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pcdet/datasets/kitti/kitti_object_eval_python/README.md
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pcdet/datasets/kitti/kitti_object_eval_python/README.md
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# kitti-object-eval-python
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**Note**: This is borrowed from [traveller59/kitti-object-eval-python](https://github.com/traveller59/kitti-object-eval-python)
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Fast kitti object detection eval in python(finish eval in less than 10 second), support 2d/bev/3d/aos. , support coco-style AP. If you use command line interface, numba need some time to compile jit functions.
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## Dependencies
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Only support python 3.6+, need `numpy`, `skimage`, `numba`, `fire`. If you have Anaconda, just install `cudatoolkit` in anaconda. Otherwise, please reference to this [page](https://github.com/numba/numba#custom-python-environments) to set up llvm and cuda for numba.
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* Install by conda:
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```
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conda install -c numba cudatoolkit=x.x (8.0, 9.0, 9.1, depend on your environment)
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```
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## Usage
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* commandline interface:
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```
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python evaluate.py evaluate --label_path=/path/to/your_gt_label_folder --result_path=/path/to/your_result_folder --label_split_file=/path/to/val.txt --current_class=0 --coco=False
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```
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* python interface:
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```Python
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import kitti_common as kitti
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from eval import get_official_eval_result, get_coco_eval_result
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def _read_imageset_file(path):
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with open(path, 'r') as f:
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lines = f.readlines()
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return [int(line) for line in lines]
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det_path = "/path/to/your_result_folder"
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dt_annos = kitti.get_label_annos(det_path)
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gt_path = "/path/to/your_gt_label_folder"
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gt_split_file = "/path/to/val.txt" # from https://xiaozhichen.github.io/files/mv3d/imagesets.tar.gz
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val_image_ids = _read_imageset_file(gt_split_file)
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gt_annos = kitti.get_label_annos(gt_path, val_image_ids)
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print(get_official_eval_result(gt_annos, dt_annos, 0)) # 6s in my computer
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print(get_coco_eval_result(gt_annos, dt_annos, 0)) # 18s in my computer
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```
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