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Commit 7fb202b3 authored by Cao Yuhang's avatar Cao Yuhang Committed by Kai Chen
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new model zoo (#548) 

* new model zoo

* update model url and performance

* update pytorch version
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MODEL_ZOO.md
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### Software environment
- Python 3.6 / 3.7
- PyTorch 1.0
- PyTorch Nightly
- CUDA 9.0.176
- CUDNN 7.0.4
- NCCL 2.1.15
......@@ -46,108 +46,108 @@ We released RPN, Faster R-CNN and Mask R-CNN models in the first version. More m
| Backbone | Style | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | AR1000 | Download |
|:--------:|:-------:|:-------:|:--------:|:-------------------:|:--------------:|:------:|:--------:|
| R-50-FPN | caffe | 1x | 4.5 | 0.379 | 14.4 | 58.2 | - |
| R-50-FPN | pytorch | 1x | 4.8 | 0.407 | 14.5 | 57.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_r50_fpn_1x_20181010-4a9c0712.pth) |
| R-50-FPN | pytorch | 2x | 4.8 | 0.407 | 14.5 | 57.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_r50_fpn_2x_20181010-88a4a471.pth) |
| R-101-FPN | caffe | 1x | 7.4 | 0.513 | 11.1 | 59.4 | - |
| R-101-FPN | pytorch | 1x | 8.0 | 0.552 | 11.1 | 58.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_r101_fpn_1x_20181129-f50da4bd.pth) |
| R-101-FPN | pytorch | 2x | 8.0 | 0.552 | 11.1 | 59.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_r101_fpn_2x_20181129-e42c6c9a.pth) |
| X-101-32x4d-FPN | pytorch |1x | 9.9 | 0.691 | 8.3 | 59.4 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_x101_32x4d_fpn_1x_20181218-7e379d26.pth)
| X-101-32x4d-FPN | pytorch |2x | 9.9 | 0.691 | 8.3 | 59.9 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_x101_32x4d_fpn_2x_20181218-0510af40.pth)
| X-101-64x4d-FPN | pytorch |1x | 14.6 | 1.032 | 6.2 | 59.8 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_x101_64x4d_fpn_1x_20181218-c1a24f1f.pth)
| X-101-64x4d-FPN | pytorch |2x | 14.6 | 1.032 | 6.2 | 60.0 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_x101_64x4d_fpn_2x_20181218-c22bdd70.pth)
| R-50-FPN | caffe | 1x | 3.3 | 0.253 | 16.9 | 58.2 | - |
| R-50-FPN | pytorch | 1x | 3.5 | 0.276 | 17.7 | 57.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_r50_fpn_1x_20181010-4a9c0712.pth) |
| R-50-FPN | pytorch | 2x | | | | 57.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_r50_fpn_2x_20181010-88a4a471.pth) |
| R-101-FPN | caffe | 1x | 5.2 | 0.379 | 13.9 | 59.4 | - |
| R-101-FPN | pytorch | 1x | 5.4 | 0.396 | 14.4 | 58.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_r101_fpn_1x_20181129-f50da4bd.pth) |
| R-101-FPN | pytorch | 2x | | | | 59.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_r101_fpn_2x_20181129-e42c6c9a.pth) |
| X-101-32x4d-FPN | pytorch |1x | 6.6 | 0.589 | 11.8 | 59.4 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_x101_32x4d_fpn_1x_20181218-7e379d26.pth)
| X-101-32x4d-FPN | pytorch |2x | | | | 59.9 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_x101_32x4d_fpn_2x_20181218-0510af40.pth)
| X-101-64x4d-FPN | pytorch |1x | 9.5 | 0.955 | 8.3 | 59.8 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_x101_64x4d_fpn_1x_20181218-c1a24f1f.pth)
| X-101-64x4d-FPN | pytorch |2x | | | | 60.0 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/rpn_x101_64x4d_fpn_2x_20181218-c22bdd70.pth)
### Faster R-CNN
| Backbone | Style | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | Download |
|:--------:|:-------:|:-------:|:--------:|:-------------------:|:--------------:|:------:|:--------:|
| R-50-FPN | caffe | 1x | 4.9 | 0.525 | 10.0 | 36.7 | - |
| R-50-FPN | pytorch | 1x | 5.1 | 0.554 | 9.9 | 36.4 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_r50_fpn_1x_20181010-3d1b3351.pth) |
| R-50-FPN | pytorch | 2x | 5.1 | 0.554 | 9.9 | 37.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_r50_fpn_2x_20181010-443129e1.pth) |
| R-101-FPN | caffe | 1x | 7.4 | 0.663 | 8.4 | 38.8 | - |
| R-101-FPN | pytorch | 1x | 8.0 | 0.698 | 8.3 | 38.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_r101_fpn_1x_20181129-d1468807.pth) |
| R-101-FPN | pytorch | 2x | 8.0 | 0.698 | 8.3 | 39.4 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_r101_fpn_2x_20181129-73e7ade7.pth) |
| X-101-32x4d-FPN | pytorch | 1x| 9.9 | 0.842 | 7.0 | 40.2 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_x101_32x4d_fpn_1x_20181218-ad81c133.pth)
| X-101-32x4d-FPN | pytorch | 2x| 9.9 | 0.842 | 7.0 | 40.5 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_x101_32x4d_fpn_2x_20181218-0ed58946.pth)
| X-101-64x4d-FPN | pytorch | 1x| 14.1 | 1.181 | 5.2 | 41.3 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_x101_64x4d_fpn_1x_20181218-c9c69c8f.pth)
| X-101-64x4d-FPN | pytorch | 2x| 14.1 | 1.181 | 5.2 | 40.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_x101_64x4d_fpn_2x_20181218-fe94f9b8.pth)
| R-50-FPN | caffe | 1x | 3.6 | 0.333 | 12.9 | 36.7 | - |
| R-50-FPN | pytorch | 1x | 3.8 | 0.353 | 12.5 | 36.4 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_r50_fpn_1x_20181010-3d1b3351.pth) |
| R-50-FPN | pytorch | 2x | | | | 37.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_r50_fpn_2x_20181010-443129e1.pth) |
| R-101-FPN | caffe | 1x | 5.5 | 0.465 | 10.7 | 38.8 | - |
| R-101-FPN | pytorch | 1x | 5.7 | 0.474 | 10.8 | 38.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_r101_fpn_1x_20181129-d1468807.pth) |
| R-101-FPN | pytorch | 2x | | | | 39.4 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_r101_fpn_2x_20181129-73e7ade7.pth) |
| X-101-32x4d-FPN | pytorch | 1x| 6.9 | 0.672 | 9.3 | 40.2 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_x101_32x4d_fpn_1x_20181218-ad81c133.pth)
| X-101-32x4d-FPN | pytorch | 2x| | | | 40.5 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_x101_32x4d_fpn_2x_20181218-0ed58946.pth)
| X-101-64x4d-FPN | pytorch | 1x| 9.8 | 1.040 | 7.1 | 41.3 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_x101_64x4d_fpn_1x_20181218-c9c69c8f.pth)
| X-101-64x4d-FPN | pytorch | 2x| | | | 40.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/faster_rcnn_x101_64x4d_fpn_2x_20181218-fe94f9b8.pth)
### Mask R-CNN
| Backbone | Style | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | mask AP | Download |
|:--------:|:-------:|:-------:|:--------:|:-------------------:|:--------------:|:------:|:-------:|:--------:|
| R-50-FPN | caffe | 1x | 5.9 | 0.658 | 7.7 | 37.5 | 34.4 | - |
| R-50-FPN | pytorch | 1x | 5.8 | 0.690 | 7.7 | 37.3 | 34.2 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_r50_fpn_1x_20181010-069fa190.pth) |
| R-50-FPN | pytorch | 2x | 5.8 | 0.690 | 7.7 | 38.6 | 35.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_r50_fpn_2x_20181010-41d35c05.pth) |
| R-101-FPN | caffe | 1x | 8.8 | 0.791 | 7.0 | 39.9 | 36.1 | - |
| R-101-FPN | pytorch | 1x | 9.1 | 0.825 | 6.7 | 39.4 | 35.9 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_r101_fpn_1x_20181129-34ad1961.pth) |
| R-101-FPN | pytorch | 2x | 9.1 | 0.825 | 6.7 | 40.4 | 36.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_r101_fpn_2x_20181129-a254bdfc.pth) |
| X-101-32x4d-FPN | pytorch | 1x| 10.9 | 0.972 | 5.8 | 41.2 | 37.2 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_x101_32x4d_fpn_1x_20181218-44e635cc.pth)
| X-101-32x4d-FPN | pytorch | 2x| 10.9 | 0.972 | 5.8 | 41.4 | 37.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_x101_32x4d_fpn_2x_20181218-f023dffa.pth)
| X-101-64x4d-FPN | pytorch | 1x| 14.1 | 1.302 | 4.7 | 42.2 | 38.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_x101_64x4d_fpn_1x_20181218-cb159987.pth)
| X-101-64x4d-FPN | pytorch | 2x| 14.1 | 1.302 | 4.7 | 42.0 | 37.8 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_x101_64x4d_fpn_2x_20181218-ea936e44.pth)
| R-50-FPN | caffe | 1x | 3.8 | 0.430 | 9.9 | 37.5 | 34.4 | - |
| R-50-FPN | pytorch | 1x | 3.9 | 0.453 | 9.6 | 37.3 | 34.2 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_r50_fpn_1x_20181010-069fa190.pth) |
| R-50-FPN | pytorch | 2x | | | | 38.6 | 35.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_r50_fpn_2x_20181010-41d35c05.pth) |
| R-101-FPN | caffe | 1x | 5.7 | 0.534 | 8.8 | 39.9 | 36.1 | - |
| R-101-FPN | pytorch | 1x | 5.8 | 0.571 | 8.9 | 39.4 | 35.9 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_r101_fpn_1x_20181129-34ad1961.pth) |
| R-101-FPN | pytorch | 2x | | | | 40.4 | 36.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_r101_fpn_2x_20181129-a254bdfc.pth) |
| X-101-32x4d-FPN | pytorch | 1x| 7.1 | 0.759 | 7.9 | 41.2 | 37.2 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_x101_32x4d_fpn_1x_20181218-44e635cc.pth)
| X-101-32x4d-FPN | pytorch | 2x| | | | 41.4 | 37.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_x101_32x4d_fpn_2x_20181218-f023dffa.pth)
| X-101-64x4d-FPN | pytorch | 1x| 10.0 | 1.102 | 5.8 | 42.2 | 38.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_x101_64x4d_fpn_1x_20181218-cb159987.pth)
| X-101-64x4d-FPN | pytorch | 2x| | | | 42.0 | 37.8 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/mask_rcnn_x101_64x4d_fpn_2x_20181218-ea936e44.pth)
### Fast R-CNN (with pre-computed proposals)
| Backbone | Style | Type | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | mask AP | Download |
|:--------:|:-------:|:------:|:-------:|:--------:|:-------------------:|:--------------:|:------:|:-------:|:--------:|
| R-50-FPN | caffe | Faster | 1x | 3.5 | 0.348 | 14.6 | 36.6 | - | - |
| R-50-FPN | pytorch | Faster | 1x | 4.0 | 0.375 | 14.5 | 35.8 | - | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_rcnn_r50_fpn_1x_20181010-08160859.pth) |
| R-50-FPN | pytorch | Faster | 2x | 4.0 | 0.375 | 14.5 | 37.1 | - | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_rcnn_r50_fpn_2x_20181010-d263ada5.pth) |
| R-101-FPN| caffe | Faster | 1x | 7.1 | 0.484 | 11.9 | 38.4 | - | - |
| R-101-FPN| pytorch | Faster | 1x | 7.6 | 0.540 | 11.8 | 38.1 | - | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_rcnn_r101_fpn_1x_20181129-ffaa2eb0.pth) |
| R-101-FPN| pytorch | Faster | 2x | 7.6 | 0.540 | 11.8 | 38.8 | - | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_rcnn_r101_fpn_2x_20181129-9dba92ce.pth) |
| R-50-FPN | caffe | Mask | 1x | 5.4 | 0.473 | 10.7 | 37.3 | 34.5 | - |
| R-50-FPN | pytorch | Mask | 1x | 5.3 | 0.504 | 10.6 | 36.8 | 34.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_mask_rcnn_r50_fpn_1x_20181010-e030a38f.pth) |
| R-50-FPN | pytorch | Mask | 2x | 5.3 | 0.504 | 10.6 | 37.9 | 34.8 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_mask_rcnn_r50_fpn_2x_20181010-5048cb03.pth) |
| R-101-FPN| caffe | Mask | 1x | 8.6 | 0.607 | 9.5 | 39.4 | 36.1 | - |
| R-101-FPN| pytorch | Mask | 1x | 9.0 | 0.656 | 9.3 | 38.9 | 35.8 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_mask_rcnn_r101_fpn_1x_20181129-2273fa9b.pth) |
| R-101-FPN| pytorch | Mask | 2x | 9.0 | 0.656 | 9.3 | 39.9 | 36.4 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_mask_rcnn_r101_fpn_2x_20181129-bf63ec5e.pth) |
| R-50-FPN | caffe | Faster | 1x | 3.3 | 0.242 | 18.4 | 36.6 | - | - |
| R-50-FPN | pytorch | Faster | 1x | 3.5 | 0.250 | 16.5 | 35.8 | - | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_rcnn_r50_fpn_1x_20181010-08160859.pth) |
| R-50-FPN | pytorch | Faster | 2x | | | | 37.1 | - | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_rcnn_r50_fpn_2x_20181010-d263ada5.pth) |
| R-101-FPN| caffe | Faster | 1x | 5.2 | 0.355 | 14.4 | 38.6 | - | - |
| R-101-FPN| pytorch | Faster | 1x | 5.4 | 0.388 | 13.2 | 38.1 | - | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_rcnn_r101_fpn_1x_20181129-ffaa2eb0.pth) |
| R-101-FPN| pytorch | Faster | 2x | | | | 38.8 | - | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_rcnn_r101_fpn_2x_20181129-9dba92ce.pth) |
| R-50-FPN | caffe | Mask | 1x | 3.4 | 0.328 | 12.8 | 37.3 | 34.5 | - |
| R-50-FPN | pytorch | Mask | 1x | 3.5 | 0.346 | 12.7 | 36.8 | 34.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_mask_rcnn_r50_fpn_1x_20181010-e030a38f.pth) |
| R-50-FPN | pytorch | Mask | 2x | | | | 37.9 | 34.8 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_mask_rcnn_r50_fpn_2x_20181010-5048cb03.pth) |
| R-101-FPN| caffe | Mask | 1x | 5.2 | 0.429 | 11.2 | 39.4 | 36.1 | - |
| R-101-FPN| pytorch | Mask | 1x | 5.4 | 0.462 | 10.9 | 38.9 | 35.8 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_mask_rcnn_r101_fpn_1x_20181129-2273fa9b.pth) |
| R-101-FPN| pytorch | Mask | 2x | | | | 39.9 | 36.4 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/fast_mask_rcnn_r101_fpn_2x_20181129-bf63ec5e.pth) |
### RetinaNet
| Backbone | Style | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | Download |
|:--------:|:-------:|:-------:|:--------:|:-------------------:|:--------------:|:------:|:--------:|
| R-50-FPN | caffe | 1x | 6.7 | 0.468 | 9.4 | 35.8 | - |
| R-50-FPN | pytorch | 1x | 6.9 | 0.496 | 9.1 | 35.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_r50_fpn_1x_20181125-7b0c2548.pth) |
| R-50-FPN | pytorch | 2x | 6.9 | 0.496 | 9.1 | 36.5 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_r50_fpn_2x_20181125-8b724df2.pth) |
| R-101-FPN | caffe | 1x | 9.2 | 0.614 | 8.2 | 37.8 | - |
| R-101-FPN | pytorch | 1x | 9.6 | 0.643 | 8.1 | 37.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_r101_fpn_1x_20181129-f016f384.pth) |
| R-101-FPN | pytorch | 2x | 9.6 | 0.643 | 8.1 | 38.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_r101_fpn_2x_20181129-72c14526.pth) |
| X-101-32x4d-FPN | pytorch | 1x| 10.8 | 0.792 | 6.7 | 38.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_x101_32x4d_fpn_1x_20181218-c84d7dfc.pth)
| X-101-32x4d-FPN | pytorch | 2x| 10.8 | 0.792 | 6.7 | 39.3 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_x101_32x4d_fpn_2x_20181218-8596452d.pth)
| X-101-64x4d-FPN | pytorch | 1x| 14.6 | 1.128 | 5.3 | 40.0 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_x101_64x4d_fpn_1x_20181218-a0a22662.pth)
| X-101-64x4d-FPN | pytorch | 2x| 14.6 | 1.128 | 5.3 | 39.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_x101_64x4d_fpn_2x_20181218-5e88d045.pth)
| R-50-FPN | caffe | 1x | 3.4 | 0.285 | 12.5 | 35.8 | - |
| R-50-FPN | pytorch | 1x | 3.6 | 0.308 | 12.1 | 35.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_r50_fpn_1x_20181125-3d3c2142.pth) |
| R-50-FPN | pytorch | 2x | | | | 36.5 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_r50_fpn_2x_20181125-e0dbec97.pth) |
| R-101-FPN | caffe | 1x | 5.3 | 0.410 | 10.4 | 37.8 | - |
| R-101-FPN | pytorch | 1x | 5.5 | 0.429 | 10.9 | 37.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_r101_fpn_1x_20181129-f738a02f.pth) |
| R-101-FPN | pytorch | 2x | | | | 38.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_r101_fpn_2x_20181129-f654534b.pth) |
| X-101-32x4d-FPN | pytorch | 1x| 6.7 | 0.632 | 9.3 | 39.0 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_x101_32x4d_fpn_1x_20190501-967812ba.pth)
| X-101-32x4d-FPN | pytorch | 2x| | | | 39.3 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_x101_32x4d_fpn_2x_20181218-605dcd0a.pth)
| X-101-64x4d-FPN | pytorch | 1x| 9.6 | 0.993 | 7.0 | 40.0 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_x101_64x4d_fpn_1x_20181218-2f6f778b.pth)
| X-101-64x4d-FPN | pytorch | 2x| | | | 39.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/retinanet_x101_64x4d_fpn_2x_20181218-2f598dc5.pth)
### Cascade R-CNN
| Backbone | Style | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | Download |
|:--------:|:-------:|:-------:|:--------:|:-------------------:|:--------------:|:------:|:--------:|
| R-50-FPN | caffe | 1x | 5.0 | 0.592 | 8.1 | 40.3 | - |
| R-50-FPN | pytorch | 1x | 5.5 | 0.622 | 8.0 | 40.3 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_r50_fpn_1x_20181123-b1987c4a.pth) |
| R-50-FPN | pytorch | 20e | 5.5 | 0.622 | 8.0 | 41.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_r50_fpn_20e_20181123-db483a09.pth) |
| R-101-FPN | caffe | 1x | 8.5 | 0.731 | 7.0 | 42.2 | - |
| R-101-FPN | pytorch | 1x | 8.7 | 0.766 | 6.9 | 42.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_r101_fpn_1x_20181129-d64ebac7.pth) |
| R-101-FPN | pytorch | 20e | 8.7 | 0.766 | 6.9 | 42.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_r101_fpn_20e_20181129-b46dcede.pth) |
| X-101-32x4d-FPN | pytorch | 1x| 10.6 | 0.902 | 5.7 | 43.5 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_x101_32x4d_fpn_1x_20181218-941c0925.pth)
| X-101-32x4d-FPN | pytorch |20e| 10.6 | 0.902 | 5.7 | 44.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_x101_32x4d_fpn_2x_20181218-28f73c4c.pth)
| X-101-64x4d-FPN | pytorch | 1x| 14.1 | 1.251 | 4.6 | 44.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_x101_64x4d_fpn_1x_20181218-e2dc376a.pth)
| X-101-64x4d-FPN | pytorch |20e| 14.1 | 1.251 | 4.6 | 44.8 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_x101_64x4d_fpn_2x_20181218-5add321e.pth)
| R-50-FPN | caffe | 1x | 3.9 | 0.464 | 9.7 | 40.6 | - |
| R-50-FPN | pytorch | 1x | 4.1 | 0.455 | 10.1 | 40.5 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_r50_fpn_1x_20190501-3b6211ab.pth) |
| R-50-FPN | pytorch | 20e | | | | 41.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_r50_fpn_20e_20181123-db483a09.pth) |
| R-101-FPN | caffe | 1x | 5.8 | 0.569 | 8.7 | 42.5 | - |
| R-101-FPN | pytorch | 1x | 6.0 | 0.584 | 8.7 | 42.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_r101_fpn_1x_20181129-d64ebac7.pth) |
| R-101-FPN | pytorch | 20e | | | | 42.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_r101_fpn_20e_20181129-b46dcede.pth) |
| X-101-32x4d-FPN | pytorch | 1x| 7.2 | 0.770 | 7.8 | 43.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_x101_32x4d_fpn_1x_20190501-af628be5.pth)
| X-101-32x4d-FPN | pytorch |20e| | | | 44.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_x101_32x4d_fpn_2x_20181218-28f73c4c.pth)
| X-101-64x4d-FPN | pytorch | 1x| 10.0 | 1.133 | 6.1 | 44.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_x101_64x4d_fpn_1x_20181218-e2dc376a.pth)
| X-101-64x4d-FPN | pytorch |20e| | | | 44.8 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_rcnn_x101_64x4d_fpn_2x_20181218-5add321e.pth)
### Cascade Mask R-CNN
| Backbone | Style | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | mask AP | Download |
|:--------:|:-------:|:-------:|:--------:|:-------------------:|:--------------:|:------:|:-------:|:--------:|
| R-50-FPN | caffe | 1x | 7.5 | 0.880 | 5.8 | 41.0 | 35.6 | - |
| R-50-FPN | pytorch | 1x | 7.6 | 0.910 | 5.7 | 41.3 | 35.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_r50_fpn_1x_20181123-88b170c9.pth) |
| R-50-FPN | pytorch | 20e | 7.6 | 0.910 | 5.7 | 42.4 | 36.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_r50_fpn_20e_20181123-6e0c9713.pth) |
| R-101-FPN | caffe | 1x | 10.5 | 1.024 | 5.3 | 43.1 | 37.3 | - |
| R-101-FPN | pytorch | 1x | 10.9 | 1.055 | 5.2 | 42.7 | 37.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_r101_fpn_1x_20181129-64f00602.pth) |
| R-101-FPN | pytorch | 20e | 10.9 | 1.055 | 5.2 | 43.4 | 37.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_r101_fpn_20e_20181129-cb85151d.pth) |
| X-101-32x4d-FPN | pytorch | 1x| 12.67 | 1.181 | 4.2 | 44.4 | 38.3 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_x101_32x4d_fpn_1x_20181218-1d944c89.pth)
| X-101-32x4d-FPN | pytorch |20e| 12.67 | 1.181 | 4.2 | 44.9 | 38.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_x101_32x4d_fpn_20e_20181218-761a3473.pth)
| X-101-64x4d-FPN | pytorch | 1x| 10.87 | 1.125 | 3.6 | 45.5 | 39.2 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_x101_64x4d_fpn_1x_20181218-85953a91.pth)
| X-101-64x4d-FPN | pytorch |20e| 10.87 | 1.125 | 3.6 | 45.8 | 39.5 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_x101_64x4d_fpn_20e_20181218-630773a7.pth)
| R-50-FPN | caffe | 1x | 5.1 | 0.692 | 6.7 | 41.0 | 35.6 | - |
| R-50-FPN | pytorch | 1x | 5.3 | 0.683 | 6.5 | 41.3 | 35.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_r50_fpn_1x_20181123-88b170c9.pth) |
| R-50-FPN | pytorch | 20e | | | | 42.4 | 36.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_r50_fpn_20e_20181123-6e0c9713.pth) |
| R-101-FPN | caffe | 1x | 7.0 | 0.803 | 6.3 | 43.1 | 37.3 | - |
| R-101-FPN | pytorch | 1x | 7.2 | 0.807 | 6.1 | 42.7 | 37.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_r101_fpn_1x_20181129-64f00602.pth) |
| R-101-FPN | pytorch | 20e | | | | 43.4 | 37.6 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_r101_fpn_20e_20181129-cb85151d.pth) |
| X-101-32x4d-FPN | pytorch | 1x| 8.4 | 0.976 | 5.7 | 44.4 | 38.3 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_x101_32x4d_fpn_1x_20181218-1d944c89.pth)
| X-101-32x4d-FPN | pytorch |20e| | | | 44.9 | 38.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_x101_32x4d_fpn_20e_20181218-761a3473.pth)
| X-101-64x4d-FPN | pytorch | 1x| 11.4 | 1.33 | 4.7 | 45.3 | 39.1 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_x101_64x4d_fpn_1x_20190501-827e0a70.pth)
| X-101-64x4d-FPN | pytorch |20e| | | | 45.8 | 39.5 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/cascade_mask_rcnn_x101_64x4d_fpn_20e_20181218-630773a7.pth)
**Notes:**
......@@ -162,15 +162,15 @@ Please refer to [HTC](configs/htc/README.md) for details.
| Backbone | Size | Style | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | Download |
|:--------:|:----:|:------:|:-------:|:--------:|:-------------------:|:--------------:|:------:|:--------:|
| VGG16 | 300 | caffe | 120e | 3.5 | 0.286 | 22.9 / 29.2 | 25.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/ssd300_coco_vgg16_caffe_120e_20181221-84d7110b.pth) |
| VGG16 | 512 | caffe | 120e | 6.3 | 0.458 | 17.3 / 21.2 | 29.3 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/ssd512_coco_vgg16_caffe_120e_20181221-d48b0be8.pth) |
| VGG16 | 300 | caffe | 120e | 3.5 | 0.256 | 25.9 / 34.6 | 25.7 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/ssd300_coco_vgg16_caffe_120e_20181221-84d7110b.pth) |
| VGG16 | 512 | caffe | 120e | 7.6 | 0.412 | 20.7 / 25.4 | 29.3 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/ssd512_coco_vgg16_caffe_120e_20181221-d48b0be8.pth) |
### SSD (PASCAL VOC)
| Backbone | Size | Style | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | Download |
|:--------:|:----:|:------:|:-------:|:--------:|:-------------------:|:--------------:|:------:|:--------:|
| VGG16 | 300 | caffe | 240e | 1.2 | 0.189 | 40.1 / 58.0 | 77.8 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/ssd300_voc_vgg16_caffe_240e_20181221-2f05dd40.pth) |
| VGG16 | 512 | caffe | 240e | 2.9 | 0.261 | 28.1 / 36.2 | 80.4 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/ssd512_voc_vgg16_caffe_240e_20181221-7652ee18.pth) |
| VGG16 | 300 | caffe | 240e | 2.5 | 0.159 | 35.7 / 53.6 | 77.5 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/ssd300_voc_vgg16_caffe_240e_20190501-7160d09a.pth) |
| VGG16 | 512 | caffe | 240e | 4.3 | 0.214 | 27.5 / 35.9 | 80.0 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/ssd512_voc_vgg16_caffe_240e_20190501-ff194be1.pth) |
**Notes:**
......
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