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| title: Classify 2 | |
| emoji: 🏆 | |
| colorFrom: pink | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 5.45.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| # 🐶🐱 Image Classifier – Multi-Model | |
| Try 3 backbones (ViT / ResNet / EfficientNet) on any image. We show **top-5 predictions** and **latency** to highlight accuracy vs speed trade-offs. | |
| ## Quickstart | |
| - Upload an image | |
| - Pick a model in the dropdown | |
| - Click **Predict** | |
| ## Why this matters | |
| Different backbones behave differently. This demo makes those trade-offs visible to judges/users in one place. | |
| ## Roadmap | |
| - Eval notebook → Confusion Matrix + Accuracy + ROC (binary subsets) | |
| - Auto-publish plots to this README | |
| - n8n workflow to re-run eval on new models and notify with results | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |