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ModelZoo
SOLOv2-pytorch
Commits
2a0f2c27
Commit
2a0f2c27
authored
May 04, 2019
by
Cao Yuhang
Committed by
Kai Chen
May 03, 2019
Browse files
Add HTC benchmark (#578)
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eb4a2c3a
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configs/htc/README.md
configs/htc/README.md
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configs/htc/README.md
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2a0f2c27
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@@ -38,11 +38,11 @@ The results on COCO 2017val is shown in the below table. (results on test-dev ar
| Backbone | Style | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | mask AP | Download |
|:---------:|:-------:|:-------:|:--------:|:-------------------:|:--------------:|:------:|:-------:|:--------:|
| R-50-FPN | pytorch | 1x |
|
|
| 42.2 | 37.3 |
[
model
](
https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/htc/htc_r50_fpn_1x_20190408-878c1712.pth
)
|
| R-50-FPN | pytorch | 20e |
|
|
| 43.2 | 38.0 |
[
model
](
https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/htc/htc_r50_fpn_20e_20190408-c03b7015.pth
)
|
| R-101-FPN | pytorch | 20e |
|
|
| 44.9 | 39.4 |
[
model
](
https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/htc/htc_r101_fpn_20e_20190408-a2e586db.pth
)
|
| X-101-32x4d-FPN | pytorch |20e|
|
|
| 46.1 | 40.3 |
[
model
](
https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/htc/htc_x101_32x4d_fpn_20e_20190408-9eae4d0b.pth
)
|
| X-101-64x4d-FPN | pytorch |20e|
|
|
| 47.0 | 40.9 |
[
model
](
https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/htc/htc_x101_64x4d_fpn_20e_20190408-497f2561.pth
)
|
| R-50-FPN | pytorch | 1x |
7.4
|
0.936
|
3.5
| 42.2 | 37.3 |
[
model
](
https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/htc/htc_r50_fpn_1x_20190408-878c1712.pth
)
|
| R-50-FPN | pytorch | 20e |
-
|
-
|
-
| 43.2 | 38.0 |
[
model
](
https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/htc/htc_r50_fpn_20e_20190408-c03b7015.pth
)
|
| R-101-FPN | pytorch | 20e |
9.3
|
1.051
|
3.4
| 44.9 | 39.4 |
[
model
](
https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/htc/htc_r101_fpn_20e_20190408-a2e586db.pth
)
|
| X-101-32x4d-FPN | pytorch |20e|
5.8
|
0.769
|
3.3
| 46.1 | 40.3 |
[
model
](
https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/htc/htc_x101_32x4d_fpn_20e_20190408-9eae4d0b.pth
)
|
| X-101-64x4d-FPN | pytorch |20e|
7.5
|
1.120
|
3.0
| 47.0 | 40.9 |
[
model
](
https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/htc/htc_x101_64x4d_fpn_20e_20190408-497f2561.pth
)
|
-
In the HTC paper and COCO 2018 Challenge,
`score_thr`
is set to 0.001 for both baselines and HTC.
-
We use 8 GPUs with 2 images/GPU for R-50 and R-101 models, and 16 GPUs with 1 image/GPU for X-101 models.
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