Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

PaddlePaddle End-to-End Development Toolkit（『飞桨』深度学习全流程开发工具）

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)

Tensorflow Faster RCNN for Object Detection

OpenMMLab Pre-training Toolbox and Benchmark

🍅🍅🍅YOLOv5-Lite: Evolved from yolov5 and the size of model is only 900+kb (int8) and 1.7M (fp16). Reach 15 FPS on the Raspberry Pi 4B~

Implementation of EfficientNet model. Keras and TensorFlow Keras.

Convolutional Neural Networks to predict the aesthetic and technical quality of images.

Caffe implementation of Google MobileNet SSD detection network, with pretrained weights on VOC0712 and mAP=0.727.

🍅 Deploy ncnn on mobile phones. Support Android and iOS. 移动端ncnn部署，支持Android与iOS。

Receptive Field Block Net for Accurate and Fast Object Detection, ECCV 2018

Caffe Implementation of Google's MobileNets (v1 and v2)

Library for Fast and Flexible Human Pose Estimation

Classification models trained on ImageNet. Keras.

High level network definitions with pre-trained weights in TensorFlow

A caffe implementation of MobileNet-YOLO detection network

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

PytorchAutoDrive: Segmentation models (ERFNet, ENet, DeepLab, FCN...) and Lane detection models (SCNN, RESA, LSTR, LaneATT, BézierLaneNet...) based on PyTorch with fast training, visualization, benchmarking & deployment help

The implementation of various lightweight networks by using PyTorch. such as：MobileNetV2，MobileNeXt，GhostNet，ParNet，MobileViT、AdderNet，ShuffleNetV1-V2，LCNet，ConvNeXt，etc. ⭐⭐⭐⭐⭐

A mobilenet SSD based face detector, powered by tensorflow object detection api, trained by WIDERFACE dataset.