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huangshaoguang Goto Github PK

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huangshaoguang's Projects

deep-learning-21-examples

《21个项目玩转深度学习———基于TensorFlow的实践详解》配套代码

densebody_pytorch

PyTorch implementation of CloudWalk's recent work DenseBody

face-login

基于mtcnn/facenet/tensorflow 实现人脸识别登录系统

hand-graph-cnn

3D Hand Shape and Pose Estimation from a Single RGB Image

handpose

CrossInfoNet of CVPR 2019 for hand pose estimation

in-silico-labeling

Code for In silico labeling: Predicting fluorescent labels in unlabeled images

insightface

Face Recognition Project on MXNet

license-plate-detect-recognition-via-deep-neural-networks-accuracy-up-to-99.9

works in real-time with detection and recognition accuracy up to 99.8% for Chinese license plates: 100 ms/plate

mask_rcnn

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

mouse_cursor_control_handsfree

This HCI (Human-Computer Interaction) application in Python(3.6) will allow you to control your mouse cursor with your facial movements, works with just your regular webcam. Its hands-free, no wearable hardware or sensors needed.

mtcnn-accelerate-onet

MTCNN Face Detection & Alignment

openpose-based-gui-for-realtime-pose-estimate-and-action-recognition

GUI based on the python api of openpose in windows using cuda10 and cudnn7. Support body , hand, face keypoints estimation and data saving. Realtime gesture recognition is realized through two-layer neural network based on the skeleton collected from the gui.

openpose_train

Training repository for OpenPose

poseestimationformobile

:dancer: Real-time single person pose estimation for Android and iOS.

realtime3dposetracker-openpose

Real time 3D pose tracking and Hand Gesture Recognition using OpenPose, Python Machine Learning Toolkits, Realsense and Kinect libraries.

train-mtcnn

train mtcnn with mxnet

vision

Datasets, Transforms and Models specific to Computer Vision

yolov3-model-pruning

对 YOLOv3 做模型剪枝（network slimming），对于 oxford hand 数据集（因项目需要），模型剪枝后的参数量减少 80%，Infer 的速度达到原来 2 倍，mAP 基本不变

zed-openpose

Real-time 3D multi-person detection made easy with OpenPose and the ZED

zqcnn

一款比mini-caffe更快的Forward库，觉得好用请点星啊，400星公布快速人脸检测模型，500星公布106点landmark，600星公布人头检测模型，700星公布人脸检测套餐（六种pnet,两种rnet随意混合使用满足各种速度/精度要求）

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