Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

A PyTorch implementation of EfficientNet

Object detection, 3D detection, and pose estimation using center point detection:

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, …

Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.

中文文本分类，TextCNN，TextRNN，FastText，TextRCNN，BiLSTM_Attention，DPCNN，Transformer，基于pytorch，开箱即用。

FCOS: Fully Convolutional One-Stage Object Detection (ICCV'19)

Caffe models in TensorFlow

Safety helmet wearing detect dataset, with pretrained model

DBFace is a real-time, single-stage detector for face detection, with faster speed and higher accuracy

DSOD: Learning Deeply Supervised Object Detectors from Scratch. In ICCV 2017.

Hybrid CPU/GPU implementation of the A3C algorithm for deep reinforcement learning.

Video Object Segmentation with Re-identification

ResNet-20/32/44/56/110 on CIFAR-10 with Caffe

Base on retinaface and centerface modefied. frame work depend on pytorch.

wider face验证集的测评代码