._im.palette.dirty:
self._im.palette.rawmode_saved = self._im.palette.rawmode
pil_try_read(self._im)
# Store args
self._kwargs = dict(
as_gray=as_gray, is_gray=_palette_is_grayscale(self._im)
)
# setting mode=None is not the same as just not providing it
if pilmode is not None:
self._kwargs["mode"] = pilmode
# Set length
self._length = 1
if hasattr(self._im, "n_frames"):
self._length = self._im.n_frames
def _get_file(self):
self._we_own_fp = False
return self.request.get_file()
def _close(self):
save_pillow_close(self._im)
if self._we_own_fp:
self._fp.close()
# else: request object handles closing the _fp
def _get_length(self):
return self._length
def _seek(self, index):
try:
self._im.seek(index)
except EOFError:
raise IndexError("Could not seek to index %i" % index)
def _get_data(self, index):
if index >= self._length:
raise IndexError("Image index %i > %i" % (index, self._length))
i = self._im.tell()
if i > index:
self._seek(index) # just try
else:
while i < index: # some formats need to be read in sequence
i += 1
self._seek(i)
if self._im.palette and self._im.palette.dirty:
self._im.palette.rawmode_saved = self._im.palette.rawmode
self._im.getdata()[0]
im = pil_get_frame(self._im, **self._kwargs)
return im, self._im.info
def _get_meta_data(self, index):
if not (index is None or index == 0):
raise IndexError()
return self._im.info
class Writer(Format.Writer):
def _open(self):
Image = self.format._init_pillow()
try:
self._save_func = Image.SAVE[self.format.plugin_id]
except KeyError:
raise RuntimeError("Format %s cannot write images." % self.format.name)
self._fp = self.request.get_file()
self._meta = {}
self._written = False
def _close(self):
pass # request object handled closing _fp
def _append_data(self, im, meta):
if self._written:
raise RuntimeError(
"Format %s only supports single images." % self.format.name
)
# Pop unit dimension for grayscale images
if im.ndim == 3 and im.shape[-1] == 1:
im = im[:, :, 0]
self._written = True
self._meta.update(meta)
img = ndarray_to_pil(
im, self.format.plugin_id, self._meta.pop("prefer_uint8", True)
)
if "bits" in self._meta:
img = img.quantize() # Make it a P image, so bits arg is used
img.save(self._fp, format=self.format.plugin_id, **self._meta)
save_pillow_close(img)
def set_meta_data(self, meta):
self._meta.update(meta)
class PNGFormat(PillowFormat):
"""See :mod:`imageio.plugins.pillow_legacy`"""
class Reader(PillowFormat.Reader):
def _open(self, pilmode=None, as_gray=False, ignoregamma=True):
return PillowFormat.Reader._open(self, pilmode=pilmode, as_gray=as_gray)
def _get_data(self, index):
im, info = PillowFormat.Reader._get_data(self, index)
if not self.request.kwargs.get("ignoregamma", True):
# The gamma value in the file represents the gamma factor for the
# hardware on the system where the file was created, and is meant
# to be able to match the colors with the system on which the
# image is shown. See also issue #366
try:
gamma = float(info["gamma"])
except (KeyError, ValueError):
pass
else:
scale = float(65536 if im.dtype == np.uint16 else 255)
gain = 1.0
im[:] = ((im / scale) ** gamma) * scale * gain + 0.4999
return im, info
# --
class Writer(PillowFormat.Writer):
def _open(self, compression=None, quantize=None, interlaced=False, **kwargs):
# Better default for compression
kwargs["compress_level"] = kwargs.get("compress_level", 9)
if compression is not None:
if compression < 0 or compression > 9:
raise ValueError("Invalid PNG compression level: %r" % compression)
kwargs["compress_level"] = compression
if quantize is not None:
for bits in range(1, 9):
if 2**bits == quantize:
break
else:
raise ValueError(
"PNG quantize must be power of two, " "not %r" % quantize
)
kwargs["bits"] = bits
if interlaced:
logger.warning("PIL PNG writer cannot produce interlaced images.")
ok_keys = (
"optimize",
"transparency",
"dpi",
"pnginfo",
"bits",
"compress_level",
"icc_profile",
"dictionary",
"prefer_uint8",
)
for key in kwargs:
if key not in ok_keys:
raise TypeError("Invalid arg for PNG writer: %r" % key)
PillowFormat.Writer._open(self)
self._meta.update(kwargs)
def _append_data(self, im, meta):
if str(im.dtype) == "uint16" and (im.ndim == 2 or im.shape[-1] == 1):
im = image_as_uint(im, bitdepth=16)
else:
im = image_as_uint(im, bitdepth=8)
PillowFormat.Writer._append_data(self, im, meta)
class JPEGFormat(PillowFormat):
"""See :mod:`imageio.plugins.pillow_legacy`"""
class Reader(PillowFormat.Reader):
def _open(self, pilmode=None, as_gray=False, exifrotate=True):
return PillowFormat.Reader._open(self, pilmode=pilmode, as_gray=as_gray)
def _get_file(self):
# Pillow uses seek for JPG, so we cannot directly stream from web
if self.request.filename.startswith(
("http://", "https://")
) or ".zip/" in self.request.filename.replace("\\", "/"):
self._we_own_fp = True
return open(self.request.get_local_filename(), "rb")
else:
self._we_own_fp = False
return self.request.get_file()
def _get_data(self, index):
im, info = PillowFormat.Reader._get_data(self, index)
# Handle exif
if "exif" in info:
from PIL.ExifTags import TAGS
info["EXIF_MAIN"] = {}
for tag, value in self._im._getexif().items():
decoded = TAGS.get(tag, tag)
info["EXIF_MAIN"][decoded] = value
im = self._rotate(im, info)
return im, info
def _rotate(self, im, meta):
"""Use Orientation information from EXIF meta data to
orient the image correctly. Similar code as in FreeImage plugin.
"""
if self.request.kwargs.get("exifrotate", True):
try:
ori = meta["EXIF_MAIN"]["Orientation"]
except KeyError: # pragma: no cover
pass # Orientation not available
else: # pragma: no cover - we cannot touch all cases
# www.impulseadventure.com/photo/exif-orientation.html
if ori in [1, 2]:
pass
if ori in [3, 4]:
im = np.rot90(im, 2)
if ori in [5, 6]:
im = np.rot90(im, 3)
if ori in [7, 8]:
im = np.rot90(im)
if ori in [2, 4, 5, 7]: # Flipped cases (rare)
im = np.fliplr(im)
return im
# --
class Writer(PillowFormat.Writer):
def _open(self, quality=75, progressive=False, optimize=False, **kwargs):
# The JPEG quality can be between 0 (worst) and 100 (best)
quality = int(quality)
if quality < 0 or quality > 100:
raise ValueError("JPEG quality should be between 0 and 100.")
kwargs["quality"] = quality
kwargs["progressive"] = bool(progressive)
kwargs["optimize"] = bool(progressive)
PillowFormat.Writer._open(self)
self._meta.update(kwargs)
def _append_data(self, im, meta):
if im.ndim == 3 and im.shape[-1] == 4:
raise IOError("JPEG does not support alpha channel.")
im = image_as_uint(im, bitdepth=8)
PillowFormat.Writer._append_data(self, im, meta)
return
class JPEG2000Format(PillowFormat):
"""See :mod:`imageio.plugins.pillow_legacy`"""
class Reader(PillowFormat.Reader):
def _open(self, pilmode=None, as_gray=False):
return PillowFormat.Reader._open(self, pilmode=pilmode, as_gray=as_gray)
def _get_file(self):
# Pillow uses seek for JPG, so we cannot directly stream from web
if self.request.filename.startswith(
("http://", "https://")
) or ".zip/" in self.request.filename.replace("\\", "/"):
self._we_own_fp = True
return open(self.request.get_local_filename(), "rb")
else:
self._we_own_fp = False
return self.request.get_file()
def _get_data(self, index):
im, info = PillowFormat.Reader._get_data(self, index)
# Handle exif
if "exif" in info:
from PIL.ExifTags import TAGS
info["EXIF_MAIN"] = {}
for tag, value in self._im._getexif().items():
decoded = TAGS.get(tag, tag)
info["EXIF_MAIN"][decoded] = value
im = self._rotate(im, info)
return im, info
def _rotate(self, im, meta):
"""Use Orientation information from EXIF meta data to
orient the image correctly. Similar code as in FreeImage plugin.
"""
if self.request.kwargs.get("exifrotate", True):
try:
ori = meta["EXIF_MAIN"]["Orientation"]
except KeyError: # pragma: no cover
pass # Orientation not available
else: # pragma: no cover - we cannot touch all cases
# www.impulseadventure.com/photo/exif-orientation.html
if ori in [1, 2]:
pass
if ori in [3, 4]:
im = np.rot90(im, 2)
if ori in [5, 6]:
im = np.rot90(im, 3)
if ori in [7, 8]:
im = np.rot90(im)
if ori in [2, 4, 5, 7]: # Flipped cases (rare)
im = np.fliplr(im)
return im
# --
class Writer(PillowFormat.Writer):
def _open(self, quality_mode="rates", quality=5, **kwargs):
# Check quality - in Pillow it should be no higher than 95
if quality_mode not in {"rates", "dB"}:
raise ValueError("Quality mode should be either 'rates' or 'dB'")
quality = float(quality)
if quality_mode == "rates" and (quality < 1 or quality > 1000):
raise ValueError(
"The quality value {} seems to be an invalid rate!".format(quality)
)
elif quality_mode == "dB" and (quality < 15 or quality > 100):
raise ValueError(
"The quality value {} seems to be an invalid PSNR!".format(quality)
)
kwargs["quality_mode"] = quality_mode
kwargs["quality_layers"] = [quality]
PillowFormat.Writer._open(self)
self._meta.update(kwargs)
def _append_data(self, im, meta):
if im.ndim == 3 and im.shape[-1] == 4:
raise IOError(
"The current implementation of JPEG 2000 does not support alpha channel."
)
im = image_as_uint(im, bitdepth=8)
PillowFormat.Writer._append_data(self, im, meta)
return
def save_pillow_close(im):
# see issue #216 and #300
if hasattr(im, "close"):
if hasattr(getattr(im, "fp", None), "close"):
im.close()
# Func from skimage
# This cells contains code from scikit-image, in particular from
# http://github.com/scikit-image/scikit-image/blob/master/
# skimage/io/_plugins/pil_plugin.py
# The scikit-image license applies.
def pil_try_read(im):
try:
# this will raise an IOError if the file is not readable
im.getdata()[0]
except IOError as e:
site = "http://pillow.readthedocs.io/en/latest/installation.html"
site += "#external-libraries"
pillow_error_message = str(e)
error_message = (
'Could not load "%s" \n'
'Reason: "%s"\n'
"Please see documentation at: %s"
% (im.filename, pillow_error_message, site)
)
raise ValueError(error_message)
def _palette_is_grayscale(pil_image):
if pil_image.mode != "P":
return False
elif pil_image.info.get("transparency", None): # see issue #475
return False
# get palette as an array with R, G, B columns
# Note: starting in pillow 9.1 palettes may have less than 256 entries
palette = np.asarray(pil_image.getpalette()).reshape((-1, 3))
# Not all palette colors are used; unused colors have junk values.
start, stop = pil_image.getextrema()
valid_palette = palette[start : stop + 1]
# Image is grayscale if channel differences (R - G and G - B)
# are all zero.
return np.allclose(np.diff(valid_palette), 0)
def pil_get_frame(im, is_gray=None, as_gray=None, mode=None, dtype=None):
"""
is_gray: Whether the image *is* gray (by inspecting its palette).
as_gray: Whether the resulting image must be converted to gaey.
mode: The mode to convert to.
"""
if is_gray is None:
is_gray = _palette_is_grayscale(im)
frame = im
# Convert ...
if mode is not None:
# Mode is explicitly given ...
if mode != im.mode:
frame = im.convert(mode)
elif as_gray:
pass # don't do any auto-conversions (but do the explit one above)
elif im.mode == "P" and is_gray:
# Paletted images that are already gray by their palette
# are converted so that the resulting numpy array is 2D.
frame = im.convert("L")
elif im.mode == "P":
# Paletted images are converted to RGB/RGBA. We jump some loops to make
# this work well.
if im.info.get("transparency", None) is not None:
# Let Pillow apply the transparency, see issue #210 and #246
frame = im.convert("RGBA")
elif im.palette.mode in ("RGB", "RGBA"):
# We can do this ourselves. Pillow seems to sometimes screw
# this up if a multi-gif has a palette for each frame ...
# Create palette array
p = np.frombuffer(im.palette.getdata()[1], np.uint8)
# Restore the raw mode that was saved to be used to parse the palette
if hasattr(im.palette, "rawmode_saved"):
im.palette.rawmode = im.palette.rawmode_saved
mode = im.palette.rawmode if im.palette.rawmode else im.palette.mode
nchannels = len(mode)
# Shape it.
p.shape = -1, nchannels
if p.shape[1] == 3 or (p.shape[1] == 4 and mode[-1] == "X"):
p = np.column_stack((p[:, :3], 255 * np.ones(p.shape[0], p.dtype)))
# Swap the axes if the mode is in BGR and not RGB
if mode.startswith("BGR"):
p = p[:, [2, 1, 0]] if p.shape[1] == 3 else p[:, [2, 1, 0, 3]]
# Apply palette
frame_paletted = np.array(im, np.uint8)
try:
frame = p[frame_paletted]
except Exception:
# Ok, let PIL do it. The introduction of the branch that
# tests `im.info['transparency']` should make this happen
# much less often, but let's keep it, to be safe.
frame = im.convert("RGBA")
else:
# Let Pillow do it. Unlinke skimage, we always convert
# to RGBA; palettes can be RGBA.
if True: # im.format == 'PNG' and 'transparency' in im.info:
frame = im.convert("RGBA")
else:
frame = im.convert("RGB")
elif "A" in im.mode:
frame = im.convert("RGBA")
elif im.mode == "CMYK":
frame = im.convert("RGB")
elif im.format == "GIF" and im.mode == "RGB":
# pillow9 returns RGBA images for subsequent frames so that it can deal
# with multi-frame GIF that use frame-level palettes and don't dispose
# all areas.
# For backwards compatibility, we promote everything to RGBA.
frame = im.convert("RGBA")
# Apply a post-convert if necessary
if as_gray:
frame = frame.convert("F") # Scipy compat
elif not isinstance(frame, np.ndarray) and frame.mode == "1":
# Workaround for crash in PIL. When im is 1-bit, the call array(im)
# can cause a segfault, or generate garbage. See
# https://github.com/scipy/scipy/issues/2138 and
# https://github.com/python-pillow/Pillow/issues/350.
#
# This converts im from a 1-bit image to an 8-bit image.
frame = frame.convert("L")
# Convert to numpy array
if im.mode.startswith("I;16"):
# e.g. in16 PNG's
shape = im.size
dtype = ">u2" if im.mode.endswith("B") else "<u2"
if "S" in im.mode:
dtype = dtype.replace("u", "i")
frame = np.frombuffer(frame.tobytes(), dtype).copy()
frame.shape = shape[::-1]
else:
# Use uint16 for PNG's in mode I
if im.format == "PNG" and im.mode == "I" and dtype is None:
dtype = "uint16"
frame = np.array(frame, dtype=dtype)
return frame
def ndarray_to_pil(arr, format_str=None, prefer_uint8=True):
from PIL import Image
if arr.ndim == 3:
arr = image_as_uint(arr, bitdepth=8)
mode = {3: "RGB", 4: "RGBA"}[arr.shape[2]]
elif format_str in ["png", "PNG"]:
mode = "I;16"
mode_base = "I"
if arr.dtype.kind == "f":
arr = image_as_uint(arr)
elif prefer_uint8 and arr.max() < 256 and arr.min() >= 0:
arr = arr.astype(np.uint8)
mode = mode_base = "L"
else:
arr = image_as_uint(arr, bitdepth=16)
else:
arr = image_as_uint(arr, bitdepth=8)
mode = "L"
mode_base = "L"
if mode == "I;16" and int(getattr(Image, "__version__", "0").split(".")[0]) < 6:
# Pillow < v6.0.0 has limited support for the "I;16" mode,
# requiring us to fall back to this expensive workaround.
# tobytes actually creates a copy of the image, which is costly.
array_buffer = arr.tobytes()
if arr.ndim == 2:
im = Image.new(mode_base, arr.T.shape)
im.frombytes(array_buffer, "raw", mode)
else:
image_shape = (arr.shape[1], arr.shape[0])
im = Image.frombytes(mode, image_shape, array_buffer)
return im
else:
return Image.fromarray(arr, mode)
# imported for backwards compatibility
from .pillowmulti import GIFFormat, TIFFFormat # noqa: E402, F401

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@@ -1,329 +0,0 @@
"""
PIL formats for multiple images.
"""
import logging
import numpy as np
from .pillow_legacy import PillowFormat, ndarray_to_pil, image_as_uint
logger = logging.getLogger(__name__)
NeuQuant = None # we can implement this when we need it
class TIFFFormat(PillowFormat):
_modes = "i" # arg, why bother; people should use the tiffile version
_description = "TIFF format (Pillow)"
class GIFFormat(PillowFormat):
"""See :mod:`imageio.plugins.pillow_legacy`"""
_modes = "iI"
_description = "Static and animated gif (Pillow)"
# GIF reader needs no modifications compared to base pillow reader
class Writer(PillowFormat.Writer):
def _open(
self,
loop=0,
duration=None,
fps=10,
palettesize=256,
quantizer=0,
subrectangles=False,
):
# Check palettesize
palettesize = int(palettesize)
if palettesize < 2 or palettesize > 256:
raise ValueError("GIF quantize param must be 2..256")
if palettesize not in [2, 4, 8, 16, 32, 64, 128, 256]:
palettesize = 2 ** int(np.log2(128) + 0.999)
logger.warning(
"Warning: palettesize (%r) modified to a factor of "
"two between 2-256." % palettesize
)
# Duratrion / fps
if duration is None:
self._duration = 1.0 / float(fps)
elif isinstance(duration, (list, tuple)):
self._duration = [float(d) for d in duration]
else:
self._duration = float(duration)
# loop
loop = float(loop)
if loop <= 0 or loop == float("inf"):
loop = 0
loop = int(loop)
# Subrectangles / dispose
subrectangles = bool(subrectangles)
self._dispose = 1 if subrectangles else 2
# The "0" (median cut) quantizer is by far the best
fp = self.request.get_file()
self._writer = GifWriter(
fp, subrectangles, loop, quantizer, int(palettesize)
)
def _close(self):
self._writer.close()
def _append_data(self, im, meta):
im = image_as_uint(im, bitdepth=8)
if im.ndim == 3 and im.shape[-1] == 1:
im = im[:, :, 0]
duration = self._duration
if isinstance(duration, list):
duration = duration[min(len(duration) - 1, self._writer._count)]
dispose = self._dispose
self._writer.add_image(im, duration, dispose)
return
def intToBin(i):
return i.to_bytes(2, byteorder="little")
class GifWriter:
"""Class that for helping write the animated GIF file. This is based on
code from images2gif.py (part of visvis). The version here is modified
to allow streamed writing.
"""
def __init__(
self,
file,
opt_subrectangle=True,
opt_loop=0,
opt_quantizer=0,
opt_palette_size=256,
):
self.fp = file
self.opt_subrectangle = opt_subrectangle
self.opt_loop = opt_loop
self.opt_quantizer = opt_quantizer
self.opt_palette_size = opt_palette_size
self._previous_image = None # as np array
self._global_palette = None # as bytes
self._count = 0
from PIL.GifImagePlugin import getdata
self.getdata = getdata
def add_image(self, im, duration, dispose):
# Prepare image
im_rect, rect = im, (0, 0)
if self.opt_subrectangle:
im_rect, rect = self.getSubRectangle(im)
im_pil = self.converToPIL(im_rect, self.opt_quantizer, self.opt_palette_size)
# Get pallette - apparently, this is the 3d element of the header
# (but it has not always been). Best we've got. Its not the same
# as im_pil.palette.tobytes().
from PIL.GifImagePlugin import getheader
palette = getheader(im_pil)[0][3]
# Write image
if self._count == 0:
self.write_header(im_pil, palette, self.opt_loop)
self._global_palette = palette
self.write_image(im_pil, palette, rect, duration, dispose)
# assert len(palette) == len(self._global_palette)
# Bookkeeping
self._previous_image = im
self._count += 1
def write_header(self, im, globalPalette, loop):
# Gather info
header = self.getheaderAnim(im)
appext = self.getAppExt(loop)
# Write
self.fp.write(header)
self.fp.write(globalPalette)
self.fp.write(appext)
def close(self):
self.fp.write(";".encode("utf-8")) # end gif
def write_image(self, im, palette, rect, duration, dispose):
fp = self.fp
# Gather local image header and data, using PIL's getdata. That
# function returns a list of bytes objects, but which parts are
# what has changed multiple times, so we put together the first
# parts until we have enough to form the image header.
data = self.getdata(im)
imdes = b""
while data and len(imdes) < 11:
imdes += data.pop(0)
assert len(imdes) == 11
# Make image descriptor suitable for using 256 local color palette
lid = self.getImageDescriptor(im, rect)
graphext = self.getGraphicsControlExt(duration, dispose)
# Write local header
if (palette != self._global_palette) or (dispose != 2):
# Use local color palette
fp.write(graphext)
fp.write(lid) # write suitable image descriptor
fp.write(palette) # write local color table
fp.write(b"\x08") # LZW minimum size code
else:
# Use global color palette
fp.write(graphext)
fp.write(imdes) # write suitable image descriptor
# Write image data
for d in data:
fp.write(d)
def getheaderAnim(self, im):
"""Get animation header. To replace PILs getheader()[0]"""
bb = b"GIF89a"
bb += intToBin(im.size[0])
bb += intToBin(im.size[1])
bb += b"\x87\x00\x00"
return bb
def getImageDescriptor(self, im, xy=None):
"""Used for the local color table properties per image.
Otherwise global color table applies to all frames irrespective of
whether additional colors comes in play that require a redefined
palette. Still a maximum of 256 color per frame, obviously.
Written by Ant1 on 2010-08-22
Modified by Alex Robinson in Janurari 2011 to implement subrectangles.
"""
# Defaule use full image and place at upper left
if xy is None:
xy = (0, 0)
# Image separator,
bb = b"\x2C"
# Image position and size
bb += intToBin(xy[0]) # Left position
bb += intToBin(xy[1]) # Top position
bb += intToBin(im.size[0]) # image width
bb += intToBin(im.size[1]) # image height
# packed field: local color table flag1, interlace0, sorted table0,
# reserved00, lct size111=7=2^(7 + 1)=256.
bb += b"\x87"
# LZW minimum size code now comes later, begining of [imagedata] blocks
return bb
def getAppExt(self, loop):
"""Application extension. This part specifies the amount of loops.
If loop is 0 or inf, it goes on infinitely.
"""
if loop == 1:
return b""
if loop == 0:
loop = 2**16 - 1
bb = b""
if loop != 0: # omit the extension if we would like a nonlooping gif
bb = b"\x21\xFF\x0B" # application extension
bb += b"NETSCAPE2.0"
bb += b"\x03\x01"
bb += intToBin(loop)
bb += b"\x00" # end
return bb
def getGraphicsControlExt(self, duration=0.1, dispose=2):
"""Graphics Control Extension. A sort of header at the start of
each image. Specifies duration and transparancy.
Dispose
-------
* 0 - No disposal specified.
* 1 - Do not dispose. The graphic is to be left in place.
* 2 - Restore to background color. The area used by the graphic
must be restored to the background color.
* 3 - Restore to previous. The decoder is required to restore the
area overwritten by the graphic with what was there prior to
rendering the graphic.
* 4-7 -To be defined.
"""
bb = b"\x21\xF9\x04"
bb += chr((dispose & 3) << 2).encode("utf-8")
# low bit 1 == transparency,
# 2nd bit 1 == user input , next 3 bits, the low two of which are used,
# are dispose.
bb += intToBin(int(duration * 100 + 0.5)) # in 100th of seconds
bb += b"\x00" # no transparant color
bb += b"\x00" # end
return bb
def getSubRectangle(self, im):
"""Calculate the minimal rectangle that need updating. Returns
a two-element tuple containing the cropped image and an x-y tuple.
Calculating the subrectangles takes extra time, obviously. However,
if the image sizes were reduced, the actual writing of the GIF
goes faster. In some cases applying this method produces a GIF faster.
"""
# Cannot do subrectangle for first image
if self._count == 0:
return im, (0, 0)
prev = self._previous_image
# Get difference, sum over colors
diff = np.abs(im - prev)
if diff.ndim == 3:
diff = diff.sum(2)
# Get begin and end for both dimensions
X = np.argwhere(diff.sum(0))
Y = np.argwhere(diff.sum(1))
# Get rect coordinates
if X.size and Y.size:
x0, x1 = int(X[0]), int(X[-1] + 1)
y0, y1 = int(Y[0]), int(Y[-1] + 1)
else: # No change ... make it minimal
x0, x1 = 0, 2
y0, y1 = 0, 2
return im[y0:y1, x0:x1], (x0, y0)
def converToPIL(self, im, quantizer, palette_size=256):
"""Convert image to Paletted PIL image.
PIL used to not do a very good job at quantization, but I guess
this has improved a lot (at least in Pillow). I don't think we need
neuqant (and we can add it later if we really want).
"""
im_pil = ndarray_to_pil(im, "gif")
if quantizer in ("nq", "neuquant"):
# NeuQuant algorithm
nq_samplefac = 10 # 10 seems good in general
im_pil = im_pil.convert("RGBA") # NQ assumes RGBA
nqInstance = NeuQuant(im_pil, nq_samplefac) # Learn colors
im_pil = nqInstance.quantize(im_pil, colors=palette_size)
elif quantizer in (0, 1, 2):
# Adaptive PIL algorithm
if quantizer == 2:
im_pil = im_pil.convert("RGBA")
else:
im_pil = im_pil.convert("RGB")
im_pil = im_pil.quantize(colors=palette_size, method=quantizer)
else:
raise ValueError("Invalid value for quantizer: %r" % quantizer)
return im_pil

File diff suppressed because it is too large Load Diff

View File

@@ -1,156 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
""" Read/Write images using SimpleITK.
Backend: `Insight Toolkit <https://itk.org/>`_
.. note::
To use this plugin you have to install its backend::
pip install imageio[itk]
The ItkFormat uses the ITK or SimpleITK library to support a range of
ITK-related formats. It also supports a few common formats (e.g. PNG and JPEG).
Parameters
----------
None
"""
from ..core import Format, has_module
_itk = None # Defer loading to load_lib() function.
def load_lib():
global _itk, _read_function, _write_function
try:
import itk as _itk
_read_function = _itk.imread
_write_function = _itk.imwrite
except ImportError:
try:
import SimpleITK as _itk
_read_function = _itk.ReadImage
_write_function = _itk.WriteImage
except ImportError:
raise ImportError(
"itk could not be found. "
"Please try "
" python -m pip install itk "
"or "
" python -m pip install simpleitk "
"or refer to "
" https://itkpythonpackage.readthedocs.io/ "
"for further instructions."
)
return _itk
# Split up in real ITK and all supported formats.
ITK_FORMATS = (
".gipl",
".ipl",
".mha",
".mhd",
".nhdr",
"nia",
"hdr",
".nrrd",
".nii",
".nii.gz",
".img",
".img.gz",
".vtk",
"hdf5",
"lsm",
"mnc",
"mnc2",
"mgh",
"mnc",
"pic",
)
ALL_FORMATS = ITK_FORMATS + (
".bmp",
".jpeg",
".jpg",
".png",
".tiff",
".tif",
".dicom",
".dcm",
".gdcm",
)
class ItkFormat(Format):
"""See :mod:`imageio.plugins.simpleitk`"""
def _can_read(self, request):
# If the request is a format that only this plugin can handle,
# we report that we can do it; a useful error will be raised
# when simpleitk is not installed. For the more common formats
# we only report that we can read if the library is installed.
if request.extension in ITK_FORMATS:
return True
if has_module("itk.ImageIOBase") or has_module("SimpleITK"):
return request.extension in ALL_FORMATS
def _can_write(self, request):
if request.extension in ITK_FORMATS:
return True
if has_module("itk.ImageIOBase") or has_module("SimpleITK"):
return request.extension in ALL_FORMATS
# -- reader
class Reader(Format.Reader):
def _open(self, pixel_type=None, fallback_only=None, **kwargs):
if not _itk:
load_lib()
args = ()
if pixel_type is not None:
args += (pixel_type,)
if fallback_only is not None:
args += (fallback_only,)
self._img = _read_function(self.request.get_local_filename(), *args)
def _get_length(self):
return 1
def _close(self):
pass
def _get_data(self, index):
# Get data
if index != 0:
error_msg = "Index out of range while reading from itk file"
raise IndexError(error_msg)
# Return array and empty meta data
return _itk.GetArrayFromImage(self._img), {}
def _get_meta_data(self, index):
error_msg = "The itk plugin does not support meta data, currently."
raise RuntimeError(error_msg)
# -- writer
class Writer(Format.Writer):
def _open(self):
if not _itk:
load_lib()
def _close(self):
pass
def _append_data(self, im, meta):
_itk_img = _itk.GetImageFromArray(im)
_write_function(_itk_img, self.request.get_local_filename())
def set_meta_data(self, meta):
error_msg = "The itk plugin does not support meta data, currently."
raise RuntimeError(error_msg)

View File

@@ -1,753 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
""" Read SPE files.
Backend: internal
This plugin supports reading files saved in the Princeton Instruments
SPE file format.
Parameters for reading
----------------------
char_encoding : str
Character encoding used to decode strings in the metadata. Defaults
to "latin1".
check_filesize : bool
The number of frames in the file is stored in the file header. However,
this number may be wrong for certain software. If this is `True`
(default), derive the number of frames also from the file size and
raise a warning if the two values do not match.
sdt_meta : bool
If set to `True` (default), check for special metadata written by the
`SDT-control` software. Does not have an effect for files written by
other software.
Metadata for reading
--------------------
ROIs : list of dict
Regions of interest used for recording images. Each dict has the
"top_left" key containing x and y coordinates of the top left corner,
the "bottom_right" key with x and y coordinates of the bottom right
corner, and the "bin" key with number of binned pixels in x and y
directions.
comments : list of str
The SPE format allows for 5 comment strings of 80 characters each.
controller_version : int
Hardware version
logic_output : int
Definition of output BNC
amp_hi_cap_low_noise : int
Amp switching mode
mode : int
Timing mode
exp_sec : float
Alternative exposure in seconds
date : str
Date string
detector_temp : float
Detector temperature
detector_type : int
CCD / diode array type
st_diode : int
Trigger diode
delay_time : float
Used with async mode
shutter_control : int
Normal, disabled open, or disabled closed
absorb_live : bool
on / off
absorb_mode : int
Reference strip or file
can_do_virtual_chip : bool
True or False whether chip can do virtual chip
threshold_min_live : bool
on / off
threshold_min_val : float
Threshold minimum value
threshold_max_live : bool
on / off
threshold_max_val : float
Threshold maximum value
time_local : str
Experiment local time
time_utc : str
Experiment UTC time
adc_offset : int
ADC offset
adc_rate : int
ADC rate
adc_type : int
ADC type
adc_resolution : int
ADC resolution
adc_bit_adjust : int
ADC bit adjust
gain : int
gain
sw_version : str
Version of software which created this file
spare_4 : bytes
Reserved space
readout_time : float
Experiment readout time
type : str
Controller type
clockspeed_us : float
Vertical clock speed in microseconds
readout_mode : ["full frame", "frame transfer", "kinetics", ""]
Readout mode. Empty string means that this was not set by the
Software.
window_size : int
Window size for Kinetics mode
file_header_ver : float
File header version
chip_size : [int, int]
x and y dimensions of the camera chip
virt_chip_size : [int, int]
Virtual chip x and y dimensions
pre_pixels : [int, int]
Pre pixels in x and y dimensions
post_pixels : [int, int],
Post pixels in x and y dimensions
geometric : list of {"rotate", "reverse", "flip"}
Geometric operations
sdt_major_version : int
(only for files created by SDT-control)
Major version of SDT-control software
sdt_minor_version : int
(only for files created by SDT-control)
Minor version of SDT-control software
sdt_controller_name : str
(only for files created by SDT-control)
Controller name
exposure_time : float
(only for files created by SDT-control)
Exposure time in seconds
color_code : str
(only for files created by SDT-control)
Color channels used
detection_channels : int
(only for files created by SDT-control)
Number of channels
background_subtraction : bool
(only for files created by SDT-control)
Whether background subtraction war turned on
em_active : bool
(only for files created by SDT-control)
Whether EM was turned on
em_gain : int
(only for files created by SDT-control)
EM gain
modulation_active : bool
(only for files created by SDT-control)
Whether laser modulation (“attenuate”) was turned on
pixel_size : float
(only for files created by SDT-control)
Camera pixel size
sequence_type : str
(only for files created by SDT-control)
Type of sequnce (standard, TOCCSL, arbitrary, …)
grid : float
(only for files created by SDT-control)
Sequence time unit (“grid size”) in seconds
n_macro : int
(only for files created by SDT-control)
Number of macro loops
delay_macro : float
(only for files created by SDT-control)
Time between macro loops in seconds
n_mini : int
(only for files created by SDT-control)
Number of mini loops
delay_mini : float
(only for files created by SDT-control)
Time between mini loops in seconds
n_micro : int (only for files created by SDT-control)
Number of micro loops
delay_micro : float (only for files created by SDT-control)
Time between micro loops in seconds
n_subpics : int
(only for files created by SDT-control)
Number of sub-pictures
delay_shutter : float
(only for files created by SDT-control)
Camera shutter delay in seconds
delay_prebleach : float
(only for files created by SDT-control)
Pre-bleach delay in seconds
bleach_time : float
(only for files created by SDT-control)
Bleaching time in seconds
recovery_time : float
(only for files created by SDT-control)
Recovery time in seconds
comment : str
(only for files created by SDT-control)
User-entered comment. This replaces the "comments" field.
datetime : datetime.datetime
(only for files created by SDT-control)
Combines the "date" and "time_local" keys. The latter two plus
"time_utc" are removed.
modulation_script : str
(only for files created by SDT-control)
Laser modulation script. Replaces the "spare_4" key.
"""
from datetime import datetime
import logging
import os
from typing import Any, Callable, Dict, Mapping, Optional, Sequence, Union
import numpy as np
from ..core import Format
logger = logging.getLogger(__name__)
class Spec:
"""SPE file specification data
Tuples of (offset, datatype, count), where offset is the offset in the SPE
file and datatype is the datatype as used in `numpy.fromfile`()
`data_start` is the offset of actual image data.
`dtypes` translates SPE datatypes (0...4) to numpy ones, e. g. dtypes[0]
is dtype("<f") (which is np.float32).
`controllers` maps the `type` metadata to a human readable name
`readout_modes` maps the `readoutMode` metadata to something human readable
although this may not be accurate since there is next to no documentation
to be found.
"""
basic = {
"datatype": (108, "<h"), # dtypes
"xdim": (42, "<H"),
"ydim": (656, "<H"),
"xml_footer_offset": (678, "<Q"),
"NumFrames": (1446, "<i"),
"file_header_ver": (1992, "<f"),
}
metadata = {
# ROI information
"NumROI": (1510, "<h"),
"ROIs": (
1512,
np.dtype(
[
("startx", "<H"),
("endx", "<H"),
("groupx", "<H"),
("starty", "<H"),
("endy", "<H"),
("groupy", "<H"),
]
),
10,
),
# chip-related sizes
"xDimDet": (6, "<H"),
"yDimDet": (18, "<H"),
"VChipXdim": (14, "<h"),
"VChipYdim": (16, "<h"),
# other stuff
"controller_version": (0, "<h"),
"logic_output": (2, "<h"),
"amp_high_cap_low_noise": (4, "<H"), # enum?
"mode": (8, "<h"), # enum?
"exposure_sec": (10, "<f"),
"date": (20, "<10S"),
"detector_temp": (36, "<f"),
"detector_type": (40, "<h"),
"st_diode": (44, "<h"),
"delay_time": (46, "<f"),
# shutter_control: normal, disabled open, disabled closed
# But which one is which?
"shutter_control": (50, "<H"),
"absorb_live": (52, "<h"),
"absorb_mode": (54, "<H"),
"can_do_virtual_chip": (56, "<h"),
"threshold_min_live": (58, "<h"),
"threshold_min_val": (60, "<f"),
"threshold_max_live": (64, "<h"),
"threshold_max_val": (66, "<f"),
"time_local": (172, "<7S"),
"time_utc": (179, "<7S"),
"adc_offset": (188, "<H"),
"adc_rate": (190, "<H"),
"adc_type": (192, "<H"),
"adc_resolution": (194, "<H"),
"adc_bit_adjust": (196, "<H"),
"gain": (198, "<H"),
"comments": (200, "<80S", 5),
"geometric": (600, "<H"), # flags
"sw_version": (688, "<16S"),
"spare_4": (742, "<436S"),
"XPrePixels": (98, "<h"),
"XPostPixels": (100, "<h"),
"YPrePixels": (102, "<h"),
"YPostPixels": (104, "<h"),
"readout_time": (672, "<f"),
"xml_footer_offset": (678, "<Q"),
"type": (704, "<h"), # controllers
"clockspeed_us": (1428, "<f"),
"readout_mode": (1480, "<H"), # readout_modes
"window_size": (1482, "<H"),
"file_header_ver": (1992, "<f"),
}
data_start = 4100
dtypes = {
0: np.dtype(np.float32),
1: np.dtype(np.int32),
2: np.dtype(np.int16),
3: np.dtype(np.uint16),
8: np.dtype(np.uint32),
}
controllers = [
"new120 (Type II)",
"old120 (Type I)",
"ST130",
"ST121",
"ST138",
"DC131 (PentaMax)",
"ST133 (MicroMax/Roper)",
"ST135 (GPIB)",
"VTCCD",
"ST116 (GPIB)",
"OMA3 (GPIB)",
"OMA4",
]
# This was gathered from random places on the internet and own experiments
# with the camera. May not be accurate.
readout_modes = ["full frame", "frame transfer", "kinetics"]
# Do not decode the following metadata keys into strings, but leave them
# as byte arrays
no_decode = ["spare_4"]
class SDTControlSpec:
"""Extract metadata written by the SDT-control software
Some of it is encoded in the comment strings
(see :py:meth:`parse_comments`). Also, date and time are encoded in a
peculiar way (see :py:meth:`get_datetime`). Use :py:meth:`extract_metadata`
to update the metadata dict.
"""
months = {
# Convert SDT-control month strings to month numbers
"Jän": 1,
"Jan": 1,
"Feb": 2,
"Mär": 3,
"Mar": 3,
"Apr": 4,
"Mai": 5,
"May": 5,
"Jun": 6,
"Jul": 7,
"Aug": 8,
"Sep": 9,
"Okt": 10,
"Oct": 10,
"Nov": 11,
"Dez": 12,
"Dec": 12,
}
sequence_types = {
# TODO: complete
"SEQU": "standard",
"SETO": "TOCCSL",
"KINE": "kinetics",
"SEAR": "arbitrary",
}
class CommentDesc:
"""Describe how to extract a metadata entry from a comment string"""
n: int
"""Which of the 5 SPE comment fields to use."""
slice: slice
"""Which characters from the `n`-th comment to use."""
cvt: Callable[[str], Any]
"""How to convert characters to something useful."""
scale: Union[None, float]
"""Optional scaling factor for numbers"""
def __init__(
self,
n: int,
slice: slice,
cvt: Callable[[str], Any] = str,
scale: Optional[float] = None,
):
self.n = n
self.slice = slice
self.cvt = cvt
self.scale = scale
comments = {
"sdt_major_version": CommentDesc(4, slice(66, 68), int),
"sdt_minor_version": CommentDesc(4, slice(68, 70), int),
"sdt_controller_name": CommentDesc(4, slice(0, 6), str),
"exposure_time": CommentDesc(1, slice(64, 73), float, 10**-6),
"color_code": CommentDesc(4, slice(10, 14), str),
"detection_channels": CommentDesc(4, slice(15, 16), int),
"background_subtraction": CommentDesc(4, 14, lambda x: x == "B"),
"em_active": CommentDesc(4, 32, lambda x: x == "E"),
"em_gain": CommentDesc(4, slice(28, 32), int),
"modulation_active": CommentDesc(4, 33, lambda x: x == "A"),
"pixel_size": CommentDesc(4, slice(25, 28), float, 0.1),
"sequence_type": CommentDesc(
4, slice(6, 10), lambda x: __class__.sequence_types[x]
),
"grid": CommentDesc(4, slice(16, 25), float, 10**-6),
"n_macro": CommentDesc(1, slice(0, 4), int),
"delay_macro": CommentDesc(1, slice(10, 19), float, 10**-3),
"n_mini": CommentDesc(1, slice(4, 7), int),
"delay_mini": CommentDesc(1, slice(19, 28), float, 10**-6),
"n_micro": CommentDesc(1, slice(7, 10), int),
"delay_micro": CommentDesc(1, slice(28, 37), float, 10**-6),
"n_subpics": CommentDesc(1, slice(7, 10), int),
"delay_shutter": CommentDesc(1, slice(73, 79), float, 10**-6),
"delay_prebleach": CommentDesc(1, slice(37, 46), float, 10**-6),
"bleach_time": CommentDesc(1, slice(46, 55), float, 10**-6),
"recovery_time": CommentDesc(1, slice(55, 64), float, 10**-6),
}
@staticmethod
def parse_comments(comments: Sequence[str]) -> Union[Dict, None]:
"""Extract SDT-control metadata from comments
Parameters
----------
comments
List of SPE file comments, typically ``metadata["comments"]``.
Returns
-------
If SDT-control comments were detected, return a dict of metadata, else
`None`.
"""
sdt_md = {}
if comments[4][70:] != "COMVER0500":
logger.debug("SDT-control comments not found.")
return None
sdt_md = {}
for name, spec in SDTControlSpec.comments.items():
try:
v = spec.cvt(comments[spec.n][spec.slice])
if spec.scale is not None:
v *= spec.scale
except Exception as e:
logger.debug(
"Failed to decode SDT-control metadata " f'field "{name}": {e}'
)
sdt_md[name] = v
comment = comments[0] + comments[2]
sdt_md["comment"] = comment.strip()
return sdt_md
@staticmethod
def get_datetime(date: str, time: str) -> Union[datetime, None]:
"""Turn date and time saved by SDT-control into proper datetime object
Parameters
----------
date
SPE file date, typically ``metadata["date"]``.
time
SPE file date, typically ``metadata["time_local"]``.
Returns
-------
File's datetime if parsing was succsessful, else None.
"""
try:
month = __class__.months[date[2:5]]
return datetime(
int(date[5:9]),
month,
int(date[0:2]),
int(time[0:2]),
int(time[2:4]),
int(time[4:6]),
)
except Exception as e:
logger.info(f"Failed to decode date from SDT-control metadata: {e}.")
@staticmethod
def extract_metadata(meta: Mapping, char_encoding: str = "latin1"):
"""Extract SDT-control metadata from SPE metadata
SDT-control stores some metadata in comments and other fields.
Extract them and remove unused entries.
Parameters
----------
meta
SPE file metadata. Modified in place.
char_encoding
Character encoding used to decode strings in the metadata.
"""
sdt_meta = __class__.parse_comments(meta["comments"])
if not sdt_meta:
return
# This file has SDT-control metadata
meta.pop("comments")
meta.update(sdt_meta)
# Get date and time in a usable format
dt = __class__.get_datetime(meta["date"], meta["time_local"])
if dt:
meta["datetime"] = dt
meta.pop("date")
meta.pop("time_local")
sp4 = meta["spare_4"]
try:
meta["modulation_script"] = sp4.decode(char_encoding)
meta.pop("spare_4")
except UnicodeDecodeError:
logger.warning(
"Failed to decode SDT-control laser "
"modulation script. Bad char_encoding?"
)
# Get rid of unused data
meta.pop("time_utc")
meta.pop("exposure_sec")
class SpeFormat(Format):
"""See :mod:`imageio.plugins.spe`"""
def _can_read(self, request):
return request.extension in self.extensions
def _can_write(self, request):
return False
class Reader(Format.Reader):
def _open(self, char_encoding="latin1", check_filesize=True, sdt_meta=True):
self._file = self.request.get_file()
self._char_encoding = char_encoding
info = self._parse_header(Spec.basic)
self._file_header_ver = info["file_header_ver"]
self._dtype = Spec.dtypes[info["datatype"]]
self._shape = (info["ydim"], info["xdim"])
self._len = info["NumFrames"]
self._sdt_meta = sdt_meta
if check_filesize:
# Some software writes incorrect `NumFrames` metadata.
# To determine the number of frames, check the size of the data
# segment -- until the end of the file for SPE<3, until the
# xml footer for SPE>=3.
data_end = (
info["xml_footer_offset"]
if info["file_header_ver"] >= 3
else os.path.getsize(self.request.get_local_filename())
)
line = data_end - Spec.data_start
line //= self._shape[0] * self._shape[1] * self._dtype.itemsize
if line != self._len:
logger.warning(
"The file header of %s claims there are %s frames, "
"but there are actually %s frames.",
self.request.filename,
self._len,
line,
)
self._len = min(line, self._len)
self._meta = None
def _get_meta_data(self, index):
if self._meta is None:
if self._file_header_ver < 3:
self._init_meta_data_pre_v3()
else:
self._init_meta_data_post_v3()
return self._meta
def _close(self):
# The file should be closed by `self.request`
pass
def _init_meta_data_pre_v3(self):
self._meta = self._parse_header(Spec.metadata)
nr = self._meta.pop("NumROI", None)
nr = 1 if nr < 1 else nr
self._meta["ROIs"] = roi_array_to_dict(self._meta["ROIs"][:nr])
# chip sizes
self._meta["chip_size"] = [
self._meta.pop("xDimDet", None),
self._meta.pop("yDimDet", None),
]
self._meta["virt_chip_size"] = [
self._meta.pop("VChipXdim", None),
self._meta.pop("VChipYdim", None),
]
self._meta["pre_pixels"] = [
self._meta.pop("XPrePixels", None),
self._meta.pop("YPrePixels", None),
]
self._meta["post_pixels"] = [
self._meta.pop("XPostPixels", None),
self._meta.pop("YPostPixels", None),
]
# comments
self._meta["comments"] = [str(c) for c in self._meta["comments"]]
# geometric operations
g = []
f = self._meta.pop("geometric", 0)
if f & 1:
g.append("rotate")
if f & 2:
g.append("reverse")
if f & 4:
g.append("flip")
self._meta["geometric"] = g
# Make some additional information more human-readable
t = self._meta["type"]
if 1 <= t <= len(Spec.controllers):
self._meta["type"] = Spec.controllers[t - 1]
else:
self._meta["type"] = ""
m = self._meta["readout_mode"]
if 1 <= m <= len(Spec.readout_modes):
self._meta["readout_mode"] = Spec.readout_modes[m - 1]
else:
self._meta["readout_mode"] = ""
# bools
for k in (
"absorb_live",
"can_do_virtual_chip",
"threshold_min_live",
"threshold_max_live",
):
self._meta[k] = bool(self._meta[k])
# frame shape
self._meta["frame_shape"] = self._shape
# Extract SDT-control metadata if desired
if self._sdt_meta:
SDTControlSpec.extract_metadata(self._meta, self._char_encoding)
def _parse_header(self, spec):
ret = {}
# Decode each string from the numpy array read by np.fromfile
decode = np.vectorize(lambda x: x.decode(self._char_encoding))
for name, sp in spec.items():
self._file.seek(sp[0])
cnt = 1 if len(sp) < 3 else sp[2]
v = np.fromfile(self._file, dtype=sp[1], count=cnt)
if v.dtype.kind == "S" and name not in Spec.no_decode:
# Silently ignore string decoding failures
try:
v = decode(v)
except Exception:
logger.warning(
'Failed to decode "{}" metadata '
"string. Check `char_encoding` "
"parameter.".format(name)
)
try:
# For convenience, if the array contains only one single
# entry, return this entry itself.
v = v.item()
except ValueError:
v = np.squeeze(v)
ret[name] = v
return ret
def _init_meta_data_post_v3(self):
info = self._parse_header(Spec.basic)
self._file.seek(info["xml_footer_offset"])
xml = self._file.read()
self._meta = {"__xml": xml}
def _get_length(self):
if self.request.mode[1] in "vV":
return 1
else:
return self._len
def _get_data(self, index):
if index < 0:
raise IndexError("Image index %i < 0" % index)
if index >= self._len:
raise IndexError("Image index %i > %i" % (index, self._len))
if self.request.mode[1] in "vV":
if index != 0:
raise IndexError("Index has to be 0 in v and V modes")
self._file.seek(Spec.data_start)
data = np.fromfile(
self._file,
dtype=self._dtype,
count=self._shape[0] * self._shape[1] * self._len,
)
data = data.reshape((self._len,) + self._shape)
else:
self._file.seek(
Spec.data_start
+ index * self._shape[0] * self._shape[1] * self._dtype.itemsize
)
data = np.fromfile(
self._file, dtype=self._dtype, count=self._shape[0] * self._shape[1]
)
data = data.reshape(self._shape)
return data, self._get_meta_data(index)
def roi_array_to_dict(a):
"""Convert the `ROIs` structured arrays to :py:class:`dict`
Parameters
----------
a : numpy.ndarray:
Structured array containing ROI data
Returns
-------
list of dict
One dict per ROI. Keys are "top_left", "bottom_right", and "bin",
values are tuples whose first element is the x axis value and the
second element is the y axis value.
"""
dict_list = []
a = a[["startx", "starty", "endx", "endy", "groupx", "groupy"]]
for sx, sy, ex, ey, gx, gy in a:
roi_dict = {
"top_left": [int(sx), int(sy)],
"bottom_right": [int(ex), int(ey)],
"bin": [int(gx), int(gy)],
}
dict_list.append(roi_dict)
return dict_list

View File

@@ -1,336 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
""" Read/Write SWF files.
Backend: internal
Shockwave flash (SWF) is a media format designed for rich and
interactive animations. This plugin makes use of this format to
store a series of images in a lossless format with good compression
(zlib). The resulting images can be shown as an animation using
a flash player (such as the browser).
SWF stores images in RGBA format. RGB or grayscale images are
automatically converted. SWF does not support meta data.
Parameters for reading
----------------------
loop : bool
If True, the video will rewind as soon as a frame is requested
beyond the last frame. Otherwise, IndexError is raised. Default False.
Parameters for saving
---------------------
fps : int
The speed to play the animation. Default 12.
loop : bool
If True, add a tag to the end of the file to play again from
the first frame. Most flash players will then play the movie
in a loop. Note that the imageio SWF Reader does not check this
tag. Default True.
html : bool
If the output is a file on the file system, write an html file
(in HTML5) that shows the animation. Default False.
compress : bool
Whether to compress the swf file. Default False. You probably don't
want to use this. This does not decrease the file size since
the images are already compressed. It will result in slower
read and write time. The only purpose of this feature is to
create compressed SWF files, so that we can test the
functionality to read them.
"""
import os
import zlib
import logging
from io import BytesIO
import numpy as np
from ..core import Format, read_n_bytes, image_as_uint
logger = logging.getLogger(__name__)
_swf = None # lazily loaded in lib()
def load_lib():
global _swf
from . import _swf
return _swf
class SWFFormat(Format):
"""See :mod:`imageio.plugins.swf`"""
def _can_read(self, request):
tmp = request.firstbytes[0:3].decode("ascii", "ignore")
if tmp in ("FWS", "CWS"):
return True
def _can_write(self, request):
if request.extension in self.extensions:
return True
# -- reader
class Reader(Format.Reader):
def _open(self, loop=False):
if not _swf:
load_lib()
self._arg_loop = bool(loop)
self._fp = self.request.get_file()
# Check file ...
tmp = self.request.firstbytes[0:3].decode("ascii", "ignore")
if tmp == "FWS":
pass # OK
elif tmp == "CWS":
# Compressed, we need to decompress
bb = self._fp.read()
bb = bb[:8] + zlib.decompress(bb[8:])
# Wrap up in a file object
self._fp = BytesIO(bb)
else:
raise IOError("This does not look like a valid SWF file")
# Skip first bytes. This also tests support got seeking ...
try:
self._fp.seek(8)
self._streaming_mode = False
except Exception:
self._streaming_mode = True
self._fp_read(8)
# Skip header
# Note that the number of frames is there, which we could
# potentially use, but the number of frames does not necessarily
# correspond to the number of images.
nbits = _swf.bits2int(self._fp_read(1), 5)
nbits = 5 + nbits * 4
Lrect = nbits / 8.0
if Lrect % 1:
Lrect += 1
Lrect = int(Lrect)
self._fp_read(Lrect + 3)
# Now the rest is basically tags ...
self._imlocs = [] # tuple (loc, sze, T, L1)
if not self._streaming_mode:
# Collect locations of frame, while skipping through the data
# This does not read any of the tag *data*.
try:
while True:
isimage, sze, T, L1 = self._read_one_tag()
loc = self._fp.tell()
if isimage:
# Still need to check if the format is right
format = ord(self._fp_read(3)[2:])
if format == 5: # RGB or RGBA lossless
self._imlocs.append((loc, sze, T, L1))
self._fp.seek(loc + sze) # Skip over tag
except IndexError:
pass # done reading
def _fp_read(self, n):
return read_n_bytes(self._fp, n)
def _close(self):
pass
def _get_length(self):
if self._streaming_mode:
return np.inf
else:
return len(self._imlocs)
def _get_data(self, index):
# Check index
if index < 0:
raise IndexError("Index in swf file must be > 0")
if not self._streaming_mode:
if self._arg_loop and self._imlocs:
index = index % len(self._imlocs)
if index >= len(self._imlocs):
raise IndexError("Index out of bounds")
if self._streaming_mode:
# Walk over tags until we find an image
while True:
isimage, sze, T, L1 = self._read_one_tag()
bb = self._fp_read(sze) # always read data
if isimage:
im = _swf.read_pixels(bb, 0, T, L1) # can be None
if im is not None:
return im, {}
else:
# Go to corresponding location, read data, and convert to image
loc, sze, T, L1 = self._imlocs[index]
self._fp.seek(loc)
bb = self._fp_read(sze)
# Read_pixels should return ndarry, since we checked format
im = _swf.read_pixels(bb, 0, T, L1)
return im, {}
def _read_one_tag(self):
"""
Return (True, loc, size, T, L1) if an image that we can read.
Return (False, loc, size, T, L1) if any other tag.
"""
# Get head
head = self._fp_read(6)
if not head: # pragma: no cover
raise IndexError("Reached end of swf movie")
# Determine type and length
T, L1, L2 = _swf.get_type_and_len(head)
if not L2: # pragma: no cover
raise RuntimeError("Invalid tag length, could not proceed")
# Read data
isimage = False
sze = L2 - 6
# bb = self._fp_read(L2 - 6)
# Parse tag
if T == 0:
raise IndexError("Reached end of swf movie")
elif T in [20, 36]:
isimage = True
# im = _swf.read_pixels(bb, 0, T, L1) # can be None
elif T in [6, 21, 35, 90]: # pragma: no cover
logger.warning("Ignoring JPEG image: cannot read JPEG.")
else:
pass # Not an image tag
# Done. Return image. Can be None
# return im
return isimage, sze, T, L1
def _get_meta_data(self, index):
return {} # This format does not support meta data
# -- writer
class Writer(Format.Writer):
def _open(self, fps=12, loop=True, html=False, compress=False):
if not _swf:
load_lib()
self._arg_fps = int(fps)
self._arg_loop = bool(loop)
self._arg_html = bool(html)
self._arg_compress = bool(compress)
self._fp = self.request.get_file()
self._framecounter = 0
self._framesize = (100, 100)
# For compress, we use an in-memory file object
if self._arg_compress:
self._fp_real = self._fp
self._fp = BytesIO()
def _close(self):
self._complete()
# Get size of (uncompressed) file
sze = self._fp.tell()
# set nframes, this is in the potentially compressed region
self._fp.seek(self._location_to_save_nframes)
self._fp.write(_swf.int2uint16(self._framecounter))
# Compress body?
if self._arg_compress:
bb = self._fp.getvalue()
self._fp = self._fp_real
self._fp.write(bb[:8])
self._fp.write(zlib.compress(bb[8:]))
sze = self._fp.tell() # renew sze value
# set size
self._fp.seek(4)
self._fp.write(_swf.int2uint32(sze))
self._fp = None # Disable
# Write html?
if self._arg_html and os.path.isfile(self.request.filename):
dirname, fname = os.path.split(self.request.filename)
filename = os.path.join(dirname, fname[:-4] + ".html")
w, h = self._framesize
html = HTML % (fname, w, h, fname)
with open(filename, "wb") as f:
f.write(html.encode("utf-8"))
def _write_header(self, framesize, fps):
self._framesize = framesize
# Called as soon as we know framesize; when we get first frame
bb = b""
bb += "FC"[self._arg_compress].encode("ascii")
bb += "WS".encode("ascii") # signature bytes
bb += _swf.int2uint8(8) # version
bb += "0000".encode("ascii") # FileLength (leave open for now)
bb += (
_swf.Tag().make_rect_record(0, framesize[0], 0, framesize[1]).tobytes()
)
bb += _swf.int2uint8(0) + _swf.int2uint8(fps) # FrameRate
self._location_to_save_nframes = len(bb)
bb += "00".encode("ascii") # nframes (leave open for now)
self._fp.write(bb)
# Write some initial tags
taglist = _swf.FileAttributesTag(), _swf.SetBackgroundTag(0, 0, 0)
for tag in taglist:
self._fp.write(tag.get_tag())
def _complete(self):
# What if no images were saved?
if not self._framecounter:
self._write_header((10, 10), self._arg_fps)
# Write stop tag if we do not loop
if not self._arg_loop:
self._fp.write(_swf.DoActionTag("stop").get_tag())
# finish with end tag
self._fp.write("\x00\x00".encode("ascii"))
def _append_data(self, im, meta):
# Correct shape and type
if im.ndim == 3 and im.shape[-1] == 1:
im = im[:, :, 0]
im = image_as_uint(im, bitdepth=8)
# Get frame size
wh = im.shape[1], im.shape[0]
# Write header on first frame
isfirstframe = False
if self._framecounter == 0:
isfirstframe = True
self._write_header(wh, self._arg_fps)
# Create tags
bm = _swf.BitmapTag(im)
sh = _swf.ShapeTag(bm.id, (0, 0), wh)
po = _swf.PlaceObjectTag(1, sh.id, move=(not isfirstframe))
sf = _swf.ShowFrameTag()
# Write tags
for tag in [bm, sh, po, sf]:
self._fp.write(tag.get_tag())
self._framecounter += 1
def set_meta_data(self, meta):
pass
HTML = """
<!DOCTYPE html>
<html>
<head>
<title>Show Flash animation %s</title>
</head>
<body>
<embed width="%i" height="%i" src="%s">
</html>
"""

View File

@@ -1,561 +0,0 @@
# -*- coding: utf-8 -*-
# imageio is distributed under the terms of the (new) BSD License.
""" Read/Write TIFF files.
Backend: internal
Provides support for a wide range of Tiff images using the tifffile
backend.
Parameters for reading
----------------------
offset : int
Optional start position of embedded file. By default this is
the current file position.
size : int
Optional size of embedded file. By default this is the number
of bytes from the 'offset' to the end of the file.
multifile : bool
If True (default), series may include pages from multiple files.
Currently applies to OME-TIFF only.
multifile_close : bool
If True (default), keep the handles of other files in multifile
series closed. This is inefficient when few files refer to
many pages. If False, the C runtime may run out of resources.
Parameters for saving
---------------------
bigtiff : bool
If True, the BigTIFF format is used.
byteorder : {'<', '>'}
The endianness of the data in the file.
By default this is the system's native byte order.
software : str
Name of the software used to create the image.
Saved with the first page only.
Metadata for reading
--------------------
planar_configuration : {'contig', 'planar'}
Specifies if samples are stored contiguous or in separate planes.
By default this setting is inferred from the data shape.
'contig': last dimension contains samples.
'planar': third last dimension contains samples.
resolution_unit : int
The resolution unit stored in the TIFF tag. Usually 1 means no/unknown unit,
2 means dpi (inch), 3 means dpc (centimeter).
resolution : (float, float, str)
A tuple formatted as (X_resolution, Y_resolution, unit). The unit is a
string representing one of the following units::
NONE # No unit or unit unknown
INCH # dpi
CENTIMETER # cpi
MILLIMETER
MICROMETER
compression : int
Value indicating the compression algorithm used, e.g. 5 is LZW,
7 is JPEG, 8 is deflate.
If 1, data are uncompressed.
predictor : int
Value 2 indicates horizontal differencing was used before compression,
while 3 indicates floating point horizontal differencing.
If 1, no prediction scheme was used before compression.
orientation : {'top_left', 'bottom_right', ...}
Oriented of image array.
is_rgb : bool
True if page contains a RGB image.
is_contig : bool
True if page contains a contiguous image.
is_tiled : bool
True if page contains tiled image.
is_palette : bool
True if page contains a palette-colored image and not OME or STK.
is_reduced : bool
True if page is a reduced image of another image.
is_shaped : bool
True if page contains shape in image_description tag.
is_fluoview : bool
True if page contains FluoView MM_STAMP tag.
is_nih : bool
True if page contains NIH image header.
is_micromanager : bool
True if page contains Micro-Manager metadata.
is_ome : bool
True if page contains OME-XML in image_description tag.
is_sgi : bool
True if page contains SGI image and tile depth tags.
is_mdgel : bool
True if page contains md_file_tag tag.
is_mediacy : bool
True if page contains Media Cybernetics Id tag.
is_stk : bool
True if page contains UIC2Tag tag.
is_lsm : bool
True if page contains LSM CZ_LSM_INFO tag.
description : str
Image description
description1 : str
Additional description
is_imagej : None or str
ImageJ metadata
software : str
Software used to create the TIFF file
datetime : datetime.datetime
Creation date and time
Metadata for writing
--------------------
photometric : {'minisblack', 'miniswhite', 'rgb'}
The color space of the image data.
By default this setting is inferred from the data shape.
planarconfig : {'contig', 'planar'}
Specifies if samples are stored contiguous or in separate planes.
By default this setting is inferred from the data shape.
'contig': last dimension contains samples.
'planar': third last dimension contains samples.
resolution : (float, float) or ((int, int), (int, int))
X and Y resolution in dots per inch as float or rational numbers.
description : str
The subject of the image. Saved with the first page only.
compress : int
Values from 0 to 9 controlling the level of zlib (deflate) compression.
If 0, data are written uncompressed (default).
compression : str, (int, int)
Compression scheme used while writing the image. If omitted (default) the
image is not uncompressed. Compression cannot be used to write contiguous
series. Compressors may require certain data shapes, types or value ranges.
For example, JPEG compression requires grayscale or RGB(A), uint8 or 12-bit
uint16. JPEG compression is experimental. JPEG markers and TIFF tags may not
match. Only a limited set of compression schemes are implemented. 'ZLIB' is
short for ADOBE_DEFLATE. The value is written to the Compression tag.
compressionargs:
Extra arguments passed to compression codec, e.g., compression level. Refer
to the Imagecodecs implementation for supported arguments.
predictor : bool
If True, horizontal differencing is applied before compression.
Note that using an int literal 1 actually means no prediction scheme
will be used.
volume : bool
If True, volume data are stored in one tile (if applicable) using
the SGI image_depth and tile_depth tags.
Image width and depth must be multiple of 16.
Few software can read this format, e.g. MeVisLab.
writeshape : bool
If True, write the data shape to the image_description tag
if necessary and no other description is given.
extratags: sequence of tuples
Additional tags as [(code, dtype, count, value, writeonce)].
code : int
The TIFF tag Id.
dtype : str
Data type of items in 'value' in Python struct format.
One of B, s, H, I, 2I, b, h, i, f, d, Q, or q.
count : int
Number of data values. Not used for string values.
value : sequence
'Count' values compatible with 'dtype'.
writeonce : bool
If True, the tag is written to the first page only.
Notes
-----
Global metadata is stored with the first frame in a TIFF file.
Thus calling :py:meth:`Format.Writer.set_meta_data` after the first frame
was written has no effect. Also, global metadata is ignored if metadata is
provided via the `meta` argument of :py:meth:`Format.Writer.append_data`.
If you have installed tifffile as a Python package, imageio will attempt
to use that as backend instead of the bundled backend. Doing so can
provide access to new performance improvements and bug fixes.
"""
import datetime
from ..core import Format
from ..core.request import URI_BYTES, URI_FILE
import numpy as np
import warnings
try:
import tifffile as _tifffile
except ImportError:
warnings.warn(
"ImageIO's vendored tifffile backend is deprecated and will be"
" removed in ImageIO v3. Install the tifffile directly:"
" `pip install imageio[tifffile]`",
DeprecationWarning,
)
from . import _tifffile
TIFF_FORMATS = (".tif", ".tiff", ".stk", ".lsm")
WRITE_METADATA_KEYS = (
"photometric",
"planarconfig",
"resolution",
"description",
"compress",
"compression",
"compressionargs",
"predictor",
"volume",
"writeshape",
"extratags",
"datetime",
)
READ_METADATA_KEYS = (
"planar_configuration",
"is_fluoview",
"is_nih",
"is_contig",
"is_micromanager",
"is_ome",
"is_lsm",
"is_palette",
"is_reduced",
"is_rgb",
"is_sgi",
"is_shaped",
"is_stk",
"is_tiled",
"is_mdgel",
"resolution_unit",
"compression",
"predictor",
"is_mediacy",
"orientation",
"description",
"description1",
"is_imagej",
"software",
)
class TiffFormat(Format):
"""Provides support for a wide range of Tiff images using the tifffile
backend.
Images that contain multiple pages can be read using ``imageio.mimread()``
to read the individual pages, or ``imageio.volread()`` to obtain a
single (higher dimensional) array.
Note that global metadata is stored with the first frame in a TIFF file.
Thus calling :py:meth:`Format.Writer.set_meta_data` after the first frame
was written has no effect. Also, global metadata is ignored if metadata is
provided via the `meta` argument of :py:meth:`Format.Writer.append_data`.
If you have installed tifffile as a Python package, imageio will attempt
to use that as backend instead of the bundled backend. Doing so can
provide access to new performance improvements and bug fixes.
Parameters for reading
----------------------
offset : int
Optional start position of embedded file. By default this is
the current file position.
size : int
Optional size of embedded file. By default this is the number
of bytes from the 'offset' to the end of the file.
multifile : bool
If True (default), series may include pages from multiple files.
Currently applies to OME-TIFF only.
multifile_close : bool
If True (default), keep the handles of other files in multifile
series closed. This is inefficient when few files refer to
many pages. If False, the C runtime may run out of resources.
Parameters for saving
---------------------
bigtiff : bool
If True, the BigTIFF format is used.
byteorder : {'<', '>'}
The endianness of the data in the file.
By default this is the system's native byte order.
software : str
Name of the software used to create the image.
Saved with the first page only.
Metadata for reading
--------------------
planar_configuration : {'contig', 'planar'}
Specifies if samples are stored contiguous or in separate planes.
By default this setting is inferred from the data shape.
'contig': last dimension contains samples.
'planar': third last dimension contains samples.
resolution_unit : (float, float) or ((int, int), (int, int))
X and Y resolution in dots per inch as float or rational numbers.
compression : int
Value indicating the compression algorithm used, e.g. 5 is LZW,
7 is JPEG, 8 is deflate.
If 1, data are uncompressed.
predictor : int
Value 2 indicates horizontal differencing was used before compression,
while 3 indicates floating point horizontal differencing.
If 1, no prediction scheme was used before compression.
orientation : {'top_left', 'bottom_right', ...}
Oriented of image array.
is_rgb : bool
True if page contains a RGB image.
is_contig : bool
True if page contains a contiguous image.
is_tiled : bool
True if page contains tiled image.
is_palette : bool
True if page contains a palette-colored image and not OME or STK.
is_reduced : bool
True if page is a reduced image of another image.
is_shaped : bool
True if page contains shape in image_description tag.
is_fluoview : bool
True if page contains FluoView MM_STAMP tag.
is_nih : bool
True if page contains NIH image header.
is_micromanager : bool
True if page contains Micro-Manager metadata.
is_ome : bool
True if page contains OME-XML in image_description tag.
is_sgi : bool
True if page contains SGI image and tile depth tags.
is_stk : bool
True if page contains UIC2Tag tag.
is_mdgel : bool
True if page contains md_file_tag tag.
is_mediacy : bool
True if page contains Media Cybernetics Id tag.
is_stk : bool
True if page contains UIC2Tag tag.
is_lsm : bool
True if page contains LSM CZ_LSM_INFO tag.
description : str
Image description
description1 : str
Additional description
is_imagej : None or str
ImageJ metadata
software : str
Software used to create the TIFF file
datetime : datetime.datetime
Creation date and time
Metadata for writing
--------------------
photometric : {'minisblack', 'miniswhite', 'rgb'}
The color space of the image data.
By default this setting is inferred from the data shape.
planarconfig : {'contig', 'planar'}
Specifies if samples are stored contiguous or in separate planes.
By default this setting is inferred from the data shape.
'contig': last dimension contains samples.
'planar': third last dimension contains samples.
resolution : (float, float) or ((int, int), (int, int))
X and Y resolution in dots per inch as float or rational numbers.
description : str
The subject of the image. Saved with the first page only.
compress : int
Values from 0 to 9 controlling the level of zlib (deflate) compression.
If 0, data are written uncompressed (default).
predictor : bool
If True, horizontal differencing is applied before compression.
Note that using an int literal 1 actually means no prediction scheme
will be used.
volume : bool
If True, volume data are stored in one tile (if applicable) using
the SGI image_depth and tile_depth tags.
Image width and depth must be multiple of 16.
Few software can read this format, e.g. MeVisLab.
writeshape : bool
If True, write the data shape to the image_description tag
if necessary and no other description is given.
extratags: sequence of tuples
Additional tags as [(code, dtype, count, value, writeonce)].
code : int
The TIFF tag Id.
dtype : str
Data type of items in 'value' in Python struct format.
One of B, s, H, I, 2I, b, h, i, f, d, Q, or q.
count : int
Number of data values. Not used for string values.
value : sequence
'Count' values compatible with 'dtype'.
writeonce : bool
If True, the tag is written to the first page only.
"""
def _can_read(self, request):
try:
_tifffile.TiffFile(request.get_file(), **request.kwargs)
except ValueError:
# vendored backend raises value exception
return False
except _tifffile.TiffFileError: # pragma: no-cover
# current version raises custom exception
return False
finally:
request.get_file().seek(0)
return True
def _can_write(self, request):
if request._uri_type in [URI_FILE, URI_BYTES]:
pass # special URI
elif request.extension not in self.extensions:
return False
try:
_tifffile.TiffWriter(request.get_file(), **request.kwargs)
except ValueError:
# vendored backend raises value exception
return False
except _tifffile.TiffFileError: # pragma: no-cover
# current version raises custom exception
return False
finally:
request.get_file().seek(0)
return True
# -- reader
class Reader(Format.Reader):
def _open(self, **kwargs):
# Allow loading from http; tifffile uses seek, so download first
if self.request.filename.startswith(("http://", "https://")):
self._f = f = open(self.request.get_local_filename(), "rb")
else:
self._f = None
f = self.request.get_file()
self._tf = _tifffile.TiffFile(f, **kwargs)
def _close(self):
self._tf.close()
if self._f is not None:
self._f.close()
def _get_length(self):
return len(self._tf.series)
def _get_data(self, index):
if index < 0 or index >= self._get_length():
raise IndexError("Index out of range while reading from tiff file")
im = self._tf.asarray(series=index)
meta = self._get_meta_data(index)
return im, meta
def _get_meta_data(self, index):
meta = {}
page = self._tf.pages[index or 0]
for key in READ_METADATA_KEYS:
try:
meta[key] = getattr(page, key)
except Exception:
pass
# tifffile <= 0.12.1 use datetime, newer use DateTime
for key in ("datetime", "DateTime"):
try:
meta["datetime"] = datetime.datetime.strptime(
page.tags[key].value, "%Y:%m:%d %H:%M:%S"
)
break
except Exception:
pass
if 296 in page.tags:
meta["resolution_unit"] = page.tags[296].value.value
if 282 in page.tags and 283 in page.tags and 296 in page.tags:
resolution_x = page.tags[282].value
resolution_y = page.tags[283].value
if resolution_x[1] == 0 or resolution_y[1] == 0:
warnings.warn(
"Ignoring resulution metadata, "
"because at least one direction has a 0 denominator.",
RuntimeWarning,
)
else:
meta["resolution"] = (
resolution_x[0] / resolution_x[1],
resolution_y[0] / resolution_y[1],
page.tags[296].value.name,
)
return meta
# -- writer
class Writer(Format.Writer):
def _open(self, bigtiff=None, byteorder=None, software=None):
try:
self._tf = _tifffile.TiffWriter(
self.request.get_file(),
bigtiff=bigtiff,
byteorder=byteorder,
software=software,
)
self._software = None
except TypeError:
# In tifffile >= 0.15, the `software` arg is passed to
# TiffWriter.save
self._tf = _tifffile.TiffWriter(
self.request.get_file(), bigtiff=bigtiff, byteorder=byteorder
)
self._software = software
self._meta = {}
self._frames_written = 0
def _close(self):
self._tf.close()
def _append_data(self, im, meta):
if meta is not None:
meta = self._sanitize_meta(meta)
else:
# Use global metadata for first frame
meta = self._meta if self._frames_written == 0 else {}
if self._software is not None and self._frames_written == 0:
meta["software"] = self._software
# No need to check self.request.mode; tifffile figures out whether
# this is a single page, or all page data at once.
try:
# TiffWriter.save has been deprecated in version 2020.9.30
write_meth = self._tf.write
except AttributeError:
write_meth = self._tf.save
write_meth(np.asanyarray(im), contiguous=False, **meta)
self._frames_written += 1
@staticmethod
def _sanitize_meta(meta):
ret = {}
for key, value in meta.items():
if key in WRITE_METADATA_KEYS:
# Special case of previously read `predictor` int value
# 1(=NONE) translation to False expected by TiffWriter.save
if key == "predictor" and not isinstance(value, bool):
ret[key] = value > 1
elif key == "compress" and value != 0:
warnings.warn(
"The use of `compress` is deprecated. Use `compression` and `compressionargs` instead.",
DeprecationWarning,
)
if _tifffile.__version__ < "2022":
ret["compression"] = (8, value)
else:
ret["compression"] = "zlib"
ret["compressionargs"] = {"level": value}
else:
ret[key] = value
return ret
def set_meta_data(self, meta):
self._meta = self._sanitize_meta(meta)

View File

@@ -1,434 +0,0 @@
"""Read/Write TIFF files using tifffile.
.. note::
To use this plugin you need to have `tifffile
<https://github.com/cgohlke/tifffile>`_ installed::
pip install tifffile
This plugin wraps tifffile, a powerfull library to manipulate TIFF files. It
superseeds our previous tifffile plugin and aims to expose all the features of
tifffile.
The plugin treats individual TIFF series as ndimages. A series is a sequence of
TIFF pages that, when combined describe a meaningful unit, e.g., a volumetric
image (where each slice is stored on an individual page) or a multi-color
staining picture (where each stain is stored on an individual page). Different
TIFF flavors/variants use series in different ways and, as such, the resulting
reading behavior may vary depending on the program used while creating a
particular TIFF file.
Methods
-------
.. note::
Check the respective function for a list of supported kwargs and detailed
documentation.
.. autosummary::
:toctree:
TifffilePlugin.read
TifffilePlugin.iter
TifffilePlugin.write
TifffilePlugin.properties
TifffilePlugin.metadata
Additional methods available inside the :func:`imopen <imageio.v3.imopen>`
context:
.. autosummary::
:toctree:
TifffilePlugin.iter_pages
"""
from io import BytesIO
from typing import Any, Dict, Optional, cast
import warnings
import datetime
import numpy as np
import tifffile
from ..core.request import URI_BYTES, InitializationError, Request
from ..core.v3_plugin_api import ImageProperties, PluginV3
from ..typing import ArrayLike
def _get_resolution(page):
"""Get the resolution in a py3.7 compatible way"""
metadata = {
# uncomment once py 3.7 reached EoL - in fact, refactor this
# function :)
# "resolution_unit": page.resolutionunit,
# "resolution": page.resolution,
}
if 296 in page.tags:
metadata["resolution_unit"] = page.tags[296].value.value
if 282 in page.tags and 283 in page.tags and 296 in page.tags:
resolution_x = page.tags[282].value
resolution_y = page.tags[283].value
if resolution_x[1] == 0 or resolution_y[1] == 0:
warnings.warn(
"Ignoring resulution metadata, "
"because at least one direction has a 0 denominator.",
RuntimeWarning,
)
else:
metadata["resolution"] = (
resolution_x[0] / resolution_x[1],
resolution_y[0] / resolution_y[1],
)
return metadata
def _get_datatime(page):
"""Get the datetime in a python 3.7 compatible way"""
metadata = {
# uncomment once python 3.7 is EoL
# "datetime": page.datetime,
}
try:
metadata["datetime"] = datetime.datetime.strptime(
page.tags[306].value, "%Y:%m:%d %H:%M:%S"
)
except KeyError:
pass
return metadata
class TifffilePlugin(PluginV3):
"""Support for tifffile as backend.
Parameters
----------
request : iio.Request
A request object that represents the users intent. It provides a
standard interface for a plugin to access the various ImageResources.
Check the docs for details.
kwargs : Any
Additional kwargs are forwarded to tifffile's constructor, i.e.
to ``TiffFile`` for reading or ``TiffWriter`` for writing.
"""
def __init__(self, request: Request, **kwargs) -> None:
super().__init__(request)
self._fh = None
if request.mode.io_mode == "r":
try:
self._fh = tifffile.TiffFile(request.get_file(), **kwargs)
except tifffile.tifffile.TiffFileError:
raise InitializationError("Tifffile can not read this file.")
else:
self._fh = tifffile.TiffWriter(request.get_file(), **kwargs)
# ---------------------
# Standard V3 Interface
# ---------------------
def read(self, *, index: int = None, page: int = None, **kwargs) -> np.ndarray:
"""Read a ndimage or page.
The ndimage returned depends on the value of both ``index`` and
``page``. ``index`` selects the series to read and ``page`` allows
selecting a single page from the selected series. If ``index=None``,
``page`` is understood as a flat index, i.e., the selection ignores
individual series inside the file. If both ``index`` and ``page`` are
``None``, then all the series are read and returned as a batch.
Parameters
----------
index : int
If ``int``, select the ndimage (series) located at that index inside
the file and return ``page`` from it. If ``None`` and ``page`` is
``int`` read the page located at that (flat) index inside the file.
If ``None`` and ``page=None``, read all ndimages from the file and
return them as a batch.
page : int
If ``None`` return the full selected ndimage. If ``int``, read the
page at the selected index and return it.
kwargs : Any
Additional kwargs are forwarded to TiffFile's ``as_array`` method.
Returns
-------
ndarray : np.ndarray
The decoded ndimage or page.
"""
if "key" not in kwargs:
kwargs["key"] = page
elif page is not None:
raise ValueError("Can't use `page` and `key` at the same time.")
# set plugin default for ``index``
if index is not None and "series" in kwargs:
raise ValueError("Can't use `series` and `index` at the same time.")
elif "series" in kwargs:
index = kwargs.pop("series")
elif index is not None:
pass
else:
index = 0
if index is Ellipsis and page is None:
# read all series in the file and return them as a batch
ndimage = np.stack([x for x in self.iter(**kwargs)])
else:
index = None if index is Ellipsis else index
ndimage = self._fh.asarray(series=index, **kwargs)
return ndimage
def iter(self, **kwargs) -> np.ndarray:
"""Yield ndimages from the TIFF.
Parameters
----------
kwargs : Any
Additional kwargs are forwarded to the TiffPageSeries' ``as_array``
method.
Yields
------
ndimage : np.ndarray
A decoded ndimage.
"""
for sequence in self._fh.series:
yield sequence.asarray(**kwargs)
def write(
self, ndimage: ArrayLike, *, is_batch: bool = False, **kwargs
) -> Optional[bytes]:
"""Save a ndimage as TIFF.
Parameters
----------
ndimage : ArrayLike
The ndimage to encode and write to the ImageResource.
is_batch : bool
If True, the first dimension of the given ndimage is treated as a
batch dimension and each element will create a new series.
kwargs : Any
Additional kwargs are forwarded to TiffWriter's ``write`` method.
Returns
-------
encoded_image : bytes
If the ImageResource is ``"<bytes>"``, return the encoded bytes.
Otherwise write returns None.
Notes
-----
Incremental writing is supported. Subsequent calls to ``write`` will
create new series unless ``contiguous=True`` is used, in which case the
call to write will append to the current series.
"""
if not is_batch:
ndimage = np.asarray(ndimage)[None, :]
for image in ndimage:
self._fh.write(image, **kwargs)
if self._request._uri_type == URI_BYTES:
self._fh.close()
file = cast(BytesIO, self._request.get_file())
return file.getvalue()
def metadata(
self, *, index: int = Ellipsis, page: int = None, exclude_applied: bool = True
) -> Dict[str, Any]:
"""Format-Specific TIFF metadata.
The metadata returned depends on the value of both ``index`` and
``page``. ``index`` selects a series and ``page`` allows selecting a
single page from the selected series. If ``index=Ellipsis``, ``page`` is
understood as a flat index, i.e., the selection ignores individual
series inside the file. If ``index=Ellipsis`` and ``page=None`` then
global (file-level) metadata is returned.
Parameters
----------
index : int
Select the series of which to extract metadata from. If Ellipsis, treat
page as a flat index into the file's pages.
page : int
If not None, select the page of which to extract metadata from. If
None, read series-level metadata or, if ``index=...`` global,
file-level metadata.
exclude_applied : bool
For API compatibility. Currently ignored.
Returns
-------
metadata : dict
A dictionary with information regarding the tiff flavor (file-level)
or tiff tags (page-level).
"""
if index is not Ellipsis and page is not None:
target = self._fh.series[index].pages[page]
elif index is not Ellipsis and page is None:
# This is based on my understanding that series-level metadata is
# stored in the first TIFF page.
target = self._fh.series[index].pages[0]
elif index is Ellipsis and page is not None:
target = self._fh.pages[page]
else:
target = None
metadata = {}
if target is None:
# return file-level metadata
metadata["byteorder"] = self._fh.byteorder
for flag in tifffile.TIFF.FILE_FLAGS:
flag_value = getattr(self._fh, "is_" + flag)
metadata["is_" + flag] = flag_value
if flag_value and hasattr(self._fh, flag + "_metadata"):
flavor_metadata = getattr(self._fh, flag + "_metadata")
if isinstance(flavor_metadata, tuple):
metadata.update(flavor_metadata[0])
else:
metadata.update(flavor_metadata)
else:
# tifffile may return a TiffFrame instead of a page
target = target.keyframe
metadata.update({tag.name: tag.value for tag in target.tags})
metadata.update(
{
"planar_configuration": target.planarconfig,
"compression": target.compression,
"predictor": target.predictor,
"orientation": None, # TODO
"description1": target.description1,
"description": target.description,
"software": target.software,
# update once python 3.7 reached EoL
**_get_resolution(target),
**_get_datatime(target),
}
)
return metadata
def properties(self, *, index: int = None, page: int = None) -> ImageProperties:
"""Standardized metadata.
The properties returned depend on the value of both ``index`` and
``page``. ``index`` selects a series and ``page`` allows selecting a
single page from the selected series. If ``index=Ellipsis``, ``page`` is
understood as a flat index, i.e., the selection ignores individual
series inside the file. If ``index=Ellipsis`` and ``page=None`` then
global (file-level) properties are returned. If ``index=Ellipsis``
and ``page=...``, file-level properties for the flattened index are
returned.
Parameters
----------
index : int
If ``int``, select the ndimage (series) located at that index inside
the file. If ``Ellipsis`` and ``page`` is ``int`` extract the
properties of the page located at that (flat) index inside the file.
If ``Ellipsis`` and ``page=None``, return the properties for the
batch of all ndimages in the file.
page : int
If ``None`` return the properties of the full ndimage. If ``...``
return the properties of the flattened index. If ``int``,
return the properties of the page at the selected index only.
Returns
-------
image_properties : ImageProperties
The standardized metadata (properties) of the selected ndimage or series.
"""
index = index or 0
page_idx = 0 if page in (None, Ellipsis) else page
if index is Ellipsis:
target_page = self._fh.pages[page_idx]
else:
target_page = self._fh.series[index].pages[page_idx]
if index is Ellipsis and page is None:
n_series = len(self._fh.series)
props = ImageProperties(
shape=(n_series, *target_page.shape),
dtype=target_page.dtype,
n_images=n_series,
is_batch=True,
spacing=_get_resolution(target_page)["resolution"],
)
elif index is Ellipsis and page is Ellipsis:
n_pages = len(self._fh.pages)
props = ImageProperties(
shape=(n_pages, *target_page.shape),
dtype=target_page.dtype,
n_images=n_pages,
is_batch=True,
spacing=_get_resolution(target_page)["resolution"],
)
else:
props = ImageProperties(
shape=target_page.shape,
dtype=target_page.dtype,
is_batch=False,
spacing=_get_resolution(target_page)["resolution"],
)
return props
def close(self) -> None:
if self._fh is not None:
self._fh.close()
super().close()
# ------------------------------
# Add-on Interface inside imopen
# ------------------------------
def iter_pages(self, index=..., **kwargs):
"""Yield pages from a TIFF file.
This generator walks over the flat index of the pages inside an
ImageResource and yields them in order.
Parameters
----------
index : int
The index of the series to yield pages from. If Ellipsis, walk over
the file's flat index (and ignore individual series).
kwargs : Any
Additional kwargs are passed to TiffPage's ``as_array`` method.
Yields
------
page : np.ndarray
A page stored inside the TIFF file.
"""
if index is Ellipsis:
pages = self._fh.pages
else:
pages = self._fh.series[index]
for page in pages:
yield page.asarray(**kwargs)