L. D. Xiao's repositories
computer-vision-in-action
《计算机视觉实战演练:算法与应用》中文电子书、源码、读者交流社区(更新中,可以先 star)
albumentations
Fast image augmentation library and easy to use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about library: https://www.mdpi.com/2078-2489/11/2/125
Bilibili-plus
课程视频、PPT和源代码:侯捷C++系列;台大郭彦甫MATLAB
CascadeTabNet
This repository contains the code and implementation details of the CascadeTabNet paper "CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents"
computervision-recipes
Best Practices, code samples, and documentation for Computer Vision.
coremltools
Core ML Community Tools.
CRNN_Chinese_Characters_Rec
(CRNN) Chinese Characters Recognition.
detr
End-to-End Object Detection with Transformers
Dive-into-DL-PyTorch
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
eng-practices
Google's Engineering Practices documentation
face_recognition
The world's simplest facial recognition api for Python and the command line
facenet-pytorch
Pretrained Pytorch face detection (MTCNN) and recognition (InceptionResnet) models
featuretools
An open source python library for automated feature engineering
jd_seckill
京东秒杀商品抢购,目前只支持茅台抢购,不支持其他商品!
machine_learning_refined
Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).
ml-visuals
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
Object-Detection-Metrics
Most popular metrics used to evaluate object detection algorithms.
PaddleOCR
Awesome OCR toolkits based on PaddlePaddle (8.6M ultra-lightweight pre-trained model, support training and deployment among server, mobile, embeded and IoT devices)
pycharm-guide
PyCharm 中文指南:安装 | 破解 | 效率 | 技巧
Statistical-Learning-Methods
Implement Statistical Leanring Methods, Li Hang the hard way. 李航《统计学习方法》一书的硬核 Python 实现
transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.