GitLab

* [video reader] inception commit

* add method save_metadata to class VideoClips in video_utils.py

* add load_metadata() method to VideoClips class

* add Exception to not catch unexpected events such as memory erros, interrupt

* fix bugs in video_plus.py

* [video reader]remove logging. update setup.py

* remove time measurement in test_video_reader.py

* Remove glog and try making ffmpeg finding more robust

* Add ffmpeg to conda build

* Add ffmpeg to conda build [again]

* Make library path finding more robust

* Missing import

* One more missing fix for import

* Py2 compatibility and change package to av to avoid version conflict with ffmpeg

* Fix for python2

* [video reader] support to decode one stream only (e.g. video/audio stream)

* remove argument _precomputed_metadata_filepath

* remove save_metadata method

* add get_metadata method

* expose _precomputed_metadata and frame_rate arguments in video dataset __init__ method

* remove ssize_t

* remove size_t to pass CI check on Windows

* add PyInit__video_reader function to pass CI check on Windows

* minor fix to define PyInit_video_reader symbol

* Make c++ video reader optional

* Temporarily revert changes to test_io

* Revert changes to python files

* Rename files to make it private

* Fix python lint

* Fix C++ lint

* add a functor object EnumClassHash to make Enum class instances usable as key type of std::unordered_map

* fix cpp format check

* script_fcn_resnet

* Make old models load

* DeepLabV3 also got torchscript-ready

* make densenet scriptable

* make py2 compat

* use torch List polyfill

* fix unpacking for checkpointing

* fewer changes to _Denseblock

* improve error message

* print traceback

* add typing dependency

* add typing dependency to travis too

* Make loading old checkpoints work

* Remove C++ extensions in favor of custom ops

* Remove unused custom_ops.cpp file

* Rename _custom_ops.py

* Reorganize functions

* Minor improvements and fixes

* Fix lint

* Fully scriptable ops

* Import types used by annotations

* Make AnchorGenerator support half precision

* Add test for fasterrcnn with double

* convert gt_boxes to right dtype

* Support Exporting GeneralizedRCNNTransform

* refactor code to address comments

* update tests

* address comments

* revert min_size to test CI

* re-revert min_size

* Adds optional fill colour to rotate

* bug fix

* Make custom ops differentiable

and replace autograd.Function. Use ops unconditionally.

We may consider removing the extension functions in a follow-up.

The code-path is tested by the exisitng tests for differentiability.

* add scripting gradchecks tests and use intlist

* fix implicit tuple conversion for gcc-5

* fix merge

* Revert "Revert "Register Torchvision Ops as Cutom Ops (#1267)" (#1316)"

This reverts commit fe234fc8.

* Make import of C++ extensions lazy

* define python initialization functions for extension

* Fix lint

* fix url

* update comment

This reverts commit 78f169b5.

* Register torchvision ops

* install ORT only with python 3

* remane lib + address other comments

* fix lint

* fix lib copy

* find file with pattern instead of suffix

* use relative path

* revert rename and use imp to find lib

* fix typo

* make shufflenet scriptable

* make resnet18 scriptable

* set downsample to identity instead of __constants__ api

* use __constants__ for downsample instead of identity

* import tensor to fix flake

* use torch.Tensor type annotation instead of import

* fixed typo

* fixed some more typos and grammer

* Fix flakiness of test_randomresized_params

* Real fix

* Reduce number of iters

* Use Tensor.data_ptr instead of .data

* use pytorch-nightly in CI

* Fix bug of changing input tensor in function

The original code will change the image tensor passed in by multiplying it by 255. The PR fixes that.

* fix inplace multiplication in save_image

Fixed video labelling after `subset` call for HMDB51 dataset (hmdb51.py) (EDIT: UCF101 as well) (#1240)

* Fixed video labelling after subset for HMDB51 dataset

* Fixed video labelling after subset for HMDB51 dataset
Co-authored-by: Eric Tang <etang21@stanford.edu>
Co-authored-by: Ryan Cao <ryancao@stanford.edu>

* UCF 101 Labeling fixes

- Analogous fix to HMDB51 to maintain correct labels after the train-test split
- Additional change to the `select_fold` method in `ucf101.py` to correctly reflect the annotation format
Co-authored-by: Ryan Cao <ryancao@stanford.edu>
Co-authored-by: Eric Tang <etang21@stanford.edu>

Following a similar line of inquiry to pytorch/audio#217

`self.fc1(x)` converts the shape of `x` into "N x 1024", and `self.fc2(x)` converts into "N x num_classes".

By adding `print(x.shape)` under each comment line, the console displays as follows (batch_size is 1):

```text
torch.Size([1, 2048])
torch.Size([1, 1024])
torch.Size([1, 1024])
torch.Size([1, 1024])
torch.Size([1, 1000])
```

* Add docs for video models

* Fix docstrings for resnet and vgg

* [WIP] Minor cleanups on R3d

* Move all models to video/resnet.py

* Remove old files

* Make tests less memory intensive

* Lint

* Fix typo and add pretraing arg to training script

* Expose docs for io and ops package

Had do modify the docstrings to use Napoleon NumPy style, because Napoleon Google Style doesn't support multiple return arguments

* Add video section

* Add docs to UCF101 and HMDB51 datasets

* Remove extra line

* Lint

* Move RandomClipSampler to references

* Lint and bugfix

Also add docs

* Copy classification scripts for video classification

* Initial version of video classification

* add version

* Training of r2plus1d_18 on kinetics work

Gives even slightly better results than expected, with 57.336 top1 clip accuracy. But we count some clips twice in this evaluation

* Cleanups on training script

* Lint

* Minor improvements

* Remove some hacks

* Lint

* Optimize read_video_timestamps for some formats

* Add some tests

* fix stl10

* fix lsun

* Miscellaneous fixes and improvements

* Guard against videos without video stream

* Fix lint

* Add test for packed b-frames videos

* Fix missing import