| title: Medical Image Segmentation Gradio App | |
| emoji: 🌖 | |
| colorFrom: gray | |
| colorTo: indigo | |
| sdk: gradio | |
| sdk_version: 3.36.1 | |
| app_file: app.py | |
| pinned: false | |
| # Medical Image Segmentation Gradio App | |
| For the Gradio app we've removed the dependency on pytorch-lightning otherwise used in the project. | |
| The `load_lightning_SD_to_Usual_SD.ipynb` notebook contains the steps used to convert pytorch-lightning checkpoint to a regular model checkpoint. This was mainly done to reduce the file size (977 MB --> 244 MB). | |
| You can download the original saved checkpoint from over here: [wandb artifact](https://wandb.ai/veb-101/UM_medical_segmentation/artifacts/model/model-jsr2fn8v/v0/files) | |
| Or via Python: | |
| ```python | |
| import wandb | |
| run = wandb.init() | |
| artifact = run.use_artifact('veb-101/UM_medical_segmentation/model-jsr2fn8v:v0', type='model') | |
| artifact_dir = artifact.download() | |
| ``` | |