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-# 3D Person Segmentation and Anaglyph Generation
-
-title: Object Segmentation
-emoji: 👁
-colorFrom: gray
-colorTo: pink
-sdk: gradio
-sdk_version: 5.22.0
-app_file: src/app.py
-pinned: false
-
-
-## Lab Report
-
-### Introduction
-This project implements a sophisticated 3D image processing system that combines person segmentation with stereoscopic and anaglyph image generation. The main objectives were to:
-1. Accurately segment people from images using advanced AI models
-2. Generate stereoscopic 3D effects from 2D images
-3. Create red-cyan anaglyph images for 3D viewing
-4. Provide an interactive web interface for real-time processing
-
-### Methodology
-
-#### Tools and Technologies Used
-- **SegFormer (nvidia/segformer-b0)**: State-of-the-art transformer-based model for semantic segmentation
-- **PyTorch**: Deep learning framework for running the SegFormer model
-- **OpenCV**: Image processing operations and mask refinement
-- **Gradio**: Web interface development
-- **NumPy**: Efficient array operations for image manipulation
-- **PIL (Python Imaging Library)**: Image loading and basic transformations
-
-#### Implementation Steps
-
-1. **Person Segmentation**
-   - Utilized SegFormer model fine-tuned on ADE20K dataset
-   - Applied post-processing with erosion and Gaussian blur for mask refinement
-   - Implemented mask scaling and centering for various input sizes
-
-2. **Stereoscopic Processing**
-   - Created depth simulation through horizontal pixel shifting
-   - Implemented parallel view stereo pair generation
-   - Added configurable interaxial distance for 3D effect adjustment
-
-3. **Anaglyph Generation**
-   - Combined left and right eye views into red-cyan anaglyph
-   - Implemented color channel separation and recombination
-   - Added background image support with proper masking
-
-4. **User Interface**
-   - Developed interactive web interface using Gradio
-   - Added real-time parameter adjustment capabilities
-   - Implemented support for custom background images
-
-### Results
-
-The system produces three main outputs:
-1. Segmentation mask showing the isolated person
-2. Side-by-side stereo pair for parallel viewing
-3. Red-cyan anaglyph image for 3D glasses viewing
-
-Key Features:
-- Adjustable person size (10-200%)
-- Configurable interaxial distance (0-10 pixels)
-- Optional custom background support
-- Real-time processing and preview
-
-### Discussion
-
-#### Technical Challenges
-1. **Mask Alignment**: Ensuring proper alignment between segmentation masks and background images required careful consideration of image dimensions and aspect ratios.
-2. **Stereo Effect Quality**: Balancing the interaxial distance for comfortable viewing while maintaining the 3D effect.
-3. **Performance Optimization**: Efficient processing of large images while maintaining real-time interaction.
-
-#### Learning Outcomes
-- Deep understanding of stereoscopic image generation
-- Experience with state-of-the-art segmentation models
-- Practical knowledge of image processing techniques
-- Web interface development for ML applications
-
-### Conclusion
-
-This project successfully demonstrates the integration of modern AI-powered segmentation with classical stereoscopic image processing techniques. The system provides an accessible way to create 3D effects from regular 2D images.
-
-#### Future Work
-- Implementation of depth-aware 3D effect generation
-- Support for video processing
-- Additional 3D viewing formats (side-by-side, over-under)
-- Enhanced background replacement options
-- Mobile device optimization
-
-## Setup
-
-```bash
-pip install -r requirements.txt
-```
-
-## Usage
-
-```bash
-cd src
-python app.py
-```
-
-## Parameters
-
-- **Person Image**: Upload an image containing a person
-- **Background Image**: (Optional) Custom background image
-- **Interaxial Distance**: Adjust the 3D effect strength (0-10)
-- **Person Size**: Adjust the size of the person in the output (10-200%)
-
-## Output Types
-
-1. **Segmentation Mask**: Shows the isolated person
-2. **Stereo Pair**: Side-by-side stereo image for parallel viewing
-3. **Anaglyph**: Red-cyan 3D image viewable with anaglyph glasses
-