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Data augmentation strategies for object detection? Could you point me to good resources or best practices you know of?
1 project | reddit.com/r/computervision | 30 Oct 2021
You can definitely look at Albumentation - we had a ton of success working with this library https://github.com/albumentations-team/albumentations
Albumentations 1.1.0 Was Released
1 project | news.ycombinator.com | 5 Oct 2021
Optimization for semantic segmentation!
1 project | reddit.com/r/deeplearning | 6 Sep 2021
[P] Albumentations 1.0 is released (a Python library for image augmentation)
4 projects | reddit.com/r/MachineLearning | 1 Jun 2021
Full release notes: https://github.com/albumentations-team/albumentations/releases/tag/1.0.04 projects | reddit.com/r/MachineLearning | 1 Jun 2021
If you want to know what changed in the latest versions, please refer to the [Release Notes](https://github.com/albumentations-team/albumentations/releases) page.
[Urgent Help] CNN model not working desirably
1 project | reddit.com/r/neuralnetworks | 30 Apr 2021
Image augmentation could help amplify your dataset without needing additional training data. Check out albumentations. It’s super easy.
What's A Simple Custom Segmentation Pipeline?
3 projects | reddit.com/r/computervision | 12 Feb 2021
I would also suggest labelme, it's pretty easy to use. Just type "labelme" in the shell after pip installing and you will see the GUI. There are tools to convert to coco format (like https://github.com/fcakyon/labelme2coco) if needed, for instance for Detectron2.
What are some alternatives?
imgaug - Image augmentation for machine learning experiments.
YOLO-Mosaic - Perform mosaic image augmentation on data for training a YOLO model
labelme - Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
autogluon - AutoGluon: AutoML for Text, Image, and Tabular Data
BlenderProc - A procedural Blender pipeline for photorealistic training image generation
mmsegmentation - OpenMMLab Semantic Segmentation Toolbox and Benchmark.
cvlib - A simple, high level, easy to use, open source Computer Vision library for Python.
bpycv - Computer vision utils for Blender (generate instance annoatation, depth and 6D pose by one line code)
image-statistics-matching - Methods for alignment of global image statistics aimed at unsupervised Domain Adaptation and Data Augmentation
HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision