TommyZihao/Train_Custom_Dataset resource

Health v2 · maintenance only

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Adoption not part of the score

4096 stars · 764 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A free open-source Chinese tutorial collection (Jupyter Notebooks plus videos) teaching how to annotate your own datasets and train, evaluate, test, and deploy AI models, primarily with PyTorch. It covers image classification, transfer learning, object tracking, OCR, style transfer, and LLM summarization, aimed at helping students complete AI graduation projects.

Use cases

• learn to train a custom image classification model with pytorch
• annotate my own dataset for machine learning
• fine-tune a pretrained imagenet model on my images
• evaluate a classifier with confusion matrix and roc curves
• visualize model features with tsne and umap
• do an ai graduation project in two days
• learn ocr text recognition and cyclegan style transfer

When to choose

• you are a student or beginner wanting guided, video-backed tutorials in Chinese for training custom vision models
• you need end-to-end coverage from dataset annotation to deployment for a course or thesis project

When to avoid

• you need production-grade, maintained library code rather than educational notebooks
• you require a permissively licensed dependency - the repo has no license and restricts use to non-commercial teaching and research

Facets

learning-resource · maturity active

machine-learning image-processing computer-vision ocr data-science deep-learning computer-vision education tutorials artificial-intelligence python cross-platform pytorch jupyter-notebook transfer-learning image-classification dataset-annotation chinese graduation-project model-deployment tsne cyclegan gpu

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markdown · JSON · MCP: product_card(name="TommyZihao/Train_Custom_Dataset")