图像分割学习

本仓库旨在为初学者提供一个友好的图像语义分割入门环境。它包含了完整的处理流程,帮助您开始探索这一重要的计算机视觉领域。

概述

图像语义分割是将数字图像划分为多个分段或区域的过程,每个分段或区域对应图像中的特定物体或区域。这项任务在自动驾驶、医疗影像分析和场景理解等广泛应用中都扮演着关键角色。

在这个仓库中,您将找到多种流行的语义分割模型的实现,包括广泛使用的 U-Net 架构。代码设计简洁易懂,方便修改,非常适合初学者和资深研究人员。

特性

完整的工作流程: 涵盖从数据集准备到模型训练、评估和部署的整个语义分割workflow。 可定制的配置: 轻松调整超参数、数据集路径等设置,满足您的特定需求。 面向初学者: 代码结构和注释设计都非常友好,适合对该领域新手。 快速上手 要开始使用,请克隆本仓库并按照 README 中的说明进行操作。您将找到详细的设置说明,包括环境配置和数据集准备。

除了常用的torch之外,你可能额外需要安装

pip install -U segmentation-models-pytorch

git clone https://github.com/drowning-in-codes/Image-Segmentation-Playground.git
cd Image-Segmentation-Playground

贡献 欢迎对本项目进行贡献!如果您发现任何问题,有改进建议或想添加新功能,请随时提交 pull request 或创建 issue。

许可证 本项目采用 MIT 许可证

Image Segmentation Playground

This repository serves as a beginner-friendly introduction to the field of image semantic segmentation. It provides a comprehensive workflow, including multiple state-of-the-art models, to help you get started with this fascinating and valuable computer vision task.

Overview

Image semantic segmentation is the process of partitioning a digital image into multiple segments or regions, each of which corresponds to a specific object or area within the image. This task is crucial in a wide range of applications, such as autonomous driving, medical image analysis, and scene understanding.

In this repository, you will find implementations of several popular semantic segmentation models, including the widely-used U-Net architecture. The code is designed to be easy to understand and modify, making it an excellent starting point for both beginners and experienced researchers.

Features

• Comprehensive Workflow: The repository covers the entire semantic segmentation workflow, from dataset preparation to model training, evaluation, and deployment.
• Customizable Configurations: Easily adjust hyperparameters, dataset paths, and other settings to fit your specific needs.
• Beginner-Friendly: The code is structured and commented to be easily understandable for those new to the field of semantic segmentation.

Except for torch and other basic tools,you may also neet to:

pip install -U segmentation-models-pytorch

Getting Started

To get started, simply clone the repository and follow the instructions in the README. You'll find detailed setup instructions, including environment configuration and dataset preparation.

git clone https://github.com/drowning-in-codes/Image-Segmentation-Playground.git
cd Image-Segmentation-Playground