chitra
review_object_detection_metrics
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| chitra | review_object_detection_metrics | |
|---|---|---|
| 1 | 2 | |
| 223 | 1,007 | |
| 0.4% | - | |
| 3.2 | 0.0 | |
| 28 days ago | 4 months ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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.
chitra
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Answer: Resizing image and its bounding box
Another way of doing this is to use CHITRA
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?
tf-keras-vis - Neural network visualization toolkit for tf.keras
globox - A package to read and convert object detection datasets (COCO, YOLO, PascalVOC, LabelMe, CVAT, OpenImage, ...) and evaluate them with COCO and PascalVOC metrics.
img2dataset - Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.
imageset-viewer - Pascal VOC BBox Viewer
gallery - BentoML Example Projects 🎨
examples - Learn to create a desktop app with Python and Qt
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
yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x
pytest-visual - A visual testing framework for ML with automated change detection
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.
pytorch-toolbelt - PyTorch extensions for fast R&D prototyping and Kaggle farming
Text2Poster-ICASSP-22 - Official implementation of the ICASSP-2022 paper "Text2Poster: Laying Out Stylized Texts on Retrieved Images"