![]() ![]() Input #0, rtsp, : streamed by the RTSP serverÄuration: N/A, start: 0. Guessed Channel Layout for Input Stream #0.1 : mono Code to demonstrate a simple face detection model running on a video streamed over RTSP checkrtspexceptions.py. OpenCVs frontal face haar cascade detector Codes rtsppoc.py. Could not find codec parameters for stream 0 (Video: h264, none): unspecified sizeĬonsider increasing the value for the 'analyzeduration' and 'probesize' options The goal is to take a video file from disk, turn it into an RTSP stream, serve it across the LAN to another PC, and capture this video stream into OpenCV. For video, it will select stream 0 from B. ![]() ![]() out1.mkv is a Matroska container file and accepts video, audio and subtitle streams, so ffmpeg will try to select one of each type. My output ffmpeg version 3.1.1 Copyright (c) 2000-2016 the FFmpeg developers built with gcc 4.8 (Ubuntu 4.8.4-2ubuntu1~14.04.1)Ĭonfiguration: -enable-gpl -enable-libfaac -enable-libmp3lame -enable-libopencore-amrnb -enable-libopencore-amrwb -enable-libtheora -enable-libvorbis -enable-libx264 -enable-libxvid -enable-nonfree -enable-postproc -enable-version3 -enable-x11grab -disable-yasm There are three output files specified, and for the first two, no -map options are set, so ffmpeg will select streams for these two files automatically. ffmpeg -re -i input -f rtsp -rtsptransport tcp rtsp://localhost:8888/live.sdp ffplay -rtspflags listen rtsp://localhost:8888/live. You can find several scripts, I used an aption of this. There is also an option to build OpenCV with CUDA support. ![]() $ ffmpeg -i -f image2 -vf fps=fps=1/120 img%03d.jpg There is also an easy way to get an up-to-date OpenCV (currently 4.5.3) with FFMPEG support using: python3 -m pip install opencv-python But this has no hardware accelaration at all (neither OpenCV nor the FFMPEG integration). pip install python-ffmpeg-video-streaming Alternatively, add the dependency directly to your requirements.txt file: python-ffmpeg-video-streaming>0.1 Quickstart. it basically download the already build image. Other option is using already build image from DockerHub which is significantly faster. To build other versions, select different Dockerfile. I could not able to get the frames from the ip camera. git clone cd dockerpython-opencv-ffmpeg docker image build -t valian/docker-python-opencv-ffmpeg -f Dockerfile-py2.I used the following command to get the frames from RTSP h264 codec. ![]()
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