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This repository contains Python code that implements an image augmentation pipeline using the albumentations library. The pipeline performs various augmentations on input images and corresponding labels and saves the augmented images and labels in separate directories.

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Albumentations

Image Augmentation Pipeline This Python code implements an image augmentation pipeline using the albumentations library. The pipeline performs various augmentations on input images and corresponding labels, and saves the augmented images and labels in separate directories.

Dependencies

Python 3.x OpenCV (cv2) library albumentations library

Usage

Place the input images and corresponding labels in separate directories named "Images" and "Labels", respectively. Run the Python code to generate augmented images and labels. The augmented images and labels will be saved in separate directories named "augmented_images" and "augmented_labels", respectively.

Augmentations

The following augmentations are performed on input images and corresponding labels: Horizontal Flip Vertical Flip Random Rotation (90 degrees) Rotation (up to 45 degrees)

Output

The augmented images and labels are saved in separate directories named "augmented_images" and "augmented_labels", respectively. The output files are named in the format "i_j.png", where "i" is the index of the input image and "j" is the index of the augmented image.

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This repository contains Python code that implements an image augmentation pipeline using the albumentations library. The pipeline performs various augmentations on input images and corresponding labels and saves the augmented images and labels in separate directories.

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