The CCPD can be downloaded from this link using either the Google or BaiduYun drive links.
This dataset is divided into 3 sets: train, val, test. Labels for each set can be found under the splits
directory of the dataset.
CCPD-Green dataset is already separated into different folders and thus does not require labels.
The annotations for each image are embedded into the filename of the image. The format is described on their official website here.
After downloading the dataset, the directory structure should be like as follows:
CCPD2019
|--- ccpd_base
| |--- <image_name>.jpg
| |--- <image_name>.jpg
| |--- ...
|--- ccpd_blur
| |--- <image_name>.jpg
| |--- <image_name>.jpg
| |--- ...
|--- ...
|--- ...
|--- ...
|--- splits
To prepare the data for text detection, you can run the following commands:
python tools/dataset_converters/convert.py \
--dataset_name ccpd --task det \
--image_dir path/to/CCPD2019/ \
--label_dir path/to/CCPD2019/splits/train.txt \
--output_path path/to/CCPD2019/det_gt.txt
label_dir
is not required for CCPD-Green dataset.
The generated standard annotation file det_gt.txt
will now be placed under the folder CCPD2019/
.
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