import os import glob import shutil La Puerta Secreta Pelicula Google Drive - Coraline Y
To provide the correct preparation steps, I need to clarify the output format you require, as typically refers to a dataset of Machine-Readable Zone (MRZ) or identity document images used for text detection and recognition. Zee 100 Pro Online
# logic to parse the specific ground truth format of MIDV-699 # (MIDV usually comes with XML or JSON coordinates for text regions) def parse_midv699_ground_truth(gt_file): # Implement parsing logic here based on the specific annotation file structure # Return cropped image path and label pass
# Example workflow with open(train_list_path, 'w', encoding='utf-8') as train_f: # Iterate through data, crop MRZ regions, and save labels # for item in dataset: # crop_image(...) # train_f.write(f"path/to/crop.jpg\t{text_label}\n") pass
I am ready to help you with the dataset preparation.
# Define paths raw_data_path = './midv699_raw' output_path = './midv699_processed' train_list_path = os.path.join(output_path, 'train_list.txt') val_list_path = os.path.join(output_path, 'val_list.txt')