Update README.md

README.md

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 pinned: false
 short_description: Code is designed to identify dog breeds from uploaded image
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+This repository contains a Gradio application that uses a vanilla (ImageNet-pretrained) VGG16 model to classify images. The application: (1). Allows users to upload or drag-and-drop an image. (2). Displays the top 3 ImageNet classes predicted by VGG16. (3). Lets users adjust a confidence threshold slider to filter out low-confidence predictions.
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+Features: (1). Image Upload: Users can drag & drop or click to upload an image. (2). Confidence Threshold: A slider that filters predictions below a chosen probability. (3). Custom UI: (Optional) Custom background or gradient for a more website-like appearance. (4). Fast Inference: Powered by PyTorch and TorchVision’s pretrained VGG16 model.
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+Contributing: (1). Fork the repo. (2). Create your feature branch: git checkout -b feature/awesome-feature. (3). Commit your changes: git commit -m 'Add awesome feature'. (4). Push to the branch: git push origin feature/awesome-feature. (5). Create a new Pull Request on GitHub or share your branch to merge changes.
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+License: This project is open-sourced under the MIT License. See the LICENSE file for details (include a license file if you wish).
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference