GeoCOCO VS labelme2coco

Compare GeoCOCO vs labelme2coco and see what are their differences.

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GeoCOCO labelme2coco
1 1
4 248
- -
8.8 3.8
8 months ago 20 days ago
Python Python
GNU General Public License v3.0 only 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.
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GeoCOCO

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

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 | /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 GeoCOCO and labelme2coco you can also consider the following projects:

datumaro - Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.

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

qgis-earthengine-examples - A collection of 300+ Python examples for using Google Earth Engine in QGIS

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

WhiteboxTools-ArcGIS - ArcGIS Python Toolbox for WhiteboxTools

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

label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format

coco-viewer - Minimalistic COCO Dataset Viewer in Tkinter

sahi - Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

mmsegmentation - OpenMMLab Semantic Segmentation Toolbox and Benchmark.

cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/opencv/cvat]

autogluon - Fast and Accurate ML in 3 Lines of Code