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README.md

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-# DINOv3 Patch Similarity Viewer
-
-![Gradio Test app](assets/GradioAppTest.gif)
-
-> **Note:** This README and repository are for educational purposes. The creation of this repo was inspired by the DINOv3 paper to help visualize and understand the output of the model.
-
-## Purpose
-
-This repository provides interactive tools to visualize and explore patch-wise similarity in images using the DINOv3 vision transformer model. It is designed for researchers, students, and practitioners interested in understanding how self-supervised vision transformers perceive and relate different regions of an image.
-
-## About DINOv3
-
-- **Paper:** [DINOv3: Self-supervised Vision Transformers with Enormous Teacher Models](https://arxiv.org/abs/2508.10104)
-- **Meta Research Page:** [Meta DINOv3 Publication](https://ai.meta.com/dinov3/)
-- **Official GitHub:** [facebookresearch/dinov3](https://github.com/facebookresearch/dinov3)
-
-**Note:**  
-The DINOv3 model weights require access approval.  
-You can request access via the [Meta Research page](https://ai.meta.com/resources/models-and-libraries/dinov3-downloads/) or by selecting the desired model on [Hugging Face model collection](https://huggingface.co/collections/facebook/dinov3-68924841bd6b561778e31009).
-
-## Features
-
-- **Interactive Visualization:** Click on image patches or use arrow keys to explore patch similarity heatmaps.
-- **Single or Two-Image Mode:** If one image is specified, shows self-similarity. If two images are specified, shows both self-similarity and cross-image similarity overlays interactively.
-- **Image Preprocessing:** Loads and pads images without resizing, preserving the original aspect ratio.
-- **Cosine Similarity Calculation:** Computes and visualizes cosine similarity between image patches.
-- **Robust Fallback:** If an image URL fails to load, a default image is used.
-
-## Installation
-
-Install dependencies with:
-
-```bash
-pip install -r requirements.txt
-```
-
-## Model Selection
-
-You can choose from several DINOv3 models available on Hugging Face (click to view each model card):
-
-LVD-1689M Dataset (Web data)
-- ViT
-    - [facebook/dinov3-vit7b16-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-vit7b16-pretrain-lvd1689m)
-    - [facebook/dinov3-vits16-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-vits16-pretrain-lvd1689m)
-    - [facebook/dinov3-vits16plus-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-vits16plus-pretrain-lvd1689m)
-    - [facebook/dinov3-vitb16-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-vitb16-pretrain-lvd1689m)
-    - [facebook/dinov3-vitl16-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-vitl16-pretrain-lvd1689m)
-    - [facebook/dinov3-vith16plus-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-vith16plus-pretrain-lvd1689m)
-
-- ConvNeXt
-    - [facebook/dinov3-convnext-tiny-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-convnext-tiny-pretrain-lvd1689m)
-    - [facebook/dinov3-convnext-small-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-convnext-small-pretrain-lvd1689m)
-    - [facebook/dinov3-convnext-base-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-convnext-base-pretrain-lvd1689m)
-    - [facebook/dinov3-convnext-large-pretrain-lvd1689m](https://huggingface.co/facebook/dinov3-convnext-large-pretrain-lvd1689m)
-
-SAT-493M Dataset (Satellite data)
-- ViT
-    - [facebook/dinov3-vitl16-pretrain-sat493m](https://huggingface.co/facebook/dinov3-vitl16-pretrain-sat493m)
-    - [facebook/dinov3-vit7b16-pretrain-sat493m](https://huggingface.co/facebook/dinov3-vit7b16-pretrain-sat493m)
-
-## Usage
-
-### Gradio app
-
-Run the Gradio app:
-
-```bash
-python app.py
-```
-
-After runnig the app, go to [http://localhost:7860/](http://localhost:7860/) to see the app running.
-
-Then: 
-- Choose Dataset and model name
-- For Single image similarity:
-    - Choose only one file or URL
-- For 2 image similarity:
-    - Choose images from file and/or URL
-- Click button "Initialize / Update "
-- Select the desired patch from the image
-- Watch the results
-
-**Note:** 
-*Overlay alpha* is the intensity of the overlay of patches on top of image
-
-### Python Script
-
-Run the interactive viewer with the default COCO image:
-
-```bash
-python DINOv3CosSimilarity.py
-```
-
-#### Single Image Mode
-
-Specify your own image (local path or URL):
-
-```bash
-python DINOv3CosSimilarity.py --image path/to/your/image.jpg
-python DINOv3CosSimilarity.py --image https://yourdomain.com/image.png
-```
-
-#### Two Image Mode
-
-Specify two images (local paths or URLs):
-
-```bash
-python DINOv3CosSimilarity.py --image1 path/to/image1.jpg --image2 path/to/image2.jpg
-python DINOv3CosSimilarity.py --image1 https://yourdomain.com/image1.png --image2 https://yourdomain.com/image2.png
-```
-
-#### Model Selection
-
-Specify the model with `--model` (default is vits16):
-
-```bash
-python DINOv3CosSimilarity.py --model facebook/dinov3-vitb16-pretrain-lvd1689m
-```
-
-#### Other Options
-
-- `--show_grid` : Draw patch grid
-- `--annotate_indices` : Write patch indices on cells
-- `--overlay_alpha <float>` : Set heatmap alpha (default 0.55)
-- `--patch_size <int>` : Override patch size (default: model's patch size)
-
-#### Controls
-
-- Mouse click to select a patch
-- Arrow keys to move selection
-- '1', '2', or 't' to switch active image (in two-image mode)
-- 'q' to quit
-
-## Demo Single Image
-
-![Interactive Patch Similarity Demo](assets/Test_Interactive_video.gif)
-
-## Demo 2 Images
-
-![Multiple Interactive Patch Similarity Demo](assets/Multiple_Interactive_test_video.gif)
-
-### Jupyter Notebook
-
-1. Open `PatchCosSimilarity.ipynb` in Jupyter Notebook.
-2. Run the cells to load an image and visualize patch similarities.
-3. Set `url1` for single-image mode, or both `url1` and `url2` for two-image mode.
-4. If an image fails to load, a default image will be used automatically.
-5. Set the `model_id` variable to any of the models listed above (see commented lines at the top of the notebook).
-
-**Notebook Controls:**  
-- Mouse click to select a patch  
-- Arrow keys to move selection  
-- '1', '2', or 't' to switch active image (in two-image mode)
-
-## License
-
-This project is licensed under the MIT License. See the `LICENSE` file for details.
-
-## Acknowledgments
-
-This project utilizes the DINOv3 model from Hugging Face's Transformers library, along with PyTorch, Matplotlib, and Pillow
+---
+title: DINOv3 Interactive Patch Cosine Similarity
+emoji: 🏃
+colorFrom: yellow
+colorTo: gray
+sdk: gradio
+sdk_version: 5.43.1
+app_file: app.py
+pinned: false
+license: mit
+short_description: Interactive tool to visualize patch-wise similarity in image
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference