hippunfold
albumentations
| hippunfold | albumentations | |
|---|---|---|
| 3 | 30 | |
| 46 | 13,637 | |
| - | 1.4% | |
| 8.5 | 9.1 | |
| 9 days ago | about 22 hours ago | |
| Python | Python | |
| MIT License | MIT License |
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.
hippunfold
albumentations
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Recapping the AI, Machine Learning and Data Science Meetup - May 30, 2024
In this presentation, we explore key strategies for boosting the adoption of open-source libraries, using Albumentations.ai as a case study. We will cover the importance of community engagement, continuous innovation, and comprehensive documentation in driving a project’s success. Through the lens of Albumentations.ai’s growth, attendees will gain insights into effective practices for promoting their open source projects within the machine learning and broader developer communities.
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Recapping the AI, Machine Learning and Data Science Meetup — May 8, 2024
In this brief walkthrough, I will illustrate how to leverage open-source FiftyOne and Anomalib to build deployment-ready anomaly detection models. First, we will load and visualize the MVTec AD dataset in the FiftyOne App. Next, we will use Albumentations to test out augmentation techniques. We will then train an anomaly detection model with Anomalib and evaluate the model with FiftyOne.
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Augment specific classes?
You can use albumentations if you are comfortable with using open source libraries https://github.com/albumentations-team/albumentations
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Ask HN: What side projects landed you a job?
One of the members of the core team of our open-source library https://albumentations.ai/
It was not the only reason he was hired; it was a solid addition to his already good performance at the interviews.
Or at least that is what the hiring manager later said.
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The Lack of Compensation in Open Source Software Is Unsustainable
I am one of the creators and maintainers of https://albumentations.ai/.
- 12800+ stars
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Burn Deep Learning Framework Release 0.7.0: Revamped (de)serialization, optimizer & module overhaul, initial ONNX support and tons of new features.
Is something planned to support data augmentations? Something like https://albumentations.ai/
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How to label augmented images for training YOLO algorithm?
Here you go: https://albumentations.ai/
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Unstable Diffusion bounces back with $19,000 raised in one day, by using Stripe
I think they should use some data augmentation techniques like I am using for Infinity AI if you wanna see more here. Note that most of these do not work for image generation.
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Tokyo Drift : detecting drift in images with NannyML and Whylogs
Our second approach was a more automated one. Here the idea was to try out an image augmentation library, Albumentations, and use it for adversarial attacks. This time, instead of one-shot images, we applied the transformations at random time ranges. We chose for these transformations also to be more subtle than then one-shot images, such as vertical flips, grayscaling, downscaling, …
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[D] Improve machine learning with same number of images
Check out albumentations. If your use case is segmentation, check out the offline augmentation of this project
What are some alternatives?
yolo_tracking - BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models
imgaug - Image augmentation for machine learning experiments.
YOLO-Mosaic - Perform mosaic image augmentation on data for training a YOLO model
labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.
autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
BlenderProc - A procedural Blender pipeline for photorealistic training image generation
ttach - Image Test Time Augmentation with PyTorch!
image-statistics-matching - Methods for alignment of global image statistics aimed at unsupervised Domain Adaptation and Data Augmentation
cvlib - A simple, high level, easy to use, open source Computer Vision library for Python.
SickZil-Machine - Manga/Comics Translation Helper Tool
VoTT - Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.