webcamremovebg:删除网络摄像头图像的背景并将结果流式传输到虚拟视频设备中

# WebCam Remove Background A Python script to remove background of a webcam image and stream the result into a virtual video device. The background removal is based on face detection with OpenCV within each image. ## Requirements - Tested with Python 3.7 - Requires [V4L2-Loopback](https://github.com/umlaeute/v4l2loopback). In Ubuntu this is available as the package `v4l2loopback-utils` and its dependencies. **HOWEVER** under Ubuntu 18.04 with recent Kernel, the module has a [bug](https://github.com/umlaeute/v4l2loopback/issues/172) (see [here](https://github.com/jremmons/pyfakewebcam/issues/5#issuecomment-612167782) also). Hence, it is advised to install `v4l2loopback` from github source. ## Usage 1. create a virtual video device ```bash $ sudo modprobe v4l2loopback devices=1 video_nr=20 card_label='v4l2loopback' exclusive_caps=1 ``` 2. Make sure you the video device `/dev/video20` has been created. 3. Run `python removeCamBg.py` ## Command line arguments See `python removeCamBg.py --help`. ``` usage: removeCamBg.py [-h] [-b BACKGROUND] [-u MASK_UPDATE] [-d MASK_DECAY] [-m MASK_MAX] [-c CAMERA_ID] [--debug] Read a webcam image and replace all background with pixels from a custom image. optional arguments: -h, --help show this help message and exit -b BACKGROUND, --background BACKGROUND Filename of the background image. By default, it's a noisy image -u MASK_UPDATE, --mask-update MASK_UPDATE Update the face mask every u frames -d MASK_DECAY, --mask-decay MASK_DECAY Upon losing the face, how fast shall the face fade away. Between 0 and 1. 0 Means to delete mask immediately, 1 means keep mask forever. -m MASK_MAX, --mask-max MASK_MAX Maximum blending factor of the detected face, between 0 and 1. 1 means the face is not transparent at all. 0 means face it not visible at all -c CAMERA_ID, --camera-id CAMERA_ID Id of the video capturing device to open. Will use 0 by default, that will open the default backend camera. --debug If set, show the resulting image in a debug window ``` ## Example Result Holding a newspaper in front of the camera yields these results. Input image:  Output image with some blending.