Faster interpretation of the original COCOEval
Project description
Faster-COCO-Eval
Disclaimer
I often use this project, but I saw it abandoned and without a public repository on github. Also, part of the project remained unfinished for a long time. I implemented some of the author's ideas and decided to make the results publicly available.
Faster-COCO-Eval base
This package wraps a facebook C++ implementation of COCO-eval operations found in the pycocotools package. This implementation greatly speeds up the evaluation time for coco's AP metrics, especially when dealing with a high number of instances in an image.
Comparison
For our use case with a test dataset of 5000 images from the coco val dataset. Testing was carried out using the mmdetection framework and the eval_metric.py script. The indicators are presented below.
Visualization of testing comparison.ipynb available in directory examples/comparison Tested with yolo3 model (bbox eval) and yoloact model (segm eval)
Type | COCOeval | COCOeval_faster | Profit |
---|---|---|---|
bbox | 18.477 sec. | 7.345 sec. | 2.5x faster |
segm | 29.819 sec. | 15.840 sec. | 2x faster |
Feautures
This library provides not only validation functions, but also error visualization functions. Including visualization of errors in the image.
You can study in more detail in the examples and Wiki.
Usage
Code examples for using the library are available on the Wiki
Update history
Available via link history.md
License
The original module was licensed with apache 2, I will continue with the same license. Distributed under the apache version 2.0 license, see license for more information.
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