Grab raw (2 byte per pixel data)

C++
,
5

The only modification was the bit shifting increased from 3 to 6. And added image saving and text saving lines for understanding what happening. Also tried to recreate the colors at the end of the script, but not much luck.

cap = cv2.VideoCapture(1, cv2.CAP_MSMF)
# set width and height
cols, rows = 400, 400,
cap.set(cv2.CAP_PROP_FRAME_WIDTH, cols)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, rows)
cap.set(cv2.CAP_PROP_FPS, 30)
cap.set(cv2.CAP_PROP_CONVERT_RGB, 0)

# Fetch undecoded RAW video streams
cap.set(cv2.CAP_PROP_FORMAT, -1)  # Format of the Mat objects. Set value -1 to fetch 
undecoded RAW video streams (as Mat 8UC1)
while True:
    # Capture frame-by-frame
    ret, frame = cap.read()#read into np array with [1,320000] h*w*2 byte
    #print(frame.shape)
    if not ret:
        break
    # Convert the frame from uint8 elements to big-endian signed int16 format.
    frame = frame.reshape(rows, cols*2) # Reshape to 800*400
    #cv2.imwrite('framereshaped.png', frame)
    frame = frame.astype(np.uint16) # Convert uint8 elements to uint16 elements
    #cv2.imwrite('framecasted.png', frame)
    np.savetxt('test.txt', frame, fmt="%d")
    frame = (frame[:, 0::2] << 8) + frame[:, 1::2]  # Convert from little endian to big endian (apply byte swap), the result is 340x240.
    #cv2.imwrite('framebigendian.png', frame)
    np.savetxt('testendian.txt', frame, fmt="%d")
    frame = frame.view(np.int16)
    np.savetxt('testint16.txt', frame, fmt="%d")
    #cv2.imwrite('frameview16.png', frame)
    # Apply some processing for disapply (this part is just "cosmetics"):
    frame_roi = frame[:, 10:-10]  # Crop 320x240 (the left and right parts are not meant to be displayed).
    # frame_roi = cv2.medianBlur(frame_roi, 3)  # Clean the dead pixels (just for better viewing the image).
    frame_roi = frame_roi << 6  # shift the 6 most left bits
    #cv2.imwrite('frameshifted.png', frame_roi)
    normed = cv2.normalize(frame_roi, None, 0, 255, cv2.NORM_MINMAX, cv2.CV_8UC3)  # Convert to uint8 with normalizing (just for viewing the image).
    #cv2.imwrite('framenormed.png', normed)
    gray = cv2.cvtColor(normed, cv2.COLOR_BAYER_RG2RGB)