Skip to main content

Object detection augmentations.

Project description


Some augmentations that I hasn't found in other repositories and libraries.

Current augmentations:

Getting Started

pip install augmixations  

Example with default parameters


from augmixations import Cutmix, Cutout, Mixup    

Using Cutmix:

#bg_img - The image into which a rectangle will be inserted
#fg_img - The image from which a random rectangle will be cut 

cutmix = Cutmix()
img, boxes, labels = cutmix(bg_img, bg_boxes, bg_labels, fg_img, fg_boxes, fg_labels)  


Using Cutout:

cutout = Cutout()
new_img, new_boxes, new_labels = cutmix(img, boxes, labels)


Using Mixup:

mixup = Mixup()
image, boxes, labels = mixup(first_img, first_boxes, first_labels, 
                             second_img, second_boxes, second_labels)


Advansed usage

You can pass special configs to the cutmix function to override its behavior.

Cutmix Advanced Usage


Issues should be raised directly in the repository. For professional support and recommendations please

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for augmixations, version 0.2.21
Filename, size File type Python version Upload date Hashes
Filename, size augmixations-0.2.21-py3-none-any.whl (19.6 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size augmixations-0.2.21.tar.gz (14.5 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page