mirror of https://github.com/open-mmlab/mmyolo.git
146 lines
4.5 KiB
Markdown
146 lines
4.5 KiB
Markdown
# Dataset preparation and description
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## DOTA Dataset
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### Download dataset
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The DOTA dataset can be downloaded from [DOTA](https://captain-whu.github.io/DOTA/dataset.html)
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or [OpenDataLab](https://opendatalab.org.cn/DOTA_V1.0).
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We recommend using [OpenDataLab](https://opendatalab.org.cn/DOTA_V1.0) to download the dataset, as the folder structure has already been arranged as needed and can be directly extracted without the need to adjust the folder structure.
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Please unzip the file and place it in the following structure.
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```none
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${DATA_ROOT}
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├── train
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│ ├── images
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│ │ ├── P0000.png
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│ │ ├── ...
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│ ├── labelTxt-v1.0
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│ │ ├── labelTxt
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│ │ │ ├── P0000.txt
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│ │ │ ├── ...
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│ │ ├── trainset_reclabelTxt
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│ │ │ ├── P0000.txt
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│ │ │ ├── ...
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├── val
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│ ├── images
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│ │ ├── P0003.png
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│ │ ├── ...
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│ ├── labelTxt-v1.0
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│ │ ├── labelTxt
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│ │ │ ├── P0003.txt
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│ │ │ ├── ...
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│ │ ├── valset_reclabelTxt
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│ │ │ ├── P0003.txt
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│ │ │ ├── ...
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├── test
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│ ├── images
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│ │ ├── P0006.png
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│ │ ├── ...
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```
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The folder ending with reclabelTxt stores the labels for the horizontal boxes and is not used when slicing.
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### Split DOTA dataset
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Script `tools/dataset_converters/dota/dota_split.py` can split and prepare DOTA dataset.
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```shell
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python tools/dataset_converters/dota/dota_split.py \
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[--splt-config ${SPLIT_CONFIG}] \
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[--data-root ${DATA_ROOT}] \
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[--out-dir ${OUT_DIR}] \
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[--ann-subdir ${ANN_SUBDIR}] \
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[--phase ${DATASET_PHASE}] \
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[--nproc ${NPROC}] \
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[--save-ext ${SAVE_EXT}] \
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[--overwrite]
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```
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shapely is required, please install shapely first by `pip install shapely`.
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**Description of all parameters**：
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- `--split-config` : The split config for image slicing.
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- `--data-root`: Root dir of DOTA dataset.
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- `--out-dir`: Output dir for split result.
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- `--ann-subdir`: The subdir name for annotation. Defaults to `labelTxt-v1.0`.
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- `--phase`: Phase of the data set to be prepared. Defaults to `trainval test`
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- `--nproc`: Number of processes. Defaults to 8.
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- `--save-ext`: Extension of the saved image. Defaults to `png`
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- `--overwrite`: Whether to allow overwrite if annotation folder exist.
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Based on the configuration in the DOTA paper, we provide two commonly used split config.
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- `./split_config/single_scale.json` means single-scale split.
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- `./split_config/multi_scale.json` means multi-scale split.
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DOTA dataset usually uses the trainval set for training and the test set for online evaluation, since most papers
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provide the results of online evaluation. If you want to evaluate the model performance locally firstly, please split
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the train set and val set.
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Examples:
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Split DOTA trainval set and test set with single scale.
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```shell
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python tools/dataset_converters/dota/dota_split.py
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--split-config 'tools/dataset_converters/dota/split_config/single_scale.json'
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--data-root ${DATA_ROOT} \
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--out-dir ${OUT_DIR}
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```
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If you want to split DOTA-v1.5 dataset, which have different annotation dir 'labelTxt-v1.5'.
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```shell
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python tools/dataset_converters/dota/dota_split.py
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--split-config 'tools/dataset_converters/dota/split_config/single_scale.json'
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--data-root ${DATA_ROOT} \
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--out-dir ${OUT_DIR} \
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--ann-subdir 'labelTxt-v1.5'
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```
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If you want to split DOTA train and val set with single scale.
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```shell
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python tools/dataset_converters/dota/dota_split.py
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--split-config 'tools/dataset_converters/dota/split_config/single_scale.json'
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--data-root ${DATA_ROOT} \
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--phase train val \
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--out-dir ${OUT_DIR}
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```
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For multi scale split:
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```shell
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python tools/dataset_converters/dota/dota_split.py
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--split-config 'tools/dataset_converters/dota/split_config/multi_scale.json'
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--data-root ${DATA_ROOT} \
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--out-dir ${OUT_DIR}
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```
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The new data structure is as follows:
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```none
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${OUT_DIR}
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├── trainval
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│ ├── images
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│ │ ├── P0000__1024__0___0.png
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│ │ ├── ...
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│ ├── annfiles
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│ │ ├── P0000__1024__0___0.txt
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│ │ ├── ...
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├── test
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│ ├── images
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│ │ ├── P0006__1024__0___0.png
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│ │ ├── ...
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│ ├── annfiles
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│ │ ├── P0006__1024__0___0.txt
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│ │ ├── ...
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```
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Then change `data_root` to ${OUT_DIR}.
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