review_object_detection_metrics
globox
| review_object_detection_metrics | globox | |
|---|---|---|
| 2 | 1 | |
| 1,007 | 149 | |
| - | - | |
| 0.0 | 7.3 | |
| 4 months ago | 13 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | 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.
review_object_detection_metrics
- How to run PyQt5 applications on Ubuntu (WSLg)?
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Links to papers or books that discuss model evaluation methods for object detection models
This is a good repository for you to start. https://github.com/rafaelpadilla/review_object_detection_metrics Ultimately you would want to compute the precision, recall, average precision, average recall, and mean Average Precision (mAP) that you’ve probably seen in many papers. Good luck!
globox
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Package for object detection database management and evaluation
My project is hosted on Github here: https://github.com/laclouis5/globox. Learning is a continuous and never ending process, so feel free to comment my work or propose enhancements. I hope that my modest contribution will help people that were in the same situation as me years ago!
What are some alternatives?
chitra - A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.
DA-RetinaNet - Official Detectron2 implementation of DA-RetinaNet of our Image and Vision Computing 2021 work 'An unsupervised domain adaptation scheme for single-stage artwork recognition in cultural sites'
imageset-viewer - Pascal VOC BBox Viewer
DA-Faster-RCNN - Detectron2 implementation of DA-Faster R-CNN, Domain Adaptive Faster R-CNN for Object Detection in the Wild
examples - Learn to create a desktop app with Python and Qt
bbox-visualizer - Make drawing and labeling bounding boxes easy as cake
yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x
labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.
YOLO-Coco-Dataset-Custom-Classes-Extractor - Get specific classes from the Coco Dataset with annotations for the Yolo Object Detection model for building custom object detection models.
datumaro - Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.