Update README.md

README.md

@@ -1,149 +1,159 @@
-# Structura AI: Depth & Structural Masking Web Application
-
-Structura AI is a web-based image analysis tool that generates a structural mask by combining monocular depth estimation and texture-based feature detection.
-The system integrates MiDaS (DPT-Hybrid) for depth prediction with OpenCV-based edge, corner, and texture fusion to produce a detailed, high-frequency structural representation of any input image.
-
-This mask is useful for segmentation workflows, diffusion model conditioning, preprocessing for generative AI, architectural analysis, and general computer vision pipelines.
-
----
-
-## Features
-
-* MiDaS Depth Estimation: High-quality depth prediction using the DPT-Hybrid model.
-* Combined Structural Masking: Fusion of depth gradients, edges (Canny), Laplacian detail, and Harris corner responses.
-* FastAPI Backend: Clean API endpoint (`POST /mask/`) returning PNG masks with inference time metadata.
-* Web UI: A simple and modern interface built with HTML, CSS, and JavaScript allowing image upload, preview, overlay visualization, and mask download.
-* Docker Support: Fully dockerized and ready for deployment on services such as Hugging Face Spaces.
-
----
-
-## Demo
-
-This section is reserved for demo images and demo videos.
-Add examples such as:
-
-* Original input image
-* Generated structural mask
-* Overlay visualization
-* A short screen recording demonstrating the UI
-
----
-
-## Technology Stack
-
-Backend: FastAPI, Uvicorn
-AI / Computer Vision: PyTorch, MiDaS, OpenCV (headless), NumPy
-Frontend: HTML, CSS, JavaScript
-Deployment: Docker, Hugging Face Spaces
-
----
-
-## Repository Structure
-
-```
-structura-ai/
-├── app.py
-├── depth_texture_mask.py
-├── requirements.txt
-├── Dockerfile
-├── templates/
-│   └── index.html
-└── static/
-    ├── styles.css
-    ├── app.js
-    └── logo.svg
-```
-
----
-
-## Local Installation and Usage
-
-### 1. Clone the Repository
-
-```
-git clone https://github.com/PritamTheCoder/midas-depth-texture-mask-api.git
-cd midas-depth-texture-mask-api
-```
-
-### 2. Create and Activate a Virtual Environment
-
-```
-python -m venv venv
-
-# Windows
-venv\Scripts\activate
-
-# macOS / Linux
-source venv/bin/activate
-```
-
-### 3. Install Dependencies
-
-```
-pip install -r requirements.txt
-```
-
-### 4. Start the Application
-
-```
-uvicorn app:app --reload --host 0.0.0.0 --port 8000
-```
-
-### 5. Access the Web UI
-
-Open the browser and navigate to:
-[http://127.0.0.1:8000/](http://127.0.0.1:8000/)
-
-The MiDaS model weights will automatically download on the first startup.
-
----
-
-## Deployment on Hugging Face Spaces (Docker)
-
-The project includes a Dockerfile configured for seamless deployment on Hugging Face Spaces.
-
-### Required File Structure
-
-Ensure the following files are present at the repository root:
-
-```
-Dockerfile
-app.py
-depth_texture_mask.py
-requirements.txt
-templates/
-static/
-```
-
-### Deployment Steps
-
-1. Create a new Hugging Face Space.
-2. Select "Docker" as the runtime.
-3. Upload or commit all repository files.
-4. Hugging Face will automatically:
-
-   * Build the Docker image
-   * Install dependencies
-   * Expose the correct port
-   * Start the FastAPI server
-
-The application will then be available as a hosted interactive web demo.
-
----
-
-## License
-
-This project is licensed under the MIT License.
-See the LICENSE file for details.
-
----
-
-## Acknowledgements
-
-MiDaS by Intel-ISL
-FastAPI for backend framework
-OpenCV for feature detection and image processing
-PyTorch for deep learning inference support
-Hugging Face for deployment infrastructure
-
----
+---
+license: mit
+title: 'Structura AI: Depth & Structural Masking'
+sdk: docker
+emoji: 🚀
+colorFrom: indigo
+colorTo: blue
+pinned: true
+app_port: 8000
+---
+
+# Structura AI: Depth & Structural Masking Web Application
+
+Structura AI is a web-based image analysis tool that generates a structural mask by combining monocular depth estimation and texture-based feature detection.
+The system integrates MiDaS (DPT-Hybrid) for depth prediction with OpenCV-based edge, corner, and texture fusion to produce a detailed, high-frequency structural representation of any input image.
+
+This mask is useful for segmentation workflows, diffusion model conditioning, preprocessing for generative AI, architectural analysis, and general computer vision pipelines.
+
+---
+
+## Features
+
+* MiDaS Depth Estimation: High-quality depth prediction using the DPT-Hybrid model.
+* Combined Structural Masking: Fusion of depth gradients, edges (Canny), Laplacian detail, and Harris corner responses.
+* FastAPI Backend: Clean API endpoint (`POST /mask/`) returning PNG masks with inference time metadata.
+* Web UI: A simple and modern interface built with HTML, CSS, and JavaScript allowing image upload, preview, overlay visualization, and mask download.
+* Docker Support: Fully dockerized and ready for deployment on services such as Hugging Face Spaces.
+
+---
+
+## Demo
+
+This section is reserved for demo images and demo videos.
+Add examples such as:
+
+* Original input image
+* Generated structural mask
+* Overlay visualization
+* A short screen recording demonstrating the UI
+
+---
+
+## Technology Stack
+
+Backend: FastAPI, Uvicorn
+AI / Computer Vision: PyTorch, MiDaS, OpenCV (headless), NumPy
+Frontend: HTML, CSS, JavaScript
+Deployment: Docker, Hugging Face Spaces
+
+---
+
+## Repository Structure
+
+```
+structura-ai/
+├── app.py
+├── depth_texture_mask.py
+├── requirements.txt
+├── Dockerfile
+├── templates/
+│   └── index.html
+└── static/
+    ├── styles.css
+    └── app.js
+```
+
+---
+
+## Local Installation and Usage
+
+### 1. Clone the Repository
+
+```
+git clone https://github.com/PritamTheCoder/midas-depth-texture-mask-api.git
+cd midas-depth-texture-mask-api
+```
+
+### 2. Create and Activate a Virtual Environment
+
+```
+python -m venv venv
+
+# Windows
+venv\Scripts\activate
+
+# macOS / Linux
+source venv/bin/activate
+```
+
+### 3. Install Dependencies
+
+```
+pip install -r requirements.txt
+```
+
+### 4. Start the Application
+
+```
+uvicorn app:app --reload --host 0.0.0.0 --port 8000
+```
+
+### 5. Access the Web UI
+
+Open the browser and navigate to:
+[http://127.0.0.1:8000/](http://127.0.0.1:8000/)
+
+The MiDaS model weights will automatically download on the first startup.
+
+---
+
+## Deployment on Hugging Face Spaces (Docker)
+
+The project includes a Dockerfile configured for seamless deployment on Hugging Face Spaces.
+
+### Required File Structure
+
+Ensure the following files are present at the repository root:
+
+```
+Dockerfile
+app.py
+depth_texture_mask.py
+requirements.txt
+templates/
+static/
+```
+
+### Deployment Steps
+
+1. Create a new Hugging Face Space.
+2. Select "Docker" as the runtime.
+3. Upload or commit all repository files.
+4. Hugging Face will automatically:
+
+   * Build the Docker image
+   * Install dependencies
+   * Expose the correct port
+   * Start the FastAPI server
+
+The application will then be available as a hosted interactive web demo.
+
+---
+
+## License
+
+This project is licensed under the MIT License.
+See the LICENSE file for details.
+
+---
+
+## Acknowledgements
+
+MiDaS by Intel-ISL
+FastAPI for backend framework
+OpenCV for feature detection and image processing
+PyTorch for deep learning inference support
+Hugging Face for deployment infrastructure
+
+---