albumentations VS rembg-greenscreen

Compare albumentations vs rembg-greenscreen and see what are their differences.

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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albumentations rembg-greenscreen
28 2
13,395 254
1.9% -
8.3 0.0
5 days ago 11 months 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.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.

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.

rembg-greenscreen

Posts with mentions or reviews of rembg-greenscreen. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-07-26.

What are some alternatives?

When comparing albumentations and rembg-greenscreen you can also consider the following projects:

imgaug - Image augmentation for machine learning experiments.

backgroundremover - Background Remover lets you Remove Background from images and video using AI with a simple command line interface that is free and open source.

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

U-2-Net - The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."

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

PixelLib - Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/

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

segmentation_models - Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

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

segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.

BlenderProc - A procedural Blender pipeline for photorealistic training image generation

ttach - Image Test Time Augmentation with PyTorch!