DeepLab v3+ model in PyTorch. Support different backbones.

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)

Classification models trained on ImageNet. Keras.

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

でぃーぷらーにんぐを無限にやってディープラーニングでDeepLearningするための実装CheatSheet

猫狗大战

Support PointRend, Fast_SCNN, HRNet, Deeplabv3_plus(xception, resnet, mobilenet), ContextNet, FPENet, DABNet, EdaNet, ENet, Espnetv2, RefineNet, UNet, DANet, HRNet, DFANet, HardNet, LedNet, OCNet, EncNet, DuNet, CGNet, CCNet, BiSeNet, PSPNet, ICNet, FCN, deeplab)

A treasure chest for image classification powered by PaddlePaddle

AI Papers

AI场景分类竞赛

This is an ongoing re-implementation of DeepLab_v3_plus on pytorch which is trained on VOC2012 and use ResNet101 for backbone.

COVID-19 Detection Chest X-rays and CT scans: COVID-19 Detection based on Chest X-rays and CT Scans using four Transfer Learning algorithms: VGG16, ResNet50, InceptionV3, Xception. The models were trained for 500 epochs on around 1000 Chest X-rays and around 750 CT Scan images on Google Colab GPU. A Flask App was later developed wherein user can upload Chest X-rays or CT Scans and get the output of possibility of COVID infection.

Xception implemented with caffe

Train/Eval the popular network by TF-Slim,include mobilenet/shufflenet/squeezenet/resnet/inception/vgg/alexnet

Easy-to-use scripts for training and inferencing with Xception on your own dataset

Deep learning based tool for image processing. No need for Programing and GPU.

training a classification model with xray14 dataset

Xception V1 model in Tensorflow with pretrained weights on ImageNet

Pytorch implementation of DeepLab V3+

Generating image captions using Xception Network and Beam Search in Keras

99.7% accuracy solution for Dogs vs Cats Redux Kaggle competition

An approach to detecting face masks in crowded places built using RetinaNet Face for face mask detection and Xception network for classification.

pytorch-1.1 torchvision-0.3

Simple Eye Blink Detection with CNN

Lightweight Facial Expression(emotion) Recognition model

Chainer implementation of the paper "Xception: Deep Learning with Depthwise Separable Convolutions" (https://arxiv.org/abs/1610.02357).

Implementation of state-of-the-art models to do segmentation over our own dataset.

Covid-19 and Pneumonia detection from X-ray Images from the paper: https://doi.org/10.1016/j.imu.2020.100360

👣 “恒锐杯”鞋印花纹图像类别判定挑战赛