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| title: BioClip Image Classification | |
| emoji: 🌿 | |
| colorFrom: green | |
| colorTo: blue | |
| sdk: gradio | |
| sdk_version: 3.27.0 | |
| app_file: app.py | |
| pinned: false | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
| # BioClip Image Classification | |
| This Hugging Face Space demonstrates image classification using the BioClip model. Upload an image to get a prediction of its class, along with the top 3 most similar classes and file paths. | |
| ## How to Use | |
| 1. Open the Gradio interface in this Space. | |
| 2. Upload an image using the provided input area. | |
| 3. The model will process the image and return: | |
| - The predicted class | |
| - The top 3 most similar classes | |
| - The top 3 most similar file paths from the dataset | |
| ## About the Model | |
| This Space uses the BioClip model, which is designed for biological image classification. The model is loaded from the Hugging Face model hub (imageomics/bioclip). | |
| ## Technical Details | |
| - The Space uses Gradio for the user interface. | |
| - It employs FAISS indexes for efficient similarity search. | |
| - The classification is performed using a k-nearest neighbors approach with majority voting. | |
| ## Note | |
| The FAISS indexes are downloaded at runtime. Make sure your Space has internet access to download these files when the app starts. |