lvhan028 e929201827
[Docs] reorganize the documents in English and update the contents based on v0.5.0 status (#531)
* checkout qq group qrcode

* update the cover image

* update build doc

* reorganize chapters

* update readme

* remove index of build on different platforms in readthedocs

* update benchmark

* update get started document in Chinese based on the prebuild package

* update get_started

* re-style benchmark

* update get_started in zh_cn

* update get_started in english

* update get_started in english

* update get_started in english

* update get_started doc

* update according to reviewer comments

* update linker ci

* fix(.github/scripts/check_doc_linker.py): skip code block

* specify PYTHONPATH

* update get_started

* update diagram

* rename some documents

* fix according to reviewer comments

Co-authored-by: tpoisonooo <khj.application@aliyun.com>
2022-06-07 18:05:51 +08:00

2.3 KiB

MMRotate Support

MMRotate is an open-source toolbox for rotated object detection based on PyTorch. It is a part of the OpenMMLab project.

MMRotate installation tutorial

Please refer to official installation guide to install the codebase.

MMRotate models support

Model Task ONNX Runtime TensorRT NCNN PPLNN OpenVINO Model config
RotatedRetinaNet RotatedDetection Y Y N N N config
Oriented RCNN RotatedDetection Y N N N N config

Example

# convert ort
python tools/deploy.py \
configs/mmrotate/rotated-detection_onnxruntime_dynamic.py \
$MMROTATE_DIR/configs/rotated_retinanet/rotated_retinanet_obb_r50_fpn_1x_dota_le135.py \
$MMROTATE_DIR/checkpoints/rotated_retinanet_obb_r50_fpn_1x_dota_le135-e4131166.pth \
$MMROTATE_DIR/demo/demo.jpg \
--work-dir work-dirs/mmrotate/rotated_retinanet/ort \
--device cpu

# compute metric
python tools/test.py \
    configs/mmrotate/rotated-detection_onnxruntime_dynamic.py \
    $MMROTATE_DIR/configs/rotated_retinanet/rotated_retinanet_obb_r50_fpn_1x_dota_le135.py \
    --model work-dirs/mmrotate/rotated_retinanet/ort/end2end.onnx \
    --metrics mAP

# generate submit file
python tools/test.py \
    configs/mmrotate/rotated-detection_onnxruntime_dynamic.py \
    $MMROTATE_DIR/configs/rotated_retinanet/rotated_retinanet_obb_r50_fpn_1x_dota_le135.py \
    --model work-dirs/mmrotate/rotated_retinanet/ort/end2end.onnx \
    --format-only \
    --metric-options submission_dir=work-dirs/mmrotate/rotated_retinanet/ort/Task1_results

Note

  • Usually, mmrotate models need some extra information for the input image, but we can't get it directly. So, when exporting the model, you can use $MMROTATE_DIR/demo/demo.jpg as input.