This is example of dockerization of computer vision engine for Angelcam.
INSTALLATION OF PREREQUISITES:
All you need is docker and docker-compose.
For docker installation use this guide:
- minimum required Linux kernel version is 3.10
For docker-compose installation use this guide:
- yml files for docker-compose debug.yml: - run "docker-compose -f debug.yml up" - this yml file is for debug purposes. It will write out configuration parameters used for engine start, output of engine and logs from engine - engine will use same configuration file default_config.ini as default.yml default.yml: - run "docker-compose -f default.yml up -d" - check if docker container (engine) is running and not restarting (docker ps) - this is similar to real start of engine. CV engine will be started with default_config.ini. After that engine will try to connect to the server test.yml: - run "docker-compose -f test.yml up" - this is test of CV engine functionality. It will write output logs, events and video to ./output
- data for testing purposes face.mp4: - used for functional test
- configuration files default_config.ini - configuration used for start of engine on real server test_config.ini - configuration used for testing purposes
- files needed by engine, but not dependent on camera (e.g. some learned models)
- source files
- recipe for example of CV engine dockerization
- file for compilation andinstallation of CV engine
- you can explore inside of container by "docker-compose -f debug.yml run engine /bin/bash"
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