update codes

mmdet/configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_ms_poly_1x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .mask_rcnn_r50_fpn_1x_coco import *
+
+from mmcv.transforms import RandomChoiceResize
+from mmengine.model.weight_init import PretrainedInit
+
+model = dict(
+    # use caffe img_norm
+    data_preprocessor=dict(
+        mean=[103.530, 116.280, 123.675],
+        std=[1.0, 1.0, 1.0],
+        bgr_to_rgb=False),
+    backbone=dict(
+        norm_cfg=dict(requires_grad=False),
+        style='caffe',
+        init_cfg=dict(
+            type=PretrainedInit,
+            checkpoint='open-mmlab://detectron2/resnet50_caffe')))
+train_pipeline = [
+    dict(type=LoadImageFromFile, backend_args={{_base_.backend_args}}),
+    dict(
+        type=LoadAnnotations, with_bbox=True, with_mask=True, poly2mask=False),
+    dict(
+        type=RandomChoiceResize,
+        scales=[(1333, 640), (1333, 672), (1333, 704), (1333, 736),
+                (1333, 768), (1333, 800)],
+        keep_ratio=True),
+    dict(type=RandomFlip, prob=0.5),
+    dict(type=PackDetInputs)
+]
+
+train_dataloader.update(dict(dataset=dict(pipeline=train_pipeline)))

mmdet/configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_ms_poly_2x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .mask_rcnn_r50_caffe_fpn_ms_poly_1x_coco import *
+
+train_cfg = dict(max_epochs=24)
+# learning rate
+param_scheduler = [
+    dict(type=LinearLR, start_factor=0.001, by_epoch=False, begin=0, end=500),
+    dict(
+        type=MultiStepLR,
+        begin=0,
+        end=24,
+        by_epoch=True,
+        milestones=[16, 22],
+        gamma=0.1)
+]

mmdet/configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_ms_poly_3x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .mask_rcnn_r50_caffe_fpn_ms_poly_1x_coco import *
+
+train_cfg = dict(max_epochs=36)
+# learning rate
+param_scheduler = [
+    dict(type=LinearLR, start_factor=0.001, by_epoch=False, begin=0, end=500),
+    dict(
+        type=MultiStepLR,
+        begin=0,
+        end=24,
+        by_epoch=True,
+        milestones=[28, 34],
+        gamma=0.1)
+]

mmdet/configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_poly_1x_coco_v1.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .mask_rcnn_r50_fpn_1x_coco import *
+
+from mmengine.model.weight_init import PretrainedInit
+
+from mmdet.models.losses import SmoothL1Loss
+
+model = dict(
+    # use caffe img_norm
+    data_preprocessor=dict(
+        mean=[103.530, 116.280, 123.675],
+        std=[1.0, 1.0, 1.0],
+        bgr_to_rgb=False),
+    backbone=dict(
+        norm_cfg=dict(requires_grad=False),
+        style='caffe',
+        init_cfg=dict(
+            type=PretrainedInit,
+            checkpoint='open-mmlab://detectron2/resnet50_caffe')),
+    rpn_head=dict(
+        loss_bbox=dict(type=SmoothL1Loss, beta=1.0 / 9.0, loss_weight=1.0)),
+    roi_head=dict(
+        bbox_roi_extractor=dict(
+            roi_layer=dict(
+                type=RoIAlign, output_size=7, sampling_ratio=2,
+                aligned=False)),
+        bbox_head=dict(
+            loss_bbox=dict(type=SmoothL1Loss, beta=1.0, loss_weight=1.0)),
+        mask_roi_extractor=dict(
+            roi_layer=dict(
+                type=RoIAlign, output_size=14, sampling_ratio=2,
+                aligned=False))))

mmdet/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .._base_.datasets.coco_instance import *
+    from .._base_.default_runtime import *
+    from .._base_.models.mask_rcnn_r50_fpn import *
+    from .._base_.schedules.schedule_1x import *

mmdet/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_wandb_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .._base_.datasets.coco_instance import *
+    from .._base_.default_runtime import *
+    from .._base_.models.mask_rcnn_r50_fpn import *
+    from .._base_.schedules.schedule_1x import *
+
+from mmengine.visualization import LocalVisBackend, WandbVisBackend
+
+vis_backends.update(dict(type=WandbVisBackend))
+vis_backends.update(dict(type=LocalVisBackend))
+visualizer.update(dict(vis_backends=vis_backends))
+
+# MMEngine support the following two ways, users can choose
+# according to convenience
+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+default_hooks.update(dict(checkpoint=dict(interval=4)))
+
+train_cfg.update(dict(val_interval=2))

mmdet/configs/mask_rcnn/mask_rcnn_r50_fpn_2x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .._base_.datasets.coco_instance import *
+    from .._base_.default_runtime import *
+    from .._base_.models.mask_rcnn_r50_fpn import *
+    from .._base_.schedules.schedule_2x import *

mmdet/configs/mask_rcnn/mask_rcnn_r50_fpn_8xb8_amp_lsj_200e_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.

mmdet/configs/mask_rcnn/mask_rcnn_r50_fpn_amp_1x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .mask_rcnn_r50_fpn_1x_coco import *
+
+from mmengine.optim.optimizer.amp_optimizer_wrapper import AmpOptimWrapper
+
+optim_wrapper.update(dict(type=AmpOptimWrapper))

mmdet/configs/mask_rcnn/mask_rcnn_r50_fpn_ms_poly_-3x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .._base_.models.mask_rcnn_r50_fpn import *
+    from ..common.ms_poly_3x_coco_instance import *

mmdet/configs/mask_rcnn/mask_rcnn_r50_fpn_poly_1x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .._base_.datasets.coco_instance import *
+    from .._base_.default_runtime import *
+    from .._base_.models.mask_rcnn_r50_fpn import *
+    from .._base_.schedules.schedule_1x import *
+
+train_pipeline = [
+    dict(type=LoadImageFromFile, backend_args=backend_args),
+    dict(
+        type=LoadAnnotations, with_bbox=True, with_mask=True, poly2mask=False),
+    dict(type=Resize, scale=(1333, 800), keep_ratio=True),
+    dict(type=RandomFlip, prob=0.5),
+    dict(type=PackDetInputs),
+]
+train_dataloader.update(dict(dataset=dict(pipeline=train_pipeline)))

mmdet/configs/mask_rcnn/mask_rcnn_x101_32x4d_fpn_1x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .mask_rcnn_r101_fpn_1x_coco import *
+
+from mmengine.model.weight_init import PretrainedInit
+
+from mmdet.models.backbones.resnext import ResNeXt
+
+model = dict(
+    backbone=dict(
+        type=ResNeXt,
+        depth=101,
+        groups=32,
+        base_width=4,
+        num_stages=4,
+        out_indices=(0, 1, 2, 3),
+        frozen_stages=1,
+        norm_cfg=dict(type=BatchNorm2d, requires_grad=True),
+        style='pytorch',
+        init_cfg=dict(
+            type=PretrainedInit, checkpoint='open-mmlab://resnext101_32x4d')))

mmdet/configs/mask_rcnn/mask_rcnn_x101_32x4d_fpn_2x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .mask_rcnn_r50_fpn_2x_coco import *
+
+from mmengine.model.weight_init import PretrainedInit
+
+from mmdet.models import ResNeXt
+
+model = dict(
+    backbone=dict(
+        type=ResNeXt,
+        depth=101,
+        groups=32,
+        base_width=4,
+        num_stages=4,
+        out_indices=(0, 1, 2, 3),
+        frozen_stages=1,
+        norm_cfg=dict(type=BatchNorm2d, requires_grad=True),
+        style='pytorch',
+        init_cfg=dict(
+            type=PretrainedInit, checkpoint='open-mmlab://resnext101_32x4d')))

mmdet/configs/mask_rcnn/mask_rcnn_x101_32x4d_fpn_ms_poly_3x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from ..common.ms_poly_3x_coco_instance import *
+    from .._base_.models.mask_rcnn_r50_fpn import *
+
+from mmengine.model.weight_init import PretrainedInit
+
+from mmdet.models.backbones import ResNeXt
+
+model = dict(
+    backbone=dict(
+        type=ResNeXt,
+        depth=101,
+        groups=32,
+        base_width=4,
+        num_stages=4,
+        out_indices=(0, 1, 2, 3),
+        frozen_stages=1,
+        norm_cfg=dict(type=BatchNorm2d, requires_grad=True),
+        style='pytorch',
+        init_cfg=dict(
+            type=PretrainedInit, checkpoint='open-mmlab://resnext101_32x4d')))

mmdet/configs/mask_rcnn/mask_rcnn_x101_32x8d_fpn_1x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .mask_rcnn_x101_32x4d_fpn_1x_coco import *
+
+model = dict(
+    # ResNeXt-101-32x8d model trained with Caffe2 at FB,
+    # so the mean and std need to be changed.
+    data_preprocessor=dict(
+        mean=[103.530, 116.280, 123.675],
+        std=[57.375, 57.120, 58.395],
+        bgr_to_rgb=False),
+    backbone=dict(
+        type=ResNeXt,
+        depth=101,
+        groups=32,
+        base_width=8,
+        num_stages=4,
+        out_indices=(0, 1, 2, 3),
+        frozen_stages=1,
+        norm_cfg=dict(type=BatchNorm2d, requires_grad=False),
+        style='pytorch',
+        init_cfg=dict(
+            type=PretrainedInit,
+            checkpoint='open-mmlab://detectron2/resnext101_32x8d')))

mmdet/configs/mask_rcnn/mask_rcnn_x101_32x8d_fpn_ms_poly_1x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .mask_rcnn_r101_fpn_1x_coco import *
+
+from mmcv.transforms import RandomChoiceResize, RandomFlip
+from mmcv.transforms.loading import LoadImageFromFile
+
+from mmdet.datasets.transforms.formatting import PackDetInputs
+from mmdet.datasets.transforms.loading import LoadAnnotations
+from mmdet.models.backbones import ResNeXt
+
+model = dict(
+    # ResNeXt-101-32x8d model trained with Caffe2 at FB,
+    # so the mean and std need to be changed.
+    data_preprocessor=dict(
+        mean=[103.530, 116.280, 123.675],
+        std=[57.375, 57.120, 58.395],
+        bgr_to_rgb=False),
+    backbone=dict(
+        type=ResNeXt,
+        depth=101,
+        groups=32,
+        base_width=8,
+        num_stages=4,
+        out_indices=(0, 1, 2, 3),
+        frozen_stages=1,
+        norm_cfg=dict(type=BatchNorm2d, requires_grad=False),
+        style='pytorch',
+        init_cfg=dict(
+            type=PretrainedInit,
+            checkpoint='open-mmlab://detectron2/resnext101_32x8d')))
+
+backend_args = None
+train_pipeline = [
+    dict(type=LoadImageFromFile, backend_args=backend_args),
+    dict(
+        type=LoadAnnotations, with_bbox=True, with_mask=True, poly2mask=False),
+    dict(
+        type=RandomChoiceResize,
+        scales=[(1333, 640), (1333, 672), (1333, 704), (1333, 736),
+                (1333, 768), (1333, 800)],
+        keep_ratio=True),
+    dict(type=RandomFlip, prob=0.5),
+    dict(type=PackDetInputs),
+]
+
+train_dataloader = dict(dataset=dict(pipeline=train_pipeline))

mmdet/configs/mask_rcnn/mask_rcnn_x101_32x8d_fpn_ms_poly_3x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from ..common.ms_poly_3x_coco_instance import *
+    from .._base_.models.mask_rcnn_r50_fpn import *
+
+from mmdet.models.backbones import ResNeXt
+
+model = dict(
+    # ResNeXt-101-32x8d model trained with Caffe2 at FB,
+    # so the mean and std need to be changed.
+    data_preprocessor=dict(
+        mean=[103.530, 116.280, 123.675],
+        std=[57.375, 57.120, 58.395],
+        bgr_to_rgb=False),
+    backbone=dict(
+        type=ResNeXt,
+        depth=101,
+        groups=32,
+        base_width=8,
+        num_stages=4,
+        out_indices=(0, 1, 2, 3),
+        frozen_stages=1,
+        norm_cfg=dict(type=BatchNorm2d, requires_grad=False),
+        style='pytorch',
+        init_cfg=dict(
+            type=PretrainedInit,
+            checkpoint='open-mmlab://detectron2/resnext101_32x8d')))

mmdet/configs/mask_rcnn/mask_rcnn_x101_64_4d_fpn_1x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .mask_rcnn_x101_32x4d_fpn_1x_coco import *
+
+model = dict(
+    backbone=dict(
+        type=ResNeXt,
+        depth=101,
+        groups=64,
+        base_width=4,
+        num_stages=4,
+        out_indices=(0, 1, 2, 3),
+        frozen_stages=1,
+        norm_cfg=dict(type=BatchNorm2d, requires_grad=True),
+        style='pytorch',
+        init_cfg=dict(
+            type=PretrainedInit, checkpoint='open-mmlab://resnext101_64x4d')))

mmdet/configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_2x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from .mask_rcnn_x101_32x4d_fpn_2x_coco import *
+
+model = dict(
+    backbone=dict(
+        type=ResNeXt,
+        depth=101,
+        groups=64,
+        base_width=4,
+        num_stages=4,
+        out_indices=(0, 1, 2, 3),
+        frozen_stages=1,
+        norm_cfg=dict(type=BatchNorm2d, requires_grad=True),
+        style='pytorch',
+        init_cfg=dict(
+            type=PretrainedInit, checkpoint='open-mmlab://resnext101_64x4d')))

mmdet/configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_ms_poly_3x_coco.py

+# Copyright (c) OpenMMLab. All rights reserved.
+
+# Please refer to https://mmengine.readthedocs.io/en/latest/advanced_tutorials/config.html#a-pure-python-style-configuration-file-beta for more details. # noqa
+# mmcv >= 2.0.1
+# mmengine >= 0.8.0
+
+from mmengine.config import read_base
+
+with read_base():
+    from ..common.ms_poly_3x_coco_instance import *
+    from .._base_.models.mask_rcnn_r50_fpn import *
+
+from mmdet.models.backbones import ResNeXt
+
+model = dict(
+    backbone=dict(
+        type=ResNeXt,
+        depth=101,
+        groups=64,
+        base_width=4,
+        num_stages=4,
+        out_indices=(0, 1, 2, 3),
+        frozen_stages=1,
+        norm_cfg=dict(type=BatchNorm2d, requires_grad=True),
+        style='pytorch',
+        init_cfg=dict(
+            type=PretrainedInit, checkpoint='open-mmlab://resnext101_64x4d')))