https://github.com/kimiaak/choke-coverage
A software to measure energy waste in a reactor by analyzing the percentage of white pixels within a specific circular region of an image.
https://github.com/kimiaak/choke-coverage
computer-vision monitoring opencv pillow python
Last synced: about 2 months ago
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A software to measure energy waste in a reactor by analyzing the percentage of white pixels within a specific circular region of an image.
- Host: GitHub
- URL: https://github.com/kimiaak/choke-coverage
- Owner: KimiaaK
- License: gpl-3.0
- Created: 2024-10-28T04:32:26.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-09T06:54:59.000Z (over 1 year ago)
- Last Synced: 2025-04-04T07:43:59.867Z (about 1 year ago)
- Topics: computer-vision, monitoring, opencv, pillow, python
- Language: PowerShell
- Homepage:
- Size: 5.71 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Choke Coverage Analysis
## Overview
This 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.
The project is split into three main stages:
1. **Image Processing Setup**: Load and preprocess images to grayscale format and define the circular region of interest.
2. **Image Analysis**: Analyze individual images by applying a threshold to detect white pixels and calculate the percentage of white pixels in the defined region.
3. **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.
## Project Structure
- `image_processing_setup.py`: Handles loading and preprocessing of images, including converting them to grayscale and defining the circular region of interest.
- `image_analysis.py`: Analyzes individual images by identifying white pixels within a circular region and calculating the percentage.
- `batch_processing_analysis.py`: Processes multiple images, calculates percentages, and visualizes the results.
## How to Use
1. Clone the repository:
```bash
git clone
cd choke_coverage_analysis
```
2. Install the required Python libraries using `pip`:
```bash
pip install -r requirements.txt
```
Alternatively, you can install them manually:
```bash
pip install numpy pillow matplotlib
```
3. Place your images in the root directory and update the `image_paths` list in `batch_processing_analysis.py` with the correct file paths.
4. Run the batch processing script to analyze all images:
```bash
python batch_processing_analysis.py
```
## Example Output
After running the batch analysis, you will see:
- The percentage of white pixels for each image.
- The average percentage of white pixels across all images.
- A linear plot visualizing the rate of white pixels across the images.
- A visual representation of the measurement
## Analysis Results
Here are some example outputs of the image processing:
### Original Image, Thresholded Image, and Visual Representation
## Requirements
- Python 3.x
- Libraries: `numpy`, `pillow`, `matplotlib`
## Contact
Author: Kimia K
Feel free to reach out if you have any questions or suggestions for improvements!