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| title: RefDiffNet | |
| emoji: 🔬 | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: "4.44.0" | |
| python_version: "3.10" | |
| app_file: app.py | |
| pinned: false | |
| license: agpl-3.0 | |
| # RefDiffNet — PCB Reference–Defect Enrichment (A11_CA) | |
| **Space:** [vinayedula/RefDiffNet](https://huggingface.co/spaces/vinayedula/RefDiffNet) | |
| Gradio demo for the **A11_CA** prebackbone trained with YOLO12n on HR-IPCB. | |
| - **Inputs:** defect PCB image + golden reference image | |
| - **Output:** enriched image (`enriched = defect + α · gate · delta`) | |
| Weights: `weights/prebackbone_a11_ca.pt` (~few MB, prebackbone only — not full `best.pt`) | |
| ## Deploy to Hugging Face Spaces | |
| ### 1. Prepare the Space folder locally | |
| From the VYOLO repo root: | |
| ```bash | |
| cd /mnt/data/vinay/work/VYOLO | |
| bash hf_prebackbone_demo/prepare_space.sh | |
| ``` | |
| This will: | |
| - Copy the custom **Ultralytics** fork into `hf_prebackbone_demo/vendor/` | |
| - Extract `prebackbone_a11_ca.pt` from `best.pt` (small file for the Space) | |
| - Copy example image pairs into `hf_prebackbone_demo/examples/` | |
| ### 2. Create a new Space on Hugging Face | |
| 1. Go to [huggingface.co/new-space](https://huggingface.co/new-space) | |
| 2. Choose **Gradio** SDK | |
| 3. Clone the empty Space repo locally | |
| ### 3. Push to [vinayedula/RefDiffNet](https://huggingface.co/spaces/vinayedula/RefDiffNet) | |
| ```bash | |
| cd hf_prebackbone_demo | |
| bash deploy_to_refdiffnet.sh | |
| ``` | |
| Or manually: | |
| ```bash | |
| git clone https://huggingface.co/spaces/vinayedula/RefDiffNet | |
| cd RefDiffNet | |
| # copy app.py, vendor/, weights/prebackbone_a11_ca.pt, examples/, etc. | |
| git add . && git commit -m "RefDiffNet demo" && git push | |
| ``` | |
| > **Note:** `prebackbone_a11_ca.pt` is only a few MB (no LFS needed). Full `best.pt` is optional. | |
| ### 4. Space settings (recommended) | |
| | Setting | Value | | |
| |---------|--------| | |
| | Hardware | CPU Basic (works) or **GPU** for faster loads | | |
| | Secrets | Optional: `HF_TOKEN` if weights are in a private model repo | | |
| ### Alternative: host weights on the Hub | |
| Upload `prebackbone_a11_ca.pt` to a model repo, then set: | |
| ``` | |
| HF_MODEL_REPO=YOUR_USER/YOUR_MODEL | |
| ``` | |
| The app downloads `prebackbone_a11_ca.pt` from that repo. | |
| ## Run locally | |
| ```bash | |
| cd hf_prebackbone_demo | |
| pip install -r requirements.txt | |
| pip install -e ../ultralytics # custom fork with A11_CA | |
| python extract_prebackbone_weights.py --ckpt /path/to/best.pt | |
| export PREBACKBONE_ONLY_WEIGHTS=weights/prebackbone_a11_ca.pt | |
| python app.py | |
| ``` | |
| Open http://localhost:7860 | |
| ## Environment variables | |
| | Variable | Description | | |
| |----------|-------------| | |
| | `PREBACKBONE_ONLY_WEIGHTS` | Path to `prebackbone_a11_ca.pt` | | |
| | `PREBACKBONE_FULL_CKPT` | Full `best.pt` (only for one-time extraction) | | |
| | `HF_MODEL_REPO` | Hub repo with `prebackbone_a11_ca.pt` | | |
| | `PREBACKBONE_IMGSZ` | Letterbox size (default `640`) | | |
| | `ULTRALYTICS_ROOT` | Path to ultralytics repo if not vendored | | |
| | `PORT` | Gradio port (default `7860`) | | |