添加openmmlab测试用例

openmmlab_test/mmdetection-speed_xinpian/configs/empirical_attention/faster_rcnn_r50_fpn_attention_1111_1x_coco.py

+_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'
+model = dict(
+    backbone=dict(plugins=[
+        dict(
+            cfg=dict(
+                type='GeneralizedAttention',
+                spatial_range=-1,
+                num_heads=8,
+                attention_type='1111',
+                kv_stride=2),
+            stages=(False, False, True, True),
+            position='after_conv2')
+    ]))

openmmlab_test/mmdetection-speed_xinpian/configs/empirical_attention/faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco.py

+_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'
+model = dict(
+    backbone=dict(
+        plugins=[
+            dict(
+                cfg=dict(
+                    type='GeneralizedAttention',
+                    spatial_range=-1,
+                    num_heads=8,
+                    attention_type='1111',
+                    kv_stride=2),
+                stages=(False, False, True, True),
+                position='after_conv2')
+        ],
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
+        stage_with_dcn=(False, True, True, True)))

openmmlab_test/mmdetection-speed_xinpian/configs/empirical_attention/metafile.yml

+Collections:
+  - Name: Empirical Attention
+    Metadata:
+      Training Data: COCO
+      Training Techniques:
+        - SGD with Momentum
+        - Weight Decay
+      Training Resources: 8x NVIDIA V100 GPUs
+      Architecture:
+        - Deformable Convolution
+        - FPN
+        - RPN
+        - ResNet
+        - RoIAlign
+        - Spatial Attention
+    Paper: https://arxiv.org/pdf/1904.05873
+    README: configs/empirical_attention/README.md
+
+Models:
+  - Name: faster_rcnn_r50_fpn_attention_1111_1x_coco
+    In Collection: Empirical Attention
+    Config: configs/empirical_attention/faster_rcnn_r50_fpn_attention_1111_1x_coco.py
+    Metadata:
+      Training Memory (GB): 8.0
+      inference time (s/im): 0.07246
+      Epochs: 12
+    Results:
+      - Task: Object Detection
+        Dataset: COCO
+        Metrics:
+          box AP: 40.0
+    Weights: https://download.openmmlab.com/mmdetection/v2.0/empirical_attention/faster_rcnn_r50_fpn_attention_1111_1x_coco/faster_rcnn_r50_fpn_attention_1111_1x_coco_20200130-403cccba.pth
+
+  - Name: faster_rcnn_r50_fpn_attention_0010_1x_coco
+    In Collection: Empirical Attention
+    Config: configs/empirical_attention/faster_rcnn_r50_fpn_attention_0010_1x_coco.py
+    Metadata:
+      Training Memory (GB): 4.2
+      inference time (s/im): 0.05435
+      Epochs: 12
+    Results:
+      - Task: Object Detection
+        Dataset: COCO
+        Metrics:
+          box AP: 39.1
+    Weights: https://download.openmmlab.com/mmdetection/v2.0/empirical_attention/faster_rcnn_r50_fpn_attention_0010_1x_coco/faster_rcnn_r50_fpn_attention_0010_1x_coco_20200130-7cb0c14d.pth
+
+  - Name: faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco
+    In Collection: Empirical Attention
+    Config: configs/empirical_attention/faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco.py
+    Metadata:
+      Training Memory (GB): 8.0
+      inference time (s/im): 0.07874
+      Epochs: 12
+    Results:
+      - Task: Object Detection
+        Dataset: COCO
+        Metrics:
+          box AP: 42.1
+    Weights: https://download.openmmlab.com/mmdetection/v2.0/empirical_attention/faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco/faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco_20200130-8b2523a6.pth
+
+  - Name: faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco
+    In Collection: Empirical Attention
+    Config: configs/empirical_attention/faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco.py
+    Metadata:
+      Training Memory (GB): 4.2
+      inference time (s/im): 0.05848
+      Epochs: 12
+    Results:
+      - Task: Object Detection
+        Dataset: COCO
+        Metrics:
+          box AP: 42.0
+    Weights: https://download.openmmlab.com/mmdetection/v2.0/empirical_attention/faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco/faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco_20200130-1a2e831d.pth

openmmlab_test/mmdetection-speed_xinpian/configs/fast_rcnn/README.md

+# Fast R-CNN
+
+## Introduction
+
+<!-- [ALGORITHM] -->
+
+```latex
+@inproceedings{girshick2015fast,
+  title={Fast r-cnn},
+  author={Girshick, Ross},
+  booktitle={Proceedings of the IEEE international conference on computer vision},
+  year={2015}
+}
+```
+
+## Results and models

openmmlab_test/mmdetection-speed_xinpian/configs/fast_rcnn/fast_rcnn_r101_caffe_fpn_1x_coco.py

+_base_ = './fast_rcnn_r50_caffe_fpn_1x_coco.py'
+model = dict(
+    pretrained='open-mmlab://detectron2/resnet101_caffe',
+    backbone=dict(depth=101))

openmmlab_test/mmdetection-speed_xinpian/configs/fast_rcnn/fast_rcnn_r101_fpn_1x_coco.py

+_base_ = './fast_rcnn_r50_fpn_1x_coco.py'
+model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))

openmmlab_test/mmdetection-speed_xinpian/configs/fast_rcnn/fast_rcnn_r101_fpn_2x_coco.py

+_base_ = './fast_rcnn_r50_fpn_2x_coco.py'
+model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))

openmmlab_test/mmdetection-speed_xinpian/configs/fast_rcnn/fast_rcnn_r50_caffe_fpn_1x_coco.py

+_base_ = './fast_rcnn_r50_fpn_1x_coco.py'
+
+model = dict(
+    pretrained='open-mmlab://detectron2/resnet50_caffe',
+    backbone=dict(
+        norm_cfg=dict(type='BN', requires_grad=False), style='caffe'))
+
+# use caffe img_norm
+img_norm_cfg = dict(
+    mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)
+train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='LoadProposals', num_max_proposals=2000),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='Pad', size_divisor=32),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'proposals', 'gt_bboxes', 'gt_labels']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='LoadProposals', num_max_proposals=None),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(1333, 800),
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='Pad', size_divisor=32),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='ToTensor', keys=['proposals']),
+            dict(
+                type='ToDataContainer',
+                fields=[dict(key='proposals', stack=False)]),
+            dict(type='Collect', keys=['img', 'proposals']),
+        ])
+]
+data = dict(
+    train=dict(pipeline=train_pipeline),
+    val=dict(pipeline=test_pipeline),
+    test=dict(pipeline=test_pipeline))

openmmlab_test/mmdetection-speed_xinpian/configs/fast_rcnn/fast_rcnn_r50_fpn_1x_coco.py

+_base_ = [
+    '../_base_/models/fast_rcnn_r50_fpn.py',
+    '../_base_/datasets/coco_detection.py',
+    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
+]
+dataset_type = 'CocoDataset'
+data_root = 'data/coco/'
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='LoadProposals', num_max_proposals=2000),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='Pad', size_divisor=32),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'proposals', 'gt_bboxes', 'gt_labels']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='LoadProposals', num_max_proposals=None),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(1333, 800),
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='Pad', size_divisor=32),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='ToTensor', keys=['proposals']),
+            dict(
+                type='ToDataContainer',
+                fields=[dict(key='proposals', stack=False)]),
+            dict(type='Collect', keys=['img', 'proposals']),
+        ])
+]
+data = dict(
+    samples_per_gpu=2,
+    workers_per_gpu=2,
+    train=dict(
+        proposal_file=data_root + 'proposals/rpn_r50_fpn_1x_train2017.pkl',
+        pipeline=train_pipeline),
+    val=dict(
+        proposal_file=data_root + 'proposals/rpn_r50_fpn_1x_val2017.pkl',
+        pipeline=test_pipeline),
+    test=dict(
+        proposal_file=data_root + 'proposals/rpn_r50_fpn_1x_val2017.pkl',
+        pipeline=test_pipeline))

openmmlab_test/mmdetection-speed_xinpian/configs/fast_rcnn/fast_rcnn_r50_fpn_2x_coco.py

+_base_ = './fast_rcnn_r50_fpn_1x_coco.py'
+
+# learning policy
+lr_config = dict(step=[16, 22])
+runner = dict(type='EpochBasedRunner', max_epochs=24)

openmmlab_test/mmdetection-speed_xinpian/configs/faster_rcnn/README.md

+# Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
+
+## Introduction
+
+<!-- [ALGORITHM] -->
+
+```latex
+@article{Ren_2017,
+   title={Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks},
+   journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
+   publisher={Institute of Electrical and Electronics Engineers (IEEE)},
+   author={Ren, Shaoqing and He, Kaiming and Girshick, Ross and Sun, Jian},
+   year={2017},
+   month={Jun},
+}
+```
+
+## Results and models
+
+|    Backbone     |  Style  | Lr schd | Mem (GB) | Inf time (fps) | box AP | Config | Download |
+| :-------------: | :-----: | :-----: | :------: | :------------: | :----: | :------: | :--------: |
+|    R-50-DC5     |  caffe  |   1x    | -        | -              | 37.2   | [config](https://github.com/open-mmlab/mmdetection/blob/master/configs/faster_rcnn/faster_rcnn_r50_caffe_dc5_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_caffe_dc5_1x_coco/faster_rcnn_r50_caffe_dc5_1x_coco_20201030_151909-531f0f43.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_caffe_dc5_1x_coco/faster_rcnn_r50_caffe_dc5_1x_coco_20201030_151909.log.json) |
+|    R-50-FPN     |  caffe  |   1x    | 3.8      |                | 37.8   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_caffe_fpn_1x_coco/faster_rcnn_r50_caffe_fpn_1x_coco_bbox_mAP-0.378_20200504_180032-c5925ee5.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_caffe_fpn_1x_coco/faster_rcnn_r50_caffe_fpn_1x_coco_20200504_180032.log.json) |
+|    R-50-FPN     | pytorch |   1x    | 4.0      | 21.4           | 37.4   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_1x_coco_20200130-047c8118.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_1x_coco_20200130_204655.log.json) |
+|    R-50-FPN     | pytorch |   2x    | -        | -              | 38.4   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r50_fpn_2x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_2x_coco/faster_rcnn_r50_fpn_2x_coco_bbox_mAP-0.384_20200504_210434-a5d8aa15.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_2x_coco/faster_rcnn_r50_fpn_2x_coco_20200504_210434.log.json) |
+|    R-101-FPN    |  caffe  |   1x    | 5.7      |                | 39.8   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r101_caffe_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r101_caffe_fpn_1x_coco/faster_rcnn_r101_caffe_fpn_1x_coco_bbox_mAP-0.398_20200504_180057-b269e9dd.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r101_caffe_fpn_1x_coco/faster_rcnn_r101_caffe_fpn_1x_coco_20200504_180057.log.json) |
+|    R-101-FPN    | pytorch |   1x    | 6.0      | 15.6           | 39.4   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r101_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r101_fpn_1x_coco/faster_rcnn_r101_fpn_1x_coco_20200130-f513f705.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r101_fpn_1x_coco/faster_rcnn_r101_fpn_1x_coco_20200130_204655.log.json) |
+|    R-101-FPN    | pytorch |   2x    | -        | -              | 39.8   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r101_fpn_2x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r101_fpn_2x_coco/faster_rcnn_r101_fpn_2x_coco_bbox_mAP-0.398_20200504_210455-1d2dac9c.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r101_fpn_2x_coco/faster_rcnn_r101_fpn_2x_coco_20200504_210455.log.json) |
+| X-101-32x4d-FPN | pytorch |   1x    | 7.2      | 13.8           | 41.2   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_x101_32x4d_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_32x4d_fpn_1x_coco/faster_rcnn_x101_32x4d_fpn_1x_coco_20200203-cff10310.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_32x4d_fpn_1x_coco/faster_rcnn_x101_32x4d_fpn_1x_coco_20200203_000520.log.json) |
+| X-101-32x4d-FPN | pytorch |   2x    | -        | -              | 41.2   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_x101_32x4d_fpn_2x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_32x4d_fpn_2x_coco/faster_rcnn_x101_32x4d_fpn_2x_coco_bbox_mAP-0.412_20200506_041400-64a12c0b.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_32x4d_fpn_2x_coco/faster_rcnn_x101_32x4d_fpn_2x_coco_20200506_041400.log.json) |
+| X-101-64x4d-FPN | pytorch |   1x    | 10.3     | 9.4            | 42.1   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_x101_64x4d_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_64x4d_fpn_1x_coco/faster_rcnn_x101_64x4d_fpn_1x_coco_20200204-833ee192.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_64x4d_fpn_1x_coco/faster_rcnn_x101_64x4d_fpn_1x_coco_20200204_134340.log.json) |
+| X-101-64x4d-FPN | pytorch |   2x    | -        | -              | 41.6   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_x101_64x4d_fpn_2x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_64x4d_fpn_2x_coco/faster_rcnn_x101_64x4d_fpn_2x_coco_20200512_161033-5961fa95.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_64x4d_fpn_2x_coco/faster_rcnn_x101_64x4d_fpn_2x_coco_20200512_161033.log.json)  |
+
+## Different regression loss
+
+We trained with R-50-FPN pytorch style backbone for 1x schedule.
+
+|    Backbone     | Loss type | Mem (GB) | Inf time (fps) | box AP | Config | Download |
+| :-------------: | :-------: | :------: | :------------: | :----: | :------: | :--------: |
+|    R-50-FPN     |  L1Loss   | 4.0      | 21.4           | 37.4   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_1x_coco_20200130-047c8118.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_1x_coco_20200130_204655.log.json) |
+|    R-50-FPN     |  IoULoss  |          |                | 37.9   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_iou_1x_coco-fdd207f3.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_iou_1x_coco_20200506_095954.log.json)  |
+|    R-50-FPN     |  GIoULoss |          |                | 37.6   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_giou_1x_coco-0eada910.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_giou_1x_coco_20200505_161120.log.json)  |
+|    R-50-FPN     |  BoundedIoULoss |          |                | 37.4   | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_bounded_iou_1x_coco-98ad993b.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_bounded_iou_1x_coco_20200505_160738.log.json)  |
+
+## Pre-trained Models
+
+We also train some models with longer schedules and multi-scale training. The users could finetune them for downstream tasks.
+
+|    Backbone     |  Style  | Lr schd | Mem (GB) | Inf time (fps) | box AP | Config | Download |
+| :-------------: | :-----: | :-----: | :------: | :------------: | :----: | :------: | :--------: |
+|    [R-50-DC5](./faster_rcnn_r50_caffe_dc5_mstrain_1x_coco.py)          |  caffe  |   1x    | -        |                | 37.4   | [config](https://github.com/open-mmlab/mmdetection/blob/master/configs/faster_rcnn/faster_rcnn_r50_caffe_dc5_mstrain_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_caffe_dc5_mstrain_1x_coco/faster_rcnn_r50_caffe_dc5_mstrain_1x_coco_20201028_233851-b33d21b9.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_caffe_dc5_mstrain_1x_coco/faster_rcnn_r50_caffe_dc5_mstrain_1x_coco_20201028_233851.log.json) |
+|    [R-50-DC5](./faster_rcnn_r50_caffe_dc5_mstrain_3x_coco.py)          |  caffe  |   3x    | -        |                | 38.7   | [config](https://github.com/open-mmlab/mmdetection/blob/master/configs/faster_rcnn/faster_rcnn_r50_caffe_dc5_mstrain_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_caffe_dc5_mstrain_3x_coco/faster_rcnn_r50_caffe_dc5_mstrain_3x_coco_20201028_002107-34a53b2c.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_caffe_dc5_mstrain_3x_coco/faster_rcnn_r50_caffe_dc5_mstrain_3x_coco_20201028_002107.log.json) |
+|    [R-50-FPN](./faster_rcnn_r50_caffe_fpn_mstrain_2x_coco.py)     |  caffe  |   2x    | 3.7      |                | 39.7   |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_2x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_2x_coco/faster_rcnn_r50_caffe_fpn_mstrain_2x_coco_bbox_mAP-0.397_20200504_231813-10b2de58.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_2x_coco/faster_rcnn_r50_caffe_fpn_mstrain_2x_coco_20200504_231813.log.json) |
+|    [R-50-FPN](./faster_rcnn_r50_caffe_fpn_mstrain_3x_coco.py)     |  caffe  |   3x    | 3.7      |                | 39.9   |  [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_3x_coco/faster_rcnn_r50_caffe_fpn_mstrain_3x_coco_20210526_095054-f002305e.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_3x_coco/faster_rcnn_r50_caffe_fpn_mstrain_3x_coco_20210526_095054.log.json) |
+|    [R-50-FPN](./faster_rcnn_r50_fpn_mstrain_3x_coco.py)     |  pytorch  |   3x    | 3.9      |                | 40.3   |  [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r50_fpn_mstrain_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_mstrain_3x_coco/faster_rcnn_r50_fpn_mstrain_3x_coco_20210524_110822-3a066a07.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_mstrain_3x_coco/faster_rcnn_r50_caffe_fpn_mstrain_3x_coco_20210524_110822.log.json) |
+|    [R-101-FPN](./faster_rcnn_r101_caffe_fpn_mstrain_3x_coco.py)     |  caffe  |   3x    | 5.6      |                | 42.0   |  [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r101_caffe_fpn_mstrain_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r101_caffe_fpn_mstrain_3x_coco/faster_rcnn_r101_caffe_fpn_mstrain_3x_coco_20210526_095742-9178be4b.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r101_caffe_fpn_mstrain_3x_coco/faster_rcnn_r101_caffe_fpn_mstrain_3x_coco_20210526_095742.log.json) |
+|    [R-101-FPN](./faster_rcnn_r101_fpn_mstrain_3x_coco.py)     |  pytorch  |   3x    | 5.8      |                | 41.8   |  [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_r101_fpn_mstrain_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r101_fpn_mstrain_3x_coco/faster_rcnn_r101_fpn_mstrain_3x_coco_20210524_110822-78060bff.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r101_fpn_mstrain_3x_coco/faster_rcnn_r101_fpn_mstrain_3x_coco_20210524_110822.log.json) |
+|    [X-101-32x4d-FPN](./faster_rcnn_x101_32x4d_fpn_mstrain_3x_coco.py)     |  pytorch  |   3x    | 7.0      |                | 42.5   |  [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_x101_32x4d_fpn_mstrain_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_32x4d_fpn_mstrain_3x_coco/faster_rcnn_x101_32x4d_fpn_mstrain_3x_coco_20210524_124151-e8595dde.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_32x4d_fpn_mstrain_3x_coco/faster_rcnn_x101_32x4d_fpn_mstrain_3x_coco_20210524_124151.log.json) |
+|    [X-101-32x8d-FPN](./faster_rcnn_x101_32x8d_fpn_mstrain_3x_coco.py)     |  pytorch  |   3x    | 10.1      |                | 42.4   |  [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_x101_32x8d_fpn_mstrain_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_32x8d_fpn_mstrain_3x_coco/faster_rcnn_x101_32x8d_fpn_mstrain_3x_coco_20210604_182954-002e082a.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_32x8d_fpn_mstrain_3x_coco/faster_rcnn_x101_32x8d_fpn_mstrain_3x_coco_20210604_182954.log.json) |
+|    [X-101-64x4d-FPN](./faster_rcnn_x101_64x4d_fpn_mstrain_3x_coco.py)     |  pytorch  |   3x    | 10.0      |                | 43.1   |  [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/faster_rcnn/faster_rcnn_x101_64x4d_fpn_mstrain_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_64x4d_fpn_mstrain_3x_coco/faster_rcnn_x101_64x4d_fpn_mstrain_3x_coco_20210524_124528-26c63de6.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_x101_64x4d_fpn_mstrain_3x_coco/faster_rcnn_x101_64x4d_fpn_mstrain_3x_coco_20210524_124528.log.json) |
+
+We further finetune some pre-trained models on the COCO subsets, which only contain only a few of the 80 categories.
+
+| Backbone                                                     | Style | Class name         | Pre-traind model                                             | Mem (GB) | box AP | Config                                                       | Download                                                     |
+| ------------------------------------------------------------ | ----- | ------------------ | ------------------------------------------------------------ | -------- | ------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
+| [R-50-FPN](./faster_rcnn_r50_caffe_fpn_mstrain_1x_coco-person.py)          | caffe | person             | [R-50-FPN-Caffe-3x](./faster_rcnn_r50_caffe_fpn_mstrain_3x_coco.py) | 3.7      | 55.8   | [config](./faster_rcnn_r50_caffe_fpn_mstrain_1x_coco-person.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco-person/faster_rcnn_r50_fpn_1x_coco-person_20201216_175929-d022e227.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco-person/faster_rcnn_r50_fpn_1x_coco-person_20201216_175929.log.json)                                                 |
+| [R-50-FPN](./faster_rcnn_r50_caffe_fpn_mstrain_1x_coco-person-bicycle-car.py) | caffe | person-bicycle-car | [R-50-FPN-Caffe-3x](./faster_rcnn_r50_caffe_fpn_mstrain_3x_coco.py) | 3.7      | 44.1   | [config](./faster_rcnn_r50_caffe_fpn_mstrain_1x_coco-person-bicycle-car.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco-person-bicycle-car/faster_rcnn_r50_fpn_1x_coco-person-bicycle-car_20201216_173117-6eda6d92.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco-person-bicycle-car/faster_rcnn_r50_fpn_1x_coco-person-bicycle-car_20201216_173117.log.json) |

openmmlab_test/mmdetection-speed_xinpian/configs/faster_rcnn/faster_rcnn_r101_caffe_fpn_1x_coco.py

+_base_ = './faster_rcnn_r50_caffe_fpn_1x_coco.py'
+model = dict(
+    pretrained='open-mmlab://detectron2/resnet101_caffe',
+    backbone=dict(depth=101))

openmmlab_test/mmdetection-speed_xinpian/configs/faster_rcnn/faster_rcnn_r101_caffe_fpn_mstrain_3x_coco.py

+_base_ = 'faster_rcnn_r50_fpn_mstrain_3x_coco.py'
+
+model = dict(
+    pretrained='open-mmlab://detectron2/resnet101_caffe',
+    backbone=dict(
+        depth=101,
+        norm_cfg=dict(requires_grad=False),
+        norm_eval=True,
+        style='caffe'))
+
+# use caffe img_norm
+img_norm_cfg = dict(
+    mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)
+train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(
+        type='Resize',
+        img_scale=[(1333, 640), (1333, 800)],
+        multiscale_mode='range',
+        keep_ratio=True),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='Pad', size_divisor=32),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(1333, 800),
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='Pad', size_divisor=32),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img']),
+        ])
+]
+
+data = dict(
+    train=dict(dataset=dict(pipeline=train_pipeline)),
+    val=dict(pipeline=test_pipeline),
+    test=dict(pipeline=test_pipeline))

openmmlab_test/mmdetection-speed_xinpian/configs/faster_rcnn/faster_rcnn_r101_fpn_1x_coco.py

+_base_ = './faster_rcnn_r50_fpn_1x_coco.py'
+model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))

openmmlab_test/mmdetection-speed_xinpian/configs/faster_rcnn/faster_rcnn_r101_fpn_2x_coco.py

+_base_ = './faster_rcnn_r50_fpn_2x_coco.py'
+model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))

openmmlab_test/mmdetection-speed_xinpian/configs/faster_rcnn/faster_rcnn_r101_fpn_mstrain_3x_coco.py

+_base_ = 'faster_rcnn_r50_fpn_mstrain_3x_coco.py'
+
+model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))

openmmlab_test/mmdetection-speed_xinpian/configs/faster_rcnn/faster_rcnn_r50_caffe_c4_1x_coco.py

+_base_ = [
+    '../_base_/models/faster_rcnn_r50_caffe_c4.py',
+    '../_base_/datasets/coco_detection.py',
+    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
+]
+# use caffe img_norm
+img_norm_cfg = dict(
+    mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)
+train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='Pad', size_divisor=32),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(1333, 800),
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='Pad', size_divisor=32),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img']),
+        ])
+]
+data = dict(
+    train=dict(pipeline=train_pipeline),
+    val=dict(pipeline=test_pipeline),
+    test=dict(pipeline=test_pipeline))
+# optimizer
+optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)

openmmlab_test/mmdetection-speed_xinpian/configs/faster_rcnn/faster_rcnn_r50_caffe_dc5_1x_coco.py

+_base_ = [
+    '../_base_/models/faster_rcnn_r50_caffe_dc5.py',
+    '../_base_/datasets/coco_detection.py',
+    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
+]
+# use caffe img_norm
+img_norm_cfg = dict(
+    mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)
+train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='Pad', size_divisor=32),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(1333, 800),
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='Pad', size_divisor=32),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img']),
+        ])
+]
+data = dict(
+    train=dict(pipeline=train_pipeline),
+    val=dict(pipeline=test_pipeline),
+    test=dict(pipeline=test_pipeline))

openmmlab_test/mmdetection-speed_xinpian/configs/faster_rcnn/faster_rcnn_r50_caffe_dc5_mstrain_1x_coco.py

+_base_ = [
+    '../_base_/models/faster_rcnn_r50_caffe_dc5.py',
+    '../_base_/datasets/coco_detection.py',
+    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
+]
+# use caffe img_norm
+img_norm_cfg = dict(
+    mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)
+train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(
+        type='Resize',
+        img_scale=[(1333, 640), (1333, 672), (1333, 704), (1333, 736),
+                   (1333, 768), (1333, 800)],
+        multiscale_mode='value',
+        keep_ratio=True),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='Pad', size_divisor=32),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(1333, 800),
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='Pad', size_divisor=32),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img']),
+        ])
+]
+data = dict(
+    train=dict(pipeline=train_pipeline),
+    val=dict(pipeline=test_pipeline),
+    test=dict(pipeline=test_pipeline))

openmmlab_test/mmdetection-speed_xinpian/configs/faster_rcnn/faster_rcnn_r50_caffe_dc5_mstrain_3x_coco.py

+_base_ = './faster_rcnn_r50_caffe_dc5_mstrain_1x_coco.py'
+# learning policy
+lr_config = dict(step=[28, 34])
+runner = dict(type='EpochBasedRunner', max_epochs=36)