AugLy
albumentations
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AugLy | albumentations | |
---|---|---|
14 | 28 | |
4,899 | 13,395 | |
0.5% | 1.9% | |
6.0 | 8.3 | |
about 1 month ago | 6 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | 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.
AugLy
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Meta's A.I. exodus: Top talent quits as lab tries to keep pace with rivals
Their recent effort to generate training data for spotting stuff that includes unsanctioned narratives comes to mind. https://github.com/facebookresearch/AugLy
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Next steps for after classification
Data augmentation is usually helpful: https://github.com/facebookresearch/AugLy
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The hand-picked selection of the best Python libraries released in 2021
AugLy.
- Prefer volume or quality for BERT-based Text classification model
- Augly - An augmentation library for audio, image, video, and text from facebook
- [D] What's the best method to generate synthetic data for an image with text? Small dataset
- AugLy is opensourse now.
- Facebook is open-sourcing AugLy, a library that uses data augmentations to evaluate and improve ML models
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Integration test: Complexity of privacy-preserving bird call bio-sensor for distributed ecological monitoring?
Some of the technologies which could be integrated include differential privacy, distributed online machine learning, misinformation resilience and multi-party computation, all within the context of smart contracts and bioinformatics.
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[N] Facebook AI Open Sources AugLy: A New Python Library For Data Augmentation To Develop Robust Machine Learning Models
Facebook Blog: https://ai.facebook.com/blog/augly-a-new-data-augmentation-library-to-help-build-more-robust-ai-models/
albumentations
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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
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What are the best programs/scripts for image augmentation of YOLO5 training dataset. Something like roboflow but free)
I think this is the most popular open source project: https://github.com/albumentations-team/albumentations
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To get dataset for face image restoration.
You can also curate your own dataset by using open source images (https://universe.roboflow.com/search?q=faces%20images%3E1000) and open source augmentations (https://github.com/albumentations-team/albumentations). Or you can do use the augmentation UI (https://docs.roboflow.com/image-transformations/image-augmentation) to apply noise, blurring, shear, crop, etc.
What are some alternatives?
imgaug - Image augmentation for machine learning experiments.
speechbrain - A PyTorch-based Speech Toolkit
YOLO-Mosaic - Perform mosaic image augmentation on data for training a YOLO model
PySyft - Perform data science on data that remains in someone else's server
labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.
BlenderProc - A procedural Blender pipeline for photorealistic training image generation
autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]
Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b