[Feature] Torchvision high-precision ResNet model

configs/faster_rcnn/README.md

@@ -64,6 +64,14 @@ We further finetune some pre-trained models on the COCO subsets, which only cont
 | [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) | [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) | [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) |
 
+## Torchvision New Receipe (TNR)
+
+Torchvision released its high-precision ResNet models. The training details can be found on the [Pytorch website](https://pytorch.org/blog/how-to-train-state-of-the-art-models-using-torchvision-latest-primitives/). Here, we have done grid searches on learning rate and weight decay and found the optimal hyper-parameter on the detection task.
+
+| Backbone | Style | Lr schd | Mem (GB) | Inf time (fps) | box AP | Config | Download |
+| :-------------: | :-----: | :-----: | :------: | :------------: | :----: | :------: | :--------: |
+| [R-50-TNR](./faster_rcnn_r50_fpn_tnr-pretrain_1x_coco.py) | pytorch | 1x | - | | 40.2 | [config](https://github.com/open-mmlab/mmdetection/blob/master/configs/faster_rcnn/faster_rcnn_r50_fpn_tnr-pretrain_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_tnr-pretrain_1x_coco/faster_rcnn_r50_fpn_tnr-pretrain_1x_coco_20220320_085147-efedfda4.pth) | [log](https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_tnr-pretrain_1x_coco/faster_rcnn_r50_fpn_tnr-pretrain_1x_coco_20220320_085147-efedfda4.log.json) |
+
 ## Citation
 
 ```latex

configs/faster_rcnn/faster_rcnn_r50_fpn_tnr-pretrain_1x_coco.py

@@ -0,0 +1,17 @@
+_base_ = [
+ '../_base_/models/faster_rcnn_r50_fpn.py',
+ '../_base_/datasets/coco_detection.py',
+ '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
+]
+
+checkpoint = 'https://download.pytorch.org/models/resnet50-11ad3fa6.pth'
+model = dict(
+ backbone=dict(init_cfg=dict(type='Pretrained', checkpoint=checkpoint)))
+
+# `lr` and `weight_decay` have been searched to be optimal.
+optimizer = dict(
+ _delete_=True,
+ type='AdamW',
+ lr=0.0001,
+ weight_decay=0.1,
+ paramwise_cfg=dict(norm_decay_mult=0., bypass_duplicate=True))

configs/faster_rcnn/metafile.yml

@@ -405,3 +405,23 @@ Models:
  Metrics:
  box AP: 43.1
  Weights: 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
+
+ - Name: faster_rcnn_r50_fpn_tnr-pretrain_1x_coco
+ In Collection: Faster R-CNN
+ Config: configs/faster_rcnn/faster_rcnn_r50_fpn_tnr-pretrain_1x_coco.py
+ Metadata:
+ Training Memory (GB): 4.0
+ inference time (ms/im):
+ - value: 46.73
+ hardware: V100
+ backend: PyTorch
+ batch size: 1
+ mode: FP32
+ resolution: (800, 1333)
+ Epochs: 12
+ Results:
+ - Task: Object Detection
+ Dataset: COCO
+ Metrics:
+ box AP: 40.2
+ Weights: https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_tnr-pretrain_1x_coco/faster_rcnn_r50_fpn_tnr-pretrain_1x_coco_20220320_085147-efedfda4.pth