This version introduces several improvements and fixes.

Support for arbitrary input sizes for models

It is now possible to feed larger images than 224x224 into the models in torchvision.
We added an adaptive pooling just before the classifier, which adapts the size of the feature maps before the last layer, allowing for larger input images.
Relevant PRs: #744 #747 #746 #672 #643

Bugfixes

• Fix invalid argument error when using lsun method in windows (#508)
• Fix FashionMNIST loading MNIST (#640)
• Fix inception v3 input transform for trace & onnx (#621)

Datasets

• Add support for webp and tiff images in ImageFolder #736 #724
• Add K-MNIST dataset #687
• Add Cityscapes dataset #695 #725 #739 #700
• Add Flicker 8k and 30k datasets #674
• Add VOCDetection and VOCSegmentation datasets #663
• Add SBU Captioned Photo Dataset (#665)
• Updated URLs for EMNIST #726
• MNIST and FashionMNIST now have their own 'raw' and 'processed' folder #601
• Add metadata to some datasets (#501)

Improvements

• Allow RandomCrop to crop in the padded region #564
• ColorJitter now supports min/max values #548
• Generalize resnet to use block.extension #487
• Move area calculation out of for loop in RandomResizedCrop #641
• Add option to zero-init the residual branch in resnet (#498)
• Improve error messages in to_pil_image #673
• Added the option of converting to tensor for numpy arrays having only two dimensions in to_tensor (#686)
• Optimize _find_classes in DatasetFolder via scandir in Python3 (#559)
• Add padding_mode to RandomCrop (#489 #512)
• Make DatasetFolder more generic (#527)
• Add in-place option to normalize (#699)
• Add Hamming and Box interpolations to transforms.py (#693)
• Added the support of 2-channel Image modes such as 'LA' and adding a mode in 4 channel modes (#688)
• Improve support for 'P' image mode in pad (#683)
• Make torchvision depend on pillow-simd if already installed (#522)
• Make tests run faster (#745)
• Add support for non-square crops in RandomResizedCrop (#715)

Breaking changes

• save_images now round to nearest integer #754

Misc

• Added code coverage to travis #703
• Add downloads and docs badge to README (#702)
• Add progress to download_url #497 #524 #535
• Replace 'residual' with 'identity' in resnet.py (#679)
• Consistency changes in the models
• Refactored MNIST and CIFAR to have data and target fields #578 #594
• Update torchvision to newer versions of PyTorch
• Relax assertion in transforms.Lambda.__init__ (#637)
• Cast MNIST target to int (#605)
• Change default target type of FakedDataset to long (#581)
• Improve docs of functional transforms (#602)
• Docstring improvements
• Add is_image_file to folder_dataset (#507)
• Add deprecation warning in MNIST train[test]_labels[data] (#742)
• Mention TORCH_MODEL_ZOO in models documentation. (#624)
• Add scipy as a dependency to setup.py (#675)
• Added size information for inception v3 (#719)