image-statistics-matching VS albumentations

Compare image-statistics-matching vs albumentations and see what are their differences.

image-statistics-matching

Methods for alignment of global image statistics aimed at unsupervised Domain Adaptation and Data Augmentation (by continental)

albumentations

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125 (by albumentations-team)
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image-statistics-matching albumentations
1 28
24 13,395
- 1.9%
2.1 8.3
almost 2 years ago 4 days ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

image-statistics-matching

Posts with mentions or reviews of image-statistics-matching. We have used some of these posts to build our list of alternatives and similar projects.

albumentations

Posts with mentions or reviews of albumentations. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-06.

What are some alternatives?

When comparing image-statistics-matching and albumentations you can also consider the following projects:

cvlib - A simple, high level, easy to use, open source Computer Vision library for Python.

imgaug - Image augmentation for machine learning experiments.

tfaug - tensorflow easy image augmentation package

YOLO-Mosaic - Perform mosaic image augmentation on data for training a YOLO model

auto-blog-banner - 🌌 A Python script to generate blog banners from command line.

labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.

autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/

caer - High-performance Vision library in Python. Scale your research, not boilerplate.

Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0

BlenderProc - A procedural Blender pipeline for photorealistic training image generation

ttach - Image Test Time Augmentation with PyTorch!