comment here

src/interface.jl

@@ -27,7 +27,7 @@ vecToDict(vec::Vector{UInt8}) = copy(JSON3.read(String(vec)))
     # https://pyshine.com/Video-and-bidirectional-text-streaming/
     using CondaPkg; CondaPkg.add_pip("pybase64"); CondaPkg.add_pip("opencv-python"); CondaPkg.add("jsons"); CondaPkg.add("numpy");
     using PythonCall
-    cv = pyimport("cv2")
+    cv2 = pyimport("cv2")
     base64 = pyimport("pybase64")
     np = pyimport("numpy")
 
@@ -39,10 +39,10 @@ vecToDict(vec::Vector{UInt8}) = copy(JSON3.read(String(vec)))
     webcam = cv2.VideoCapture(0)
 
     _, frame_1 = webcam.read()      # julia's PythonCall python-obj numpy array
-    # frame_1 = cv.imread("20.jpg")     
+    # cv2_bgr_img = cv2.imread("20.jpg")     
 
     # compress image data formats in order to make network transfer easier.
-    _, buffer = cv.imencode(".jpg", frame_1)    
+    _, buffer = cv2.imencode(".jpg", cv2_bgr_img)    
 
     jpg_as_pyStr = base64.b64encode(buffer).decode("utf-8")
     jpg_as_juliaStr = pyconvert(String, jpg_as_pyStr)   # for base64, python string or julia string is the same
@@ -56,7 +56,7 @@ vecToDict(vec::Vector{UInt8}) = copy(JSON3.read(String(vec)))
     img_str = payload["img"]    # payload received thru mqtt
     buf = base64.b64decode(img_str)
     buffer = np.frombuffer(buf, dtype=np.uint8)
-    frame_1 = cv.imdecode(buffer, 1)
+    frame_1 = cv2.imdecode(buffer, 1)
     frame_1_julia = pyconvert(Array, frame_1);
     img_julia_RGB = imageUtils.np2juliaImage(frame_1_julia)