WLAN's starred repositories
Human-Segmentation-PyTorch
Human segmentation models, training/inference code, and trained weights, implemented in PyTorch
mobile-deeplab-v3-plus
Deeplab-V3+ model with MobilenetV2/MobilenetV3 on TensorFlow for mobile deployment.
Person-Segmentation-Keras
Person segmentation with Keras (SegNet, Unet, etc.)
ORB_Segmentation
使用语义分割将图像中的人分离出来,将原始图像中提取的ORB特征点落在人身上的剔除(用于SLAM的位姿估计).
fastdvdnet
FastDVDnet: A Very Fast Deep Video Denoising algorithm
camera-RGB-controller
Real-time RGB channel separator for camera
Ultra-Light-Fast-Generic-Face-Detector-1MB
💎1MB lightweight face detection model (1MB轻量级人脸检测模型)
keras-yolo3
A Keras implementation of YOLOv3 (Tensorflow backend)
tensorflow-lite-YOLOv3
YOLOv3: convert .weights to .tflite format for tensorflow lite. Convert .weights to .pb format for tensorflow serving
WIDER_FACE_data_conversion_for_YOLOv3
将WIDER_FACE数据集转换成yolov3需要的格式
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
🔥 TensorFlow Code for technical report: "YOLOv3: An Incremental Improvement"
tensorflow-yolo-v3
Implementation of YOLO v3 object detector in Tensorflow (TF-Slim)
YOLOv3_TensorFlow
Complete YOLO v3 TensorFlow implementation. Support training on your own dataset.
keras-yolo3-detection
YOLO v3 物体检测算法
face_detection_in_realtime
This repository is the implementation of face detection in real time using YOLOv3 framework with keras(tensorflow backend). For use in embeded devices, so I choose a computation-efficient CNN architecture named ShuffleNet version 2 and train it from scratch(about 50 epoches) on FDDB.
realtime-glasses-detection
Eyeglasses detection for real-time videos based on face alignment with Dlib and OpenCV-Python
tfjs-models
Pretrained models for TensorFlow.js
MTCNN-Tensorflow
Reproduce MTCNN using Tensorflow
tensorflow-MTCNN
人脸检测MTCNN算法,采用tensorflow框架编写,从理解到训练,中文注释完全,含测试和训练,支持摄像头
MTCNN-Tensorflow
mtcnn-tf
deeplearning_ai_books
deeplearning.ai(吴恩达老师的深度学习课程笔记及资源)
Fast-MTCNN
a casual work about retraining to optimize mtcnn Pnet and ONet. it can achieve 100+fps on CPU with minSize 60 (1920x1080) on intel i7 6700k