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[Feat]: Support PETR in 1.1 in
projects
(#2175)
* rebase * petr3d- * petr3d-to-petr * delete_NormalizeMultiviewImage * rename_PETR * rename_PETR * fix_bug * fix_bug * fix_bug * fix_bug * fix_bug * fix_bug * fix_bug * revise * remove_builder * remove_builder * remove_use_external * remove_use_external * remove_PadMultiViewImage * remove_PadMultiViewImage * remove-AddCamInfo * remove-LidarBox3dVersionTransfrom * remove-LidarBox3dVersionTransfrom-and-AddCamInfo * fix__init__ * remove-redundent-config * code-polish * remove-builder * remove-builder * remove-redundent-files * replace-forward-train-and-test * remove-redundent__init__ * remove_petr * remove-hierarchtecture
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# PETR | ||
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This is an README for `PETR`. | ||
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## Description | ||
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Author: @SekiroRong. | ||
This is an implementation of *PETR*. | ||
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## Usage | ||
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<!-- For a typical model, this section should contain the commands for training and testing. You are also suggested to dump your environment specification to env.yml by `conda env export > env.yml`. --> | ||
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### Training commands | ||
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In MMDet3D's root directory, run the following command to train the model: | ||
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```bash | ||
python tools/train.py projects/PETR/config/petr/petr_vovnet_gridmask_p4_800x320.py | ||
``` | ||
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### Testing commands | ||
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In MMDet3D's root directory, run the following command to test the model: | ||
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```bash | ||
python tools/test.py projects/PETR/config/petr/petr_vovnet_gridmask_p4_800x320.py ${CHECKPOINT_PATH} | ||
``` | ||
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## Results | ||
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<!-- List the results as usually done in other model's README. [Example](https://github.com/open-mmlab/mmdetection3d/edit/dev-1.x/configs/fcos3d/README.md) | ||
You should claim whether this is based on the pre-trained weights, which are converted from the official release; or it's a reproduced result obtained from retraining the model in this project. --> | ||
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This Result is trained by petr_vovnet_gridmask_p4_800x320.py and use [weights](https://drive.google.com/file/d/1ABI5BoQCkCkP4B0pO5KBJ3Ni0tei0gZi/view?usp=sharing) as pretrain weight. | ||
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| Backbone | Lr schd | Mem (GB) | Inf time (fps) | mAP | NDS | Download | | ||
| :----------------------------------------------------------------------------------------------: | :-----: | :------: | :------------: | :--: | :--: | :----------------------: | | ||
| [petr_vovnet_gridmask_p4_800x320](projects/PETR/configs/petr/petr_vovnet_gridmask_p4_800x320.py) | 1x | 7.62 | 18.7 | 38.3 | 43.5 | [model](<>) \| [log](<>) | | ||
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``` | ||
mAP: 0.3830 | ||
mATE: 0.7547 | ||
mASE: 0.2683 | ||
mAOE: 0.4948 | ||
mAVE: 0.8331 | ||
mAAE: 0.2056 | ||
NDS: 0.4358 | ||
Eval time: 118.7s | ||
Per-class results: | ||
Object Class AP ATE ASE AOE AVE AAE | ||
car 0.567 0.538 0.151 0.086 0.873 0.212 | ||
truck 0.341 0.785 0.213 0.113 0.821 0.234 | ||
bus 0.426 0.766 0.201 0.128 1.813 0.343 | ||
trailer 0.216 1.116 0.227 0.649 0.640 0.122 | ||
construction_vehicle 0.093 1.118 0.483 1.292 0.217 0.330 | ||
pedestrian 0.453 0.685 0.293 0.644 0.535 0.238 | ||
motorcycle 0.374 0.700 0.253 0.624 1.291 0.154 | ||
bicycle 0.345 0.622 0.262 0.775 0.475 0.011 | ||
traffic_cone 0.539 0.557 0.319 nan nan nan | ||
barrier 0.476 0.661 0.279 0.142 nan nan | ||
``` |
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