StreamGear Examples¶

StreamGear Live-Streaming Usage with PiGear¶

In this example, we will be Live-Streaming video-frames from Raspberry Pi (with Camera Module connected) using PiGear API and StreamGear API's Real-time Frames Mode:

Use -window_size & -extra_window_size FFmpeg parameters for controlling number of frames to be kept in Chunks. Less these value, less will be latency.

After every few chunks (equal to the sum of -window_size & -extra_window_size values), all chunks will be overwritten in Live-Streaming. Thereby, since newer chunks in manifest/playlist will contain NO information of any older ones, and therefore resultant DASH/HLS stream will play only the most recent frames.

In this mode, StreamGear DOES NOT automatically maps video-source audio to generated streams. You need to manually assign separate audio-source through -audio attribute of stream_params dictionary parameter.

PiGear API now fully supports the newer picamera2 python library under the hood for Raspberry Pi camera modules. Follow this guide ➶ for its installation.

Make sure to complete Raspberry Pi Camera Hardware-specific settings prior using the PiGear API, otherwise nothing will work.

DASHHLS

New Picamera2 backendLegacy Picamera backend

# import required libraries
from vidgear.gears import PiGear
from vidgear.gears import StreamGear
from libcamera import Transform
import cv2

# formulate various Picamera2 API 
# configurational parameters
options = {
    "queue": True,
    "buffer_count": 4,
    "controls": {"Brightness": 0.5, "ExposureValue": 2.0},
    "transform": Transform(hflip=1),
    "auto_align_output_config": True,  # auto-align camera configuration
}

# open pi video stream with defined parameters
stream = PiGear(resolution=(640, 480), framerate=60, logging=True, **options).start()

# enable livestreaming and retrieve framerate from CamGear Stream and
# pass it as `-input_framerate` parameter for controlled framerate
stream_params = {"-input_framerate": stream.framerate, "-livestream": True}

# describe a suitable manifest-file location/name
streamer = StreamGear(output="dash_out.mpd", **stream_params)

# loop over
while True:

    # read frames from stream
    frame = stream.read()

    # check for frame if Nonetype
    if frame is None:
        break

    # {do something with the frame here}

    # send frame to streamer
    streamer.stream(frame)

    # Show output window
    cv2.imshow("Output Frame", frame)

    # check for 'q' key if pressed
    key = cv2.waitKey(1) & 0xFF
    if key == ord("q"):
        break

# close output window
cv2.destroyAllWindows()

# safely close video stream
stream.stop()

# safely close streamer
streamer.close()

Under the hood, PiGear API (version 0.3.3 onwards) prioritizes the new picamera2 API backend.

However, PiGear API seamlessly switches to the legacy picamera backend, if the picamera2 library is unavailable or not installed.

It is advised to enable logging(logging=True) to see which backend is being used.

You could also enforce the legacy picamera API backend in PiGear by using the enforce_legacy_picamera user-defined optional parameter boolean attribute.

# import required libraries
from vidgear.gears import PiGear
from vidgear.gears import StreamGear
import cv2

# formulate various Picamera API 
# configurational parameters
options = {
    "hflip": True,
    "exposure_mode": "auto",
    "iso": 800,
    "exposure_compensation": 15,
    "awb_mode": "horizon",
    "sensor_mode": 0,
}

# open pi video stream with defined parameters
stream = PiGear(resolution=(640, 480), framerate=60, logging=True, **options).start()

# enable livestreaming and retrieve framerate from CamGear Stream and
# pass it as `-input_framerate` parameter for controlled framerate
stream_params = {"-input_framerate": stream.framerate, "-livestream": True}

# describe a suitable manifest-file location/name
streamer = StreamGear(output="dash_out.mpd", **stream_params)

# loop over
while True:

    # read frames from stream
    frame = stream.read()

    # check for frame if Nonetype
    if frame is None:
        break

    # {do something with the frame here}

    # send frame to streamer
    streamer.stream(frame)

    # Show output window
    cv2.imshow("Output Frame", frame)

    # check for 'q' key if pressed
    key = cv2.waitKey(1) & 0xFF
    if key == ord("q"):
        break

# close output window
cv2.destroyAllWindows()

# safely close video stream
stream.stop()

# safely close streamer
streamer.close()