# yeyun111/dlcv_for_beginners

《深度学习与计算机视觉》配套代码

Repository: https://github.com/yeyun111/dlcv_for_beginners
Canonical: https://ross.abutalabs.com/products/dlcv_for_beginners
Homepage: https://frombeijingwithlove.github.io/dlcv_for_beginners/
Language: Python
License: BSD-3-Clause
License Family: permissive
Topics: computer-vision, book, beginners, example, deep-learning, caffe, mxnet, pytorch, u-net, model-fusion, gan, siamese, adversarial, unet, classification, regression, segmentation, detection, generative
Last push: 2020-11-30T02:18:46+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3542, "days_push": 2103, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1505, forks 629 (observed 2026-08-28T04:04:54.940961+00:00)

## What it is
Companion code repository for the Chinese book 'Deep Learning and Computer Vision: A Practical Introduction', containing example code across Caffe, MXNet, and PyTorch. It covers beginner-level deep learning tasks such as classification, regression, detection, segmentation, Siamese networks, GANs, and model fusion.

## Use cases
- learn deep learning and computer vision from book examples
- train MNIST classifiers with Caffe or MXNet
- build a Siamese network and visualize embeddings with t-SNE
- generate adversarial examples
- train a 2D GAN in PyTorch
- do transfer learning from ImageNet for food classification
- try image segmentation with U-Net in PyTorch
- visualize convolutional kernels and class activation maps

## When to choose
- you are a beginner following the book and want runnable example code
- you want to learn classic Caffe or MXNet workflows
- you need simple, self-contained deep learning examples

## When to avoid
- you need up-to-date frameworks or modern best practices, as the latter half of the book content is outdated
- you need maintained code with active support, since the repo is no longer updated
- you need production-ready pipelines

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: machine-learning, computer-vision, image-processing, data-visualization
- domain: deep-learning, computer-vision, machine-learning, tutorials
- platform: python, cross-platform
- tags: book-companion-code, caffe, mxnet, pytorch, gan, siamese-network, unet, image-classification, object-detection, image-segmentation, beginner-friendly, chinese

## Member repositories
- yeyun111/dlcv_for_beginners (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:54.940961+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:32:43.461306+00:00, confidence not recorded.
  - readme: https://github.com/yeyun111/dlcv_for_beginners (fetched 2026-08-28T04:04:54.940961+00:00, sha 7a3ff17d16a1)
- Data as of 2026-08-30T08:39:29.467469+00:00.