GitLab

* Making quantized inception torchscriptable.

* Adding a test.

* Fix mypy warning.

* Remove model download from tests

* Refactor trainable_layers checks in detection models

* Bugfix

* Finish tests and fixes

* Fix lint

* style: Added annotation typing for shufflenet

* fix: Removed duplicate type hint

* refactor: Removed un-necessary import

* fix: Fixed constructor typing

* style: Added black formatting on depthwise_conv

* style: Fixed stage typing in shufflenet

* style: Added annotation typing for densenet

* fix: Fixed import

* refactor: Removed un-necessary import

* fix: Fixed constructor typing

* chore: Updated mypy.ini

* fix: Fixed tuple typing

* style: Ignored some mypy errors

* style: Fixed typing

* fix: Added missing constructor typing

* changes to value error

* fixes it :)

* simpler fix

* Overwriting FrozenBN eps=0.0 if pretrained=True for detection models.

* Moving the method to detection utils and adding comments.

* style: Added annotation typing for vgg

* fix: Fixed annotation typing

* refactor: Removed un-necessary import

* fix: Added missing annotation for kwargs

* fix: Fixed constructor typing

* refactor: Refactored typing to minize changes

* refactor: Refactored typing cast

* fix: Fixed module list typing

* fix: Fixed constructor typing in models._utils

* fix: Fixed constructor typing in models.alexnet

* fix: Fixed constructor typing in models.mnasnet

* fix: Fixed constructor typing in models.squeezenet

* style: Added annotation typing for mmobilenet

* fix: Fixed type hinting of adaptive pooling

* refactor: Removed un-necessary import

* fix: Fixed constructor typing

* fix: Fixed list typing

* style: Added annotation typing for googlenet

* fix: Removed duplicate typing

* refactor: Moved factory function after class definition to fix typing

* fix: Fixed annotation typing

* refactor: Removed un-necessary import

* fix: Fixed typing

* refactor: Moved back up helper function and quote typed it

* style: Added annotation typing for inception

* refactor: Moved factory function after class definition

* style: Changed attribute setting for type hinting

* refactor: Removed un-necessary import

* fix: Fixed typing in constructors

* fix: Fixed kwargs typing

* style: Fixed lint

* refactor: Moved helpers function back and quote typed it

* style: Added annotation typing for resnet

* fix: Fixed annotation to pass classes

* fix: Fixed annotation typing

* fix: Fixed annotation typing

* fix: Fixed annotation typing for resnet

* refactor: Removed un-necessary import

* fix: Fixed constructor typing

* style: Added black formatting on _resnet

* style: Added annotation typing for squeezenet

* feat: Added typing for kwargs

* style: Added annotation typing for mnasnet

* refactor: Removed un-necessary import

* style: Added typing in models._utils

* fix: Removed non-necessary import

* fix: Removed type annotation of forward method

* refactor: Removed un-necessary import

* Vectorize operations, across all feaure levels.

* Remove unnecessary other_outputs variable.

* Split per feature level.

* Perform batched_nms across feature levels.

* Add extra parameter for limiting detections before and after nms.

* Restoring default threshold.

* Apply suggestions from code review
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Renaming variable.
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Add rough implementation of RetinaNet.

* Move AnchorGenerator to a seperate file.

* Move box similarity to Matcher.

* Expose extra blocks in FPN.

* Expose retinanet in __init__.py.

* Use P6 and P7 in FPN for retinanet.

* Use parameters from retinanet for anchor generation.

* General fixes for retinanet model.

* Implement loss for retinanet heads.

* Output reshaped outputs from retinanet heads.

* Add postprocessing of detections.

* Small fixes.

* Remove unused argument.

* Remove python2 invocation of super.

* Add postprocessing for additional outputs.

* Add missing import of ImageList.

* Remove redundant import.

* Simplify class correction.

* Fix pylint warnings.

* Remove the label adjustment for background class.

* Set default score threshold to 0.05.

* Add weight initialization for regression layer.

* Allow training on images with no annotations.

* Use smooth_l1_loss with beta value.

* Add more typehints for TorchScript conversions.

* Fix linting issues.

* Fix type hints in postprocess_detections.

* Fix type annotations for TorchScript.

* Fix inconsistency with matched_idxs.

* Add retinanet model test.

* Add missing JIT annotations.

* Remove redundant model construction

Make tests pass

* Fix bugs during training on newer PyTorch and unused params in DDP

Needs cleanup and to add back support for images with no annotations

* Cleanup resnet_fpn_backbone

* Use L1 loss for regression

Gives 1mAP improvement over smooth l1

* Disable support for images with no annotations

Need to fix distributed first

* Fix retinanet tests

Need to deduplicate those box checks

* Fix Lint

* Add pretrained model

* Add training info for retinanet
Co-authored-by: Hans Gaiser <hansg91@gmail.com>
Co-authored-by: Hans Gaiser <hans.gaiser@robovalley.com>
Co-authored-by: Hans Gaiser <hans.gaiser@robohouse.com>

Co-authored-by: vfdev <vfdev.5@gmail.com>

Change the default anchor generator settings to default Faster RCNN version(without FPN), so it is hopefully less misleading. Also add an assert to grad_anchors functions to make sure people use it as it is aspected.

* Readme for video models.

* Adressing @fmassa comments
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

Replace nonzero by where, now that it works with just a condition

* partially enable mypy for .models

* fix existing errors

* ignore error instead of using Union

* fix type hints and move degenerate boxes to a function in torchvision.models.detection.generalized_rcnn

* format code

* format code

* changed to static method

* revert imports

* changed to method

* revert procedure for degenerating boxes

* Update transform.py

* Update transform.py

* Try remove eager scripting calls

* remove script call
Co-authored-by: eellison <eellison@fb.com>
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Remove interpolate in favor of PyTorch's implementation

* Bugfix

* Bugfix

* Add norm_layer to MobileNetV2

* Add simple test case

* Small fix

Co-authored-by: eellison <eellison@fb.com>

* add layer freezing param to maskrcnn_resnet50_fpn

* freeze ayer param in keypointrcnn_resnet50_fpn

* layer freeze tests for mask and keypoint rcnn

* correct linting errors

* correct linting errors.

* correct linting errors

* Fix #2221, DenseNet issue with gradient checkpoints (memory_efficient=True)

* Add grad/param count test for mem_efficient densenet

* Fixing nms on boxes when no detection

* test

* Fix for scale_factor computation

* remove newline

* Fix for mask_rcnn dynanmic axes

* Clean up

* Update transform.py

* Fix for torchscript

* Fix scripting errors

* Fix annotation

* Fix lint

* Fix annotation

* Fix for interpolate scripting

* Fix for scripting

* refactoring

* refactor the code

* Fix annotation

* Fixed annotations

* Added test for resize

* lint

* format

* bump ORT

* ort-nightly version

* Going to ort 1.1.0

* remove version

* install typing-extension

* Export model for images with no detection

* Upgrade ort nightly

* update ORT

* Update test_onnx.py

* updated tests

* Updated tests

* merge

* Update transforms.py

* Update cityscapes.py

* Update celeba.py

* Update caltech.py

* Update pkg_helpers.bash

* Clean up

* Clean up for dynamic split

* Remove extra casts

* flake8

* Fix for mask rcnn no detection export

* clean up

* Enable mask rcnn tests

* Added test

* update ORT

* Update .travis.yml

* fix annotation

* Clean up roi_heads

* clean up

* clean up misc ops