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| title: Image Selector Backend | |
| emoji: 🖼️ | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: docker | |
| app_port: 7860 | |
| pinned: false | |
| license: mit | |
| # Image Selector Backend API | |
| A FastAPI backend for intelligent image deduplication and selection. Upload images, group similar ones using ResNet50 embeddings, and keep only the best image from each group based on aesthetics scoring. | |
| ## 🚀 Features | |
| - **Smart Deduplication**: Groups similar images using deep learning embeddings | |
| - **Aesthetics Scoring**: Ranks images within each group using a CLIP-based aesthetics model | |
| - **REST API**: Simple endpoints for upload, process, progress tracking, and download | |
| - **Per-User Sessions**: Each user gets isolated processing and temporary storage | |
| - **Auto Cleanup**: Temporary files are removed after download | |
| ## 📡 API Endpoints | |
| ### Health Check | |
| ``` | |
| GET / | |
| ``` | |
| Returns: `{"status": "ok"}` | |
| ### Upload Images | |
| ``` | |
| POST /upload | |
| ``` | |
| Form fields: | |
| - `user_id` (text): Your unique session ID | |
| - `file` (file): Image file to upload | |
| ### Start Processing | |
| ``` | |
| POST /process | |
| ``` | |
| Form fields: | |
| - `user_id` (text): Your session ID | |
| - `similarity` (float, optional): Similarity threshold (default: 0.87) | |
| - `use_aesthetics` (bool, optional): Enable aesthetics scoring (default: true) | |
| ### Check Progress | |
| ``` | |
| GET /progress/{user_id} | |
| ``` | |
| Returns processing status, percentage, and ETA. | |
| ### Download Results | |
| ``` | |
| GET /download/{user_id} | |
| ``` | |
| Returns a ZIP file containing the best images from each group. | |
| ## 🔧 How It Works | |
| 1. **Upload**: Send images with a unique `user_id` | |
| 2. **Process**: Trigger processing - the backend will: | |
| - Generate embeddings for all images | |
| - Group similar images (similarity threshold configurable) | |
| - Score each image using an aesthetics model | |
| - Keep the best image from each group | |
| 3. **Download**: Retrieve a ZIP of selected images | |
| 4. **Auto-cleanup**: All temporary files are deleted after download | |
| ## 💻 Local Development | |
| ```bash | |
| git clone <this-repo> | |
| cd <repo-folder> | |
| pip install -r requirements.txt | |
| uvicorn main:app --host 0.0.0.0 --port 7860 | |
| ``` | |
| ## 🎨 Frontend | |
| Use with the web UI: | |
| - [Image Selector Frontend](https://github.com/basilbenny1002/image-selector-front-end) | |
| ## 📦 Tech Stack | |
| - **FastAPI**: Modern async web framework | |
| - **PyTorch**: Deep learning for embeddings | |
| - **ResNet50**: Feature extraction model | |
| - **CLIP**: Aesthetics prediction model | |
| - **SQLite**: Temporary embeddings storage | |
| ## ⚠️ Notes for HuggingFace Spaces | |
| - Uses `/tmp` for ephemeral storage (free tier) | |
| - For persistent storage, upgrade to a paid tier and data will use `/data` | |
| - Model weights download on first run (~500MB for ResNet50 + aesthetics model) | |
| - GPU recommended for faster processing (upgrade to T4 or better) | |
| ## 📄 License | |
| MIT License - see LICENSE file | |
| ## 🔗 Project Origin | |
| Based on [Image-Selecter](https://github.com/basilbenny1002/Image-Selecter) | |