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| title: SynLayers | |
| emoji: "🧩" | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: gradio | |
| python_version: "3.10" | |
| app_file: app.py | |
| suggested_hardware: a100-large | |
| startup_duration_timeout: 2h | |
| short_description: "GPU Space for SynLayers real-world layer decomposition" | |
| models: | |
| - SynLayers/Bbox-caption-8b | |
| pinned: false | |
| # SynLayers Demo | |
| This folder now contains a unified real-world inference demo: | |
| 1. `demo/infer` runs the fixed-prompt VLM caption + bbox detector. | |
| 2. `infer/infer.py` runs SynLayers decomposition with `infer/infer.yaml`. | |
| 3. `demo/real_world_pipeline.py` stitches the two stages together for one uploaded image. | |
| 4. `demo/app.py` provides a Gradio interface that can be used locally or adapted for a Hugging Face Space. | |
| ## Full GPU Space | |
| For a production Hugging Face Space, use GPU hardware and set: | |
| ```text | |
| SYNLAYERS_MODEL_REPO=SynLayers/Bbox-caption-8b | |
| ``` | |
| This lets the Space: | |
| - load the bbox detector from your uploaded model repo root | |
| - load SynLayers Pipeline | |
| ## Local Run | |
| From the `SynLayers` root: | |
| ```bash | |
| python demo/app.py | |
| ``` | |
| Or run the unified CLI directly: | |
| ```bash | |
| python demo/real_world_pipeline.py \ | |
| --image "/path/to/your/image.png" | |
| ``` | |