Nailfold-enhance 1.0.0

Nailfold images and videos enhance

Nailfold Enhance SDK

中文版 | English Version

项目简介

Nailfold Enhance SDK 是一款专注于甲襞微循环医学影像增强的工具包，通过优化的图像处理算法提升甲襞血管清晰度，辅助医学诊断与研究。

核心功能

• 单张/批量处理甲襞图像，支持主流格式（JPG/PNG/BMP等）
• 逐帧增强甲襞视频，保留动态微循环特征
• 递归处理文件夹内影像，保持原始目录结构
• 自定义增强参数，适配不同质量的原始影像
• 实时进度追踪，支持回调函数监控处理状态

安装方法

通过 pip 安装 SDK 及依赖：

pip install opencv-python numpy
pip install nailfold-image-enhance-1.0.0-py3-none-any.whl
pip install nailfold-image-enhance-1.0.0.tar.gz

快速开始

1. 增强单张甲襞图像

from nailfold_image_enhance import enhance_image

# 使用默认配置增强图像
enhance_image(
    input_path="path/to/nailfold_image.jpg",
    output_path="path/to/enhanced_image.jpg"
)

2. 增强甲襞视频（带进度追踪）

from nailfold_image_enhance import enhance_video

def progress_callback(percent):
    print(f"处理进度：{percent}%", end="\r")

# 增强视频并显示实时进度
enhance_video(
    input_path="path/to/nailfold_video.mp4",
    output_path="path/to/enhanced_video.mp4",
    progress_callback=progress_callback
)

3. 批量处理图像文件夹

from nailfold_image_enhance import enhance_images_in_folder

# 批量处理整个文件夹
enhance_images_in_folder(
    input_path="path/to/input_images",
    output_path="path/to/output_images",
    suffix="_enhanced"
)

关键特性

• 算法针对甲襞血管特征优化，避免过度增强导致的伪影
• 支持医学影像格式及主流视频格式（MP4/AVI 等）
• 自动创建输出目录，保持原始文件结构
• 可通过配置类调整增强强度，适配低光照、高噪声场景

文档资源

• 使用指南：详细示例与操作步骤
• API 参考：完整接口与参数说明

系统要求

• Python 3.8+
• 依赖库：OpenCV (4.5+)、NumPy (1.21+)
• 支持 Windows/macOS/Linux 系统

Nailfold Enhance SDK

中文版 | English Version

Project Introduction

Nailfold Enhance SDK is a toolkit focused on enhancing nailfold microcirculation medical images. It improves clarity and detail recognition of nailfold blood vessels through optimized image processing algorithms, assisting in medical diagnosis and research.

Core Features

• Enhance single/batch nailfold images, supporting mainstream formats (JPG/PNG/BMP, etc.)
• Enhance nailfold videos frame by frame, preserving dynamic microcirculation features
• Recursively process images in folders, maintaining original directory structure
• Customize enhancement parameters to adapt to raw images of different quality
• Real-time progress tracking, supporting callback functions to monitor processing status

Quick Installation

Install the SDK and dependencies via pip:

pip install opencv-python numpy
pip install nailfold-image-enhance-1.0.0-py3-none-any.whl
pip install nailfold-image-enhance-1.0.0.tar.gz

Quick Start

1. Enhance a Single Nailfold Image

from nailfold_image_enhance import enhance_image

# Enhance image with default configuration
enhance_image(
    input_path="path/to/nailfold_image.jpg",
    output_path="path/to/enhanced_image.jpg"
)

2. Enhance Nailfold Video (with Progress Tracking)

from nailfold_image_enhance import enhance_video

def progress_callback(percent):
    print(f"Processing progress: {percent}%", end="\r")

# Enhance video and display real-time progress
enhance_video(
    input_path="path/to/nailfold_video.mp4",
    output_path="path/to/enhanced_video.mp4",
    progress_callback=progress_callback
)

3. Batch Process Image Folder

from nailfold_image_enhance import enhance_images_in_folder

# Batch process the entire folder
enhance_images_in_folder(
    input_path="path/to/input_images",
    output_path="path/to/output_images",
    suffix="_enhanced"
)

Key Features

• Algorithms optimized for nailfold vessel features to avoid artifacts from over-enhancement
• Supports medical imaging formats and mainstream video formats (MP4/AVI, etc.)
• Automatically creates output directories, maintaining original file structure
• Adjustable enhancement intensity via configuration class, adapting to low-light, high-noise scenarios

Documentation Resources

• User Guide: Detailed examples and operation steps
• API Reference: Complete interface and parameter descriptions

System Requirements

• Python 3.7+
• Dependencies: OpenCV (4.12+), NumPy (1.21+)
• Supports Windows/macOS/Linux systems