to_darknet#

Dataset.to_darknet(output_path: Path | str, copy_images: bool = False, overwrite_images: bool = True, overwrite_labels: bool = True, create_split_folder: bool = False) → None[source]#

Save dataset in darknet format, readable by darknet . Save in the same folder the images, annotations and data files

Parameters:

  • output_path – folder where images and annotations will be stored

  • copy_images – If set to False, will create a symbolic link instead of copying. Much faster, but needs to keep original images in the same relative path. Defaults to False.

  • overwrite_images – if set to False, will skip images that are already copied. Defaults to True.

  • overwrite_labels – if set to False, will skip annotation that are already created. Defaults to True.

  • create_split_folder – if set to True, will create a dedicated folder for each split and will save images in it. Image paths in {split}.txt will be changed accordingly. Note that this changes the dataset structure. Defaults to False

See also