Skip to main content

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

For a detailed usage guide, please refer to the documentation.

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", process_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", process_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", process_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", process_type="batch", mode="singular", augmentations=augmentations, verbose=True, warn_verbose=True)

License

This work is licensed under an MIT License.

Metadata

Release files for cvaugmentor 1.0.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for cvaugmentor 1.0.5
File Size Uploaded
CVAugmentor-1.0.5.tar.gz 11.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for cvaugmentor 1.0.5
File Interpreter ABI Platform
CVAugmentor-1.0.5-py3-none-any.whl Python 3 none any Details

Total release size: 25.4 kB

Release files / CVAugmentor-1.0.5.tar.gz

Download URL CVAugmentor-1.0.5.tar.gz
Size 11.1 kB
Tags Source
SHA-256 checksum
How to use checksums
c2c780ea78926bb68fb16cb1cd05b7ea4f6022883e0d2db6bd581c7d392dc25b
BLAKE2b-256 checksum
How to use checksums
456202aa82415a78d19bf53a31a7de6a26cb60659e8e4544e7c46af21be89656
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.9.16

Release files / CVAugmentor-1.0.5-py3-none-any.whl

Download URL CVAugmentor-1.0.5-py3-none-any.whl
Size 14.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
70b44dfb324b721266f3525896f089c68528d9b739bb858ba30002c1a6ec999d
BLAKE2b-256 checksum
How to use checksums
563d8cecd636971e85571d9053e2600f96391cc40474ebfbe03f12aa04f90bb1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.9.16

Release history Release notifications | RSS feed

2.0.0

2 release files

1.1.2

2 release files

1.1.1

2 release files

1.1.0

2 release files

1.0.9

2 release files

1.0.8

2 release files

1.0.7

2 release files

1.0.6

2 release files

This release

1.0.5 This release

2 release files

1.0.4

2 release files

1.0.3

2 release files

1.0.2

2 release files

1.0.1

2 release files

1.0.0

2 release files

0.0.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page