#5353rd of 65 in Learning and cookbooks
deep-learning-for-image-processing
Chinese video course on vision networks with PyTorch and TensorFlow code
- Stars
- 26.4k
- License
- GPL-3.0
- Last commit
- Jan 2026
- Language
- Python
25,964 on 10 Apr 202626,438 on 30 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
A Chinese-language course covering image classification, object detection, semantic and instance segmentation, and keypoint detection. Each topic links to Bilibili videos that explain the network, then build and train it in PyTorch and, for many classification models, TensorFlow 2 (Keras). Slides are in the course_ppt folder.
Who it is for: Chinese speakers learning computer vision networks in PyTorch or TensorFlow
Strengths
- Spans classification, detection, segmentation and keypoints, from LeNet to Swin Transformer and ConvNeXt
- Most classification models are built in both PyTorch and TensorFlow 2
- Source walkthroughs for Faster-RCNN, SSD, YOLOv3 SPP, U-Net, Mask R-CNN and HRNet
- Slides are downloadable from the course_ppt folder
Weaknesses
- README and videos are Chinese only, no English version
- Lessons are hosted on Bilibili, outside the repository
- Detection, segmentation and keypoint lessons are PyTorch only
- No LLM or diffusion content; topics are CNN and Transformer vision models
What it needs
- Needs PyTorch, TensorFlow 2
Quick answers
Is deep-learning-for-image-processing open source?
Yes. Its code is on GitHub under the GPL-3.0 license.
Also in Learning and cookbooks
See all 65| Rank | Project | Score |
|---|---|---|
| 1 | ai-engineering-from-scratchHands-on AI engineering curriculum with 542 lessons across 20 phases | 89 out of 100 |
| 2 | generative-ai-for-beginners21-lesson course on building generative AI apps in Python and TypeScript | 81 out of 100 |
| 3 | rag_techniquesCollection of 42 runnable notebooks implementing RAG techniques | 79 out of 100 |
| #4 | cs249r_bookOpen textbook and course materials for machine learning systems engineering | 79 out of 100 |
| #5 | ai-agents-for-beginners18-lesson course on building AI agents with Microsoft Agent Framework | 78 out of 100 |