imageset-viewer
review_object_detection_metrics
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| imageset-viewer | review_object_detection_metrics | |
|---|---|---|
| 1 | 2 | |
| 64 | 1,007 | |
| - | - | |
| 4.4 | 0.0 | |
| 10 months ago | 4 months ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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imageset-viewer
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!
What are some alternatives?
chitra - A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.
coco-viewer - Minimalistic COCO Dataset Viewer in Tkinter
globox - A package to read and convert object detection datasets (COCO, YOLO, PascalVOC, LabelMe, CVAT, OpenImage, ...) and evaluate them with COCO and PascalVOC metrics.
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
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.