Machine Learning

You can easily connect your favorite machine learning framework with Label Studio by using Heartex SDK.

That gives you the opportunities to use:

Here is a quick example tutorial on how to do that with simple image classification:

  1. Create a new project

    label-studio init --template=image_classification imgcls
  1. Clone pyheartex, and start serving

    git clone https://github.com/heartexlabs/pyheartex.git
    cd pyheartex/examples/docker
    docker-compose up -d
  2. Specify running server url in imgcls/config.json:

    "ml_backend": {
      "url": "http://localhost:9090",
      "model_name": "my_super_model"
    }
  3. Launch Label Studio server:

    label-studio start imgcls

Once you’re satisfied with pre-labeling results, you can immediately send prediction requests via REST API:

curl -X POST -H 'Content-Type: application/json' -d '{"image_url": "https://go.heartex.net/static/samples/sample.jpg"}' http://localhost:8200/predict

Feel free to play around any other models & frameworks apart from image classifiers! (see instructions here)

Debugging

When something goes wrong, for example your predictions are failing, first thing to do is to check the log

docker exec -it model_server sh -c "tail -n50 /tmp/wsgi.log"