HugsVision VS labelme2coco

Compare HugsVision vs labelme2coco and see what are their differences.

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HugsVision labelme2coco
1 1
188 247
- -
0.0 3.8
9 months ago 8 days ago
Jupyter Notebook Python
MIT License 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.
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.

HugsVision

Posts with mentions or reviews of HugsVision. 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 HugsVision and labelme2coco you can also consider the following projects:

poolformer - PoolFormer: MetaFormer Is Actually What You Need for Vision (CVPR 2022 Oral)

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

Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.

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

fashionpedia-api - Python API for Fashionpedia Dataset

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

ganspace - Discovering Interpretable GAN Controls [NeurIPS 2020]

coco-viewer - Minimalistic COCO Dataset Viewer in Tkinter

CoordConv

mmsegmentation - OpenMMLab Semantic Segmentation Toolbox and Benchmark.

Transformer-Explainability - [CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

autogluon - Fast and Accurate ML in 3 Lines of Code