datamodules.IndexedFormats.utils package
Submodules
datamodules.IndexedFormats.utils.image_analytics module
- get_analytics(input_path: Path, data_folder_name: str, gt_folder_name: str, train_folder_name: str, get_img_gt_path_list_func: callable, inmem: bool = False, workers: int = 8) Tuple[Dict[str, Any], Dict[str, Any]][source]
Get the analytics for the dataset. If the analytics file is not present, it will be computed and saved.
- Parameters:
workers (int) – Number of workers to calculate the mean and std
inmem (bool) – Load the images in memory or load them separately
input_path (Path) – Path to the root of the dataset
data_folder_name (str) – Name of the folder containing the data
gt_folder_name (str) – Name of the folder containing the ground truth
train_folder_name (str) – Name of the folder containing the training data
get_img_gt_path_list_func (Callable[[Path, str, str], List[Tuple[Path, Path]]]) – Function to get the list of image and ground truth paths
- Returns:
Tuple of analytics for the data and ground truth
- Return type:
Tuple[Dict[str, Any], Dict[str, Any]]
datamodules.IndexedFormats.utils.output_tools module
- save_output_page_image(image_name, output_image, output_folder: Path, class_encoding: List[Tuple[int]])[source]
Helper function to save the output during testing in the DIVAHisDB format
- Parameters:
image_name (str) – name of the image that is saved
output_image (np.ndarray) – output image at full size
output_folder (Path) – path to the output folder for the test data
class_encoding (List[Tuple[int]]) – list with the class encodings