CamGear API References

class CamGear:
    """
    CamGear supports a diverse range of video streams which can handle/control video stream almost any IP/USB Cameras, multimedia video file format (upto 4k tested),
    any network stream URL such as http(s), rtp, rtsp, rtmp, mms, etc. It also supports Gstreamer's RAW pipelines.

    CamGear API provides a flexible, high-level multi-threaded wrapper around OpenCV's VideoCapture API with direct access to almost all of its available parameters.
    It relies on Threaded Queue mode for threaded, error-free and synchronized frame handling.

    CamGear internally implements `yt_dlp` backend class for seamlessly pipelining live video-frames and metadata from various streaming services like YouTube, Dailymotion,
    Twitch, and [many more ➶](https://github.com/yt-dlp/yt-dlp/blob/master/supportedsites.md#supported-sites)
    """

    def __init__(
        self,
        source=0,
        stream_mode=False,
        backend=0,
        colorspace=None,
        logging=False,
        time_delay=0,
        **options
    ):
        """
        This constructor method initializes the object state and attributes of the CamGear class.

        Parameters:
            source (based on input): defines the source for the input stream.
            stream_mode (bool): controls the exclusive **Stream Mode** for handling streaming URLs.
            backend (int): selects the backend for OpenCV's VideoCapture class.
            colorspace (str): selects the colorspace of the input stream.
            logging (bool): enables/disables logging.
            time_delay (int): time delay (in sec) before start reading the frames.
            options (dict): provides ability to alter Source Tweak Parameters.
        """
        # enable logging if specified
        self.__logging = logging if isinstance(logging, bool) else False

        # print current version
        logcurr_vidgear_ver(logging=self.__logging)

        # initialize global
        self.ytv_metadata = {}

        # check if Stream-Mode is ON (True)
        if stream_mode:
            # TODO: check GStreamer backend support
            # gst_support = check_gstreamer_support(logging=self.__logging)
            # handle special Stream Mode parameters
            stream_resolution = get_supported_resolution(
                options.pop("STREAM_RESOLUTION", "best"), logging=self.__logging
            )
            # handle Stream-Mode
            if not (yt_dlp is None):
                # extract user-defined params
                yt_stream_params = options.pop("STREAM_PARAMS", {})
                if isinstance(yt_stream_params, dict):
                    yt_stream_params = {
                        str(k).strip(): v for k, v in yt_stream_params.items()
                    }
                else:
                    yt_stream_params = {}
                try:
                    # Validate source for Yt_dlp backend
                    logger.info(
                        "Verifying Streaming URL using yt-dlp backend. Please wait..."
                    )
                    # initialize YT_backend
                    ytbackend = YT_backend(
                        source_url=source, logging=self.__logging, **yt_stream_params
                    )
                    if ytbackend:
                        # save video metadata
                        self.ytv_metadata = ytbackend.meta_data
                        # handle live-streams
                        # Throw warning for livestreams
                        ytbackend.is_livestream and logger.warning(
                            "Livestream URL detected. It is strongly recommended to use the GStreamer backend (`backend=cv2.CAP_GSTREAMER`) with these URLs."
                        )
                        # check whether stream-resolution was specified and available
                        if not (stream_resolution in ytbackend.streams.keys()):
                            logger.warning(
                                "Specified stream-resolution `{}` is not available. Reverting to `best`!".format(
                                    stream_resolution
                                )
                            )
                            # revert to best
                            stream_resolution = "best"
                        else:
                            self.__logging and logger.debug(
                                "Using `{}` resolution for streaming.".format(
                                    stream_resolution
                                )
                            )
                        # extract stream URL as source using stream-resolution
                        source = ytbackend.streams[stream_resolution]
                        # log progress
                        self.__logging and logger.debug(
                            "YouTube source ID: `{}`, Title: `{}`, Quality: `{}`".format(
                                self.ytv_metadata["id"],
                                self.ytv_metadata["title"],
                                stream_resolution,
                            )
                        )
                except Exception as e:
                    # raise error if something went wrong
                    raise ValueError(
                        "[CamGear:ERROR] :: Stream Mode is enabled but Input URL is invalid!"
                    )
            else:
                # raise import errors
                import_dependency_safe("yt_dlp")

        # assigns special parameter to global variable and clear
        # Threaded Queue Mode
        self.__threaded_queue_mode = options.pop("THREADED_QUEUE_MODE", True)
        if not isinstance(self.__threaded_queue_mode, bool):
            # reset improper values
            self.__threaded_queue_mode = True
        # Thread Timeout
        self.__thread_timeout = options.pop("THREAD_TIMEOUT", None)
        if self.__thread_timeout and isinstance(self.__thread_timeout, (int, float)):
            # set values
            self.__thread_timeout = float(self.__thread_timeout)
        else:
            # defaults to 5mins timeout
            self.__thread_timeout = None

        self.__queue = None
        # initialize queue for video files only
        if self.__threaded_queue_mode and isinstance(source, str):
            # define queue and assign it to global var
            self.__queue = queue.Queue(maxsize=96)  # max bufferlen 96 to check overflow
            # log it
            self.__logging and logger.debug(
                "Enabling Threaded Queue Mode for the current video source!"
            )
        else:
            # otherwise disable it
            self.__threaded_queue_mode = False
            # log it
            self.__logging and logger.warning(
                "Threaded Queue Mode is disabled for the current video source!"
            )

        self.__thread_timeout and logger.info(
            "Setting Video-Thread Timeout to {}s.".format(self.__thread_timeout)
        )

        # stream variable initialization
        self.stream = None

        if backend and isinstance(backend, int):
            # add backend if specified and initialize the camera stream
            if check_CV_version() == 3:
                # Different OpenCV 3.4.x statement
                self.stream = cv2.VideoCapture(source + backend)
            else:
                # Two parameters are available since OpenCV 4+ (master branch)
                self.stream = cv2.VideoCapture(source, backend)
            logger.info("Setting backend `{}` for this source.".format(backend))
        else:
            # initialize the camera stream
            self.stream = cv2.VideoCapture(source)

        # initializing colorspace variable
        self.color_space = None

        # apply attributes to source if specified
        options = {str(k).strip(): v for k, v in options.items()}
        for key, value in options.items():
            property = capPropId(key)
            not (property is None) and self.stream.set(property, value)

        # handle colorspace value
        if not (colorspace is None):
            self.color_space = capPropId(colorspace.strip())
            self.__logging and not (self.color_space is None) and logger.debug(
                "Enabling `{}` colorspace for this video stream!".format(
                    colorspace.strip()
                )
            )

        # initialize and assign frame-rate variable
        self.framerate = 0.0
        _fps = self.stream.get(cv2.CAP_PROP_FPS)
        if _fps > 1.0:
            self.framerate = _fps

        # applying time delay to warm-up webcam only if specified
        time_delay and isinstance(time_delay, (int, float)) and time.sleep(time_delay)

        # frame variable initialization
        (grabbed, self.frame) = self.stream.read()

        # check if valid stream
        if grabbed:
            # render colorspace if defined
            if not (self.color_space is None):
                self.frame = cv2.cvtColor(self.frame, self.color_space)

            # initialize and append to queue
            self.__threaded_queue_mode and self.__queue.put(self.frame)
        else:
            raise RuntimeError(
                "[CamGear:ERROR] :: Source is invalid, CamGear failed to initialize stream on this source!"
            )

        # thread initialization
        self.__thread = None

        # initialize termination flag event
        self.__terminate = Event()

        # initialize stream read flag event
        self.__stream_read = Event()

    def start(self):
        """
        Launches the internal *Threaded Frames Extractor* daemon.

        **Returns:** A reference to the CamGear class object.
        """

        self.__thread = Thread(target=self.__update, name="CamGear", args=())
        self.__thread.daemon = True
        self.__thread.start()
        return self

    def __update(self):
        """
        A **Threaded Frames Extractor**, that keep iterating frames from OpenCV's VideoCapture API to a internal monitored queue,
        until the thread is terminated, or frames runs out.
        """

        # keep iterating infinitely
        # until the thread is terminated
        # or frames runs out
        # if the thread indicator variable is set, stop the thread
        while not self.__terminate.is_set():
            # stream not read yet
            self.__stream_read.clear()

            # otherwise, read the next frame from the stream
            (grabbed, frame) = self.stream.read()

            # stream read completed
            self.__stream_read.set()

            # check for valid frame if received
            if not grabbed:
                # no frames received, then safely exit
                if self.__threaded_queue_mode:
                    if self.__queue.empty():
                        break
                    else:
                        continue
                else:
                    break

            # apply colorspace to frames if valid
            if not (self.color_space is None):
                # apply colorspace to frames
                color_frame = None
                try:
                    color_frame = cv2.cvtColor(frame, self.color_space)
                except Exception as e:
                    # Catch if any error occurred
                    color_frame = None
                    self.color_space = None
                    self.__logging and logger.exception(str(e))
                    logger.warning("Assigned colorspace value is invalid. Discarding!")
                self.frame = color_frame if not (color_frame is None) else frame
            else:
                self.frame = frame

            # append to queue
            self.__threaded_queue_mode and self.__queue.put(self.frame)

        # signal queue we're done
        self.__threaded_queue_mode and self.__queue.put(None)
        self.__threaded_queue_mode = False

        # indicate immediate termination
        self.__terminate.set()
        self.__stream_read.set()

        # release resources
        self.stream.release()

    def read(self):
        """
        Extracts frames synchronously from monitored queue, while maintaining a fixed-length frame buffer in the memory,
        and blocks the thread if the queue is full.

        **Returns:** A n-dimensional numpy array.
        """
        while self.__threaded_queue_mode and not self.__terminate.is_set():
            return self.__queue.get(timeout=self.__thread_timeout)
        # return current frame
        # only after stream is read
        return (
            self.frame
            if not self.__terminate.is_set()  # check if already terminated
            and self.__stream_read.wait(timeout=self.__thread_timeout)  # wait for it
            else None
        )

    def stop(self):
        """
        Safely terminates the thread, and release the multi-threaded resources.
        """
        self.__logging and logger.debug("Terminating processes.")
        # terminate Threaded queue mode separately
        self.__threaded_queue_mode = False

        # indicate that the thread
        # should be terminated immediately
        self.__stream_read.set()
        self.__terminate.set()

        # wait until stream resources are released (producer thread might be still grabbing frame)
        if self.__thread is not None:
            if not (self.__queue is None):
                while not self.__queue.empty():
                    try:
                        self.__queue.get_nowait()
                    except queue.Empty:
                        continue
                    self.__queue.task_done()
            self.__thread.join()