GeoCOCO
labelme2coco
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 |
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GeoCOCO
labelme2coco
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What's A Simple Custom Segmentation Pipeline?
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?
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