diff --git a/MODEL_ZOO.md b/MODEL_ZOO.md index 6690b503074d6bb3f9622bda4c1dd31e95ffe01d..473e31d491475cd247f6b914384f192d7ae491bb 100644 --- a/MODEL_ZOO.md +++ b/MODEL_ZOO.md @@ -38,46 +38,46 @@ We released RPN, Faster R-CNN and Mask R-CNN models in the first version. More m ### RPN -| Backbone | Type | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | AR1000 | Download | -| ------------------ | ---- | ------- | -------- | ---------- | -------- | ------ | -------- | -| R-50-FPN (caffe) | RPN | 1x | 4.5 | 0.379 | 14.4 | 58.2 | - | -| R-50-FPN (pytorch) | RPN | 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.pth) \| [result](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/results/rpn_r50_fpn_1x_20181010_results.pkl.json) | -| R-50-FPN (pytorch) | RPN | 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.pth) \| [result](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/results/rpn_r50_fpn_2x_20181010_results.pkl.json) | +| 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.pth) \| [result](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/results/rpn_r50_fpn_1x_20181010_results.pkl.json) | +| 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.pth) \| [result](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/results/rpn_r50_fpn_2x_20181010_results.pkl.json) | ### Faster R-CNN -| Backbone | Type | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | Download | -| ------------------ | ------ | ------- | -------- | ---------- | -------- | ------ | -------- | -| R-50-FPN (caffe) | Faster | 1x | 4.9 | 0.525 | 10.0 | 36.7 | - | -| R-50-FPN (pytorch) | Faster | 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.pth) \| [result](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/results/faster_rcnn_r50_fpn_1x_20181010_results.pkl.json) | -| R-50-FPN (pytorch) | Faster | 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.pth) \| [result](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/results/faster_rcnn_r50_fpn_2x_20181010_results.pkl.json) | +| 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.pth) \| [result](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/results/faster_rcnn_r50_fpn_1x_20181010_results.pkl.json) | +| 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.pth) \| [result](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/results/faster_rcnn_r50_fpn_2x_20181010_results.pkl.json) | ### Mask R-CNN -| Backbone | Type | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | mask AP | Download | -| ------------------ | ---- | ------- | -------- | ---------- | -------- | ------ | ------- | -------- | -| R-50-FPN (caffe) | Mask | 1x | 5.9 | 0.658 | 7.7 | 37.5 | 34.4 | - | -| R-50-FPN (pytorch) | Mask | 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.pth) \| [result](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/results/mask_rcnn_r50_fpn_1x_20181010_results.pkl.json) | -| R-50-FPN (pytorch) | Mask | 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.pth) \| [result](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/results/mask_rcnn_r50_fpn_2x_20181010_results.pkl.json) | +| 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.pth) \| [result](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/results/mask_rcnn_r50_fpn_1x_20181010_results.pkl.json) | +| 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.pth) \| [result](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/results/mask_rcnn_r50_fpn_2x_20181010_results.pkl.json) | ### Fast R-CNN (with pre-computed proposals) (coming soon) -| Backbone | Type | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | mask AP | Download | -| ------------------ | ------ | ------- | -------- | ---------- | -------- | ------ | ------ | -------- | -| R-50-FPN (caffe) | Faster | 1x | | | | | | | -| R-50-FPN (pytorch) | Faster | 1x | | | | | | | -| R-50-FPN (pytorch) | Faster | 2x | | | | | | | -| R-50-FPN (caffe) | Mask | 1x | | | | | | | -| R-50-FPN (pytorch) | Mask | 1x | | | | | | | -| R-50-FPN (pytorch) | Mask | 2x | | | | | | | +| 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 | | | | | | | +| R-50-FPN | pytorch | Faster | 1x | | | | | | | +| R-50-FPN | pytorch | Faster | 2x | | | | | | | +| R-50-FPN | caffe | Mask | 1x | | | | | | | +| R-50-FPN | pytorch | Mask | 1x | | | | | | | +| R-50-FPN | pytorch | Mask | 2x | | | | | | | ### RetinaNet (coming soon) -| Backbone | Type | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | mask AP | Download | -| ------------------ | --------- | ------- | --------- | ---------- | -------- | ------ | ------- | -------- | -| R-50-FPN (caffe) | RetinaNet | 1x | | | | | | | -| R-50-FPN (pytorch) | RetinaNet | 1x | | | | | | | -| R-50-FPN (pytorch) | RetinaNet | 2x | | | | | | | +| Backbone | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | Download | +|:--------:|:-------:|:-------:|:--------:|:-------------------:|:--------------:|:------:|:--------:| +| R-50-FPN | caffe | 1x | | | | | | +| R-50-FPN | pytorch | 1x | | | | | | +| R-50-FPN | pytorch | 2x | | | | | | ## Comparison with Detectron @@ -86,6 +86,12 @@ We compare mmdetection with [Detectron](https://github.com/facebookresearch/Dete and [Detectron.pytorch](https://github.com/roytseng-tw/Detectron.pytorch), a third-party port of Detectron to Pytorch. The backbone used is R-50-FPN. +In general, mmdetection has 3 advantages over Detectron. + +- **Higher performance** (especially in terms of mask AP) +- **Faster training speed** +- **Memory efficient** + ### Performance Detectron and Detectron.pytorch use caffe-style ResNet as the backbone.