CVAugmentor

Introduction

This is a simple tool to augment images and videos for computer vision tasks.

Available augmentations are: no_augmentation, flip, zoom, rotate, shear, grayscale, hue, saturation, brightness, exposure, blur, noise, cutout, negative,

Installation

You can install the package using pip:

pip install CVAugmentor

Usage

Single Image Augmentation

# Importing the libraries
from CVAugmentor import Augmentations as aug
from CVAugmentor import Pipeline


# Define the augmentations
augmentations = {
    "zoom": aug.zoom(),
    "flip": aug.flip(),
}

# Create a Pipeline object
p = Pipeline()

# Augment the image
p.augment(input_path="path/to/input_image", output_path="path/to/output_image", target="image", type="single", mode="singular", augmentations=augmentations, verbose=True, warn_verbose=True)

Single Video Augmentation

# Importing the libraries
from CVAugmentor import Augmentations as aug
from CVAugmentor import Pipeline


# Define the augmentations
augmentations = {
    "zoom": aug.zoom(),
    "flip": aug.flip(),
}

# Create a Pipeline object
p = Pipeline()

# Augment the video
p.augment(input_path="path/to/input_video", output_path="path/to/output_video", target="video", type="single", mode="singular", augmentations=augmentations, verbose=True, warn_verbose=True)

Augmenting Multiple Images

# Importing the libraries
from CVAugmentor import Augmentations as aug
from CVAugmentor import Pipeline


# Define the augmentations
augmentations = {
    "zoom": aug.zoom(),
    "flip": aug.flip(),
}

# Create a Pipeline object
p = Pipeline()

# Augment the images
p.augment(input_path="path/to/input_images", output_path="path/to/output_images", target="image", type="batch", mode="singular", augmentations=augmentations, verbose=True, warn_verbose=True)

Augmenting Multiple Videos

# Importing the libraries
from CVAugmentor import Augmentations as aug
from CVAugmentor import Pipeline


# Define the augmentations
augmentations = {
    "zoom": aug.zoom(),
    "flip": aug.flip(),
}

# Create a Pipeline object
p = Pipeline()

# Augment the videos
p.augment(input_path="path/to/input_videos", output_path="path/to/output_videos", target="video", type="batch", mode="singular", augmentations=augmentations, verbose=True, warn_verbose=True)

License

This work is licensed under an MIT License.