bbox-visualizer
coco-viewer
| bbox-visualizer | coco-viewer | |
|---|---|---|
| 2 | 1 | |
| 374 | 162 | |
| - | - | |
| 4.8 | 0.0 | |
| 3 months ago | 12 days ago | |
| Python | Python | |
| MIT License | MIT License |
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bbox-visualizer
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Community mingling live event, autonomous driving lecture, job opening, meet the member and more (Announcements 04.03.2021)
Meet the member - Shoumik Sharar Chowdhury. Shoumik and I had several talks the past months, he build the git project bbox-visualizer - This lets researchers draw bounding boxes and then labeling them easily with a stand-alone package. (The blog post)
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Meet the member - Shoumik Sharar Chowdhury
Another project I've worked on is the bbox-visualizer. This lets researchers draw bounding boxes and then labeling them easily with a stand-alone package. The code is very accessible and so I would encourage any open-source enthusiasts to contribute to the project. This would also be a good place to start for beginners who are just starting out with computer vision/open-source.
coco-viewer
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Any GUI to load labels and the images to verify if the bounding boxes are right?
If your dataset is in a coco format, I had a lot of success with this : https://github.com/trsvchn/coco-viewer
What are some alternatives?
nuscenes-devkit - The devkit of the nuScenes dataset.
cocojson - Utility scripts for COCO json annotation format
second.pytorch - PointPillars for KITTI object detection
labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.
diffgram - The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get the most value out of your AI Data.
labelCloud - A lightweight tool for labeling 3D bounding boxes in point clouds.
Unsupervised-Attention-guided-Image-to-Image-Translation - Unsupervised Attention-Guided Image to Image Translation
pycococreator - Helper functions to create COCO datasets
globox - A package to read and convert object detection datasets (COCO, YOLO, PascalVOC, LabelMe, CVAT, OpenImage, ...) and evaluate them with COCO and PascalVOC metrics.
sahi - Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
graph-cut-ransac - The Graph-Cut RANSAC algorithm proposed in paper: Daniel Barath and Jiri Matas; Graph-Cut RANSAC, Conference on Computer Vision and Pattern Recognition, 2018. It is available at http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Graph-Cut_RANSAC_CVPR_2018_paper.pdf
imageset-viewer - Pascal VOC BBox Viewer