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| # π CIFAR-100 ResNet-18 Hugging Face Space | |
| This directory contains the Hugging Face Space for the CIFAR-100 ResNet-18 model. | |
| ## π Files | |
| - **`app.py`** - Main Gradio application | |
| - **`requirements.txt`** - Python dependencies | |
| - **`README.md`** - Space configuration and documentation | |
| - **`test_model.py`** - Model testing script | |
| - **`.gitignore`** - Git ignore patterns | |
| ## π Model Performance | |
| - **77.45% Test Accuracy** (4.45% above 73% target) | |
| - **11.22M Parameters** (ResNet-18 architecture) | |
| - **100 CIFAR-100 Classes** supported | |
| ## π Links | |
| - **Live Space:** https://huggingface.co/spaces/santhoshv6/ERA_V4_S8_Assignment | |
| - **Model Repository:** https://github.com/santhoshv6/era_v4_s8_assignment | |
| - **Model Download:** Available from GitHub releases | |
| ## π Local Testing | |
| ```bash | |
| python test_model.py | |
| python app.py | |
| ``` | |
| ## π¦ Model Loading | |
| The app automatically downloads the trained model from GitHub releases: | |
| - URL: `https://github.com/santhoshv6/era_v4_s8_assignment/releases/download/v1.0/model_best.pth` | |
| - Size: ~85.7 MB | |
| - Format: PyTorch checkpoint with state_dict | |
| ## π― Usage | |
| 1. Upload any image (will be resized to 32x32) | |
| 2. Get top 5 predictions with confidence scores | |
| 3. Model works best with CIFAR-100 style images | |
| ## π§ Technical Details | |
| - **Framework:** PyTorch + Gradio | |
| - **Preprocessing:** Resize to 32x32, normalize with CIFAR-100 stats | |
| - **Architecture:** ResNet-18 with BasicBlocks | |
| - **Classes:** All 100 CIFAR-100 fine-grained categories |