{"id":18000198,"url":"https://github.com/kimiaak/choke-coverage","last_synced_at":"2026-05-04T01:32:38.437Z","repository":{"id":259828412,"uuid":"879528072","full_name":"KimiaaK/choke-coverage","owner":"KimiaaK","description":"A software to measure energy waste in a reactor by analyzing the percentage of white pixels within a specific circular region of an image. ","archived":false,"fork":false,"pushed_at":"2024-11-09T06:54:59.000Z","size":5991,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-04T07:43:59.867Z","etag":null,"topics":["computer-vision","monitoring","opencv","pillow","python"],"latest_commit_sha":null,"homepage":"","language":"PowerShell","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/KimiaaK.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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-10-28T04:32:26.000Z","updated_at":"2024-11-09T06:55:03.000Z","dependencies_parsed_at":"2024-10-28T07:52:04.473Z","dependency_job_id":"833aecfc-9cc8-45d0-8dbf-66561788160c","html_url":"https://github.com/KimiaaK/choke-coverage","commit_stats":null,"previous_names":["kimiaak/choke-coverage"],"tags_count":0,"template":false,"template_full_name":"datalumina/datalumina-project-template","purl":"pkg:github/KimiaaK/choke-coverage","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KimiaaK%2Fchoke-coverage","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KimiaaK%2Fchoke-coverage/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KimiaaK%2Fchoke-coverage/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KimiaaK%2Fchoke-coverage/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/KimiaaK","download_url":"https://codeload.github.com/KimiaaK/choke-coverage/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/KimiaaK%2Fchoke-coverage/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265332781,"owners_count":23748677,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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","monitoring","opencv","pillow","python"],"created_at":"2024-10-29T23:10:27.836Z","updated_at":"2026-05-04T01:32:38.399Z","avatar_url":"https://github.com/KimiaaK.png","language":"PowerShell","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Choke Coverage Analysis\n\n## Overview\n\nThis project is designed to analyze the percentage of white pixels within a specific circular region of an image. It is useful for image analysis tasks that require detecting and quantifying white areas within a defined part of an image, such as evaluating coverage in various types of samples or analyzing light reflection.\n\nThe project is split into three main stages:\n\n1. **Image Processing Setup**: Load and preprocess images to grayscale format and define the circular region of interest.\n2. **Image Analysis**: Analyze individual images by applying a threshold to detect white pixels and calculate the percentage of white pixels in the defined region.\n3. **Batch Processing and Analysis**: Process multiple images, calculate individual percentages of white pixels, and generate an average percentage as well as a visualization of results.\n\n## Project Structure\n\n- `image_processing_setup.py`: Handles loading and preprocessing of images, including converting them to grayscale and defining the circular region of interest.\n- `image_analysis.py`: Analyzes individual images by identifying white pixels within a circular region and calculating the percentage.\n- `batch_processing_analysis.py`: Processes multiple images, calculates percentages, and visualizes the results.\n\n## How to Use\n\n1. Clone the repository:\n   ```bash\n   git clone \u003crepository_url\u003e\n   cd choke_coverage_analysis\n   ```\n\n2. Install the required Python libraries using `pip`:\n   ```bash\n   pip install -r requirements.txt\n   ```\n   Alternatively, you can install them manually:\n   ```bash\n   pip install numpy pillow matplotlib\n   ```\n\n3. Place your images in the root directory and update the `image_paths` list in `batch_processing_analysis.py` with the correct file paths.\n\n4. Run the batch processing script to analyze all images:\n   ```bash\n   python batch_processing_analysis.py\n   ```\n\n## Example Output\n\nAfter running the batch analysis, you will see:\n\n- The percentage of white pixels for each image.\n- The average percentage of white pixels across all images.\n- A linear plot visualizing the rate of white pixels across the images.\n- A visual representation of the measurement\n\n  \n## Analysis Results\n\nHere are some example outputs of the image processing:\n\n### Original Image, Thresholded Image, and Visual Representation\n![Image Results 1](results/img1.png)\n![Image Results 2](results/img2.png)\n\n\n## Requirements\n\n- Python 3.x\n- Libraries: `numpy`, `pillow`, `matplotlib`\n\n## Contact\n\nAuthor: Kimia K\n\nFeel free to reach out if you have any questions or suggestions for improvements!\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkimiaak%2Fchoke-coverage","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkimiaak%2Fchoke-coverage","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkimiaak%2Fchoke-coverage/lists"}