Skip to content

README.md

Latest commit

 

History

History
108 lines (82 loc) · 4.57 KB

README.md

File metadata and controls

108 lines (82 loc) · 4.57 KB

Datasets

The procedures to get and process the datasets are described here.

Structure

This is the folder structure you need to handle data used in the CoMix repository. The data is stored in the following sub-folders:

  • original datasets
    • data/datasets: contains the downloaded raw data (from other sources), used in the CoMix repository.
  • processed datasets
    • data/datasets.unify: contains the unified data after having processed all the raw images and the splits (this folder is already present).
  • unified datasets
    • data/comix.coco: in order to evaluate the models, the data is converted to COCO format.
  • predictions
    • predicts.coco: predictions for detection models
    • predicts.caps: captioning

Data Collection

eBDtheque

The eBDtheque dataset can be downloaded from the website, after registration. Once you have downloaded the dataset, ONLY place the Pages folder into the datasets/eBDtheque folder.

Convert images

To convert the images of eBDtheque to the unified format, run the following command:

$ python comix/process/ebdtheque.py

Check the comix/process/ebdtheque.py file for the arguments, if you want to change the default values.

Manga109

According to the license of Manga109, the redistribution of the images of Manga109 is not permitted. Thus, you should download the images of Manga109 via the Manga109 webpage.

After downloading, unzip Manga109.zip into the folder datasets. Move all the contents of Manga109_released_x to the upper folder, then delete the empty directory Manga109_released_x.

Remove unused files:

cd data/datasets/Manga109
rm -rf annotations.v20*
rm -rf annotations

The folder structure should look like this:

datasets/
└── Manga109
    ├── images
    ├── books.txt
    ├── readme.txt

Convert images

To convert the images of Manga109 to the unified format, run the following command:

$ python comix/process/manga109.py

which has the following arguments:

  • --input-path: path to the Manga109 folder (default: data/datasets/Manga109)
  • --output-path: path to the output folder (default: data/datasets.unify/Manga109)
  • --override: override the existing images, annotations are always overwritten (default: False)
  • --limit: stop after the first {limit} books (default: None)

DCM

After downloading the dataset from here, unzip DCM_dataset_public_images.zip into the folder datasets. Rename the extracted directory as DCM and delete the zip file.

Convert images

The DCM dataset needs to be preprocessed before being converted into the unified format. To preprocess the DCM dataset (jpg renaming) and then convert images to the unified format, run the following command:

$ python comix/process/dcm.py

In DCM original enumeration of images starts from '001' rather than '000'. We decided to keep it.

Comics

Download the original page images. Unzip raw_pages_images.tar.gz into the folder datasets and rename the extracted folder books. Then, move this folder in an upper new created directory named comics.

The folder hierarchy should look like this:

datasets/
└── comics
    ├── books

Convert images

The Comics dataset needs to be preprocessed before being converted into the unified format. To preprocess the Comics dataset (jpg renaming) and then convert images to the unified format, run the following command:

$ python comix/process/comics.py

In Comics dataset some images are not viewable (usually first/last ones). We renamed them anyway.

Check the comix/process/comics.py file for the arguments, if you want to change the default values.

PopManga

To download the dataset, please refer to magi repository. After downloading, please locate Popmanga folder into data/datasets and rename it into popmanga. Then, inside the folder delete annotations.

Convert images

Now, you can convert the images of comics to the unified format by running the following command:

$ python comix/process/popmanga.py

SPLITS

In the path data/datasets.unify/name_of_the_dataset/splits the splits are available for every dataset except for Manga109. In particular val.csv and test.csv are available for every dataset. Furthermore, in comics there is also train.csv
⚡