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--- |
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title: ResNet50 Image Classifier |
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emoji: 🖼️ |
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colorFrom: blue |
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colorTo: red |
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sdk: streamlit |
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sdk_version: 1.22.0 |
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app_file: app.py |
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pinned: false |
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--- |
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# ResNet50 Image Classifier |
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This Streamlit application uses a ResNet50 model trained on the ImageNet-1K dataset to classify images into 1000 different categories. |
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## How to Use |
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1. Click the "Choose an image..." button or drag and drop an image |
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2. The model will automatically process your image |
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3. View the top 5 predictions with their confidence scores |
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## Model Details |
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- **Architecture**: ResNet50 |
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- **Dataset**: ImageNet-1K |
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- **Input Size**: 224x224 pixels |
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- **Number of Classes**: 1000 |
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## Example Predictions |
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The model can identify various objects, animals, and scenes, including: |
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- Common animals (dogs, cats, birds) |
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- Everyday objects |
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- Vehicles |
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- Natural scenes |
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- And many more! |
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## Technical Details |
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- Built with PyTorch and Streamlit |
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- Uses standard ImageNet preprocessing |
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- Runs inference on CPU |
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- Displays confidence scores as progress bars |
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## Note |
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For best results, use clear, well-lit images with a single main subject. |
