🔬 Intelligent Sperm Image Detection and Classification System V2.0

click 【中文版本】 complete running: code.ipynb

📝 Project Overview

This project is a biomedical image analysis system based on computer vision and image processing techniques, focusing on intelligent detection, classification, and visualization of sperm. Using advanced image processing algorithms, the project can accurately identify, locate, and classify targets from complex biomedical images.

🌟 Key Features

• 🖼️ Multi-step Image Processing Workflow
• 🔍 Precise Target Detection Algorithms
• 📊 Multi-dimensional Target Classification
• 📈 Detailed Visualization of Results
• 🧩 Modular Code Architecture

🚀 Quick Start

Prerequisites

• Python 3.8+
• pip Package Manager

Installation Steps

1. Clone the Project Repository

git clone https://github.com/yourusername/tadpole-detection.git  
cd tadpole-detection

2. Create Virtual Environment (Recommended)

python -m venv venv  
source venv/bin/activate  # Use `venv\Scripts\activate` on Windows  

3. Install Dependencies

pip install -r requirements.txt  

📖 User Guide

Basic Execution python main.py

📌 Precautions

Ensure input images are clear with appropriate contrast Recommended to use JPG or PNG formats Large or extremely complex images may require algorithm parameter adjustments

🔒 License

This project is licensed under the MIT License - see the LICENSE file for details

🙌 Acknowledgments

OpenCV Development Team NumPy Community Matplotlib Project

Disclaimer: This project is for academic research and educational purposes only and should not be directly used for clinical diagnosis.

🌐 Contact Project Homepage: [https://github.com/cyfedu-dlut/Medical-Sperm-Detection-and-Recognition-System] Email: [email protected] Personal Blog/Homepage: [https://cyfedu-dlut.github.io/PersonalWeb/]