onemetric
labelme2coco
onemetric | labelme2coco | |
---|---|---|
2 | 1 | |
58 | 248 | |
- | - | |
0.0 | 3.8 | |
over 2 years ago | about 1 month ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 only |
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onemetric
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?
torch-metrics - Metrics for model evaluation in pytorch
labelme - Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
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
bpycv - Computer vision utils for Blender (generate instance annoatation, depth and 6D pose by one line code)
coco-viewer - Minimalistic COCO Dataset Viewer in Tkinter
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
D3DShot - Extremely fast and robust screen capture on Windows with the Desktop Duplication API
HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision