- 07 Feb, 2020 4 commits
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Yuxin Wu authored
Summary: It is not the first time panoptic instant test fails with memory error: https://our.intern.facebook.com/intern/fblearner/details/166744913/operator/1735305631/ increasing the memory requirement might fix it. Reviewed By: rbgirshick Differential Revision: D19782277 fbshipit-source-id: 9beca005f807c12c5b35cf3e1a3174701e592b10
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Yuxin Wu authored
Summary: Now live at https://dl.fbaipublicfiles.com/detectron2/wheels/index.html Pull Request resolved: https://github.com/fairinternal/detectron2/pull/381 Differential Revision: D19776395 Pulled By: ppwwyyxx fbshipit-source-id: 363a7f5fa1499a1e1d91eccd055c9b5ca01cc160
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Alexander Kirillov authored
Summary: Improve documentation Reviewed By: ppwwyyxx Differential Revision: D19779790 fbshipit-source-id: 83532d40ea14d23700328f5cea956fff479356a0
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Jing Huang authored
RotatedCOCOEvaluator: Universal COCO-style evaluation between any combinations of {horizontal, rotated} PyTorch models vs. {horizontal, rotated} datasets Summary: RotatedCOCOEvaluator: Universal COCO-style evaluation between any combinations of {horizontal, rotated} PyTorch models vs. {horizontal, rotated} datasets Reviewed By: ppwwyyxx Differential Revision: D18815399 fbshipit-source-id: 7fae26f3ed3ea680706fd085cb315acb76d910fd
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- 06 Feb, 2020 4 commits
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Alexander Kirillov authored
Summary: Detaching predicted boxes from gradient computation since D2 assumes that `proposal_boxes.tensor` has `require_grad=False` Reviewed By: ppwwyyxx Differential Revision: D19762932 fbshipit-source-id: c633345435ae4d3b28e59d5f7e4e1bfed3a9b4b5
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Alexander Kirillov authored
Summary: swap `FC_DIM` and `NUM_FC` in `MODEL.ROI_MASK_HEAD` Reviewed By: ppwwyyxx Differential Revision: D19761214 fbshipit-source-id: ec909dfcae01e585ce22ac6cce3f5e3ede1645ce
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Yuxin Wu authored
Summary: And AT_CHECK is deprecated in favor of TORCH_CHECK Pull Request resolved: https://github.com/fairinternal/detectron2/pull/380 Differential Revision: D19756656 Pulled By: ppwwyyxx fbshipit-source-id: 2934b3758316c637d79a9fc63c0c3040876928b6
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Yuxin Wu authored
Summary: Pull Request resolved: https://github.com/fairinternal/detectron2/pull/379 Differential Revision: D19744414 Pulled By: ppwwyyxx fbshipit-source-id: 03b0f7f9d883c6530ac4945bf801ab7a1b59f9c0
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- 05 Feb, 2020 1 commit
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Jing Huang authored
Summary: Pull Request resolved: https://github.com/facebookresearch/detectron2/pull/760 Workaround https://github.com/pytorch/pytorch/issues/31258 Reviewed By: ppwwyyxx Differential Revision: D19609404 fbshipit-source-id: f5bcf649bf1b11dc44015e6a450975bd86d16587
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- 04 Feb, 2020 1 commit
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Yuxin Wu authored
Summary: Transition to native pytorch support that's recently added: https://github.com/pytorch/pytorch/pull/32709 adds support for conv/convtranspose. https://github.com/pytorch/pytorch/pull/32820 adds support for batchnorm. https://github.com/pytorch/pytorch/pull/32401 adds support for groupnorm. Reviewed By: rbgirshick Differential Revision: D19658831 fbshipit-source-id: 48834996809b28bdaa6ab6930676a0d54a492460
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- 03 Feb, 2020 1 commit
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Marc Szafraniec authored
Summary: [DensePose] Make new better parameters default + add Decoder Reviewed By: vkhalidov Differential Revision: D19580106 fbshipit-source-id: c62c62dd9066ea8d0d6a927e021585d412c81bd3
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- 01 Feb, 2020 3 commits
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Yuxin Wu authored
Summary: Pull Request resolved: https://github.com/fairinternal/detectron2/pull/378 Differential Revision: D19664327 Pulled By: ppwwyyxx fbshipit-source-id: 09680664a24340fe9eadbb69854c2dd74ce89591
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Yuxin Wu authored
Summary: 1. fvcore: `torch.flip` is slow (https://github.com/pytorch/pytorch/issues/16424#issuecomment-580695672). Now replaced by numpy. OpenCV would be faster. 2. detectron2: use uint8 images. they will be casted to float32 in the model during mean subtraction. Not done: using opencv to read images is also faster. But haven't opted in OpenCV yet. Reviewed By: rbgirshick Differential Revision: D19663279 fbshipit-source-id: 9cf16dee0be370a7bd23c4836ab047ce210eccb0
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Yanghan Wang authored
Summary: sometimes the reshape parameter of Reshape is from external input thus no producer. Reviewed By: newstzpz, ppwwyyxx Differential Revision: D19656521 fbshipit-source-id: 70f878d0ab5d34446ef13728ae02eae228af777a
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- 31 Jan, 2020 5 commits
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Yuxin Wu authored
Summary: So adding back old hacks. Fix https://github.com/facebookresearch/detectron2/issues/772 Pull Request resolved: https://github.com/fairinternal/detectron2/pull/377 Differential Revision: D19648921 Pulled By: ppwwyyxx fbshipit-source-id: 683a94769cae537288327e51c0f1ecd96bd04986
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Alexander Kirillov authored
Summary: readme for the PointRend project + model zoo. AWS links are broken for now. Reviewed By: ppwwyyxx Differential Revision: D19634906 fbshipit-source-id: c18a2e4e58736a0f96ce877b400db7a968151515
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Alexander Kirillov authored
Summary: PointRend for instance segmentation Reviewed By: rbgirshick, ppwwyyxx Differential Revision: D18712024 fbshipit-source-id: 4a9e882859e58d104141bb820c6da781aa42d3b8
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Alexander Kirillov authored
Summary: Add setting to StandardROIHeads to use bounding boxes predicted by the box head during training for all other heads. Reviewed By: ppwwyyxx Differential Revision: D18618799 fbshipit-source-id: 1bd1b3e89e9d90bd6f1bc9fbed64f30b6303cbef
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Yanghan Wang authored
Reviewed By: Sterbic Differential Revision: D19625998 fbshipit-source-id: 940b41833abca06a2085b35d560b80c674134db1
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- 30 Jan, 2020 4 commits
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Yuxin Wu authored
Summary: Fix https://github.com/facebookresearch/detectron2/issues/757 Pull Request resolved: https://github.com/fairinternal/detectron2/pull/376 Test Plan: ``` python -m unittest tests.test_rotated_boxes.TestRotatedBoxesLayer.test_iou_too_many_boxes_cuda ``` Reviewed By: rbgirshick Differential Revision: D19617036 Pulled By: ppwwyyxx fbshipit-source-id: 93df1ee7b3f7d939de76a1faeb6c1e10f051758c
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Yuxin Wu authored
Summary: With D19319879, evaluation will run even if the training fails. This is not a reasonable default. This reverts D19319879. The issue that D19319879 tried to solve is: when a verification failed, the resumed job would not run evaluation again and the result verification will be skipped in the resumed job (due to lack of eval metrics). It causes our integration tests to pass even though the verification has actually failed (as a result we didn't catch a accuracy regression). This issue can be addressed differently by enforcing the existence of evaluation metrics whenever `cfg.TEST.EXPECTED_RESULTS` is not empty, as done in this diff. A cleaner solution would require making more objects "checkpointable" so they know where they are after resume. Reviewed By: rbgirshick Differential Revision: D19617328 fbshipit-source-id: 105e7648ef406cf7171ae88e9ac7df983a5bc39b
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Yuxin Wu authored
Summary: Pytorch changes the behavior of copy_ to preserve memory layout, in the stack of https://github.com/pytorch/pytorch/pull/30089. Our kernel needs to adopt to such change. Reviewed By: rbgirshick Differential Revision: D19617086 fbshipit-source-id: 992a0e957aa86c48152ffdcea1e9c184b3a47be2
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Luka Sterbic authored
Summary: Original commit changeset: f45acba6d502 Reviewed By: JanEbbing Differential Revision: D19619669 fbshipit-source-id: 0cc0f01fde1ca3c500d43b1a145d8cddbc659b6c
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- 29 Jan, 2020 2 commits
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Ross Girshick authored
Summary: The current logic for finding feature normalization modules is based on fragile string matching. For models that include norm modules in, for example, an `nn.Sequential` the logic fails to detect the module (because it appears like `0.weight`, `0.bias`, ...). This diff makes the matching more robust by matching against a set of normalization module types. The downside is that this set needs to be maintained if new normalization types, that do not inherit from any of these, are added. Reviewed By: ppwwyyxx Differential Revision: D19393513 fbshipit-source-id: e81fe36df7e09ec33addbca515cefdfd86c69fb9
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Yanghan Wang authored
Summary: Previously during inference ProtobufModel.forward is numpy->numpy, which doesn't contain device information. This diff changes it to torch.Tensor->torch.Tensor thus can return tensors on the proper device. Worth mention that it's possible to return outputs with mixed devices (some on cpu and some on gpu), so `infer_device_type` is called to analyze output device types given known input device types. `_wrapped_model.device` is stored to figure out input device types. Reviewed By: ppwwyyxx Differential Revision: D19568765 fbshipit-source-id: f45acba6d502c6100a2d8d29508f01c550c1c43d
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- 28 Jan, 2020 1 commit
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Qing authored
Summary: Pull Request resolved: https://github.com/facebookresearch/detectron2/pull/759 Differential Revision: D19599357 Pulled By: ppwwyyxx fbshipit-source-id: 8608d418d872f75c0ff99dece7152a180e685571
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- 26 Jan, 2020 1 commit
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Yuxin Wu authored
Summary: Pull Request resolved: https://github.com/fairinternal/detectron2/pull/375 Differential Revision: D19573699 Pulled By: ppwwyyxx fbshipit-source-id: 64e4d8b2c1f2aee802403893fa9f3c325bb69b6a
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- 25 Jan, 2020 1 commit
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Yuxin Wu authored
Summary: Pull Request resolved: https://github.com/fairinternal/detectron2/pull/374 Differential Revision: D19569460 Pulled By: ppwwyyxx fbshipit-source-id: 3cacee01b325bec0c8e2ec7fafffe90b9618a424
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- 24 Jan, 2020 3 commits
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xmyqsh authored
Summary: Pull Request resolved: https://github.com/facebookresearch/detectron2/pull/751 Differential Revision: D19554580 Pulled By: ppwwyyxx fbshipit-source-id: 131472171a62708942e7ef48ab84c889417d03d4
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Yuxin Wu authored
Summary: Pull Request resolved: https://github.com/fairinternal/detectron2/pull/373 Differential Revision: D19553213 Pulled By: ppwwyyxx fbshipit-source-id: 285396f9344c10758048a1de3101017931b0f98f
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Yanghan Wang authored
Summary: A few changes to support exporting to GPU device. - update `to_device` to directly use exposed copy ops. - call `_assign_device_option` during `export_caffe2_detection_model`. - (optional) fuse unnecessary copy ops if possible. Now exported model will match the MODEL.DEVICE. There's no need of changing inference code, because seems Caffe2 now can automatically convert cpu input to the corresponding device, (fetch output is always on cpu as numpy). Reviewed By: ppwwyyxx Differential Revision: D19504424 fbshipit-source-id: 752a4fd275c64c1d3e08f04b7ed6c41710ba1e47
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- 23 Jan, 2020 1 commit
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Sam Pepose authored
Summary: The SGD optimizer should always use `cfg.SOLVER.BASE_LR` learning rate. Bug: If the last named param is a bias term and `cfg.SOLVER.BIAS_LR_FACTOR != 1.0`, then the lr will be set to an incorrect multiple. Reviewed By: rbgirshick Differential Revision: D19517514 fbshipit-source-id: 1eacb70753df93dcd0b731548322493807d20877
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- 21 Jan, 2020 2 commits
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Gu Wang authored
Summary: Thanks for your contribution! If you're sending a large PR (e.g., >50 lines), please open an issue first about the feature / bug, and indicate how you want to contribute. See more at https://detectron2.readthedocs.io/notes/contributing.html#pull-requests about how we handle PRs. Before submitting a PR, please run `dev/linter.sh` to lint the code. Pull Request resolved: https://github.com/facebookresearch/detectron2/pull/731 Differential Revision: D19482657 Pulled By: ppwwyyxx fbshipit-source-id: dacbc0b911568ef8428f550f9752c52aff0f2585
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Yuxin Wu authored
Summary: Pull Request resolved: https://github.com/fairinternal/detectron2/pull/372 Differential Revision: D19482654 Pulled By: ppwwyyxx fbshipit-source-id: 0772df003713991085ca5f98cfa77a56d3c1f85e
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- 17 Jan, 2020 1 commit
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Yuxin Wu authored
Summary: Pull Request resolved: https://github.com/fairinternal/detectron2/pull/371 Differential Revision: D19430095 Pulled By: ppwwyyxx fbshipit-source-id: 6577d5e711342836eb48c2ddb79d9600631e3f9b
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- 16 Jan, 2020 3 commits
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Vasil Khalidov authored
Summary: Added `isort` version check to ensure that produced formatting is compliant. Reviewed By: ppwwyyxx Differential Revision: D19421825 fbshipit-source-id: 51b8c113e09a1cc233f631f3cd4b1bdc485c4652
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Sam Pepose authored
Summary: `BoxMode`, an `Enum`, is not JSON-serializable. This diff changes it to an `IntEnum` which is serializable. Reviewed By: ppwwyyxx Differential Revision: D19403320 fbshipit-source-id: 2f2b7352eafa0d983b007f5554861a952f5ba063
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Vasil Khalidov authored
Summary: Added evaluation based on GPSm metric, which uses geometric mean of geodesic distance (GPS) and mask intersection over union (IOU) as a proximity measure. As compared to the previous GPS metric, it favors good mask estimates and penalizes situations where all pixels are estimated as foreground. Created separate files for different test types (following general detectron2 structure). This way it's more convenient to run selected tests. Reviewed By: MarcSzafraniec Differential Revision: D19375107 fbshipit-source-id: bec54a897a09b9e43f3332a2e4ada19417b9ef08
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- 15 Jan, 2020 1 commit
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Vasil Khalidov authored
Summary: Visualizer import at the top level of the general RCNN module implies importing `matplotlib` at every run (tests, train, eval etc.). Currently there are quite some warnings generated by matplotlib, which clutters the outputs. I suggest to move visualizer import to the dedicated method, since most of the time, one would not need any visualization. Reviewed By: ppwwyyxx Differential Revision: D19389988 fbshipit-source-id: e6e6a00e38d084e5d19ee02400f9741186e1bb00
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- 14 Jan, 2020 1 commit
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Yuxin Wu authored
Summary: Pull Request resolved: https://github.com/fairinternal/detectron2/pull/370 Differential Revision: D19388695 Pulled By: ppwwyyxx fbshipit-source-id: 926eebc908b533f901a9894c7462d21d2b175d14
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