def predict_from_cam()

in jetson_inference/artifacts/aws.greengrass.JetsonDLRImageClassification/1.0.0/inference.py [0:0]

• 22 lines of code
• 7 McCabe index (conditional complexity)

def predict_from_cam():
    if camera is None:
        print("Unable to support camera")
        return
    if platform.machine() == "armv7l":  # RaspBerry Pi
        stream = io.BytesIO()
        camera.start_preview()
        time.sleep(2)
        camera.capture(stream, format='jpeg')
        # Construct a numpy array from the stream
        data = np.fromstring(stream.getvalue(), dtype=np.uint8)
        # "Decode" the image from the array, preserving colour
        cvimage = cv2.imdecode(data, 1)
    elif platform.machine() == "aarch64":  # Nvidia Jetson TX
        if camera.isOpened():
            ret, cvimage = camera.read()
            cv2.destroyAllWindows()
        else:
            raise RuntimeError("Cannot open the camera")
    elif platform.machine() == "x86_64":  # Deeplens
        ret, cvimage = camera.getLastFrame()
        if ret == False:
            raise RuntimeError("Failed to get frame from the stream")
    return predict_from_image(cvimage)