YOLO-Mosaic
imgaug
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| YOLO-Mosaic | imgaug | |
|---|---|---|
| 1 | 7 | |
| 7 | 14,140 | |
| - | - | |
| 0.0 | 0.0 | |
| about 3 years ago | 19 days ago | |
| Python | Python | |
| - | MIT License |
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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!
imgaug
- How to label augmented images for training YOLO algorithm?
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Improve Your Deep Learning Models with Image Augmentation
There are many good options when it comes to tools and libraries for implementing data augmentation into our deep learning pipeline. You could for instance do your own augmentations using NumPy or Pillow. Some of the most popular dedicated libraries for image augmentation include Albumentations, imgaug, and Augmentor. Both TensorFlow and PyTorch even come with their own packages dedicated to image augmentation.
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[N] Facebook AI Open Sources AugLy: A New Python Library For Data Augmentation To Develop Robust Machine Learning Models
https://github.com/aleju/imgaug This one is way better for image.
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[UPDATE!] Recognize trinkets with Isaac Item Recognizer! And also a few useful features in my newest update.
I have to improve my dataset with more backgrounds featuring obstacles. At the moment I'm working on creating a dataset with both items and trinkets, and I'm planning on using https://github.com/aleju/imgaug which will replace most of the stuff I'm doing with PIL.
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Support creation of tf.data.Dataset (data generator) and augmentation for image.
Do you acknowledge that there is ImageDataGenerator and ImgAug?
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[P] Albumentations 1.0 is released (a Python library for image augmentation)
Albumentations no longer uses the imgaug library by default. All previous imgaug augmentations in the library are reimplemented in Albumentations with the same API (but you can still install Albumentations with imgaug if you need the old augmentations).
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Bounding boxes do not completely wrap the objects with YOLOv4
I would also recommend you to give a try to TensorFlow Object Detection Model - https://github.com/tensorflow/models/tree/master/research/object_detection with augmentation - https://github.com/aleju/imgaug pipeline. The same worked for me in a similar use case where I had to localise logo on documents.
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
autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
tensorflow - An Open Source Machine Learning Framework for Everyone
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
AugLy - A data augmentations library for audio, image, text, and video.
imagezmq - A set of Python classes that transport OpenCV images from one computer to another using PyZMQ messaging.
speechbrain - A PyTorch-based Speech Toolkit
hcaptcha-challenger - 🥂 Gracefully face hCaptcha challenge with MoE(ONNX) embedded solution.
tfaug - tensorflow easy image augmentation package
png - A pure Erlang library for creating PNG images. It can currently create 8 and 16 bit RGB, RGB with alpha, indexed, grayscale and grayscale with alpha images.