GitLab

Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Moving mobilenet.py to mobilenetv2.py

* Adding mobilenet.py for BC.

* Extending ConvBNReLU for reuse.

* Reduce import scope on mobilenet to only the public and versioned classes and methods.

* Fixing incorrect doc example in MNASNet.

* Fixing incorrect output.

* Replacing all torch.jit.annotations with typing

* Replacing remaining typing

* Fix an issue that ShuffleNetV2 model is exported to a wrong ONNX file if dynamic_axes field was provided.

* Add a ut for the bug fix.

* Fix flake8 issue.

* Don't access each element in x.shape, use x.size() instead.
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

Replace tabs with spaces, add newlines to files and replace whitelist with allowlist

* Correcting incorrect types

* Add missing type statement

* Fix type annotations in unittest

* Fix TypeError

* Fix TypeError

* Fix type equality judgment

* Fix recursive compile

* Use string for class name annotation.
Co-authored-by: zhiqiang <zhiqwang@outlook.com>

* Enable support for images without annotations

* Ensuring gradient propagates to RegressionHead.

* Rewriting losses to remove branching.

* Fix the seed on DeformConv autocast test.

Adding Python type hints, correcting incorrect types, removing unnecessary vars and simplifying code. (#3045)

* refactor: Fixed typing exception throwing issues with JIT

* style: Added back mypy typing to forward

* chore: Added back densenet module as mypy exception

* Fix MNASNet docstrings so they are rendered correctly

* Add dot after url link in models docstrings for consistency

* 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