Pretrained_ConvNets_for_pytorch_NASNet,_ResNeXt,__p

# Pretrained models for Pytorch (Work in progress) The goal of this repo is: - to help to reproduce research papers results (transfer learning setups for instance), - to access pretrained ConvNets with a unique interface/API inspired by torchvision. <a href="https://travis-ci.org/Cadene/pretrained-models.pytorch"><img src="https://api.travis-ci.org/Cadene/pretrained-models.pytorch.svg?branch=master"/></a> News: - 27/10/2018: Fix compatibility issues, Add tests, Add travis - 04/06/2018: [PolyNet](https://github.com/CUHK-MMLAB/polynet) and [PNASNet-5-Large](https://arxiv.org/abs/1712.00559) thanks to [Alex Parinov](https://github.com/creafz) - 16/04/2018: [SE-ResNet* and SE-ResNeXt*](https://github.com/hujie-frank/SENet) thanks to [Alex Parinov](https://github.com/creafz) - 09/04/2018: [SENet154](https://github.com/hujie-frank/SENet) thanks to [Alex Parinov](https://github.com/creafz) - 22/03/2018: CaffeResNet101 (good for localization with FasterRCNN) - 21/03/2018: NASNet Mobile thanks to [Veronika Yurchuk](https://github.com/veronikayurchuk) and [Anastasiia](https://github.com/DagnyT) - 25/01/2018: DualPathNetworks thanks to [Ross Wightman](https://github.com/rwightman/pytorch-dpn-pretrained), Xception thanks to [T Standley](https://github.com/tstandley/Xception-PyTorch), improved TransformImage API - 13/01/2018: `pip install pretrainedmodels`, `pretrainedmodels.model_names`, `pretrainedmodels.pretrained_settings` - 12/01/2018: `python setup.py install` - 08/12/2017: update data url (/!\ `git pull` is needed) - 30/11/2017: improve API (`model.features(input)`, `model.logits(features)`, `model.forward(input)`, `model.last_linear`) - 16/11/2017: nasnet-a-large pretrained model ported by T. Durand and R. Cadene - 22/07/2017: torchvision pretrained models - 22/07/2017: momentum in inceptionv4 and inceptionresnetv2 to 0.1 - 17/07/2017: model.input_range attribut - 17/07/2017: BNInception pretrained on Imagenet ## Summary - [Installation](https://github.com/Cadene/pretrained-models.pytorch#installation) - [Quick examples](https://github.com/Cadene/pretrained-models.pytorch#quick-examples) - [Few use cases](https://github.com/Cadene/pretrained-models.pytorch#few-use-cases) - [Compute imagenet logits](https://github.com/Cadene/pretrained-models.pytorch#compute-imagenet-logits) - [Compute imagenet validation metrics](https://github.com/Cadene/pretrained-models.pytorch#compute-imagenet-validation-metrics) - [Evaluation on ImageNet](https://github.com/Cadene/pretrained-models.pytorch#evaluation-on-imagenet) - [Accuracy on valset](https://github.com/Cadene/pretrained-models.pytorch#accuracy-on-validation-set) - [Reproducing results](https://github.com/Cadene/pretrained-models.pytorch#reproducing-results) - [Documentation](https://github.com/Cadene/pretrained-models.pytorch#documentation) - [Available models](https://github.com/Cadene/pretrained-models.pytorch#available-models) - [AlexNet](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [BNInception](https://github.com/Cadene/pretrained-models.pytorch#bninception) - [CaffeResNet101](https://github.com/Cadene/pretrained-models.pytorch#caffe-resnet) - [DenseNet121](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [DenseNet161](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [DenseNet169](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [DenseNet201](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [DenseNet201](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [DualPathNet68](https://github.com/Cadene/pretrained-models.pytorch#dualpathnetworks) - [DualPathNet92](https://github.com/Cadene/pretrained-models.pytorch#dualpathnetworks) - [DualPathNet98](https://github.com/Cadene/pretrained-models.pytorch#dualpathnetworks) - [DualPathNet107](https://github.com/Cadene/pretrained-models.pytorch#dualpathnetworks) - [DualPathNet113](https://github.com/Cadene/pretrained-models.pytorch#dualpathnetworks) - [FBResNet152](https://github.com/Cadene/pretrained-models.pytorch#facebook-resnet) - [InceptionResNetV2](https://github.com/Cadene/pretrained-models.pytorch#inception) - [InceptionV3](https://github.com/Cadene/pretrained-models.pytorch#inception) - [InceptionV4](https://github.com/Cadene/pretrained-models.pytorch#inception) - [NASNet-A-Large](https://github.com/Cadene/pretrained-models.pytorch#nasnet) - [NASNet-A-Mobile](https://github.com/Cadene/pretrained-models.pytorch#nasnet) - [PNASNet-5-Large](https://github.com/Cadene/pretrained-models.pytorch#pnasnet) - [PolyNet](https://github.com/Cadene/pretrained-models.pytorch#polynet) - [ResNeXt101_32x4d](https://github.com/Cadene/pretrained-models.pytorch#resnext) - [ResNeXt101_64x4d](https://github.com/Cadene/pretrained-models.pytorch#resnext) - [ResNet101](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [ResNet152](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [ResNet18](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [ResNet34](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [ResNet50](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [SENet154](https://github.com/Cadene/pretrained-models.pytorch#senet) - [SE-ResNet50](https://github.com/Cadene/pretrained-models.pytorch#senet) - [SE-ResNet101](https://github.com/Cadene/pretrained-models.pytorch#senet) - [SE-ResNet152](https://github.com/Cadene/pretrained-models.pytorch#senet) - [SE-ResNeXt50_32x4d](https://github.com/Cadene/pretrained-models.pytorch#senet) - [SE-ResNeXt101_32x4d](https://github.com/Cadene/pretrained-models.pytorch#senet) - [SqueezeNet1_0](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [SqueezeNet1_1](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [VGG11](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [VGG13](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [VGG16](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [VGG19](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [VGG11_BN](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [VGG13_BN](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [VGG16_BN](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [VGG19_BN](https://github.com/Cadene/pretrained-models.pytorch#torchvision) - [Xception](https://github.com/Cadene/pretrained-models.pytorch#xception) - [Model API](https://github.com/Cadene/pretrained-models.pytorch#model-api) - [model.input_size](https://github.com/Cadene/pretrained-models.pytorch#modelinput_size) - [model.input_space](https://github.com/Cadene/pretrained-models.pytorch#modelinput_space) - [model.input_range](https://github.com/Cadene/pretrained-models.pytorch#modelinput_range) - [model.mean](https://github.com/Cadene/pretrained-models.pytorch#modelmean) - [model.std](https://github.com/Cadene/pretrained-models.pytorch#modelstd) - [model.features](https://github.com/Cadene/pretrained-models.pytorch#modelfeatures) - [model.logits](https://github.com/Cadene/pretrained-models.pytorch#modellogits) - [model.forward](https://github.com/Cadene/pretrained-models.pytorch#modelforward) - [Reproducing porting](https://github.com/Cadene/pretrained-models.pytorch#reproducing) - [ResNet*](https://github.com/Cadene/pretrained-models.pytorch#hand-porting-of-resnet152) - [ResNeXt*](https://github.com/Cadene/pretrained-models.pytorch#automatic-porti