The first version of the image segmentation demo integrated with the model registry and the compute sevice manager. It is adapted from a segmentation example in Dash Enterprise App Gallery.
To run this demo, docker-compose the followings (in the order):
- mlex_api: b384722
- mlex_model_registry: 65b803a
- mlex_dash_segmentation_demo
Then build the images of the models using the command make build_docker. (Currently fully supports random forest, pyMSDtorch, and kmeans model)
It supports asynchronous job submissions and results showing: choose which (completed) training results from the list to use for segmenting. Similarly, choose which (completed) segmenting (deploy) results to show.
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