mobilenet

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

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)

Deep Pose Estimation implemented using Tensorflow with Custom Architectures for fast inference.

OpenMMLab Pre-training Toolbox and Benchmark

Tensorflow Faster RCNN for Object Detection

🍅🍅🍅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~

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

Implementation of EfficientNet model. Keras and TensorFlow Keras.

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

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 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

MobileNetV3 in pytorch and ImageNet pretrained models