This demo combines several Redis data structures and Redis Modules to process a AnimalRecognitionDemostream of images and filter out the images that contain cats.
It uses:
- Redis Streams to capture the input video stream:
all - RedisGears to process this stream
- RedisAI to classify the images with MobilenetV2
It forwards the images that contain cats to a stream: cats
Docker and Python 2
To run the demo:
$ git clone https://github.com/RedisGears/AnimalRecognitionDemo.git
$ cd AnimalRecognitionDemo
# If you don't have it already, install https://git-lfs.github.com/ (On OSX: brew install git-lfs)
$ git lfs install && git lfs fetch && git lfs checkout
$ docker-compose up
If something went wrong, e.g. you skipped installing git-lfs, you need to force docker-compose to rebuild the containers
$ docker-compose up --force-recreate --build
Open a second terminal for the video capturing:
$ pip install -r camera/requirements.txt
$ python camera/read_camera.py
http://localhost:3000shows all the captured frameshttp://localhost:3001shows only the framse with cats
This demo is designed to be easy to setup, so it relies heavily on docker. You can get better performance and a higher FPS by runninng this demo outside docker. To control the FPS, edit the gear.py file.