wzmiaomiao/deep-learning-for-image-processing

This is a Chinese-language deep learning (a type of AI) tutorial series focused on image processing, teaching how to build AI systems that can look at images and perform tasks like classifying what's in them, detecting and locating objects, or precisely outlining individual objects. The repository accompanies a video course series on Bilibili (China's major video platform, similar to YouTube), with each tutorial covering a landmark AI architecture, the building blocks and patterns that define modern computer vision. The course covers dozens of well-known models: AlexNet, ResNet, YOLO (the famous object detection family), Vision Transformer, Swin Transformer, U-Net, and many more. Each model gets a video explaining how it works, then another video showing how to implement it in PyTorch (the dominant AI development framework) and sometimes TensorFlow (an alternative framework). For a Chinese-speaking developer learning computer vision AI, this is a highly regarded free tutorial resource with a clear, structured curriculum from foundational models to state-of-the-art architectures. The accompanying code is written in Python using PyTorch. For non-Chinese speakers or non-technical founders, the direct value is limited as all video content and explanations are in Chinese. However, the code in the repository itself is a useful collection of clean PyTorch implementations of major vision models if you're a developer looking for reference implementations. The repository reflects serious educational work, over 26,000 stars signals it has genuinely helped thousands of Chinese AI learners.