silversurfer343/ComputerVisionProject

1---2title: Crack Detection3emoji: 🧱4colorFrom: blue5colorTo: red6sdk: streamlit7sdk_version: 1.32.08app_file: app.py9pinned: false10---11 12# Wall Crack Detection Application13 14This application uses both traditional computer vision and deep learning approaches to detect and analyze cracks in wall images. It provides a comprehensive analysis using multiple methods including Harris Corner Detection, Hough Transform, Region-based Segmentation, SLIC, and GMM.15 16## Features17 18- Traditional CV Approach:19  - Harris Corner Detection20  - Hough Transform21  - Region-based Segmentation22  - SLIC Segmentation23  - GMM-based Segmentation24 25- Deep Learning Approach:26  - DeepLabV3 Model27  - Multiple refinement methods28  - Ensemble predictions29 30## Usage31 321. Upload a wall image (JPG/PNG/JPEG)332. Choose between Traditional CV or Deep Learning approach343. View detailed analysis and recommendations35 36## Model37 38The application uses a pre-trained DeepLabV3 model for crack detection.39 40## Requirements41 42All dependencies are listed in `requirements.txt`.