Blood Analysis Project

An automated system for analyzing blood sample images from microscopes to detect anomalies using computer vision and machine learning techniques.

Features

• Load and process microscope images of blood samples
• Detect and segment individual blood cells
• Extract features from blood cells
• Detect anomalies using machine learning
• Visualize and save analysis results

Installation

1. Clone the repository:

git clone <repository-url>
cd BloodAnalysis

2. Create and activate a virtual environment (recommended):

python -m venv venv
.\venv\Scripts\Activate

3. Install dependencies:

pip install -r requirements.txt

Project Structure

BloodAnalysis/
├── data/               # Data directory
│   ├── raw/           # Raw microscope images
│   └── processed/     # Processed images and results
├── models/            # Trained models
├── notebooks/         # Jupyter notebooks for analysis
├── src/              # Source code
│   ├── __init__.py
│   ├── image_processing.py    # Image processing functions
│   ├── anomaly_detection.py   # Anomaly detection model
│   └── main.py               # Main script
├── tests/            # Unit tests
└── requirements.txt  # Project dependencies

Usage

Command Line Interface

Analyze a blood sample image:

python src/main.py path/to/image.jpg --output results_folder --model path/to/model

Python API

from src.main import analyze_sample

# Analyze a single image
results = analyze_sample(
    "path/to/image.jpg",
    output_dir="results_folder",
    model_path="path/to/model"
)

Development

Running Tests

pytest tests/

Code Style

This project uses:

• Black for code formatting
• Flake8 for linting

Format code:

black src/ tests/

Run linter:

flake8 src/ tests/

License

This project is licensed under the MIT License.

Contributing

1. Fork the repository
2. Create your feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request