Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

📚 计算机经典编程书籍、大黑书、编程电子书、电子书、编程书籍，包括计算机基础、C/C++、Java、Python、面试题、架构设计、算法系列等经典电子书。

Achieve a tiny STL in C++11

A tool to modify ONNX models in a visualization fashion, based on Netron and Flask.

🔥🔥超过1000本的计算机经典书籍、个人笔记资料以及本人在各平台发表文章中所涉及的资源等。书籍资源包括C/C++、Java、Python、Go语言、数据结构与算法、操作系统、后端架构、计算机系统知识、数据库、计算机网络、设计模式、前端、汇编以及校招社招各种面经~

「C/C++学习+面试指南」一份涵盖大部分 C++ 程序员所需要掌握的知识。入门、进阶、深入、校招、社招，准备 C++ 学习& 面试，首选 CppGuide！

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。

Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)

机器人视觉 移动机器人 VS-SLAM ORB-SLAM2 深度学习目标检测 yolov3 行为检测 opencv PCL 机器学习 无人驾驶

Semantic segmentation models, datasets and losses implemented in PyTorch.

⚡ Yolo universal target detection model combined with EfficientNet-lite, the calculation amount is only 230Mflops(0.23Bflops), and the model size is 1.3MB

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！

YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

Tensorflow Implementation of the Semantic Segmentation DeepLab_V3 CNN

Machine Learning in Action学习笔记，一个文件夹代表一个算法，每个文件夹包含算法所需的数据集、源码和图片，图片放在pic文件夹中，数据集放在在Data文件夹内。书中的代码是python2的，有不少错误，这里代码是我用python3写的，且都能直接运行

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

Papers with code. Sorted by stars. Updated weekly.

AdvancedEAST is an algorithm used for Scene image text detect, which is primarily based on EAST, and the significant improvement was also made, which make long text predictions more accurate.

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!