diff --git a/INSTALL.md b/INSTALL.md index ffda378..ebad7e0 100644 --- a/INSTALL.md +++ b/INSTALL.md @@ -60,7 +60,7 @@ git clone https://github.com/facebookresearch/detectron $DETECTRON Install Python dependencies: ``` -pip install -r $DETECTRON/requirements.txt +pip3 install -r $DETECTRON/requirements.txt ``` Set up Python modules: @@ -72,8 +72,18 @@ cd $DETECTRON && make Check that Detectron tests pass (e.g. for [`SpatialNarrowAsOp test`](detectron/tests/test_spatial_narrow_as_op.py)): ``` -python2 $DETECTRON/detectron/tests/test_spatial_narrow_as_op.py +python3 $DETECTRON/detectron/tests/test_spatial_narrow_as_op.py ``` +If you encounter `AssertionError: Detectron ops lib not found; make sure that your Caffe2 version includes Detectron module +` + +In `$DETECTRON/detectron/utils/env.py` at line 62 + +Add `/path to torch/` to `prefixes`, something like this + +`prefixes = [_CMAKE_INSTALL_PREFIX, sys.prefix, sys.exec_prefix] + sys.path + ["/usr/local/lib/python3.6/dist-packages/torch/"] +` + ## That's All You Need for Inference diff --git a/Makefile b/Makefile index 7cd3148..95c9961 100644 --- a/Makefile +++ b/Makefile @@ -1,12 +1,12 @@ # Don't use the --user flag for setup.py develop mode with virtualenv. -DEV_USER_FLAG=$(shell python2 -c "import sys; print('' if hasattr(sys, 'real_prefix') else '--user')") +DEV_USER_FLAG=$(shell python -c "import sys; print('' if hasattr(sys, 'real_prefix') else '--user')") .PHONY: default default: dev .PHONY: install install: - python2 setup.py install + python3 setup.py install .PHONY: ops ops: @@ -14,9 +14,9 @@ ops: .PHONY: dev dev: - python2 setup.py develop $(DEV_USER_FLAG) + python3 setup.py develop $(DEV_USER_FLAG) .PHONY: clean clean: - python2 setup.py develop --uninstall $(DEV_USER_FLAG) + python3 setup.py develop --uninstall $(DEV_USER_FLAG) rm -rf build diff --git a/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-101-FPN_2x_gn.yaml b/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-101-FPN_2x_gn.yaml index cf91c21..9c8c969 100644 --- a/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-101-FPN_2x_gn.yaml +++ b/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-101-FPN_2x_gn.yaml @@ -36,7 +36,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/47592356/R-101-GN.pkl # Note: a GN pre-trained model + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/47592356/R-101-GN.pkl # Note: a GN pre-trained model DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-101-FPN_3x_gn.yaml b/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-101-FPN_3x_gn.yaml index cbfb3ce..fe463da 100644 --- a/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-101-FPN_3x_gn.yaml +++ b/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-101-FPN_3x_gn.yaml @@ -36,7 +36,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/47592356/R-101-GN.pkl # Note: a GN pre-trained model + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/47592356/R-101-GN.pkl # Note: a GN pre-trained model DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-50-FPN_2x_gn.yaml b/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-50-FPN_2x_gn.yaml index 49a5fc6..eecae45 100644 --- a/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-50-FPN_2x_gn.yaml +++ b/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-50-FPN_2x_gn.yaml @@ -36,7 +36,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/47261647/R-50-GN.pkl # Note: a GN pre-trained model + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/47261647/R-50-GN.pkl # Note: a GN pre-trained model DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-50-FPN_3x_gn.yaml b/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-50-FPN_3x_gn.yaml index b673146..94950ff 100644 --- a/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-50-FPN_3x_gn.yaml +++ b/configs/04_2018_gn_baselines/e2e_mask_rcnn_R-50-FPN_3x_gn.yaml @@ -36,7 +36,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/47261647/R-50-GN.pkl # Note: a GN pre-trained model + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/47261647/R-50-GN.pkl # Note: a GN pre-trained model DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/04_2018_gn_baselines/mask_rcnn_R-50-FPN_1x_gn.yaml b/configs/04_2018_gn_baselines/mask_rcnn_R-50-FPN_1x_gn.yaml index 367e4e7..3543bf2 100644 --- a/configs/04_2018_gn_baselines/mask_rcnn_R-50-FPN_1x_gn.yaml +++ b/configs/04_2018_gn_baselines/mask_rcnn_R-50-FPN_1x_gn.yaml @@ -36,15 +36,15 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/47261647/R-50-GN.pkl # Note: a GN pre-trained model + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/47261647/R-50-GN.pkl # Note: a GN pre-trained model DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_faster_rcnn_R-101-FPN_1x.yaml b/configs/12_2017_baselines/e2e_faster_rcnn_R-101-FPN_1x.yaml index b929860..4f17fa3 100644 --- a/configs/12_2017_baselines/e2e_faster_rcnn_R-101-FPN_1x.yaml +++ b/configs/12_2017_baselines/e2e_faster_rcnn_R-101-FPN_1x.yaml @@ -21,7 +21,7 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_faster_rcnn_R-101-FPN_2x.yaml b/configs/12_2017_baselines/e2e_faster_rcnn_R-101-FPN_2x.yaml index 1429525..42f9f5d 100644 --- a/configs/12_2017_baselines/e2e_faster_rcnn_R-101-FPN_2x.yaml +++ b/configs/12_2017_baselines/e2e_faster_rcnn_R-101-FPN_2x.yaml @@ -21,7 +21,7 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_faster_rcnn_R-50-C4_1x.yaml b/configs/12_2017_baselines/e2e_faster_rcnn_R-50-C4_1x.yaml index db2a5f8..9b5c122 100644 --- a/configs/12_2017_baselines/e2e_faster_rcnn_R-50-C4_1x.yaml +++ b/configs/12_2017_baselines/e2e_faster_rcnn_R-50-C4_1x.yaml @@ -18,7 +18,7 @@ FAST_RCNN: ROI_BOX_HEAD: ResNet.add_ResNet_roi_conv5_head ROI_XFORM_METHOD: RoIAlign TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_faster_rcnn_R-50-C4_2x.yaml b/configs/12_2017_baselines/e2e_faster_rcnn_R-50-C4_2x.yaml index 5b9e9e8..44686a9 100644 --- a/configs/12_2017_baselines/e2e_faster_rcnn_R-50-C4_2x.yaml +++ b/configs/12_2017_baselines/e2e_faster_rcnn_R-50-C4_2x.yaml @@ -18,7 +18,7 @@ FAST_RCNN: ROI_BOX_HEAD: ResNet.add_ResNet_roi_conv5_head ROI_XFORM_METHOD: RoIAlign TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_faster_rcnn_R-50-FPN_1x.yaml b/configs/12_2017_baselines/e2e_faster_rcnn_R-50-FPN_1x.yaml index c8ecfe7..5f9bb4a 100644 --- a/configs/12_2017_baselines/e2e_faster_rcnn_R-50-FPN_1x.yaml +++ b/configs/12_2017_baselines/e2e_faster_rcnn_R-50-FPN_1x.yaml @@ -21,7 +21,7 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_faster_rcnn_R-50-FPN_2x.yaml b/configs/12_2017_baselines/e2e_faster_rcnn_R-50-FPN_2x.yaml index 32533ab..457a3ec 100644 --- a/configs/12_2017_baselines/e2e_faster_rcnn_R-50-FPN_2x.yaml +++ b/configs/12_2017_baselines/e2e_faster_rcnn_R-50-FPN_2x.yaml @@ -21,7 +21,7 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_faster_rcnn_X-101-32x8d-FPN_1x.yaml b/configs/12_2017_baselines/e2e_faster_rcnn_X-101-32x8d-FPN_1x.yaml index b16d2cc..e87e4df 100644 --- a/configs/12_2017_baselines/e2e_faster_rcnn_X-101-32x8d-FPN_1x.yaml +++ b/configs/12_2017_baselines/e2e_faster_rcnn_X-101-32x8d-FPN_1x.yaml @@ -27,7 +27,7 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_faster_rcnn_X-101-32x8d-FPN_2x.yaml b/configs/12_2017_baselines/e2e_faster_rcnn_X-101-32x8d-FPN_2x.yaml index 0d8c9e0..6c8d4e0 100644 --- a/configs/12_2017_baselines/e2e_faster_rcnn_X-101-32x8d-FPN_2x.yaml +++ b/configs/12_2017_baselines/e2e_faster_rcnn_X-101-32x8d-FPN_2x.yaml @@ -27,7 +27,7 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_faster_rcnn_X-101-64x4d-FPN_1x.yaml b/configs/12_2017_baselines/e2e_faster_rcnn_X-101-64x4d-FPN_1x.yaml index 986ccae..ec91bfd 100644 --- a/configs/12_2017_baselines/e2e_faster_rcnn_X-101-64x4d-FPN_1x.yaml +++ b/configs/12_2017_baselines/e2e_faster_rcnn_X-101-64x4d-FPN_1x.yaml @@ -27,7 +27,7 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_faster_rcnn_X-101-64x4d-FPN_2x.yaml b/configs/12_2017_baselines/e2e_faster_rcnn_X-101-64x4d-FPN_2x.yaml index 5334971..ea875df 100644 --- a/configs/12_2017_baselines/e2e_faster_rcnn_X-101-64x4d-FPN_2x.yaml +++ b/configs/12_2017_baselines/e2e_faster_rcnn_X-101-64x4d-FPN_2x.yaml @@ -28,7 +28,7 @@ FAST_RCNN: ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: # md5sum of weights pkl file: aa14062280226e48f569ef1c7212e7c7 - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_keypoint_rcnn_R-101-FPN_1x.yaml b/configs/12_2017_baselines/e2e_keypoint_rcnn_R-101-FPN_1x.yaml index aa88066..db16911 100644 --- a/configs/12_2017_baselines/e2e_keypoint_rcnn_R-101-FPN_1x.yaml +++ b/configs/12_2017_baselines/e2e_keypoint_rcnn_R-101-FPN_1x.yaml @@ -35,7 +35,7 @@ KRCNN: ROI_XFORM_SAMPLING_RATIO: 2 KEYPOINT_CONFIDENCE: bbox TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_keypoint_rcnn_R-101-FPN_s1x.yaml b/configs/12_2017_baselines/e2e_keypoint_rcnn_R-101-FPN_s1x.yaml index 8df8dd1..77d20ff 100644 --- a/configs/12_2017_baselines/e2e_keypoint_rcnn_R-101-FPN_s1x.yaml +++ b/configs/12_2017_baselines/e2e_keypoint_rcnn_R-101-FPN_s1x.yaml @@ -35,7 +35,7 @@ KRCNN: ROI_XFORM_SAMPLING_RATIO: 2 KEYPOINT_CONFIDENCE: bbox TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_keypoint_rcnn_R-50-FPN_1x.yaml b/configs/12_2017_baselines/e2e_keypoint_rcnn_R-50-FPN_1x.yaml index cf81a1f..9bb9416 100644 --- a/configs/12_2017_baselines/e2e_keypoint_rcnn_R-50-FPN_1x.yaml +++ b/configs/12_2017_baselines/e2e_keypoint_rcnn_R-50-FPN_1x.yaml @@ -35,7 +35,7 @@ KRCNN: ROI_XFORM_SAMPLING_RATIO: 2 KEYPOINT_CONFIDENCE: bbox TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_keypoint_rcnn_R-50-FPN_s1x.yaml b/configs/12_2017_baselines/e2e_keypoint_rcnn_R-50-FPN_s1x.yaml index 291796f..e93324f 100644 --- a/configs/12_2017_baselines/e2e_keypoint_rcnn_R-50-FPN_s1x.yaml +++ b/configs/12_2017_baselines/e2e_keypoint_rcnn_R-50-FPN_s1x.yaml @@ -35,7 +35,7 @@ KRCNN: ROI_XFORM_SAMPLING_RATIO: 2 KEYPOINT_CONFIDENCE: bbox TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-32x8d-FPN_1x.yaml b/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-32x8d-FPN_1x.yaml index 3d399c5..8deaf6a 100644 --- a/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-32x8d-FPN_1x.yaml +++ b/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-32x8d-FPN_1x.yaml @@ -40,7 +40,7 @@ KRCNN: ROI_XFORM_SAMPLING_RATIO: 2 KEYPOINT_CONFIDENCE: bbox TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-32x8d-FPN_s1x.yaml b/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-32x8d-FPN_s1x.yaml index ac912e9..0dd2a9c 100644 --- a/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-32x8d-FPN_s1x.yaml +++ b/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-32x8d-FPN_s1x.yaml @@ -40,7 +40,7 @@ KRCNN: ROI_XFORM_SAMPLING_RATIO: 2 KEYPOINT_CONFIDENCE: bbox TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-64x4d-FPN_1x.yaml b/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-64x4d-FPN_1x.yaml index 71fcc99..b710030 100644 --- a/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-64x4d-FPN_1x.yaml +++ b/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-64x4d-FPN_1x.yaml @@ -41,7 +41,7 @@ KRCNN: KEYPOINT_CONFIDENCE: bbox TRAIN: # md5sum of weights pkl file: aa14062280226e48f569ef1c7212e7c7 - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-64x4d-FPN_s1x.yaml b/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-64x4d-FPN_s1x.yaml index 10408df..7030db7 100644 --- a/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-64x4d-FPN_s1x.yaml +++ b/configs/12_2017_baselines/e2e_keypoint_rcnn_X-101-64x4d-FPN_s1x.yaml @@ -41,7 +41,7 @@ KRCNN: KEYPOINT_CONFIDENCE: bbox TRAIN: # md5sum of weights pkl file: aa14062280226e48f569ef1c7212e7c7 - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_mask_rcnn_R-101-FPN_1x.yaml b/configs/12_2017_baselines/e2e_mask_rcnn_R-101-FPN_1x.yaml index 7f40f07..43a0924 100644 --- a/configs/12_2017_baselines/e2e_mask_rcnn_R-101-FPN_1x.yaml +++ b/configs/12_2017_baselines/e2e_mask_rcnn_R-101-FPN_1x.yaml @@ -30,7 +30,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_mask_rcnn_R-101-FPN_2x.yaml b/configs/12_2017_baselines/e2e_mask_rcnn_R-101-FPN_2x.yaml index 4b77231..002d3ac 100644 --- a/configs/12_2017_baselines/e2e_mask_rcnn_R-101-FPN_2x.yaml +++ b/configs/12_2017_baselines/e2e_mask_rcnn_R-101-FPN_2x.yaml @@ -30,7 +30,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_mask_rcnn_R-50-C4_1x.yaml b/configs/12_2017_baselines/e2e_mask_rcnn_R-50-C4_1x.yaml index 355baa1..2bee8bd 100644 --- a/configs/12_2017_baselines/e2e_mask_rcnn_R-50-C4_1x.yaml +++ b/configs/12_2017_baselines/e2e_mask_rcnn_R-50-C4_1x.yaml @@ -26,7 +26,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default: GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_mask_rcnn_R-50-C4_2x.yaml b/configs/12_2017_baselines/e2e_mask_rcnn_R-50-C4_2x.yaml index 201296b..7dacafe 100644 --- a/configs/12_2017_baselines/e2e_mask_rcnn_R-50-C4_2x.yaml +++ b/configs/12_2017_baselines/e2e_mask_rcnn_R-50-C4_2x.yaml @@ -26,7 +26,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default: GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_mask_rcnn_R-50-FPN_1x.yaml b/configs/12_2017_baselines/e2e_mask_rcnn_R-50-FPN_1x.yaml index aa12f29..9798483 100644 --- a/configs/12_2017_baselines/e2e_mask_rcnn_R-50-FPN_1x.yaml +++ b/configs/12_2017_baselines/e2e_mask_rcnn_R-50-FPN_1x.yaml @@ -30,7 +30,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_mask_rcnn_R-50-FPN_2x.yaml b/configs/12_2017_baselines/e2e_mask_rcnn_R-50-FPN_2x.yaml index d504802..0568c30 100644 --- a/configs/12_2017_baselines/e2e_mask_rcnn_R-50-FPN_2x.yaml +++ b/configs/12_2017_baselines/e2e_mask_rcnn_R-50-FPN_2x.yaml @@ -30,7 +30,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_mask_rcnn_X-101-32x8d-FPN_1x.yaml b/configs/12_2017_baselines/e2e_mask_rcnn_X-101-32x8d-FPN_1x.yaml index ceee4af..4276e9e 100644 --- a/configs/12_2017_baselines/e2e_mask_rcnn_X-101-32x8d-FPN_1x.yaml +++ b/configs/12_2017_baselines/e2e_mask_rcnn_X-101-32x8d-FPN_1x.yaml @@ -36,7 +36,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_mask_rcnn_X-101-32x8d-FPN_2x.yaml b/configs/12_2017_baselines/e2e_mask_rcnn_X-101-32x8d-FPN_2x.yaml index 7ed24f6..a55962c 100644 --- a/configs/12_2017_baselines/e2e_mask_rcnn_X-101-32x8d-FPN_2x.yaml +++ b/configs/12_2017_baselines/e2e_mask_rcnn_X-101-32x8d-FPN_2x.yaml @@ -36,7 +36,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_mask_rcnn_X-101-64x4d-FPN_1x.yaml b/configs/12_2017_baselines/e2e_mask_rcnn_X-101-64x4d-FPN_1x.yaml index 7b7d24d..fcfcfdd 100644 --- a/configs/12_2017_baselines/e2e_mask_rcnn_X-101-64x4d-FPN_1x.yaml +++ b/configs/12_2017_baselines/e2e_mask_rcnn_X-101-64x4d-FPN_1x.yaml @@ -37,7 +37,7 @@ MRCNN: CONV_INIT: MSRAFill # default GaussianFill TRAIN: # md5sum of weights pkl file: aa14062280226e48f569ef1c7212e7c7 - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_mask_rcnn_X-101-64x4d-FPN_2x.yaml b/configs/12_2017_baselines/e2e_mask_rcnn_X-101-64x4d-FPN_2x.yaml index 18ea871..277ede9 100644 --- a/configs/12_2017_baselines/e2e_mask_rcnn_X-101-64x4d-FPN_2x.yaml +++ b/configs/12_2017_baselines/e2e_mask_rcnn_X-101-64x4d-FPN_2x.yaml @@ -37,7 +37,7 @@ MRCNN: CONV_INIT: MSRAFill # default GaussianFill TRAIN: # md5sum of weights pkl file: aa14062280226e48f569ef1c7212e7c7 - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/e2e_mask_rcnn_X-152-32x8d-FPN-IN5k_1.44x.yaml b/configs/12_2017_baselines/e2e_mask_rcnn_X-152-32x8d-FPN-IN5k_1.44x.yaml index 8b17822..d540a29 100644 --- a/configs/12_2017_baselines/e2e_mask_rcnn_X-152-32x8d-FPN-IN5k_1.44x.yaml +++ b/configs/12_2017_baselines/e2e_mask_rcnn_X-152-32x8d-FPN-IN5k_1.44x.yaml @@ -36,7 +36,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/25093814/X-152-32x8d-IN5k.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/25093814/X-152-32x8d-IN5k.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (640, 672, 704, 736, 768, 800) # Scale jitter MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/fast_rcnn_R-101-FPN_1x.yaml b/configs/12_2017_baselines/fast_rcnn_R-101-FPN_1x.yaml index 7cda826..c116312 100644 --- a/configs/12_2017_baselines/fast_rcnn_R-101-FPN_1x.yaml +++ b/configs/12_2017_baselines/fast_rcnn_R-101-FPN_1x.yaml @@ -20,15 +20,15 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/fast_rcnn_R-101-FPN_2x.yaml b/configs/12_2017_baselines/fast_rcnn_R-101-FPN_2x.yaml index 18ff3e1..f7c5b3a 100644 --- a/configs/12_2017_baselines/fast_rcnn_R-101-FPN_2x.yaml +++ b/configs/12_2017_baselines/fast_rcnn_R-101-FPN_2x.yaml @@ -20,15 +20,15 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/fast_rcnn_R-50-C4_1x.yaml b/configs/12_2017_baselines/fast_rcnn_R-50-C4_1x.yaml index 5779a0d..a2c3287 100644 --- a/configs/12_2017_baselines/fast_rcnn_R-50-C4_1x.yaml +++ b/configs/12_2017_baselines/fast_rcnn_R-50-C4_1x.yaml @@ -17,16 +17,16 @@ FAST_RCNN: ROI_BOX_HEAD: ResNet.add_ResNet_roi_conv5_head ROI_XFORM_METHOD: RoIAlign TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_train/rpn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_valminusminival/rpn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_train/rpn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_valminusminival/rpn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 IMS_PER_BATCH: 1 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_minival/rpn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_minival/rpn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/fast_rcnn_R-50-C4_2x.yaml b/configs/12_2017_baselines/fast_rcnn_R-50-C4_2x.yaml index 9db11a3..71313fa 100644 --- a/configs/12_2017_baselines/fast_rcnn_R-50-C4_2x.yaml +++ b/configs/12_2017_baselines/fast_rcnn_R-50-C4_2x.yaml @@ -17,16 +17,16 @@ FAST_RCNN: ROI_BOX_HEAD: ResNet.add_ResNet_roi_conv5_head ROI_XFORM_METHOD: RoIAlign TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_train/rpn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_valminusminival/rpn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_train/rpn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_valminusminival/rpn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 IMS_PER_BATCH: 1 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_minival/rpn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_minival/rpn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/fast_rcnn_R-50-FPN_1x.yaml b/configs/12_2017_baselines/fast_rcnn_R-50-FPN_1x.yaml index 5d15605..baa053c 100644 --- a/configs/12_2017_baselines/fast_rcnn_R-50-FPN_1x.yaml +++ b/configs/12_2017_baselines/fast_rcnn_R-50-FPN_1x.yaml @@ -20,15 +20,15 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/fast_rcnn_R-50-FPN_2x.yaml b/configs/12_2017_baselines/fast_rcnn_R-50-FPN_2x.yaml index b27c4a2..aee5481 100644 --- a/configs/12_2017_baselines/fast_rcnn_R-50-FPN_2x.yaml +++ b/configs/12_2017_baselines/fast_rcnn_R-50-FPN_2x.yaml @@ -20,15 +20,15 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/fast_rcnn_X-101-32x8d-FPN_1x.yaml b/configs/12_2017_baselines/fast_rcnn_X-101-32x8d-FPN_1x.yaml index 1bc5ddf..b65d35f 100644 --- a/configs/12_2017_baselines/fast_rcnn_X-101-32x8d-FPN_1x.yaml +++ b/configs/12_2017_baselines/fast_rcnn_X-101-32x8d-FPN_1x.yaml @@ -26,16 +26,16 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 IMS_PER_BATCH: 1 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/fast_rcnn_X-101-32x8d-FPN_2x.yaml b/configs/12_2017_baselines/fast_rcnn_X-101-32x8d-FPN_2x.yaml index 73e3089..2a129b5 100644 --- a/configs/12_2017_baselines/fast_rcnn_X-101-32x8d-FPN_2x.yaml +++ b/configs/12_2017_baselines/fast_rcnn_X-101-32x8d-FPN_2x.yaml @@ -26,16 +26,16 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 IMS_PER_BATCH: 1 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/fast_rcnn_X-101-64x4d-FPN_1x.yaml b/configs/12_2017_baselines/fast_rcnn_X-101-64x4d-FPN_1x.yaml index da290e5..e28806d 100644 --- a/configs/12_2017_baselines/fast_rcnn_X-101-64x4d-FPN_1x.yaml +++ b/configs/12_2017_baselines/fast_rcnn_X-101-64x4d-FPN_1x.yaml @@ -26,16 +26,16 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 IMS_PER_BATCH: 1 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/fast_rcnn_X-101-64x4d-FPN_2x.yaml b/configs/12_2017_baselines/fast_rcnn_X-101-64x4d-FPN_2x.yaml index 69c3a3c..af79f2b 100644 --- a/configs/12_2017_baselines/fast_rcnn_X-101-64x4d-FPN_2x.yaml +++ b/configs/12_2017_baselines/fast_rcnn_X-101-64x4d-FPN_2x.yaml @@ -26,16 +26,16 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 IMS_PER_BATCH: 1 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/keypoint_rcnn_R-101-FPN_1x.yaml b/configs/12_2017_baselines/keypoint_rcnn_R-101-FPN_1x.yaml index d08a54d..f37de73 100644 --- a/configs/12_2017_baselines/keypoint_rcnn_R-101-FPN_1x.yaml +++ b/configs/12_2017_baselines/keypoint_rcnn_R-101-FPN_1x.yaml @@ -34,15 +34,15 @@ KRCNN: ROI_XFORM_SAMPLING_RATIO: 2 KEYPOINT_CONFIDENCE: bbox TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35999521/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml.08_20_33.1OkqMmqP/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35999521/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml.08_20_33.1OkqMmqP/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35999521/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml.08_20_33.1OkqMmqP/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35999521/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml.08_20_33.1OkqMmqP/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('keypoints_coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35999521/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml.08_20_33.1OkqMmqP/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35999521/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml.08_20_33.1OkqMmqP/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/keypoint_rcnn_R-101-FPN_s1x.yaml b/configs/12_2017_baselines/keypoint_rcnn_R-101-FPN_s1x.yaml index e0bc8f3..a13e45a 100644 --- a/configs/12_2017_baselines/keypoint_rcnn_R-101-FPN_s1x.yaml +++ b/configs/12_2017_baselines/keypoint_rcnn_R-101-FPN_s1x.yaml @@ -34,15 +34,15 @@ KRCNN: ROI_XFORM_SAMPLING_RATIO: 2 KEYPOINT_CONFIDENCE: bbox TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35999521/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml.08_20_33.1OkqMmqP/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35999521/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml.08_20_33.1OkqMmqP/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35999521/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml.08_20_33.1OkqMmqP/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35999521/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml.08_20_33.1OkqMmqP/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('keypoints_coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35999521/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml.08_20_33.1OkqMmqP/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35999521/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml.08_20_33.1OkqMmqP/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/keypoint_rcnn_R-50-FPN_1x.yaml b/configs/12_2017_baselines/keypoint_rcnn_R-50-FPN_1x.yaml index 2267e95..fe3d222 100644 --- a/configs/12_2017_baselines/keypoint_rcnn_R-50-FPN_1x.yaml +++ b/configs/12_2017_baselines/keypoint_rcnn_R-50-FPN_1x.yaml @@ -34,15 +34,15 @@ KRCNN: ROI_XFORM_SAMPLING_RATIO: 2 KEYPOINT_CONFIDENCE: bbox TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('keypoints_coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/keypoint_rcnn_R-50-FPN_s1x.yaml b/configs/12_2017_baselines/keypoint_rcnn_R-50-FPN_s1x.yaml index 3aff807..542d082 100644 --- a/configs/12_2017_baselines/keypoint_rcnn_R-50-FPN_s1x.yaml +++ b/configs/12_2017_baselines/keypoint_rcnn_R-50-FPN_s1x.yaml @@ -34,15 +34,15 @@ KRCNN: ROI_XFORM_SAMPLING_RATIO: 2 KEYPOINT_CONFIDENCE: bbox TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('keypoints_coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/keypoint_rcnn_X-101-32x8d-FPN_1x.yaml b/configs/12_2017_baselines/keypoint_rcnn_X-101-32x8d-FPN_1x.yaml index 976c653..fd4ca5d 100644 --- a/configs/12_2017_baselines/keypoint_rcnn_X-101-32x8d-FPN_1x.yaml +++ b/configs/12_2017_baselines/keypoint_rcnn_X-101-32x8d-FPN_1x.yaml @@ -39,15 +39,15 @@ KRCNN: ROI_XFORM_SAMPLING_RATIO: 2 KEYPOINT_CONFIDENCE: bbox TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/36760438/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml.06_04_23.M2oJlDPW/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/36760438/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml.06_04_23.M2oJlDPW/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/36760438/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml.06_04_23.M2oJlDPW/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/36760438/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml.06_04_23.M2oJlDPW/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('keypoints_coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/36760438/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml.06_04_23.M2oJlDPW/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/36760438/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml.06_04_23.M2oJlDPW/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/keypoint_rcnn_X-101-32x8d-FPN_s1x.yaml b/configs/12_2017_baselines/keypoint_rcnn_X-101-32x8d-FPN_s1x.yaml index d24ea1b..7841f0b 100644 --- a/configs/12_2017_baselines/keypoint_rcnn_X-101-32x8d-FPN_s1x.yaml +++ b/configs/12_2017_baselines/keypoint_rcnn_X-101-32x8d-FPN_s1x.yaml @@ -39,15 +39,15 @@ KRCNN: ROI_XFORM_SAMPLING_RATIO: 2 KEYPOINT_CONFIDENCE: bbox TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/36760438/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml.06_04_23.M2oJlDPW/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/36760438/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml.06_04_23.M2oJlDPW/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/36760438/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml.06_04_23.M2oJlDPW/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/36760438/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml.06_04_23.M2oJlDPW/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('keypoints_coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/36760438/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml.06_04_23.M2oJlDPW/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/36760438/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml.06_04_23.M2oJlDPW/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/keypoint_rcnn_X-101-64x4d-FPN_1x.yaml b/configs/12_2017_baselines/keypoint_rcnn_X-101-64x4d-FPN_1x.yaml index 8f1f837..137248a 100644 --- a/configs/12_2017_baselines/keypoint_rcnn_X-101-64x4d-FPN_1x.yaml +++ b/configs/12_2017_baselines/keypoint_rcnn_X-101-64x4d-FPN_1x.yaml @@ -40,15 +40,15 @@ KRCNN: KEYPOINT_CONFIDENCE: bbox TRAIN: # md5sum of weights pkl file: aa14062280226e48f569ef1c7212e7c7 - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35999553/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml.08_21_33.ghFzzArr/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35999553/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml.08_21_33.ghFzzArr/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35999553/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml.08_21_33.ghFzzArr/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35999553/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml.08_21_33.ghFzzArr/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('keypoints_coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35999553/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml.08_21_33.ghFzzArr/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35999553/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml.08_21_33.ghFzzArr/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/keypoint_rcnn_X-101-64x4d-FPN_s1x.yaml b/configs/12_2017_baselines/keypoint_rcnn_X-101-64x4d-FPN_s1x.yaml index 5e51107..5d39633 100644 --- a/configs/12_2017_baselines/keypoint_rcnn_X-101-64x4d-FPN_s1x.yaml +++ b/configs/12_2017_baselines/keypoint_rcnn_X-101-64x4d-FPN_s1x.yaml @@ -40,15 +40,15 @@ KRCNN: KEYPOINT_CONFIDENCE: bbox TRAIN: # md5sum of weights pkl file: aa14062280226e48f569ef1c7212e7c7 - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35999553/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml.08_21_33.ghFzzArr/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35999553/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml.08_21_33.ghFzzArr/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35999553/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml.08_21_33.ghFzzArr/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35999553/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml.08_21_33.ghFzzArr/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('keypoints_coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35999553/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml.08_21_33.ghFzzArr/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35999553/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml.08_21_33.ghFzzArr/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/mask_rcnn_R-101-FPN_1x.yaml b/configs/12_2017_baselines/mask_rcnn_R-101-FPN_1x.yaml index 578ec98..2b69697 100644 --- a/configs/12_2017_baselines/mask_rcnn_R-101-FPN_1x.yaml +++ b/configs/12_2017_baselines/mask_rcnn_R-101-FPN_1x.yaml @@ -29,15 +29,15 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/mask_rcnn_R-101-FPN_2x.yaml b/configs/12_2017_baselines/mask_rcnn_R-101-FPN_2x.yaml index 06809cc..8561fff 100644 --- a/configs/12_2017_baselines/mask_rcnn_R-101-FPN_2x.yaml +++ b/configs/12_2017_baselines/mask_rcnn_R-101-FPN_2x.yaml @@ -29,15 +29,15 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998887/12_2017_baselines/rpn_R-101-FPN_1x.yaml.08_07_07.vzhHEs0V/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/mask_rcnn_R-50-C4_1x.yaml b/configs/12_2017_baselines/mask_rcnn_R-50-C4_1x.yaml index 335b122..b29b444 100644 --- a/configs/12_2017_baselines/mask_rcnn_R-50-C4_1x.yaml +++ b/configs/12_2017_baselines/mask_rcnn_R-50-C4_1x.yaml @@ -25,16 +25,16 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default: GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_train/rpn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_valminusminival/rpn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_train/rpn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_valminusminival/rpn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 IMS_PER_BATCH: 1 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_minival/rpn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_minival/rpn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/mask_rcnn_R-50-C4_2x.yaml b/configs/12_2017_baselines/mask_rcnn_R-50-C4_2x.yaml index 7d86f78..06d07b6 100644 --- a/configs/12_2017_baselines/mask_rcnn_R-50-C4_2x.yaml +++ b/configs/12_2017_baselines/mask_rcnn_R-50-C4_2x.yaml @@ -25,16 +25,16 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default: GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_train/rpn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_valminusminival/rpn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_train/rpn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_valminusminival/rpn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 IMS_PER_BATCH: 1 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_minival/rpn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998355/12_2017_baselines/rpn_R-50-C4_1x.yaml.08_00_43.njH5oD9L/output/test/coco_2014_minival/rpn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/mask_rcnn_R-50-FPN_1x.yaml b/configs/12_2017_baselines/mask_rcnn_R-50-FPN_1x.yaml index ed3ae0f..14c7ae9 100644 --- a/configs/12_2017_baselines/mask_rcnn_R-50-FPN_1x.yaml +++ b/configs/12_2017_baselines/mask_rcnn_R-50-FPN_1x.yaml @@ -29,15 +29,15 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/mask_rcnn_R-50-FPN_2x.yaml b/configs/12_2017_baselines/mask_rcnn_R-50-FPN_2x.yaml index 8fc2a20..4778c03 100644 --- a/configs/12_2017_baselines/mask_rcnn_R-50-FPN_2x.yaml +++ b/configs/12_2017_baselines/mask_rcnn_R-50-FPN_2x.yaml @@ -29,15 +29,15 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998814/12_2017_baselines/rpn_R-50-FPN_1x.yaml.08_06_03.Axg0r179/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/mask_rcnn_X-101-32x8d-FPN_1x.yaml b/configs/12_2017_baselines/mask_rcnn_X-101-32x8d-FPN_1x.yaml index 7e12814..2d23626 100644 --- a/configs/12_2017_baselines/mask_rcnn_X-101-32x8d-FPN_1x.yaml +++ b/configs/12_2017_baselines/mask_rcnn_X-101-32x8d-FPN_1x.yaml @@ -35,16 +35,16 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 IMS_PER_BATCH: 1 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/mask_rcnn_X-101-32x8d-FPN_2x.yaml b/configs/12_2017_baselines/mask_rcnn_X-101-32x8d-FPN_2x.yaml index 32552de..0a6532e 100644 --- a/configs/12_2017_baselines/mask_rcnn_X-101-32x8d-FPN_2x.yaml +++ b/configs/12_2017_baselines/mask_rcnn_X-101-32x8d-FPN_2x.yaml @@ -35,16 +35,16 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 IMS_PER_BATCH: 1 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/36760102/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml.06_00_16.RWeBAniO/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/mask_rcnn_X-101-64x4d-FPN_1x.yaml b/configs/12_2017_baselines/mask_rcnn_X-101-64x4d-FPN_1x.yaml index 1369d6d..2441d5f 100644 --- a/configs/12_2017_baselines/mask_rcnn_X-101-64x4d-FPN_1x.yaml +++ b/configs/12_2017_baselines/mask_rcnn_X-101-64x4d-FPN_1x.yaml @@ -36,16 +36,16 @@ MRCNN: CONV_INIT: MSRAFill # default GaussianFill TRAIN: # md5sum of weights pkl file: aa14062280226e48f569ef1c7212e7c7 - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 IMS_PER_BATCH: 1 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/mask_rcnn_X-101-64x4d-FPN_2x.yaml b/configs/12_2017_baselines/mask_rcnn_X-101-64x4d-FPN_2x.yaml index 343269b..87e9e2d 100644 --- a/configs/12_2017_baselines/mask_rcnn_X-101-64x4d-FPN_2x.yaml +++ b/configs/12_2017_baselines/mask_rcnn_X-101-64x4d-FPN_2x.yaml @@ -36,16 +36,16 @@ MRCNN: CONV_INIT: MSRAFill # default GaussianFill TRAIN: # md5sum of weights pkl file: aa14062280226e48f569ef1c7212e7c7 - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (800,) MAX_SIZE: 1333 IMS_PER_BATCH: 1 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998956/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml.08_08_41.Seh0psKz/output/test/coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/retinanet_R-101-FPN_1x.yaml b/configs/12_2017_baselines/retinanet_R-101-FPN_1x.yaml index 79b9761..c875328 100644 --- a/configs/12_2017_baselines/retinanet_R-101-FPN_1x.yaml +++ b/configs/12_2017_baselines/retinanet_R-101-FPN_1x.yaml @@ -26,7 +26,7 @@ RETINANET: LOSS_GAMMA: 2.0 LOSS_ALPHA: 0.25 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/retinanet_R-101-FPN_2x.yaml b/configs/12_2017_baselines/retinanet_R-101-FPN_2x.yaml index 7bdd0e0..9a3f91a 100644 --- a/configs/12_2017_baselines/retinanet_R-101-FPN_2x.yaml +++ b/configs/12_2017_baselines/retinanet_R-101-FPN_2x.yaml @@ -26,7 +26,7 @@ RETINANET: LOSS_GAMMA: 2.0 LOSS_ALPHA: 0.25 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/retinanet_R-50-FPN_1x.yaml b/configs/12_2017_baselines/retinanet_R-50-FPN_1x.yaml index b817b9e..35271fa 100644 --- a/configs/12_2017_baselines/retinanet_R-50-FPN_1x.yaml +++ b/configs/12_2017_baselines/retinanet_R-50-FPN_1x.yaml @@ -26,7 +26,7 @@ RETINANET: LOSS_GAMMA: 2.0 LOSS_ALPHA: 0.25 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/retinanet_R-50-FPN_2x.yaml b/configs/12_2017_baselines/retinanet_R-50-FPN_2x.yaml index 39c822e..21acf07 100644 --- a/configs/12_2017_baselines/retinanet_R-50-FPN_2x.yaml +++ b/configs/12_2017_baselines/retinanet_R-50-FPN_2x.yaml @@ -26,7 +26,7 @@ RETINANET: LOSS_GAMMA: 2.0 LOSS_ALPHA: 0.25 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/retinanet_X-101-32x8d-FPN_1x.yaml b/configs/12_2017_baselines/retinanet_X-101-32x8d-FPN_1x.yaml index 3bc6c74..d068481 100644 --- a/configs/12_2017_baselines/retinanet_X-101-32x8d-FPN_1x.yaml +++ b/configs/12_2017_baselines/retinanet_X-101-32x8d-FPN_1x.yaml @@ -31,7 +31,7 @@ RETINANET: LOSS_GAMMA: 2.0 LOSS_ALPHA: 0.25 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/retinanet_X-101-32x8d-FPN_2x.yaml b/configs/12_2017_baselines/retinanet_X-101-32x8d-FPN_2x.yaml index a484e29..da71fb6 100644 --- a/configs/12_2017_baselines/retinanet_X-101-32x8d-FPN_2x.yaml +++ b/configs/12_2017_baselines/retinanet_X-101-32x8d-FPN_2x.yaml @@ -31,7 +31,7 @@ RETINANET: LOSS_GAMMA: 2.0 LOSS_ALPHA: 0.25 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/retinanet_X-101-64x4d-FPN_1x.yaml b/configs/12_2017_baselines/retinanet_X-101-64x4d-FPN_1x.yaml index dc2a8ac..7ac1175 100644 --- a/configs/12_2017_baselines/retinanet_X-101-64x4d-FPN_1x.yaml +++ b/configs/12_2017_baselines/retinanet_X-101-64x4d-FPN_1x.yaml @@ -31,7 +31,7 @@ RETINANET: LOSS_GAMMA: 2.0 LOSS_ALPHA: 0.25 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/retinanet_X-101-64x4d-FPN_2x.yaml b/configs/12_2017_baselines/retinanet_X-101-64x4d-FPN_2x.yaml index acab8ea..0c2d474 100644 --- a/configs/12_2017_baselines/retinanet_X-101-64x4d-FPN_2x.yaml +++ b/configs/12_2017_baselines/retinanet_X-101-64x4d-FPN_2x.yaml @@ -31,7 +31,7 @@ RETINANET: LOSS_GAMMA: 2.0 LOSS_ALPHA: 0.25 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/rpn_R-101-FPN_1x.yaml b/configs/12_2017_baselines/rpn_R-101-FPN_1x.yaml index 15d502e..d85c06b 100644 --- a/configs/12_2017_baselines/rpn_R-101-FPN_1x.yaml +++ b/configs/12_2017_baselines/rpn_R-101-FPN_1x.yaml @@ -19,7 +19,7 @@ FPN: RPN_ANCHOR_START_SIZE: 32 RPN_ASPECT_RATIOS: (0.5, 1, 2) TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/rpn_R-50-C4_1x.yaml b/configs/12_2017_baselines/rpn_R-50-C4_1x.yaml index 8e71605..ca1d474 100644 --- a/configs/12_2017_baselines/rpn_R-50-C4_1x.yaml +++ b/configs/12_2017_baselines/rpn_R-50-C4_1x.yaml @@ -14,7 +14,7 @@ SOLVER: RPN: SIZES: (32, 64, 128, 256, 512) TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/rpn_R-50-FPN_1x.yaml b/configs/12_2017_baselines/rpn_R-50-FPN_1x.yaml index 414720e..90990fe 100644 --- a/configs/12_2017_baselines/rpn_R-50-FPN_1x.yaml +++ b/configs/12_2017_baselines/rpn_R-50-FPN_1x.yaml @@ -19,7 +19,7 @@ FPN: RPN_ANCHOR_START_SIZE: 32 RPN_ASPECT_RATIOS: (0.5, 1, 2) TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml b/configs/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml index 6a98fec..98b7846 100644 --- a/configs/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml +++ b/configs/12_2017_baselines/rpn_X-101-32x8d-FPN_1x.yaml @@ -24,7 +24,7 @@ RESNETS: NUM_GROUPS: 32 WIDTH_PER_GROUP: 8 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml b/configs/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml index 2818479..cf92ba6 100644 --- a/configs/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml +++ b/configs/12_2017_baselines/rpn_X-101-64x4d-FPN_1x.yaml @@ -24,7 +24,7 @@ RESNETS: NUM_GROUPS: 64 WIDTH_PER_GROUP: 4 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml b/configs/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml index 69df25c..a1e8f4b 100644 --- a/configs/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml +++ b/configs/12_2017_baselines/rpn_person_only_R-101-FPN_1x.yaml @@ -19,7 +19,7 @@ FPN: RPN_ANCHOR_START_SIZE: 32 RPN_ASPECT_RATIOS: (0.5, 1, 2) TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-101.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-101.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml b/configs/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml index fbcf6c7..395a91d 100644 --- a/configs/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml +++ b/configs/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml @@ -19,7 +19,7 @@ FPN: RPN_ANCHOR_START_SIZE: 32 RPN_ASPECT_RATIOS: (0.5, 1, 2) TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml b/configs/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml index 45a24c7..a797dda 100644 --- a/configs/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml +++ b/configs/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml @@ -24,7 +24,7 @@ RESNETS: NUM_GROUPS: 32 WIDTH_PER_GROUP: 8 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/20171220/X-101-32x8d.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml b/configs/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml index 7c1588e..4f7b308 100644 --- a/configs/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml +++ b/configs/12_2017_baselines/rpn_person_only_X-101-64x4d-FPN_1x.yaml @@ -24,7 +24,7 @@ RESNETS: NUM_GROUPS: 64 WIDTH_PER_GROUP: 4 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/FBResNeXt/X-101-64x4d.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 diff --git a/configs/cascade_rcnn_baselines/e2e_mask_cascade_rcnn_dual-X-152-32x8d-FPN-IN5k_1.44x.yaml b/configs/cascade_rcnn_baselines/e2e_mask_cascade_rcnn_dual-X-152-32x8d-FPN-IN5k_1.44x.yaml index b632926..7e1f755 100644 --- a/configs/cascade_rcnn_baselines/e2e_mask_cascade_rcnn_dual-X-152-32x8d-FPN-IN5k_1.44x.yaml +++ b/configs/cascade_rcnn_baselines/e2e_mask_cascade_rcnn_dual-X-152-32x8d-FPN-IN5k_1.44x.yaml @@ -6,7 +6,7 @@ MODEL: MASK_ON: True CASCADE_ON: True CLS_AGNOSTIC_BBOX_REG: True # default: False -NUM_GPUS: 8 +NUM_GPUS: 1 SOLVER: WEIGHT_DECAY: 0.0001 LR_POLICY: steps_with_decay @@ -44,16 +44,18 @@ CASCADE_RCNN: TEST_STAGE: 3 TEST_ENSEMBLE: True TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/25093814/X-152-32x8d-IN5k.pkl - DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') + #WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/25093814/X-152-32x8d-IN5k.pkl + #WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/25093814/X-152-32x8d-IN5k.pkl + WEIGHTS: '/home/madhav3101/detectron/Detectron_install/detectron/def_model/X-152-32x8d-IN5k.pkl' + DATASETS: ('coco_2014_train', 'coco_2014_val') SCALES: (640, 672, 704, 736, 768, 800) # Scale jitter MAX_SIZE: 1333 IMS_PER_BATCH: 1 BATCH_SIZE_PER_IM: 512 RPN_PRE_NMS_TOP_N: 2000 # Per FPN level TEST: - DATASETS: ('coco_2015_test-dev',) - #DATASETS: ('coco_2014_minival',) + #DATASETS: ('coco_2015_test-dev',) + DATASETS: ('coco_2014_val',) SCALE: 800 MAX_SIZE: 1333 NMS: 0.5 diff --git a/configs/getting_started/tutorial_1gpu_e2e_faster_rcnn_R-50-FPN.yaml b/configs/getting_started/tutorial_1gpu_e2e_faster_rcnn_R-50-FPN.yaml index 1a5040b..83ea2ac 100644 --- a/configs/getting_started/tutorial_1gpu_e2e_faster_rcnn_R-50-FPN.yaml +++ b/configs/getting_started/tutorial_1gpu_e2e_faster_rcnn_R-50-FPN.yaml @@ -38,7 +38,7 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train',) SCALES: (500,) MAX_SIZE: 833 diff --git a/configs/getting_started/tutorial_2gpu_e2e_faster_rcnn_R-50-FPN.yaml b/configs/getting_started/tutorial_2gpu_e2e_faster_rcnn_R-50-FPN.yaml index e98f8df..a8df147 100644 --- a/configs/getting_started/tutorial_2gpu_e2e_faster_rcnn_R-50-FPN.yaml +++ b/configs/getting_started/tutorial_2gpu_e2e_faster_rcnn_R-50-FPN.yaml @@ -38,7 +38,7 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train',) SCALES: (500,) MAX_SIZE: 833 diff --git a/configs/getting_started/tutorial_4gpu_e2e_faster_rcnn_R-50-FPN.yaml b/configs/getting_started/tutorial_4gpu_e2e_faster_rcnn_R-50-FPN.yaml index f38ae90..5ffffc6 100644 --- a/configs/getting_started/tutorial_4gpu_e2e_faster_rcnn_R-50-FPN.yaml +++ b/configs/getting_started/tutorial_4gpu_e2e_faster_rcnn_R-50-FPN.yaml @@ -38,7 +38,7 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train',) SCALES: (500,) MAX_SIZE: 833 diff --git a/configs/getting_started/tutorial_8gpu_e2e_faster_rcnn_R-50-FPN.yaml b/configs/getting_started/tutorial_8gpu_e2e_faster_rcnn_R-50-FPN.yaml index a1781c5..21ce1fe 100644 --- a/configs/getting_started/tutorial_8gpu_e2e_faster_rcnn_R-50-FPN.yaml +++ b/configs/getting_started/tutorial_8gpu_e2e_faster_rcnn_R-50-FPN.yaml @@ -38,7 +38,7 @@ FAST_RCNN: ROI_XFORM_RESOLUTION: 7 ROI_XFORM_SAMPLING_RATIO: 2 TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train',) SCALES: (500,) MAX_SIZE: 833 diff --git a/configs/test_time_aug/e2e_mask_rcnn_R-50-FPN_2x.yaml b/configs/test_time_aug/e2e_mask_rcnn_R-50-FPN_2x.yaml index 6360f0a..c2bfd3b 100644 --- a/configs/test_time_aug/e2e_mask_rcnn_R-50-FPN_2x.yaml +++ b/configs/test_time_aug/e2e_mask_rcnn_R-50-FPN_2x.yaml @@ -30,7 +30,7 @@ MRCNN: DILATION: 1 # default 2 CONV_INIT: MSRAFill # default GaussianFill TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('coco_2014_train', 'coco_2014_valminusminival') SCALES: (800,) MAX_SIZE: 1333 @@ -43,7 +43,7 @@ TEST: NMS: 0.5 RPN_PRE_NMS_TOP_N: 1000 # Per FPN level RPN_POST_NMS_TOP_N: 1000 - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/35859007/12_2017_baselines/e2e_mask_rcnn_R-50-FPN_2x.yaml.01_49_07.By8nQcCH/output/train/coco_2014_train:coco_2014_valminusminival/generalized_rcnn/model_final.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/35859007/12_2017_baselines/e2e_mask_rcnn_R-50-FPN_2x.yaml.01_49_07.By8nQcCH/output/train/coco_2014_train:coco_2014_valminusminival/generalized_rcnn/model_final.pkl # -- Test time augmentation example -- # BBOX_AUG: diff --git a/configs/test_time_aug/keypoint_rcnn_R-50-FPN_1x.yaml b/configs/test_time_aug/keypoint_rcnn_R-50-FPN_1x.yaml index 0378841..8e0d17e 100644 --- a/configs/test_time_aug/keypoint_rcnn_R-50-FPN_1x.yaml +++ b/configs/test_time_aug/keypoint_rcnn_R-50-FPN_1x.yaml @@ -34,20 +34,20 @@ KRCNN: ROI_XFORM_SAMPLING_RATIO: 2 KEYPOINT_CONFIDENCE: bbox TRAIN: - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/ImageNetPretrained/MSRA/R-50.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl DATASETS: ('keypoints_coco_2014_train', 'keypoints_coco_2014_valminusminival') - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://s3-us-west-2.amazonaws.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_train/generalized_rcnn/rpn_proposals.pkl', 'https://dl.fbaipublicfiles.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_valminusminival/generalized_rcnn/rpn_proposals.pkl') SCALES: (640, 672, 704, 736, 768, 800) MAX_SIZE: 1333 BATCH_SIZE_PER_IM: 512 TEST: DATASETS: ('keypoints_coco_2014_minival',) - PROPOSAL_FILES: ('https://s3-us-west-2.amazonaws.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) + PROPOSAL_FILES: ('https://dl.fbaipublicfiles.com/detectron/35998996/12_2017_baselines/rpn_person_only_R-50-FPN_1x.yaml.08_10_08.0ZWmJm6F/output/test/keypoints_coco_2014_minival/generalized_rcnn/rpn_proposals.pkl',) PROPOSAL_LIMIT: 1000 SCALE: 800 MAX_SIZE: 1333 NMS: 0.5 - WEIGHTS: https://s3-us-west-2.amazonaws.com/detectron/37651887/12_2017_baselines/keypoint_rcnn_R-50-FPN_s1x.yaml.20_01_40.FDjUQ7VX/output/train/keypoints_coco_2014_train:keypoints_coco_2014_valminusminival/generalized_rcnn/model_final.pkl + WEIGHTS: https://dl.fbaipublicfiles.com/detectron/37651887/12_2017_baselines/keypoint_rcnn_R-50-FPN_s1x.yaml.20_01_40.FDjUQ7VX/output/train/keypoints_coco_2014_train:keypoints_coco_2014_valminusminival/generalized_rcnn/model_final.pkl # -- Test time augmentation example -- # BBOX_AUG: diff --git a/detectron/core/config.py b/detectron/core/config.py index bfc6a73..ab5a7d9 100644 --- a/detectron/core/config.py +++ b/detectron/core/config.py @@ -51,7 +51,7 @@ import os import os.path as osp import yaml - +import sys, io from detectron.utils.collections import AttrDict from detectron.utils.io import cache_url @@ -471,7 +471,7 @@ __C.MODEL.FASTER_RCNN = False # Indicates the model uses Cascade R-CNN -__C.MODEL.CASCADE_ON = False +__C.MODEL.CASCADE_ON = True # Indicates the model makes instance mask predictions (as in Mask R-CNN) __C.MODEL.MASK_ON = False @@ -1158,10 +1158,19 @@ def get_output_dir(datasets, training=True): def load_cfg(cfg_to_load): + #print("----",cfg_to_load) """Wrapper around yaml.load used for maintaining backward compatibility""" - assert isinstance(cfg_to_load, (file, basestring)), \ - 'Expected {} or {} got {}'.format(file, basestring, type(cfg_to_load)) - if isinstance(cfg_to_load, file): + if sys.version_info.major == 2: + assert isinstance(cfg_to_load, (file, basestring)), \ + 'Expected {} or {} got {}'.format(file, basestring, type(cfg_to_load)) + else: + assert isinstance(cfg_to_load, (io.TextIOWrapper, basestring)), \ + 'Expected {} or {} got {}'.format(io.TextIOWrapper, basestring, type(cfg_to_load)) + #assert isinstance(cfg_to_load, (file, basestring)), \ + # 'Expected {} or {} got {}'.format(file, basestring, type(cfg_to_load)) + #if isinstance(cfg_to_load, file): + # cfg_to_load = ''.join(cfg_to_load.readlines()) + if not isinstance(cfg_to_load, basestring): cfg_to_load = ''.join(cfg_to_load.readlines()) if isinstance(cfg_to_load, basestring): for old_module, new_module in iteritems(_RENAMED_MODULES): @@ -1218,6 +1227,7 @@ def _merge_a_into_b(a, b, stack=None): for k, v_ in a.items(): full_key = '.'.join(stack) + '.' + k if stack is not None else k + #print(full_key) # a must specify keys that are in b if k not in b: if _key_is_deprecated(full_key): @@ -1240,6 +1250,15 @@ def _merge_a_into_b(a, b, stack=None): raise else: b[k] = v + # walk into b, look for bytes, decode as ascii strings + # assume bytes are encoded ascii strings (thats how they are in python 2) + for k, v_ in list(b.items()): + if isinstance(v_, bytes): + b[k] = v_.decode('ascii') + elif isinstance(v_, dict): + for vkey,vval in v_.items(): + if isinstance(vval, bytes): + v_[vkey] = vval.decode('ascii') def _key_is_deprecated(full_key): @@ -1277,6 +1296,8 @@ def _decode_cfg_value(v): if isinstance(v, dict): return AttrDict(v) # All remaining processing is only applied to strings + if isinstance(v, bytes): # assume bytes are encoded ascii strings (thats how they are in python 2) + v = v.decode('ascii') if not isinstance(v, basestring): return v # Try to interpret `v` as a: @@ -1306,6 +1327,11 @@ def _check_and_coerce_cfg_value_type(value_a, value_b, key, full_key): right type. The type is correct if it matches exactly or is one of a few cases in which the type can be easily coerced. """ + if isinstance(value_a, bytes) and isinstance(value_b, bytes): + return value_a.decode('ascii') # assume bytes are encoded ascii strings (thats how they are in python 2) + if sys.version_info.major == 2 and isinstance(value_a, unicode): + assert isinstance(value_b, str) or isinstance(value_b, unicode), str(type(value_b)) + return value_a.decode('latin1') # https://github.com/tflearn/tflearn/issues/57 # The types must match (with some exceptions) type_b = type(value_b) type_a = type(value_a) @@ -1315,8 +1341,10 @@ def _check_and_coerce_cfg_value_type(value_a, value_b, key, full_key): # Exceptions: numpy arrays, strings, tuple<->list if isinstance(value_b, np.ndarray): value_a = np.array(value_a, dtype=value_b.dtype) - elif isinstance(value_b, basestring): - value_a = str(value_a) +# elif isinstance(value_b, basestring): +# value_a = str(value_a) + elif isinstance(value_b, bytes) and isinstance(value_a, str): + pass # encode to match other dict? or just leave alone? elif isinstance(value_a, tuple) and isinstance(value_b, list): value_a = list(value_a) elif isinstance(value_a, list) and isinstance(value_b, tuple): diff --git a/detectron/datasets/json_dataset.py b/detectron/datasets/json_dataset.py index 3fc095c..7adf90b 100644 --- a/detectron/datasets/json_dataset.py +++ b/detectron/datasets/json_dataset.py @@ -26,7 +26,8 @@ from __future__ import unicode_literals import copy -import cPickle as pickle +#import cPickle as pickle +import pickle import logging import numpy as np import os diff --git a/detectron/datasets/voc_eval.py b/detectron/datasets/voc_eval.py index d972ba3..70ef3aa 100644 --- a/detectron/datasets/voc_eval.py +++ b/detectron/datasets/voc_eval.py @@ -22,7 +22,7 @@ """Python implementation of the PASCAL VOC devkit's AP evaluation code.""" -import cPickle +import pickle as cPickle import logging import numpy as np import os diff --git a/detectron/modeling/ResNet.py b/detectron/modeling/ResNet.py index e9eddb9..26051b0 100644 --- a/detectron/modeling/ResNet.py +++ b/detectron/modeling/ResNet.py @@ -303,6 +303,7 @@ def add_residual_block( # sum -> ReLU # shortcut function: by default using bn; support gn + #print(cfg.RESNETS.SHORTCUT_FUNC) add_shortcut = globals()[cfg.RESNETS.SHORTCUT_FUNC] sc = add_shortcut(model, prefix, blob_in, dim_in, dim_out, stride) if inplace_sum: diff --git a/detectron/modeling/model_builder.py b/detectron/modeling/model_builder.py index 6283273..9efc74a 100644 --- a/detectron/modeling/model_builder.py +++ b/detectron/modeling/model_builder.py @@ -56,6 +56,7 @@ import detectron.modeling.rpn_heads as rpn_heads import detectron.roi_data.minibatch as roi_data_minibatch import detectron.utils.c2 as c2_utils +from detectron.utils.py3compat import bytes2string logger = logging.getLogger(__name__) @@ -148,6 +149,7 @@ def get_func(func_name): function in this module or the path to a function relative to the base 'modeling' module. """ + func_name = bytes2string(func_name) if func_name == '': return None new_func_name = name_compat.get_new_name(func_name) diff --git a/detectron/roi_data/loader.py b/detectron/roi_data/loader.py index 76ea1b5..8e7961c 100644 --- a/detectron/roi_data/loader.py +++ b/detectron/roi_data/loader.py @@ -44,7 +44,7 @@ from collections import OrderedDict import logging import numpy as np -import Queue +import queue as Queue import signal import threading import time diff --git a/detectron/utils/blob.py b/detectron/utils/blob.py index b4fa50c..0b5bf11 100644 --- a/detectron/utils/blob.py +++ b/detectron/utils/blob.py @@ -28,7 +28,8 @@ from __future__ import print_function from __future__ import unicode_literals -import cPickle as pickle +#import cPickle as pickle +import pickle import cv2 import numpy as np diff --git a/detectron/utils/coordinator.py b/detectron/utils/coordinator.py index 755601a..3c1529a 100644 --- a/detectron/utils/coordinator.py +++ b/detectron/utils/coordinator.py @@ -22,7 +22,7 @@ import contextlib import logging -import Queue +import queue as Queue import threading import traceback diff --git a/detectron/utils/env.py b/detectron/utils/env.py index cd20049..0b4e4a6 100644 --- a/detectron/utils/env.py +++ b/detectron/utils/env.py @@ -59,7 +59,7 @@ def import_nccl_ops(): def get_detectron_ops_lib(): """Retrieve Detectron ops library.""" # Candidate prefixes for the detectron ops lib path - prefixes = [_CMAKE_INSTALL_PREFIX, sys.prefix, sys.exec_prefix] + sys.path + prefixes = [_CMAKE_INSTALL_PREFIX, sys.prefix, sys.exec_prefix] + sys.path + ["/home/madhav3101/torch-env/lib/python3.7/site-packages/torch/"] # Search for detectron ops lib for prefix in prefixes: ops_path = os.path.join(prefix, 'lib/libcaffe2_detectron_ops_gpu.so') diff --git a/detectron/utils/io.py b/detectron/utils/io.py index cdd51ee..9032ec4 100644 --- a/detectron/utils/io.py +++ b/detectron/utils/io.py @@ -20,14 +20,15 @@ from __future__ import print_function from __future__ import unicode_literals -import cPickle as pickle +#import cPickle as pickle +import pickle as pickle import hashlib import logging import os import re import sys -import urllib2 - +from detectron.utils.py3compat import bytes2string +from urllib.request import urlopen logger = logging.getLogger(__name__) _DETECTRON_S3_BASE_URL = 'https://s3-us-west-2.amazonaws.com/detectron' @@ -45,17 +46,20 @@ def cache_url(url_or_file, cache_dir): path to the cached file. If the argument is not a URL, simply return it as is. """ + url_or_file = bytes2string(url_or_file) + cache_dir = bytes2string(cache_dir) is_url = re.match(r'^(?:http)s?://', url_or_file, re.IGNORECASE) is not None if not is_url: return url_or_file url = url_or_file - assert url.startswith(_DETECTRON_S3_BASE_URL), \ - ('Detectron only automatically caches URLs in the Detectron S3 ' - 'bucket: {}').format(_DETECTRON_S3_BASE_URL) + #assert url.startswith(_DETECTRON_S3_BASE_URL), \ + # ('Detectron only automatically caches URLs in the Detectron S3 ' + # 'bucket: {}').format(_DETECTRON_S3_BASE_URL) cache_file_path = url.replace(_DETECTRON_S3_BASE_URL, cache_dir) + print("---Cache File Path--",cache_file_path) if os.path.exists(cache_file_path): assert_cache_file_is_ok(url, cache_file_path) return cache_file_path @@ -65,8 +69,8 @@ def cache_url(url_or_file, cache_dir): os.makedirs(cache_file_dir) logger.info('Downloading remote file {} to {}'.format(url, cache_file_path)) - download_url(url, cache_file_path) - assert_cache_file_is_ok(url, cache_file_path) + #download_url(url, cache_file_path) + #assert_cache_file_is_ok(url, cache_file_path) return cache_file_path @@ -111,7 +115,7 @@ def download_url( Credit: https://stackoverflow.com/questions/2028517/python-urllib2-progress-hook """ - response = urllib2.urlopen(url) + response = urlopen(url) total_size = response.info().getheader('Content-Length').strip() total_size = int(total_size) bytes_so_far = 0 @@ -140,5 +144,5 @@ def _get_file_md5sum(file_name): def _get_reference_md5sum(url): """By convention the md5 hash for url is stored in url + '.md5sum'.""" url_md5sum = url + '.md5sum' - md5sum = urllib2.urlopen(url_md5sum).read().strip() + md5sum = urlopen(url_md5sum).read().strip() return md5sum diff --git a/detectron/utils/net.py b/detectron/utils/net.py index bf504e5..32cdef5 100644 --- a/detectron/utils/net.py +++ b/detectron/utils/net.py @@ -21,7 +21,8 @@ from __future__ import unicode_literals from collections import OrderedDict -import cPickle as pickle +#import cPickle as pickle +import pickle import logging import numpy as np import os @@ -59,8 +60,11 @@ def initialize_gpu_from_weights_file(model, weights_file, gpu_id=0): """ logger.info('Loading weights from: {}'.format(weights_file)) ws_blobs = workspace.Blobs() - with open(weights_file, 'r') as f: - src_blobs = pickle.load(f) + with open(weights_file, 'rb') as f: + try: + src_blobs = pickle.load(f, encoding='latin1') # the pickles from the Model Zoo (as of January 2018) seem to be encoded with latin1; see also https://github.com/tflearn/tflearn/issues/57 + except TypeError: + src_blobs = pickle.load(f) # Python 2 has no "encoding" argument for pickle if 'cfg' in src_blobs: saved_cfg = load_cfg(src_blobs['cfg']) configure_bbox_reg_weights(model, saved_cfg) @@ -141,8 +145,12 @@ def initialize_gpu_from_old_weights_file(model, weights_file, gpu_id=0): """ logger.info('Loading weights from: {}'.format(weights_file)) ws_blobs = workspace.Blobs() - with open(weights_file, 'r') as f: - src_blobs = pickle.load(f) + with open(weights_file, 'rb') as f: + try: + src_blobs = pickle.load(f, encoding='latin1') # the pickles from the Model Zoo (as of January 2018) seem to be encoded with latin1; see also https://github.com/tflearn/tflearn/issues/57 + except TypeError: + src_blobs = pickle.load(f) # Python 2 has no "encoding" argument for pickle + #src_blobs = pickle.load(f) #if 'cfg' in src_blobs: # saved_cfg = load_cfg(src_blobs['cfg']) # configure_bbox_reg_weights(model, saved_cfg) diff --git a/detectron/utils/py3compat.py b/detectron/utils/py3compat.py new file mode 100644 index 0000000..584a98f --- /dev/null +++ b/detectron/utils/py3compat.py @@ -0,0 +1,10 @@ +import sys + +def bytes2string(x): + if isinstance(x,bytes): + return x.decode('ascii') + if sys.version_info.major == 2 and isinstance(x,unicode): # 2to3 turns "unicode" into "str" but we don't want to decode "str" in python 3 + return x.decode('latin1') # the pickles from the Model Zoo (as of January 2018) seem to be encoded with latin1; see also https://github.com/tflearn/tflearn/issues/57 + assert isinstance(x,str), str(type(x)) + return x + diff --git a/detectron/utils/subprocess.py b/detectron/utils/subprocess.py index d0a72b6..09d2a23 100644 --- a/detectron/utils/subprocess.py +++ b/detectron/utils/subprocess.py @@ -27,7 +27,7 @@ import yaml import numpy as np import subprocess -import cPickle as pickle +import pickle from six.moves import shlex_quote from detectron.core.config import cfg diff --git a/requirements.txt b/requirements.txt index 8474b65..80ea44e 100644 --- a/requirements.txt +++ b/requirements.txt @@ -6,3 +6,7 @@ setuptools Cython mock scipy +google-api-python-client +future +pycocotools +networkx diff --git a/tools/convert_cityscapes_to_coco.py b/tools/convert_cityscapes_to_coco.py index 404909b..3583eca 100644 --- a/tools/convert_cityscapes_to_coco.py +++ b/tools/convert_cityscapes_to_coco.py @@ -1,3 +1,20 @@ +#!/usr/bin/env python + +# Copyright (c) 2017-present, Facebook, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +############################################################################## + from __future__ import absolute_import from __future__ import division from __future__ import print_function @@ -7,7 +24,7 @@ import h5py import json import os -import scipy.misc +import imageio import sys import cityscapesscripts.evaluation.instances2dict_with_polygons as cs @@ -57,7 +74,7 @@ def convert_coco_stuff_mat(data_dir, out_dir): {"id": idx, "name": ''.join(chr(i) for i in data[ n[0]])}) ann_dict['categories'] = categories - scipy.misc.imsave( + imageio.imsave( os.path.join(data_dir, img_name + '.png'), labelMap) image['width'] = labelMap.shape[0] image['height'] = labelMap.shape[1] diff --git a/tools/convert_coco_model_to_cityscapes.py b/tools/convert_coco_model_to_cityscapes.py index 429be86..11dec59 100644 --- a/tools/convert_coco_model_to_cityscapes.py +++ b/tools/convert_coco_model_to_cityscapes.py @@ -1,3 +1,20 @@ +#!/usr/bin/env python + +# Copyright (c) 2017-present, Facebook, Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +############################################################################## + # Convert a detection model trained for COCO into a model that can be fine-tuned # on cityscapes # @@ -9,12 +26,13 @@ from __future__ import unicode_literals import argparse -import cPickle as pickle import numpy as np import os import sys import detectron.datasets.coco_to_cityscapes_id as cs +from detectron.utils.io import load_object +from detectron.utils.io import save_object NUM_CS_CLS = 9 NUM_COCO_CLS = 81 @@ -92,8 +110,7 @@ def remove_momentum(model_dict): def load_and_convert_coco_model(args): - with open(args.coco_model_file_name, 'r') as f: - model_dict = pickle.load(f) + model_dict = load_object(args.coco_model_file_name) remove_momentum(model_dict) convert_coco_blobs_to_cityscape_blobs(model_dict) return model_dict @@ -106,7 +123,6 @@ def load_and_convert_coco_model(args): 'Weights file does not exist' weights = load_and_convert_coco_model(args) - with open(args.out_file_name, 'w') as f: - pickle.dump(weights, f, protocol=pickle.HIGHEST_PROTOCOL) + save_object(weights, args.out_file_name) print('Wrote blobs to {}:'.format(args.out_file_name)) print(sorted(weights['blobs'].keys())) diff --git a/tools/convert_pkl_to_pb.py b/tools/convert_pkl_to_pb.py index a553444..442084d 100644 --- a/tools/convert_pkl_to_pb.py +++ b/tools/convert_pkl_to_pb.py @@ -1,4 +1,4 @@ -#!/usr/bin/env python2 +#!/usr/bin/env python3 # Copyright (c) 2017-present, Facebook, Inc. # @@ -25,36 +25,36 @@ the converted model, and run_model_pb() for running the model for inference. """ -from __future__ import absolute_import -from __future__ import division -from __future__ import print_function -from __future__ import unicode_literals +from __future__ import absolute_import, division, print_function, unicode_literals import argparse import copy -import cv2 # NOQA (Must import before importing caffe2 due to bug in cv2) -import numpy as np import os import pprint import sys import caffe2.python.utils as putils -from caffe2.python import core, workspace -from caffe2.proto import caffe2_pb2 - -from detectron.core.config import assert_and_infer_cfg -from detectron.core.config import cfg -from detectron.core.config import merge_cfg_from_file -from detectron.core.config import merge_cfg_from_list -from detectron.modeling import generate_anchors -from detectron.utils.logging import setup_logging -from detectron.utils.model_convert_utils import convert_op_in_proto -from detectron.utils.model_convert_utils import op_filter -import detectron.utils.blob as blob_utils +import cv2 # NOQA (Must import before importing caffe2 due to bug in cv2) import detectron.core.test_engine as test_engine +import detectron.utils.blob as blob_utils import detectron.utils.c2 as c2_utils import detectron.utils.model_convert_utils as mutils import detectron.utils.vis as vis_utils +import numpy as np +from caffe2.caffe2.fb.predictor import predictor_exporter, predictor_py_utils +from caffe2.proto import caffe2_pb2 +from caffe2.python import core, workspace +from caffe2.python.predictor_constants import predictor_constants as predictor_constants +from detectron.core.config import ( + assert_and_infer_cfg, + cfg, + merge_cfg_from_file, + merge_cfg_from_list, +) +from detectron.modeling import generate_anchors +from detectron.utils.logging import setup_logging +from detectron.utils.model_convert_utils import convert_op_in_proto, op_filter + c2_utils.import_contrib_ops() c2_utils.import_detectron_ops() @@ -68,53 +68,74 @@ def parse_args(): parser = argparse.ArgumentParser( - description='Convert a trained network to pb format' + description="Convert a trained network to pb format" ) parser.add_argument( - '--cfg', dest='cfg_file', help='optional config file', default=None, - type=str) + "--cfg", dest="cfg_file", help="optional config file", default=None, type=str + ) parser.add_argument( - '--net_name', dest='net_name', help='optional name for the net', - default="detectron", type=str) + "--net_name", + dest="net_name", + help="optional name for the net", + default="detectron", + type=str, + ) parser.add_argument( - '--out_dir', dest='out_dir', help='output dir', default=None, - type=str) + "--out_dir", dest="out_dir", help="output dir", default=None, type=str + ) parser.add_argument( - '--test_img', dest='test_img', - help='optional test image, used to verify the model conversion', + "--test_img", + dest="test_img", + help="optional test image, used to verify the model conversion", default=None, - type=str) + type=str, + ) parser.add_argument( - '--fuse_af', dest='fuse_af', help='1 to fuse_af', - default=1, - type=int) + "--fuse_af", dest="fuse_af", help="1 to fuse_af", default=1, type=int + ) parser.add_argument( - '--device', dest='device', - help='Device to run the model on', - choices=['cpu', 'gpu'], - default='cpu', - type=str) + "--device", + dest="device", + help="Device to run the model on", + choices=["cpu", "gpu"], + default="cpu", + type=str, + ) parser.add_argument( - '--net_execution_type', dest='net_execution_type', - help='caffe2 net execution type', - choices=['simple', 'dag'], - default='simple', - type=str) + "--net_execution_type", + dest="net_execution_type", + help="caffe2 net execution type", + choices=["simple", "dag"], + default="simple", + type=str, + ) parser.add_argument( - '--use_nnpack', dest='use_nnpack', - help='Use nnpack for conv', + "--use_nnpack", + dest="use_nnpack", + help="Use nnpack for conv", default=1, - type=int) + type=int, + ) + parser.add_argument( + "--logdb", + dest="logdb", + help="output to logfiledb instead of pb files", + default=0, + type=int, + ) parser.add_argument( - 'opts', help='See detectron/core/config.py for all options', default=None, - nargs=argparse.REMAINDER) + "opts", + help="See detectron/core/config.py for all options", + default=None, + nargs=argparse.REMAINDER, + ) if len(sys.argv) == 1: parser.print_help() sys.exit(1) ret = parser.parse_args() ret.out_dir = os.path.abspath(ret.out_dir) - if ret.device == 'gpu' and ret.use_nnpack: - logger.warn('Should not use mobile engine for gpu model.') + if ret.device == "gpu" and ret.use_nnpack: + logger.warn("Should not use mobile engine for gpu model.") ret.use_nnpack = 0 return ret @@ -130,7 +151,8 @@ def reset_names(names): def convert_collect_and_distribute( - op, blobs, + op, + blobs, roi_canonical_scale, roi_canonical_level, roi_max_level, @@ -139,14 +161,17 @@ def convert_collect_and_distribute( rpn_min_level, rpn_post_nms_topN, ): - print('Converting CollectAndDistributeFpnRpnProposals' - ' Python -> C++:\n{}'.format(op)) - assert op.name.startswith('CollectAndDistributeFpnRpnProposalsOp'), \ - 'Not valid CollectAndDistributeFpnRpnProposalsOp' + print( + "Converting CollectAndDistributeFpnRpnProposals" + " Python -> C++:\n{}".format(op) + ) + assert op.name.startswith( + "CollectAndDistributeFpnRpnProposalsOp" + ), "Not valid CollectAndDistributeFpnRpnProposalsOp" inputs = [x for x in op.input] ret = core.CreateOperator( - 'CollectAndDistributeFpnRpnProposals', + "CollectAndDistributeFpnRpnProposals", inputs, list(op.output), roi_canonical_scale=roi_canonical_scale, @@ -161,29 +186,29 @@ def convert_collect_and_distribute( def convert_gen_proposals( - op, blobs, - rpn_pre_nms_topN, - rpn_post_nms_topN, - rpn_nms_thresh, - rpn_min_size, + op, blobs, rpn_pre_nms_topN, rpn_post_nms_topN, rpn_nms_thresh, rpn_min_size ): - print('Converting GenerateProposals Python -> C++:\n{}'.format(op)) - assert op.name.startswith('GenerateProposalsOp'), 'Not valid GenerateProposalsOp' + print("Converting GenerateProposals Python -> C++:\n{}".format(op)) + assert op.name.startswith("GenerateProposalsOp"), "Not valid GenerateProposalsOp" - spatial_scale = mutils.get_op_arg_valf(op, 'spatial_scale', None) + spatial_scale = mutils.get_op_arg_valf(op, "spatial_scale", None) assert spatial_scale is not None lvl = int(op.input[0][-1]) if op.input[0][-1].isdigit() else None inputs = [x for x in op.input] - anchor_name = 'anchor{}'.format(lvl) if lvl else 'anchor' + anchor_name = "anchor{}".format(lvl) if lvl else "anchor" inputs.append(anchor_name) - anchor_sizes = (cfg.FPN.RPN_ANCHOR_START_SIZE * 2.**(lvl - cfg.FPN.RPN_MIN_LEVEL),) if lvl else cfg.RPN.SIZES + anchor_sizes = ( + (cfg.FPN.RPN_ANCHOR_START_SIZE * 2.0 ** (lvl - cfg.FPN.RPN_MIN_LEVEL),) + if lvl + else cfg.RPN.SIZES + ) blobs[anchor_name] = get_anchors(spatial_scale, anchor_sizes) - print('anchors {}'.format(blobs[anchor_name])) + print("anchors {}".format(blobs[anchor_name])) ret = core.CreateOperator( - 'GenerateProposals', + "GenerateProposals", inputs, list(op.output), spatial_scale=spatial_scale, @@ -198,9 +223,10 @@ def convert_gen_proposals( def get_anchors(spatial_scale, anchor_sizes): anchors = generate_anchors.generate_anchors( - stride=1. / spatial_scale, + stride=1.0 / spatial_scale, sizes=anchor_sizes, - aspect_ratios=cfg.RPN.ASPECT_RATIOS).astype(np.float32) + aspect_ratios=cfg.RPN.ASPECT_RATIOS, + ).astype(np.float32) return anchors @@ -211,22 +237,22 @@ def reset_blob_names(blobs): def convert_net(args, net, blobs): - @op_filter() def convert_op_name(op): - if args.device != 'gpu': - if op.engine != 'DEPTHWISE_3x3': - op.engine = '' + if args.device != "gpu": + if op.engine != "DEPTHWISE_3x3": + op.engine = "" op.device_option.CopyFrom(caffe2_pb2.DeviceOption()) reset_names(op.input) reset_names(op.output) return [op] - @op_filter(type='Python') + @op_filter(type="Python") def convert_python(op): - if op.name.startswith('GenerateProposalsOp'): + if op.name.startswith("GenerateProposalsOp"): gen_proposals_op, ext_input = convert_gen_proposals( - op, blobs, + op, + blobs, rpn_min_size=float(cfg.TEST.RPN_MIN_SIZE), rpn_post_nms_topN=cfg.TEST.RPN_POST_NMS_TOP_N, rpn_pre_nms_topN=cfg.TEST.RPN_PRE_NMS_TOP_N, @@ -234,9 +260,10 @@ def convert_python(op): ) net.external_input.extend([ext_input]) return [gen_proposals_op] - elif op.name.startswith('CollectAndDistributeFpnRpnProposalsOp'): + elif op.name.startswith("CollectAndDistributeFpnRpnProposalsOp"): collect_dist_op = convert_collect_and_distribute( - op, blobs, + op, + blobs, roi_canonical_scale=cfg.FPN.ROI_CANONICAL_SCALE, roi_canonical_level=cfg.FPN.ROI_CANONICAL_LEVEL, roi_max_level=cfg.FPN.ROI_MAX_LEVEL, @@ -247,44 +274,51 @@ def convert_python(op): ) return [collect_dist_op] else: - raise ValueError('Failed to convert Python op {}'.format( - op.name)) + raise ValueError("Failed to convert Python op {}".format(op.name)) # Only convert UpsampleNearest to ResizeNearest when converting to pb so that the existing models is unchanged # https://github.com/facebookresearch/Detectron/pull/372#issuecomment-410248561 - @op_filter(type='UpsampleNearest') + @op_filter(type="UpsampleNearest") def convert_upsample_nearest(op): for arg in op.arg: - if arg.name == 'scale': + if arg.name == "scale": scale = arg.i break else: raise KeyError('No attribute "scale" in UpsampleNearest op') - resize_nearest_op = core.CreateOperator('ResizeNearest', - list(op.input), - list(op.output), - name=op.name, - width_scale=float(scale), - height_scale=float(scale)) + resize_nearest_op = core.CreateOperator( + "ResizeNearest", + list(op.input), + list(op.output), + name=op.name, + width_scale=float(scale), + height_scale=float(scale), + ) return resize_nearest_op @op_filter() def convert_rpn_rois(op): for j in range(len(op.input)): - if op.input[j] == 'rois': - print('Converting op {} input name: rois -> rpn_rois:\n{}'.format( - op.type, op)) - op.input[j] = 'rpn_rois' + if op.input[j] == "rois": + print( + "Converting op {} input name: rois -> rpn_rois:\n{}".format( + op.type, op + ) + ) + op.input[j] = "rpn_rois" for j in range(len(op.output)): - if op.output[j] == 'rois': - print('Converting op {} output name: rois -> rpn_rois:\n{}'.format( - op.type, op)) - op.output[j] = 'rpn_rois' + if op.output[j] == "rois": + print( + "Converting op {} output name: rois -> rpn_rois:\n{}".format( + op.type, op + ) + ) + op.output[j] = "rpn_rois" return [op] - @op_filter(type_in=['StopGradient', 'Alias']) + @op_filter(type_in=["StopGradient", "Alias"]) def convert_remove_op(op): - print('Removing op {}:\n{}'.format(op.type, op)) + print("Removing op {}:\n{}".format(op.type, op)) return [] # We want to apply to all operators, including converted @@ -308,20 +342,20 @@ def add_bbox_ops(args, net, blobs): # Operators for bboxes op_box = core.CreateOperator( "BBoxTransform", - ['rpn_rois', 'bbox_pred', 'im_info'], - ['pred_bbox'], + ["rpn_rois", "bbox_pred", "im_info"], + ["pred_bbox"], weights=cfg.MODEL.BBOX_REG_WEIGHTS, apply_scale=False, correct_transform_coords=True, ) new_ops.extend([op_box]) - blob_prob = 'cls_prob' - blob_box = 'pred_bbox' + blob_prob = "cls_prob" + blob_box = "pred_bbox" op_nms = core.CreateOperator( "BoxWithNMSLimit", [blob_prob, blob_box], - ['score_nms', 'bbox_nms', 'class_nms'], + ["score_nms", "bbox_nms", "class_nms"], arg=[ putils.MakeArgument("score_thresh", cfg.TEST.SCORE_THRESH), putils.MakeArgument("nms", cfg.TEST.NMS), @@ -329,17 +363,17 @@ def add_bbox_ops(args, net, blobs): putils.MakeArgument("soft_nms_enabled", cfg.TEST.SOFT_NMS.ENABLED), putils.MakeArgument("soft_nms_method", cfg.TEST.SOFT_NMS.METHOD), putils.MakeArgument("soft_nms_sigma", cfg.TEST.SOFT_NMS.SIGMA), - ] + ], ) new_ops.extend([op_nms]) - new_external_outputs.extend(['score_nms', 'bbox_nms', 'class_nms']) + new_external_outputs.extend(["score_nms", "bbox_nms", "class_nms"]) net.Proto().op.extend(new_ops) net.Proto().external_output.extend(new_external_outputs) def convert_model_gpu(args, net, init_net): - assert args.device == 'gpu' + assert args.device == "gpu" ret_net = copy.deepcopy(net) ret_init_net = copy.deepcopy(init_net) @@ -383,32 +417,31 @@ def gen_init_net(net, blobs, empty_blobs): blobs = copy.deepcopy(blobs) for x in empty_blobs: blobs[x] = np.array([], dtype=np.float32) - init_net = mutils.gen_init_net_from_blobs( - blobs, net.external_inputs) + init_net = mutils.gen_init_net_from_blobs(blobs, net.external_inputs) init_net = core.Net(init_net) return init_net def _save_image_graphs(args, all_net, all_init_net): - print('Saving model graph...') + print("Saving model graph...") mutils.save_graph( - all_net.Proto(), os.path.join(args.out_dir, "model_def.png"), - op_only=False) - print('Model def image saved to {}.'.format(args.out_dir)) + all_net.Proto(), os.path.join(args.out_dir, "model_def.png"), op_only=False + ) + print("Model def image saved to {}.".format(args.out_dir)) def _save_models(all_net, all_init_net, args): - print('Writing converted model to {}...'.format(args.out_dir)) + print("Writing converted model to {}...".format(args.out_dir)) fname = "model" if not os.path.exists(args.out_dir): os.makedirs(args.out_dir) - with open(os.path.join(args.out_dir, fname + '.pb'), 'w') as f: + with open(os.path.join(args.out_dir, fname + ".pb"), "wb") as f: f.write(all_net.Proto().SerializeToString()) - with open(os.path.join(args.out_dir, fname + '.pbtxt'), 'w') as f: + with open(os.path.join(args.out_dir, fname + ".pbtxt"), "wb") as f: f.write(str(all_net.Proto())) - with open(os.path.join(args.out_dir, fname + '_init.pb'), 'w') as f: + with open(os.path.join(args.out_dir, fname + "_init.pb"), "wb") as f: f.write(all_init_net.Proto().SerializeToString()) _save_image_graphs(args, all_net, all_init_net) @@ -455,24 +488,25 @@ def run_model_cfg(args, im, check_blobs): model, _ = load_model(args) with c2_utils.NamedCudaScope(0): cls_boxes, cls_segms, cls_keyps = test_engine.im_detect_all( - model, im, None, None, + model, im, None, None ) boxes, segms, keypoints, classes = vis_utils.convert_from_cls_format( - cls_boxes, cls_segms, cls_keyps) + cls_boxes, cls_segms, cls_keyps + ) # sort the results based on score for comparision - boxes, segms, keypoints, classes = _sort_results( - boxes, segms, keypoints, classes) + boxes, segms, keypoints, classes = _sort_results(boxes, segms, keypoints, classes) # write final results back to workspace def _ornone(res): return np.array(res) if res is not None else np.array([], dtype=np.float32) + with c2_utils.NamedCudaScope(0): - workspace.FeedBlob(core.ScopedName('result_boxes'), _ornone(boxes)) - workspace.FeedBlob(core.ScopedName('result_segms'), _ornone(segms)) - workspace.FeedBlob(core.ScopedName('result_keypoints'), _ornone(keypoints)) - workspace.FeedBlob(core.ScopedName('result_classids'), _ornone(classes)) + workspace.FeedBlob(core.ScopedName("result_boxes"), _ornone(boxes)) + workspace.FeedBlob(core.ScopedName("result_segms"), _ornone(segms)) + workspace.FeedBlob(core.ScopedName("result_keypoints"), _ornone(keypoints)) + workspace.FeedBlob(core.ScopedName("result_classids"), _ornone(classes)) # get result blobs with c2_utils.NamedCudaScope(0): @@ -481,13 +515,8 @@ def _ornone(res): return ret -def _prepare_blobs( - im, - pixel_means, - target_size, - max_size, -): - ''' Reference: blob.prep_im_for_blob() ''' +def _prepare_blobs(im, pixel_means, target_size, max_size): + """ Reference: blob.prep_im_for_blob() """ im = im.astype(np.float32, copy=False) im -= pixel_means @@ -498,17 +527,17 @@ def _prepare_blobs( im_scale = float(target_size) / float(im_size_min) if np.round(im_scale * im_size_max) > max_size: im_scale = float(max_size) / float(im_size_max) - im = cv2.resize(im, None, None, fx=im_scale, fy=im_scale, - interpolation=cv2.INTER_LINEAR) + im = cv2.resize( + im, None, None, fx=im_scale, fy=im_scale, interpolation=cv2.INTER_LINEAR + ) # Reuse code in blob_utils and fit FPN blob = blob_utils.im_list_to_blob([im]) blobs = {} - blobs['data'] = blob - blobs['im_info'] = np.array( - [[blob.shape[2], blob.shape[3], im_scale]], - dtype=np.float32 + blobs["data"] = blob + blobs["im_info"] = np.array( + [[blob.shape[2], blob.shape[3], im_scale]], dtype=np.float32 ) return blobs @@ -520,29 +549,26 @@ def run_model_pb(args, net, init_net, im, check_blobs): workspace.CreateNet(net) # input_blobs, _ = core_test._get_blobs(im, None) - input_blobs = _prepare_blobs( - im, - cfg.PIXEL_MEANS, - cfg.TEST.SCALE, cfg.TEST.MAX_SIZE - ) + input_blobs = _prepare_blobs(im, cfg.PIXEL_MEANS, cfg.TEST.SCALE, cfg.TEST.MAX_SIZE) gpu_blobs = [] - if args.device == 'gpu': - gpu_blobs = ['data'] + if args.device == "gpu": + gpu_blobs = ["data"] for k, v in input_blobs.items(): workspace.FeedBlob( core.ScopedName(k), v, - mutils.get_device_option_cuda() if k in gpu_blobs else - mutils.get_device_option_cpu() + mutils.get_device_option_cuda() + if k in gpu_blobs + else mutils.get_device_option_cpu(), ) try: workspace.RunNet(net) - scores = workspace.FetchBlob('score_nms') - classids = workspace.FetchBlob('class_nms') - boxes = workspace.FetchBlob('bbox_nms') + scores = workspace.FetchBlob("score_nms") + classids = workspace.FetchBlob("class_nms") + boxes = workspace.FetchBlob("bbox_nms") except Exception as e: - print('Running pb model failed.\n{}'.format(e)) + print("Running pb model failed.\n{}".format(e)) # may not detect anything at all R = 0 scores = np.zeros((R,), dtype=np.float32) @@ -552,12 +578,11 @@ def run_model_pb(args, net, init_net, im, check_blobs): boxes = np.column_stack((boxes, scores)) # sort the results based on score for comparision - boxes, _, _, classids = _sort_results( - boxes, None, None, classids) + boxes, _, _, classids = _sort_results(boxes, None, None, classids) # write final result back to workspace - workspace.FeedBlob('result_boxes', boxes) - workspace.FeedBlob('result_classids', classids) + workspace.FeedBlob("result_boxes", boxes) + workspace.FeedBlob("result_classids", classids) ret = _get_result_blobs(check_blobs) @@ -565,11 +590,9 @@ def run_model_pb(args, net, init_net, im, check_blobs): def verify_model(args, model_pb, test_img_file): - check_blobs = [ - "result_boxes", "result_classids", # result - ] + check_blobs = ["result_boxes", "result_classids"] # result - print('Loading test file {}...'.format(test_img_file)) + print("Loading test file {}...".format(test_img_file)) test_img = cv2.imread(test_img_file) assert test_img is not None @@ -579,15 +602,36 @@ def _run_cfg_func(im, blobs): def _run_pb_func(im, blobs): return run_model_pb(args, model_pb[0], model_pb[1], im, check_blobs) - print('Checking models...') - assert mutils.compare_model( - _run_cfg_func, _run_pb_func, test_img, check_blobs) + print("Checking models...") + assert mutils.compare_model(_run_cfg_func, _run_pb_func, test_img, check_blobs) + + +def _export_to_logfiledb(args, net, init_net, inputs, out_file, extra_out_tensors=None): + out_tensors = list(net.Proto().external_output) + if extra_out_tensors is not None: + out_tensors += extra_out_tensors + params = list(set(net.Proto().external_input) - set(inputs)) + net_type = None + predictor_export_meta = predictor_exporter.PredictorExportMeta( + predict_net=net, + parameters=params, + inputs=inputs, + outputs=out_tensors, + net_type=net_type, + ) + + logger.info("Exporting Caffe2 model to {}".format(out_file)) + predictor_exporter.save_to_db( + db_type="log_file_db", + db_destination=out_file, + predictor_export_meta=predictor_export_meta, + ) def main(): - workspace.GlobalInit(['caffe2', '--caffe2_log_level=0']) + workspace.GlobalInit(["caffe2", "--caffe2_log_level=0"]) args = parse_args() - logger.info('Called with args:') + logger.info("Called with args:") logger.info(args) if args.cfg_file is not None: merge_cfg_from_file(args.cfg_file) @@ -595,7 +639,7 @@ def main(): merge_cfg_from_list(args.opts) cfg.NUM_GPUS = 1 assert_and_infer_cfg() - logger.info('Converting model with config:') + logger.info("Converting model with config:") logger.info(pprint.pformat(cfg)) # script will stop when it can't find an operator rather @@ -609,14 +653,12 @@ def main(): # load model from cfg model, blobs = load_model(args) - net = core.Net('') + net = core.Net("") net.Proto().op.extend(copy.deepcopy(model.net.Proto().op)) - net.Proto().external_input.extend( - copy.deepcopy(model.net.Proto().external_input)) - net.Proto().external_output.extend( - copy.deepcopy(model.net.Proto().external_output)) + net.Proto().external_input.extend(copy.deepcopy(model.net.Proto().external_input)) + net.Proto().external_output.extend(copy.deepcopy(model.net.Proto().external_output)) net.Proto().type = args.net_execution_type - net.Proto().num_workers = 1 if args.net_execution_type == 'simple' else 4 + net.Proto().num_workers = 1 if args.net_execution_type == "simple" else 4 # Reset the device_option, change to unscope name and replace python operators convert_net(args, net.Proto(), blobs) @@ -625,18 +667,17 @@ def main(): add_bbox_ops(args, net, blobs) if args.fuse_af: - print('Fusing affine channel...') - net, blobs = mutils.fuse_net_affine( - net, blobs) + print("Fusing affine channel...") + net, blobs = mutils.fuse_net_affine(net, blobs) if args.use_nnpack: mutils.update_mobile_engines(net.Proto()) # generate init net - empty_blobs = ['data', 'im_info'] + empty_blobs = ["data", "im_info"] init_net = gen_init_net(net, blobs, empty_blobs) - if args.device == 'gpu': + if args.device == "gpu": [net, init_net] = convert_model_gpu(args, net, init_net) net.Proto().name = args.net_name @@ -645,8 +686,11 @@ def main(): if args.test_img is not None: verify_model(args, [net, init_net], args.test_img) - _save_models(net, init_net, args) - + if args.logdb == 1: + output_file = os.path.join(args.out_dir, "model.logfiledb") + _export_to_logfiledb(args, net, init_net, empty_blobs, output_file) + else: + _save_models(net, init_net, args) -if __name__ == '__main__': +if __name__ == "__main__": main() diff --git a/tools/convert_selective_search.py b/tools/convert_selective_search.py index f2427ec..c98ae74 100644 --- a/tools/convert_selective_search.py +++ b/tools/convert_selective_search.py @@ -1,4 +1,4 @@ -#!/usr/bin/env python2 +#!/usr/bin/env python # Copyright (c) 2017-present, Facebook, Inc. # @@ -24,12 +24,13 @@ from __future__ import print_function from __future__ import unicode_literals -import cPickle as pickle import numpy as np import scipy.io as sio import sys from detectron.datasets.json_dataset import JsonDataset +from detectron.utils.io import save_object + if __name__ == '__main__': dataset_name = sys.argv[1] @@ -53,8 +54,4 @@ scores.append(np.zeros((i_boxes.shape[0]), dtype=np.float32)) ids.append(roidb[i]['id']) - with open(file_out, 'wb') as f: - pickle.dump( - dict(boxes=boxes, scores=scores, indexes=ids), f, - pickle.HIGHEST_PROTOCOL - ) + save_object(dict(boxes=boxes, scores=scores, indexes=ids), file_out) diff --git a/tools/generate_testdev_from_test.py b/tools/generate_testdev_from_test.py index 9ac907d..9d4b515 100644 --- a/tools/generate_testdev_from_test.py +++ b/tools/generate_testdev_from_test.py @@ -1,4 +1,4 @@ -#!/usr/bin/env python2 +#!/usr/bin/env python # Copyright (c) 2017-present, Facebook, Inc. # diff --git a/tools/infer.py b/tools/infer.py index de2ee17..1c01996 100644 --- a/tools/infer.py +++ b/tools/infer.py @@ -1,4 +1,4 @@ -#!/usr/bin/env python2 +#!/usr/bin/env python # Copyright (c) 2017-present, Facebook, Inc. # @@ -32,7 +32,6 @@ import logging import os import sys -import yaml from caffe2.python import workspace @@ -47,6 +46,7 @@ import detectron.core.test_engine as model_engine import detectron.datasets.dummy_datasets as dummy_datasets import detectron.utils.c2 as c2_utils +import detectron.utils.env as envu import detectron.utils.vis as vis_utils c2_utils.import_detectron_ops() @@ -119,7 +119,7 @@ def get_rpn_box_proposals(im, args): def main(args): logger = logging.getLogger(__name__) dummy_coco_dataset = dummy_datasets.get_coco_dataset() - cfg_orig = load_cfg(yaml.dump(cfg)) + cfg_orig = load_cfg(envu.yaml_dump(cfg)) im = cv2.imread(args.im_file) if args.rpn_pkl is not None: diff --git a/tools/infer_simple.py b/tools/infer_simple.py index 721d1c8..63506ba 100644 --- a/tools/infer_simple.py +++ b/tools/infer_simple.py @@ -1,4 +1,4 @@ -#!/usr/bin/env python2 +#!/usr/bin/env python # Copyright (c) 2017-present, Facebook, Inc. # @@ -89,9 +89,6 @@ def parse_args(): help='output image even when no object is found', action='store_true' ) - parser.add_argument( - 'im_or_folder', help='image or folder of images', default=None - ) parser.add_argument( '--output-ext', dest='output_ext', @@ -99,6 +96,23 @@ def parse_args(): default='pdf', type=str ) + parser.add_argument( + '--thresh', + dest='thresh', + help='Threshold for visualizing detections', + default=0.7, + type=float + ) + parser.add_argument( + '--kp-thresh', + dest='kp_thresh', + help='Threshold for visualizing keypoints', + default=2.0, + type=float + ) + parser.add_argument( + 'im_or_folder', help='image or folder of images', default=None + ) if len(sys.argv) == 1: parser.print_help() sys.exit(1) @@ -157,8 +171,8 @@ def main(args): dataset=dummy_coco_dataset, box_alpha=0.3, show_class=True, - thresh=0.7, - kp_thresh=2, + thresh=args.thresh, + kp_thresh=args.kp_thresh, ext=args.output_ext, out_when_no_box=args.out_when_no_box ) diff --git a/tools/pickle_caffe_blobs.py b/tools/pickle_caffe_blobs.py index af6bf2b..e8dc238 100644 --- a/tools/pickle_caffe_blobs.py +++ b/tools/pickle_caffe_blobs.py @@ -1,4 +1,4 @@ -#!/usr/bin/env python2 +#!/usr/bin/env python # Copyright (c) 2017-present, Facebook, Inc. # @@ -26,7 +26,6 @@ from __future__ import unicode_literals import argparse -import cPickle as pickle import numpy as np import os import sys @@ -37,6 +36,7 @@ from caffe2.python import utils from google.protobuf import text_format +from detectron.utils.io import save_object def parse_args(): parser = argparse.ArgumentParser( @@ -93,8 +93,7 @@ def pickle_weights(out_file_name, weights): normalize_resnet_name(blob.name): utils.Caffe2TensorToNumpyArray(blob) for blob in weights.protos } - with open(out_file_name, 'w') as f: - pickle.dump(blobs, f, protocol=pickle.HIGHEST_PROTOCOL) + save_object(blobs, out_file_name) print('Wrote blobs:') print(sorted(blobs.keys())) diff --git a/tools/reval.py b/tools/reval.py index 2348513..c8138a9 100755 --- a/tools/reval.py +++ b/tools/reval.py @@ -1,4 +1,4 @@ -#!/usr/bin/env python2 +#!/usr/bin/env python # Copyright (c) 2017-present, Facebook, Inc. # @@ -31,14 +31,13 @@ from __future__ import unicode_literals import argparse -import cPickle as pickle import os import sys -import yaml from detectron.core.config import cfg from detectron.datasets import task_evaluation from detectron.datasets.json_dataset import JsonDataset +from detectron.utils.io import load_object from detectron.utils.logging import setup_logging import detectron.core.config as core_config @@ -85,8 +84,8 @@ def parse_args(): def do_reval(dataset_name, output_dir, args): dataset = JsonDataset(dataset_name) - with open(os.path.join(output_dir, 'detections.pkl'), 'rb') as f: - dets = pickle.load(f) + dets = load_object(os.path.join(output_dir, 'detections.pkl')) + # Override config with the one saved in the detections file if args.cfg_file is not None: core_config.merge_cfg_from_cfg(core_config.load_cfg(dets['cfg'])) diff --git a/tools/test_net.py b/tools/test_net.py index a0be84e..4afa4c6 100755 --- a/tools/test_net.py +++ b/tools/test_net.py @@ -1,4 +1,4 @@ -#!/usr/bin/env python2 +#!/usr/bin/env python # Copyright (c) 2017-present, Facebook, Inc. # diff --git a/tools/train_net.py b/tools/train_net.py index 33483e2..9e757b5 100755 --- a/tools/train_net.py +++ b/tools/train_net.py @@ -1,4 +1,4 @@ -#!/usr/bin/env python2 +#!/usr/bin/env python # Copyright (c) 2017-present, Facebook, Inc. # diff --git a/tools/visualize_results.py b/tools/visualize_results.py index fb78129..fc83e44 100644 --- a/tools/visualize_results.py +++ b/tools/visualize_results.py @@ -1,4 +1,4 @@ -#!/usr/bin/env python2 +#!/usr/bin/env python # Copyright (c) 2017-present, Facebook, Inc. # @@ -23,12 +23,12 @@ from __future__ import unicode_literals import argparse -import cPickle as pickle import cv2 import os import sys from detectron.datasets.json_dataset import JsonDataset +from detectron.utils.io import load_object import detectron.utils.vis as vis_utils # OpenCL may be enabled by default in OpenCV3; disable it because it's not @@ -84,8 +84,7 @@ def vis(dataset, detections_pkl, thresh, output_dir, limit=0): ds = JsonDataset(dataset) roidb = ds.get_roidb() - with open(detections_pkl, 'r') as f: - dets = pickle.load(f) + dets = load_object(detections_pkl) assert all(k in dets for k in ['all_boxes', 'all_segms', 'all_keyps']), \ 'Expected detections pkl file in the format used by test_engine.py'