albumentations
govuk-form-builder
| albumentations | govuk-form-builder | |
|---|---|---|
| 28 | 5 | |
| 13,451 | 70 | |
| 1.1% | - | |
| 8.9 | 8.7 | |
| 3 days ago | 6 days ago | |
| Python | Ruby | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
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.
govuk-form-builder
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Ask HN: What side projects landed you a job?
I build and maintain some libraries that are used by teams working on GOV.UK projects in Rails. Have been inundated with offers since their release, and they've gone on to be used in some fairly high profile things.
https://github.com/x-govuk/govuk-form-builder
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USWDS: The United States Web Design System
This is my side project, I'm a dev currently contracting at DfE. This library and the form builder[0] make working with the design system easier for Rails devs.
[0] https://govuk-form-builder.netlify.app/
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Meme, 2 images
If you dig around on GitHub you'll see most government departments have an organisation where they publish stuff. For example, here's the MoJ, DfE, Cabinet Office.
- Can I make a website entirely with Ruby?
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Why is uncoupled documentation bad?
This is definitely the best approach in my opinion, providing the people writing the docs are capable of contributing directly.
One of my projects[0] builds and deploys a static documentation site[1] on every push to master. The static site generator (Nanoc, in this case) then pulls in the library and uses it to publish its own documentation. All the examples are snippets of code[2] that are both displayed as-is and eval'd into the final output.
The guide can never be out of sync with the library.
[0] https://github.com/dfe-digital/govuk_design_system_formbuild...
[1] https://govuk-form-builder.netlify.app/
[2] https://github.com/DFE-Digital/govuk_design_system_formbuild...
What are some alternatives?
imgaug - Image augmentation for machine learning experiments.
Rails Bootstrap Forms - Official repository of the bootstrap_form gem, a Rails form builder that makes it super easy to create beautiful-looking forms using Bootstrap 5.
YOLO-Mosaic - Perform mosaic image augmentation on data for training a YOLO model
scripts-to-rule-them-all - Set of boilerplate scripts describing the normalized script pattern that GitHub uses in its projects.
labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.
django-sql-dashboard - Django app for building dashboards using raw SQL queries
autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
govuk_design_system_formbuild
Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
whitehall - Publishes government content on GOV.UK
BlenderProc - A procedural Blender pipeline for photorealistic training image generation
Docusaurus - Easy to maintain open source documentation websites.