Predictions

Torch Serve setup

Bounding Box Editor allows you to connect your own Torch Serve inference endpoint to perform bounding box predictions for images loaded within the application. For example this allows the following general workflow using PyTorch models to assist you in your annotation work:

1. Load the images you want to annotate in Bounding Box Editor.
2. Manually create annotations for a number of images.
3. Once you have created a sufficient number of annotations, export them in the format appropriate for your PyTorch model.
4. Train the model using the manually created ground-truth annotations.
5. Serve the model using Torch Serve.
6. Connect Bounding Box Editor to your inference endpoint.
7. Perform predictions on the remaining (not manually annotated) images and use them as hints to speed up the annotation procedure.

To set up a local Torch Serve server please refer to the instructions at the Torch Serve Github repository. Configuring the Torch Serve server connection and prediction settings in Bounding Box Editor is done using the Inference category in the Settings window:

Inference Settings