wc666666's repositories
Aggregation-Cross-Entropy
Aggregation Cross-Entropy for Sequence Recognition. CVPR 2019.
AlphaTree-graphic-deep-neural-network
将深度神经网络中的一些模型 进行统一的图示，便于大家对模型的理解
awesome-deep-text-detection-recognition
A curated list of resources for text detection/recognition (optical character recognition ) with deep learning methods.
Chinese_OCR_CNN-RNN-CTC
中文手写汉字识别
chineseocr_lite
超轻量级中文ocr，支持竖排文字识别, 支持ncnn推理 , psenet(8.5M) + crnn(6.3M) + anglenet(1.5M) 总模型仅17M
CRAFT-Reimplementation
CRAFT-Pyotorch：Character Region Awareness for Text Detection Reimplementation for Pytorch
CRAFT-Remade
Implementation of CRAFT Text Detection
crnn-mxnet-chinese-text-recognition
An implementation of CRNN (CNN+LSTM+warpCTC) on MxNet for chinese text recognition
crnn.pytorch
A pytorch re-implementation of Convolutional recurrent network in pytorch
cv-papers
计算机视觉相关论文整理、记录、分享; 包括图像分类、目标检测、视觉跟踪/目标跟踪、人脸识别/人脸验证、OCR/场景文本检测及识别等领域。欢迎加星,欢迎指正错误,同时也期待能够共同参与！！! 持续更新中... ...
deep-text-recognition-benchmark
Text recognition (optical character recognition) with deep learning methods.
imgaug
Image augmentation for machine learning experiments.
lihang-code
《统计学习方法》的代码实现
MegReader
A research project for text detection and recognition using PyTorch 1.2.
ocr-handwriting-recognition
This is a english handwriting recognition project
ocr_invoice
ocr system of invoice
PAN-PSEnet
Pytorch implementation of PSEnet with Pyramid Attention Network as feature extractor
PMTD
Pyramid Mask Text Detector designed by SenseTime Video Intelligence Research team.
PolarMask
Code for 'PolarMask: Single Shot Instance Segmentation with Polar Representation'
PSENet-Plus
PSENet Pytorch版本的优化与增强
stela
Scene Text Detection with Learned Anchor
tensorflow
An Open Source Machine Learning Framework for Everyone
Tensorflow-
Tensorflow实战学习笔记、代码、机器学习进阶系列
Text_Detector
Text detection model that combines Retinanet with textboxes++ for OCR
TorchDemo
Pytorch libtorch demo
Traffic-Survalance-with-Computer-Vision-and-Deep-Learning
The system takes video footage of a highway as input and provides statistics like the count of vehicles and an average estimated speed of vehicles on the highway. The statistics provided by the system can have many applications. Like, pricing the billboards on a highway for advertisement, higher the count of vehicles, higher the price. Moreover, the government can use this statistic to know how many vehicles are entering a city each day. The system internally uses YOLO object detection algorithm for vehicle detection, followed by, Centroid Tracking algorithm for tracking the detected vehicles.
USTC-CS-Courses-Resource
:heart:中国科学技术大学计算机学院课程资源(https://mbinary.xyz/ustc-cs/)
zju-icicles
浙江大学课程攻略共享计划
