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Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and…
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
brpc is an Industrial-grade RPC framework using C++ Language, which is often used in high performance system such as Search, Storage, Machine learning, Advertisement, Recommendation etc. "brpc" mea…
This repo is implemented based on detectron2 and centernet
My blogs and code for machine learning. http://cnblogs.com/pinard
Code for AAAI 2021 paper: R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object
Object detection, 3D detection, and pose estimation using center point detection:
CV算法岗知识点及面试问答汇总，主要分为计算机视觉、机器学习、图像处理和 C++基础四大块，一起努力向offers发起冲击！
A curated list of awesome self-supervised methods
Image segmentation-Object detection-Light-weight network
Demonstrate all the questions on LeetCode in the form of animation.（用动画的形式呈现解LeetCode题目的思路）
计算机基础（计算机网络/操作系统/数据库/Git...）面试问题全面总结，包含详细的follow-up question以及答案；全部采用【问题+追问+答案】的形式，即拿即用，直击互联网大厂面试；可用于模拟面试、面试前复习、短期内快速备战面试...
刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.
lightweight and efficient cnn for semantic segmentation, my blog address:
This repository contains the source code of our work on designing efficient CNNs for computer vision
MassFace: an effecient implementation using triplet loss for face recognition
The convertor/conversion of deep learning models for different deep learning frameworks/softwares.
Learn OpenCV : C++ and Python Examples
「画像処理100本ノック」中文版本！为图像处理初学者设计的 100 个问题。
📖 OpenCV-Python image processing tutorial for beginners
[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy
A collection of loss functions for medical image segmentation
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
Classification models trained on ImageNet. Keras.