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prepare_dataset.md

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Tool prepare_dataset

Overview

This tool converts original dataset to our unified meta-data, with data converters controlled by configs.

Argument: converter_config

converter_config is the path to a data_converter config file like below. If 2D perception data is not required by your method, set bbox_detector and kps2d_estimator to None. It will skip 2D perception and saves your time. For more details, see the docstring in code.

type = 'ShelfDataCovnerter'
data_root = 'datasets/Shelf'
bbox_detector = dict(
    type='MMtrackDetector',
    mmtrack_kwargs=dict(
        config='config/human_detection/' +
        'mmtrack_deepsort_faster-rcnn_fpn_4e_mot17-private-half.py',
        device='cuda'))
kps2d_estimator = dict(
    type='MMposeTopDownEstimator',
    mmpose_kwargs=dict(
        checkpoint='weight/hrnet_w48_coco_wholebody' +
        '_384x288_dark-f5726563_20200918.pth',
        config='config/human_detection/mmpose_hrnet_w48_' +
        'coco_wholebody_384x288_dark_plus.py',
        device='cuda'))
scene_range = [[300, 600]]
meta_path = 'datasets/Shelf/xrmocap_meta_testset'
visualize = True

Also, you can find our prepared config files in configs/modules/data/data_converter, with or without perception.

Argument: overwrite

By default, overwrite is False and there is a folder found at meta_path, the tool will raise an error, to avoid removal of existed files. Add --overwrite makes it True and allows the tool to overwrite any file below meta_path.

Argument: disable_log_file

By default, disable_log_file is False and a log file named converter_log_{time_str}.txt will be written. Add --disable_log_file makes it True and the tool will only print log to console.

After the tool succeeds, you will find log file in meta_path, otherwise it will be in logs/.

Argument: paths

By default, data_root and meta_path are empty, the tool takes paths in converter config file. If both of them are set, the tool takes paths from argv.

Examples

Run the tool when paths configured in campus_data_converter_testset.py.

python tool/prepare_dataset.py \
	--converter_config configs/modules/data/data_converter/campus_data_converter_testset.py

Run the tool with explicit paths.

python tool/prepare_dataset.py \
  --converter_config configs/modules/data/data_converter/campus_data_converter_testset.py \
  --data_root datasets/Campus \
  --meta_path datasets/Campus/xrmocap_meta_testset