albumentations VS labelme2coco

Compare albumentations vs labelme2coco 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 labelme2coco
6 1
9,493 76
2.9% -
8.3 0.6
3 days ago 4 days ago
Python Python
MIT License GNU General Public License v3.0 only
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 2021-06-01.

labelme2coco

Posts with mentions or reviews of labelme2coco. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-02-12.
  • What's A Simple Custom Segmentation Pipeline?
    3 projects | reddit.com/r/computervision | 12 Feb 2021
    I would also suggest labelme, it's pretty easy to use. Just type "labelme" in the shell after pip installing and you will see the GUI. There are tools to convert to coco format (like https://github.com/fcakyon/labelme2coco) if needed, for instance for Detectron2.

What are some alternatives?

When comparing albumentations and labelme2coco you can also consider the following projects:

imgaug - Image augmentation for machine learning experiments.

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

labelme - Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

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

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

autogluon - AutoGluon: AutoML for Text, Image, and Tabular Data

BlenderProc - A procedural Blender pipeline for photorealistic training image generation

mmsegmentation - OpenMMLab Semantic Segmentation Toolbox and Benchmark.

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

bpycv - Computer vision utils for Blender (generate instance annoatation, depth and 6D pose by one line code)

image-statistics-matching - Methods for alignment of global image statistics aimed at unsupervised Domain Adaptation and Data Augmentation

HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision