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--- |
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title: "AML 16" |
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version: "1.0.0" |
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emoji: "🤗" |
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colorFrom: indigo |
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colorTo: pink |
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sdk: gradio |
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sdk_version: "5.29.0" |
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app_file: app.py |
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pinned: false |
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--- |
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# AML 16 |
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This is a demo application for the best-performing model (Swin-Large) created for the AML 16 project. |
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The app uses Gradio to provide an interactive interface where users can upload an image, view the top-1 predicted scene category, see a reference image from the predicted class, and explore the top-5 prediction probabilities in a bar chart. |
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The model was trained for scene classification and deployed using Hugging Face Spaces. |
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- predict.py |
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This file handles loading the trained Swin-Large model and making predictions. |
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It loads the model weights from Hugging Face Hub, applies the correct image preprocessing, and outputs: |
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The uploaded image, |
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A reference image from the predicted class, |
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The Top-5 prediction probabilities. |
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The model was customized with an updated classifier head, and class labels are loaded from a labels.json file. A random sample image from the predicted class folder is also shown for better visualization. |
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- app.py |
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This file builds the Gradio interface. |
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It lets users upload an image, runs the prediction using predict.py, and displays: |
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The uploaded image, |
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An image for the top-1 predicted class, |
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The predicted class label, |
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A bar chart showing the Top-5 prediction probabilities. |
