Sortable and searchable compilation of pre-trained deep learning models. With demos and code.
This is running on a server without GPU, hence it seems slow.
Also, the code may look a bit like monkey-patching for the following reasons:
- Models are cloned as submodules: therefore we have to mess around with the python path :-(
- There is a queuing systems for the jobs (allows user to see their job's position in the queue)
Having spent too much time installing deep learning models just to evaluate their performance, I created this repo for several reasons:
- Access a free demo of deep learning models
- Gather available deep learning models
- Get a docker container running the model for a quick install
Requirements: Docker, docker-compose and enough space free for the model weights.
git clone https://github.com/EliotAndres/pretrained.ml --recursive
cd containers
docker-compose build
docker-compose up -d
docker ps #list images
docker attach [container_id] #attach a shell to specific image
Many models are missing. Any help is welcome ! You have two options to contribute.
Easy way: Add a model to the list without a demo:
- Fork the repo
- Edit the docs/models.yaml file (you can even edit it with Github's editor)
- Make a pull request
Other way: add a model with a demo:
- Fork the repo
- Add the model inside one of the docker containers
- Create a route in the serve.py file
- Add a demo calling the route
- Make a pull request
- Use nvidia-docker ?
- Add flag to compile Tensorflow
- Consider splitting each model in a different container ?
- Linter
- Add analytics