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‎docs/en/04-supported-codebases/mmdet3d.md

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## Install mmdet3d
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These branches are required for mmdet3d deployment
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| codebase | commit |
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| :------: | :-------: |
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| mmdet3d | v1.1.0rc1 |
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| mmcv | v2.0.0rc1 |
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| mmdet | v3.0.0rc1 |
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| mmseg | v1.0.0rc0 |
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First checkout and install mmcv/mmdet/mmseg/mmdet3d
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```bash
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python3 -m pip install openmim --user
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python3 -m mim install mmcv==2.0.0rc1 mmdet==3.0.0rc1 mmseg==1.0.0rc0 --user
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git clone https://github.com/open-mmlab/mmdetection3d --branch v1.1.0rc1
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cd mmdetection3d
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python3 -m pip install .
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cd -
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```
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After installation, `tools/check_env.py` should display mmdet3d version normally
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We could install mmdet3d through [mim](https://github.com/open-mmlab/mim).
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For other ways of installation, please refer to [here](https://mmdetection3d.readthedocs.io/en/latest/get_started.html#installation)
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```bash
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python3 tools/check_env.py
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..
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11/11 13:56:19 - mmengine - INFO - **********Codebase information**********
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11/11 13:56:19 - mmengine - INFO - mmdet: 3.0.0rc1
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11/11 13:56:19 - mmengine - INFO - mmseg: 1.0.0rc0
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..
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11/11 13:56:19 - mmengine - INFO - mmdet3d: 1.1.0rc1
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python3 -m pip install -U openmim
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python3 -m mim install "mmdet3d>=1.1.0"
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```
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## Convert model
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For example, use `tools/deploy.py` to convert centerpoint to onnxruntime format
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```bash
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export MODEL_CONFIG=/path/to/mmdetection3d/configs/centerpoint/centerpoint_pillar02_second_secfpn_head-circlenms_8xb4-cyclic-20e_nus-3d.py
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# cd to mmdeploy root directory
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# download config and model
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mim download mmdet3d --config centerpoint_pillar02_second_secfpn_head-circlenms_8xb4-cyclic-20e_nus-3d --dest .
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export MODEL_CONFIG=centerpoint_pillar02_second_secfpn_head-circlenms_8xb4-cyclic-20e_nus-3d.py
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export MODEL_PATH=https://download.openmmlab.com/mmdetection3d/v1.0.0_models/centerpoint/centerpoint_02pillar_second_secfpn_circlenms_4x8_cyclic_20e_nus/centerpoint_02pillar_second_secfpn_circlenms_4x8_cyclic_20e_nus_20210816_064624-0f3299c0.pth
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export MODEL_PATH=centerpoint_02pillar_second_secfpn_circlenms_4x8_cyclic_20e_nus_20220811_031844-191a3822.pth
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export TEST_DATA=/path/to/mmdetection3d/tests/data/nuscenes/sweeps/LIDAR_TOP/n008-2018-09-18-12-07-26-0400__LIDAR_TOP__1537287083900561.pcd.bin
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export TEST_DATA=tests/data/n008-2018-08-01-15-16-36-0400__LIDAR_TOP__1533151612397179.pcd.bin
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python3 tools/deploy.py configs/mmdet3d/voxel-detection/voxel-detection_onnxruntime_dynamic.py $MODEL_CONFIG $MODEL_PATH $TEST_DATA --work-dir centerpoint
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```
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| [pointpillars](https://github.com/open-mmlab/mmdetection3d/blob/main/configs/pointpillars/pointpillars_hv_secfpn_8xb6-160e_kitti-3d-3class.py) | voxel detection | KITTI | ✔️ | ✔️ | ✔️ |
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| [smoke](https://github.com/open-mmlab/mmdetection3d/blob/main/configs/smoke/smoke_dla34_dlaneck_gn-all_4xb8-6x_kitti-mono3d.py) | monocular detection | KITTI | ✔️ | x | ✔️ |
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- Make sure trt >= 8.4 for some bug fixed, such as ScatterND, dynamic shape crash and so on.
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- Make sure trt >= 8.6 for some bug fixed, such as ScatterND, dynamic shape crash and so on.

‎docs/zh_cn/04-supported-codebases/mmdet3d.md

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## 安装 mmdet3d
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因为依赖的 codebase 不在 master 分支，所以要切到相应分支：
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| codebase | commit |
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| :------: | :-------: |
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| mmdet3d | v1.1.0rc1 |
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| mmcv | v2.0.0rc1 |
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| mmdet | v3.0.0rc1 |
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| mmseg | v1.0.0rc0 |
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先安装前置依赖 mmcv/mmdet/mmseg，再安装 mmdet3d
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```bash
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python3 -m pip install openmim --user
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python3 -m mim install mmcv==2.0.0rc1 mmdet==3.0.0rc1 mmseg==1.0.0rc0 --user
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git clone https://github.com/open-mmlab/mmdetection3d --branch v1.1.0rc1
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cd mmdetection3d
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python3 -m pip install .
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cd -
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```
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成功后 `tools/check_env.py` 应能正常显示 mmdet3d 版本号。
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我们可以通过 [mim](https://github.com/open-mmlab/mim) 来安装 mmdet3d.
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更多安装方式可参考该[文档](https://mmdetection3d.readthedocs.io/en/latest/get_started.html#installation)
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```bash
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python3 tools/check_env.py
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..
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11/11 13:56:19 - mmengine - INFO - **********Codebase information**********
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11/11 13:56:19 - mmengine - INFO - mmdet: 3.0.0rc1
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11/11 13:56:19 - mmengine - INFO - mmseg: 1.0.0rc0
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..
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11/11 13:56:19 - mmengine - INFO - mmdet3d: 1.1.0rc1
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python3 -m pip install -U openmim
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python3 -m mim install "mmdet3d>=1.1.0"
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```
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## 模型转换
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使用 `tools/deploy.py` 把 mmdet3d 转到相应后端，以 centerpoint onnxruntime 为例：
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```bash
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export MODEL_CONFIG=/path/to/mmdetection3d/configs/centerpoint/centerpoint_pillar02_second_secfpn_head-circlenms_8xb4-cyclic-20e_nus-3d.py
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# 切换到 mmdeploy 根目录
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# 通过mim下载centerpoint模型
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mim download mmdet3d --config centerpoint_pillar02_second_secfpn_head-circlenms_8xb4-cyclic-20e_nus-3d --dest .
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export MODEL_CONFIG=centerpoint_pillar02_second_secfpn_head-circlenms_8xb4-cyclic-20e_nus-3d.py
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export MODEL_PATH=https://download.openmmlab.com/mmdetection3d/v1.0.0_models/centerpoint/centerpoint_02pillar_second_secfpn_circlenms_4x8_cyclic_20e_nus/centerpoint_02pillar_second_secfpn_circlenms_4x8_cyclic_20e_nus_20210816_064624-0f3299c0.pth
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export MODEL_PATH=centerpoint_02pillar_second_secfpn_circlenms_4x8_cyclic_20e_nus_20220811_031844-191a3822.pth
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export TEST_DATA=/path/to/mmdetection3d/tests/data/nuscenes/sweeps/LIDAR_TOP/n008-2018-09-18-12-07-26-0400__LIDAR_TOP__1537287083900561.pcd.bin
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export TEST_DATA=tests/data/n008-2018-08-01-15-16-36-0400__LIDAR_TOP__1533151612397179.pcd.bin
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python3 tools/deploy.py configs/mmdet3d/voxel-detection/voxel-detection_onnxruntime_dynamic.py $MODEL_CONFIG $MODEL_PATH $TEST_DATA --work-dir centerpoint
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```
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| [pointpillars](https://github.com/open-mmlab/mmdetection3d/blob/main/configs/pointpillars/pointpillars_hv_secfpn_8xb6-160e_kitti-3d-3class.py) | voxel detection | KITTI | ✔️ | ✔️ | ✔️ |
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| [smoke](https://github.com/open-mmlab/mmdetection3d/blob/main/configs/smoke/smoke_dla34_dlaneck_gn-all_4xb8-6x_kitti-mono3d.py) | monocular detection | KITTI | ✔️ | x | ✔️ |
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- 考虑到 ScatterND、动态 shape 等已知问题，请确保 trt >= 8.4
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- 考虑到 ScatterND、动态 shape 等已知问题，请确保 trt >= 8.6

‎tests/regression/mmdet.yml

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- deploy_config: configs/mmdet/detection/detection_tensorrt_static-640x640.py
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convert_image: *convert_image
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backend_test: *default_backend_test
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sdk_config: *sdk_dynamic
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- deploy_config: configs/mmdet/detection/single-stage_ncnn_static-640x640.py
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convert_image: *convert_image
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