Cheng Wang's repositories
Fabric-defect-detection
Fabric defect detection based on computer vision
ship-recognition
Fine-grained recognition of ships under complex sea conditions
Handwriting-recognition
Handwritten Recognition Based on BP Neural Network
label-toolbox
Toolbox for making target detection data sets
awesome-semantic-segmentation
:metal: awesome-semantic-segmentation
cambricon_mlu
AI algorithm on mlu220/270
dev-env-ubuntu
构建基于Docker容器的寒武纪开发环境
dHash
基于感知哈希的图像相似度检测
FCN.tensorflow
Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (http://fcn.berkeleyvision.org)
Fully-Convolutional-Networks
Fully Convolutional Networks for Portrait Matting
Intelligent-Traffic-Based-On-CV
本项目为2020年**软件杯Ａ组第一批赛题＂基于计算机视觉的交通场景智能应用＂．项目用python实现，主要使用YOLO模型实现道路目标如人、车、交通灯等物体的识别，使用开源的＂中文车牌识别HyperLPR＂项目实现车牌识别功能．
Jetson-Nano-Code-Collection
Jetson Nano Code Collection
keras-yolo3
A Keras implementation of YOLOv3 (Tensorflow backend)
MRI-U-net
基于U-net和MRI图像的膀胱壁边缘以及膀胱肿瘤检测
PMG-Progressive-Multi-Granularity-Training
Code release for Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches (ECCV2020)
pytorch-cifar
95.16% on CIFAR10 with PyTorch
pytorch_classification
利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码
tensorflow-serving-yolov3
本项目主要对原tensorflow-yolov3版本做了许多细节上的改进,增加了TensorFlow-Serving工程部署,训练了多个数据集，包括Visdrone2019, 安全帽等, 安全帽mAP在98%左右, 推理速度1080上608的尺寸大概25fps.
tensorflow-yolov3
🔥 pure tensorflow Implement of YOLOv3 with support to train your own dataset
Unet-Tensorflow
Tensorflow implement of U-Net
unet_keras_tensorboard
Implementation of Unet on Keras with BatchNormalization and Tensorboard visualization.
yolo_for_ship
this is a yolo for ship detection
YOLOv3-TRT-jetson-nano
基于pytorch-yolov3的trt加速方案
yolov5-deepsort-pedestrian-counting
yolov5 + deepsort实现了行人计数功能， 统计摄像头内出现过的总人数，以及对穿越自定义黄线行人计数效果如下
yolov5s_for_satellite_imagery
基于YOLOv5的卫星图像目标检测demo | A demo for satellite imagery object detection based on YOLOv5