imagezmq
YOLO-Mosaic
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| imagezmq | YOLO-Mosaic | |
|---|---|---|
| 0 | 1 | |
| 821 | 3 | |
| - | - | |
| 3.4 | 0.0 | |
| about 1 month ago | about 1 year ago | |
| Python | Python | |
| MIT License | - |
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imagezmq
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Tracking mentions began in Dec 2020.
YOLO-Mosaic
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Mosaic Image Augmentation for YOLO data
You can find my code here and I hope people find it useful. Cheers!
What are some alternatives?
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
imgaug - Image augmentation for machine learning experiments.
Beginner-Traffic-Light-Detection-OpenCV-YOLOv3 - This is a python program using YOLO and OpenCV to detect traffic lights. Works in The Netherlands, possibly other countries
imagehub - Receive and save images from multiple Raspberry Pi's
opencv-steel-darts - Automatic scoring system for steel darts using OpenCV, a Raspberry Pi 3 Model B and two webcams.
autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
lane-detection-opencv - This is for detecting any lane in the road to identify the road map