Upload README.md

README.md

@@ -1,3 +1,14 @@
+---
+title: Sea Ice SegFormer
+emoji: 🌊
+colorFrom: blue
+colorTo: green
+sdk: gradio
+sdk_version: "4.12.0"
+app_file: app.py
+pinned: false
+---
+
 # Sea Ice Segmentation — Hugging Face Space
 
 Gradio app that runs MMSegmentation SegFormer-B5 on RGB images and returns an overlayed segmentation result.
@@ -5,9 +16,6 @@ Gradio app that runs MMSegmentation SegFormer-B5 on RGB images and returns an ov
 ## Repo layout
 - `app.py` — Gradio UI and inference code.
 - `requirements.txt` — Python dependencies for the Space.
-- `model/`
-  - `segformer_mit-b5_8xb1-160k_pre-cityscapes_seaicergb0-1024x1024.py` — MMSeg config.
-  - `iter_160000.pth` — trained checkpoint (tracked with Git LFS).
 
 ## Run locally (optional)
 ```bash
@@ -17,17 +25,10 @@ python app.py
 
 ## Deploy to Hugging Face Spaces
 1. Create a new Space (SDK: Gradio). CPU is fine; GPU optional for faster inference.
-2. Push this repo to the Space remote. Ensure LFS is enabled for the `.pth`:
-   ```bash
-   git lfs install
-   git lfs track "model/*.pth"
-   git add .gitattributes model/iter_160000.pth
-   git commit -m "Add checkpoint via LFS"
-   git push
-   ```
-3. The Space will build and start. First cold-start may take a few minutes while installing dependencies.
+2. Push this repo to the Space remote (no large files needed). The Space will build and start. First cold-start may take a few minutes while installing dependencies.
 
 ## Notes
 - If your config defines `classes` and `palette`, the app will use them automatically; otherwise it falls back to generated colors.
 - Large input images are supported; overlay alpha can be adjusted in the UI.
-- To switch checkpoints or configs, update the paths at the top of `app.py`.
+- The app downloads the config and checkpoint from the model repo `triton7777/SeaIce` at runtime (no .pth stored in this Space).
+- To switch checkpoints or configs, update `REPO_ID`, `CONFIG_FILENAME`, and `CHECKPOINT_FILENAME` at the top of `app.py`.