labelme2coco
bpycv
Our great sponsors
| labelme2coco | bpycv | |
|---|---|---|
| 1 | 3 | |
| 246 | 453 | |
| - | - | |
| 3.8 | 4.6 | |
| 5 days ago | about 1 month ago | |
| Python | Python | |
| GNU General Public License v3.0 only | MIT License |
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.
labelme2coco
-
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.
bpycv
- Bpycv: Computer Vision and Deep Learning Utils for Blender
-
Python code that takes pictures from different view points of a 3d model
Blender is capable of running in a headless mode. I ‘ve had the exact same use case nearly a thousand times. This library worked out well for my purposes https://github.com/DIYer22/bpycv
-
[P] Synthetic Data for CV with Python and Blender
Can someone who knows a bit about this compare to, e.g., bpycv? Seems like they are doing very similar stuff
What are some alternatives?
labelme - Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
zpy - Synthetic data for computer vision. An open source toolkit using Blender and Python.
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
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.
learning-topology-synthetic-data - Tensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)
autogluon - AutoGluon: Fast and Accurate ML in 3 Lines of Code
pyrender - Easy-to-use glTF 2.0-compliant OpenGL renderer for visualization of 3D scenes.
mask-rcnn - Mask-RCNN training and prediction in MATLAB for Instance Segmentation
unsupervised-depth-completion-visual-inertial-odometry - Tensorflow and PyTorch implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)