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| ================================================================================ | |
| HuggingFace Space for MedSAM - Complete Package | |
| ================================================================================ | |
| WHAT YOU HAVE: | |
| -------------- | |
| β Complete HuggingFace Space setup for your MedSAM model | |
| β Drop-in replacement client for your backend | |
| β Test scripts and integration examples | |
| β Full documentation | |
| FILES IN THIS FOLDER: | |
| -------------------- | |
| π¦ FOR HUGGINGFACE SPACE (upload these): | |
| 1. app.py - Gradio app with API | |
| 2. requirements.txt - Dependencies | |
| 3. README.md - Space description | |
| 4. .gitattributes - Git LFS config | |
| + medsam_vit_b.pth - Your model (download from HF) | |
| π DOCUMENTATION: | |
| 5. QUICKSTART.md - START HERE! 5-minute deploy guide | |
| 6. DEPLOYMENT_GUIDE.md - Detailed deployment steps | |
| 7. README_INTEGRATION.md - How to use in your backend | |
| π§ CODE EXAMPLES: | |
| 8. integration_example.py - Integration examples | |
| 9. test_space.py - Test script after deployment | |
| π FOR YOUR BACKEND: | |
| ../medsam_space_client.py - Drop-in SAM replacement (already copied!) | |
| QUICK START (15 minutes total): | |
| ------------------------------- | |
| STEP 1: Deploy Space (5 min) | |
| β Read: QUICKSTART.md | |
| β Go to: https://huggingface.co/new-space | |
| β Upload: app.py, requirements.txt, README.md, .gitattributes | |
| β Download & upload: medsam_vit_b.pth (from Aniketg6/Fine-Tuned-MedSAM) | |
| β Wait for build | |
| STEP 2: Test Space (2 min) | |
| β Visit: https://huggingface.co/spaces/YOUR_USERNAME/medsam-inference | |
| β Upload image in UI | |
| β Click "Segment" | |
| β Verify it works! | |
| STEP 3: Integrate with Backend (5 min) | |
| β Read: README_INTEGRATION.md | |
| β File already copied: ../medsam_space_client.py | |
| β Update app.py (just 5 lines!) | |
| β Add to .env: MEDSAM_SPACE_URL=https://YOUR_USERNAME-medsam-inference.hf.space/api/predict | |
| STEP 4: Test Integration (3 min) | |
| β Run: python test_space.py test_image.jpg 200 150 | |
| β Start your backend: python app.py | |
| β Test your API endpoint | |
| DONE! π | |
| INTEGRATION SUMMARY: | |
| ------------------- | |
| BEFORE (in your app.py): | |
| from segment_anything import sam_model_registry, SamPredictor | |
| sam = sam_model_registry["vit_b"](checkpoint="models/sam_vit_h_4b8939.pth") | |
| sam_predictor = SamPredictor(sam) | |
| AFTER (in your app.py): | |
| from medsam_space_client import MedSAMSpacePredictor | |
| sam_predictor = MedSAMSpacePredictor(os.getenv('MEDSAM_SPACE_URL')) | |
| Everything else stays EXACTLY the same! β¨ | |
| BENEFITS: | |
| --------- | |
| β No more 2.5GB model in memory | |
| β Can deploy backend to Vercel/serverless | |
| β Model hosted on HuggingFace (free!) | |
| β Same API as SAM (drop-in replacement) | |
| COSTS: | |
| ------ | |
| HuggingFace Space: | |
| - Free tier (CPU): FREE, but slower (5-10s per image) | |
| - Paid tier (T4 GPU): $0.60/hour (~$432/month if always on) | |
| Backend Deployment: | |
| - Vercel: Free tier or $20/month (Pro) | |
| - Railway: $7-10/month | |
| - Render: Free tier or $7/month | |
| NEXT STEPS: | |
| ----------- | |
| 1. Read QUICKSTART.md | |
| 2. Deploy your Space (5 minutes) | |
| 3. Read README_INTEGRATION.md | |
| 4. Update your app.py (5 minutes) | |
| 5. Deploy your backend to Vercel/Railway | |
| 6. Deploy your frontend to Vercel | |
| 7. Celebrate! π | |
| SUPPORT: | |
| -------- | |
| - Questions about Space deployment? β DEPLOYMENT_GUIDE.md | |
| - Questions about integration? β README_INTEGRATION.md | |
| - Want to test? β test_space.py | |
| - Want examples? β integration_example.py | |
| IMPORTANT LINKS: | |
| ---------------- | |
| - Create Space: https://huggingface.co/new-space | |
| - Your Model: https://huggingface.co/Aniketg6/Fine-Tuned-MedSAM | |
| - HF Spaces Docs: https://huggingface.co/docs/hub/spaces | |
| - Vercel Docs: https://vercel.com/docs | |
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| Questions? Start with QUICKSTART.md - it has everything you need! | |
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