{"id":51718085,"url":"https://github.com/abhirupr123/crack_detective","last_synced_at":"2026-07-17T06:04:15.909Z","repository":{"id":196635194,"uuid":"667853554","full_name":"abhirupr123/crack_detective","owner":"abhirupr123","description":"Object and Image detection model developed to identify cracks and image dimensions, for the HackFest 2023 by Mistral Solutions","archived":false,"fork":false,"pushed_at":"2023-09-26T17:50:58.000Z","size":9945,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2024-04-18T06:26:27.434Z","etag":null,"topics":["computer-vision","flask","image-processing","ml-models","object-detection","object-measurement","python"],"latest_commit_sha":null,"homepage":"","language":"JavaScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/abhirupr123.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2023-07-18T12:57:39.000Z","updated_at":"2024-04-18T06:26:27.435Z","dependencies_parsed_at":null,"dependency_job_id":"d0effd7a-60f5-4dca-97b5-c0551191d770","html_url":"https://github.com/abhirupr123/crack_detective","commit_stats":null,"previous_names":["abhirupr123/crack_detective"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/abhirupr123/crack_detective","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhirupr123%2Fcrack_detective","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhirupr123%2Fcrack_detective/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhirupr123%2Fcrack_detective/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhirupr123%2Fcrack_detective/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/abhirupr123","download_url":"https://codeload.github.com/abhirupr123/crack_detective/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhirupr123%2Fcrack_detective/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":35569655,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-07-17T02:00:06.162Z","response_time":116,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["computer-vision","flask","image-processing","ml-models","object-detection","object-measurement","python"],"created_at":"2026-07-17T06:04:15.206Z","updated_at":"2026-07-17T06:04:15.904Z","avatar_url":"https://github.com/abhirupr123.png","language":"JavaScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Crack Detective\n\nA computer-vision based web application that automates vehicle damage detection and component dimension measurement.\n\n## Overview\n\n**Crack Detective** is an advanced inspection tool designed to modernize automotive and manufacturing quality checks. By leveraging Machine Learning and Computer Vision, the application provides two core capabilities:\n1.  **Crack \u0026 Dent Detection:** Identifies surface damages like cracks and dents on vehicle bodies or manufacturing parts.\n2.  **Dimension Measurement:** Measures the geometric dimensions of objects (squares, triangles, polygons, etc.) in real-time or from static images.\n\nThe project features a sleek, dark-themed React frontend and a Python (Flask) backend powered by OpenCV and ML models.\n\n## Features\n\n-   **User Authentication:** Secure Sign In and Sign Up using Firebase Auth.\n-   **Dashboard:**\n    -   Switch between \"Crack Detection\" and \"Dimension Measurement\" modes.\n    -   Integrated Webcam support for live capture.\n    -   Drag-and-drop image upload functionality.\n-   **Live Analysis:** Real-time video feed processing for dimension measurement.\n-   **Results Visualization:** View processed images with bounding boxes/annotations highlighting detected damages or measured dimensions.\n-   **Modern UI:** Responsive, dark-mode interface built with Chakra UI and Framer Motion.\n\n## Tech Stack\n\n### Frontend\n-   **React.js:** Core UI library.\n-   **Chakra UI:** Component library for accessible and responsive styling.\n-   **Framer Motion:** For smooth animations and transitions.\n-   **Firebase:** Authentication and backend services.\n-   **Axios:** HTTP client for API requests.\n\n### Backend\n-   **Python (Flask):** REST API server.\n-   **OpenCV:** Computer vision library for image processing.\n-   **NumPy:** Numerical processing.\n-   **ML Models:** Custom trained models for damage detection.\n\n## Installation \u0026 Setup\n\n### Prerequisites\n-   Node.js \u0026 npm\n-   Python 3.x\n-   Pip\n\n### 1. Clone the Repository\n```bash\ngit clone \u003crepository-url\u003e\ncd crack-detective\n```\n\n### 2. Frontend Setup\nNavigate to the frontend directory and install dependencies:\n```bash\ncd frontend\nnpm install\n```\n\nStart the React development server:\n```bash\nnpm start\n```\nThe application will run on `http://localhost:3000`.\n\n### 3. Backend Setup\nNavigate to the root directory where `app.py` is located. It is recommended to create a virtual environment:\n\n```bash\n# Create virtual environment (optional but recommended)\npython -m venv venv\nsource venv/bin/activate  # On Windows: venv\\Scripts\\activate\n\n# Install Python dependencies\npip install flask opencv-python numpy firebase-admin\n```\n\nStart the Flask server:\n```bash\npython app.py\n```\nThe server will typically run on `http://127.0.0.1:5000`.\n\n## Usage\n\n1.  **Sign Up/Login:** Create an account to access the dashboard.\n2.  **Select Mode:** Choose between \"Crack Detection\" or \"Dimension Measurement\" from the tabs.\n3.  **Input Data:**\n    *   **Upload:** Select an image file from your device.\n    *   **Camera:** Use the \"Open Camera\" button to capture a photo.\n    *   **Live Feed:** Click \"Start Live Feed\" for real-time measurement (opens a separate window).\n4.  **View Results:** After processing, click \"Show Results\" to see the analyzed image with detected defects or measurements.\n\n## Project Structure\n\n```\n├── app.py                  # Main Flask backend application\n├── crack.py                # Logic for crack/dent detection\n├── model.py                # ML model definitions/loading\n├── Measure.py              # Logic for dimension measurement\n├── main_photo.py           # Additional photo processing logic\n├── frontend/               # React Frontend\n│   ├── public/\n│   ├── src/\n│   │   ├── components/     # React components (Home, Scan, Results, etc.)\n│   │   ├── Firebase.js     # Firebase configuration\n│   │   ├── App.js          # Main App component\n│   │   └── index.js        # Entry point\n│   └── package.json\n└── images/                 # Sample images or processing output\n```\n\n## Contributing\n\nPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhirupr123%2Fcrack_detective","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabhirupr123%2Fcrack_detective","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhirupr123%2Fcrack_detective/lists"}