cocojson
labelme2coco
cocojson | labelme2coco | |
---|---|---|
1 | 1 | |
21 | 248 | |
- | - | |
0.0 | 3.8 | |
over 1 year ago | 15 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 only |
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cocojson
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?
coco-viewer - Minimalistic COCO Dataset Viewer in Tkinter
labelme - Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
datumaro - Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.
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
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
bpycv - Computer vision utils for Blender (generate instance annoatation, depth and 6D pose by one line code)
mmsegmentation - OpenMMLab Semantic Segmentation Toolbox and Benchmark.
autogluon - Fast and Accurate ML in 3 Lines of Code
mask-rcnn - Mask-RCNN training and prediction in MATLAB for Instance Segmentation
Mask_RCNN - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
sahi - Framework agnostic sliced/tiled inference + interactive ui + error analysis plots