--- title: depth-pro sdk: gradio emoji: 🚀 colorFrom: yellow colorTo: yellow pinned: false app_file: app.py short_description: web ui for depth-pro ---
Metric depth estimation determines real-world distances to objects in a scene from images. This repo provides a web UI that allows users to estimate metric depth and visualize depth maps by easily uploading images using the Depth Pro model through a simple Gradio UI interface. ## 🛠️ Getting Started ### 📦 Installation 1. **Create and activate a virtual environment:** ```bash conda create -n depth-pro -y python=3.9 conda activate depth-pro ``` 2. **Clone the depth-pro repository:** ```bash git clone https://github.com/apple/ml-depth-pro.git cd ml-depth-pro pip install -e . ``` 3. **Clone the web UI repository:** ```bash git clone https://github.com/spacewalk01/depth-pro-webui.git cd depth-pro-webui pip install -r requirements.txt ``` 4. **Download the model:** Download the model from [depth_pro.pt](https://ml-site.cdn-apple.com/models/depth-pro/depth_pro.pt) and place the file in a newly created `checkpoints` folder. ### 🚀 Running the Application 1. Launch the Gradio interface: ```bash python main.py ``` 2. Open the provided local URL in your web browser to access the interface. ## 🖼️ Usage 1. **Upload an Image:** Use the image uploader to select an image for depth estimation. 2. **Adjust Options:** - **Auto Rotate:** Enable or disable auto-rotation of the image. - **Remove Alpha:** Enable or disable the removal of the alpha channel. 3. **View Results:** - The depth map will be displayed on the interface. - The focal length in pixels will also be shown. ## 📜 License This project is licensed under the Apple License. See the [LICENSE](LICENSE) file for details. ## 🙏 Acknowledgments - [Gradio](https://www.gradio.app/) for providing an easy interface for machine learning models. - [Depth Pro](https://github.com/apple/ml-depth-pro.git) for enabling sharp monocular metric depth estimation in less than a second.