pymlimageutils 0.1.0

This package is useful for checking image data quality, separating image and label files, and splitting datasets.

mlutils

This package is useful for checking image data quality, separating image and label files, and splitting datasets.

Requirements

The package requires the following dependencies to be installed:

• os
• PIL (Python Imaging Library)
• cv2 (OpenCV)
• random
• shutil

Installation

you can install mlutils via pip: pip install mlutils

Usage

Check for corrupted images

Use the check_corrupted_images_in_directory(dir_in) function to check for corrupted images in a directory. It returns the number of corrupted images found.

from mlutils import check_corrupted_images_in_directory
check_corrupted_images_in_directory("/path/to/images/folder")

#####Check image naming conventions Use the check_naming_conventions(dir_in) function to check and fix image naming conventions in a directory. This function renames images with upper-case file extensions to lower-case and changes "jpeg" to "jpg" file extensions.

from mlutils import check_naming_conventions
check_naming_conventions("/path/to/images/folder")

####Detect and fix images with a premature ending Use the detect_and_fix_premature_ending(dir_path) function to detect and fix images with a premature ending in a directory. It returns the number of fixed images.

from mlutils import detect_and_fix_premature_ending
detect_and_fix_premature_ending("/path/to/images/folder")

####Separate and copy files Use the separate_and_copy_files(folders, dest_main_folder) function to separate image and label files from multiple folders and copy them to a new destination folder.

from mlutils import separate_and_copy_files
folders = ["/path/to/1st/images/folder", "/path/to/2nd/images/folder"]
dest_main_folder = "/path/to/destination/folder"
separate_and_copy_files(folders, dest_main_folder)

####Split a dataset Use the split_dataset(images_path, labels_path, img_val_path, label_val_path, split_fraction) function to split a dataset into training and validation sets. The function moves a fraction of images and their corresponding label files to validation folders.

from mlutils import split_dataset
images_path = "/path/to/training/images"
labels_path = "/path/to/training/labels"
img_val_path = "/path/to/validation/images"
label_val_path = "/path/to/validation/labels"
split_fraction = 0.2 # 20% of the data will be moved to validation set
split_dataset(images_path, labels_path, img_val_path, label_val_path, split_fraction)