albumentations
serenity
albumentations | serenity | |
---|---|---|
28 | 240 | |
13,451 | 28,823 | |
1.1% | 1.7% | |
8.9 | 10.0 | |
3 days ago | 4 days ago | |
Python | C++ | |
MIT License | BSD 2-clause "Simplified" 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.
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.
serenity
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Why does part of the Windows 98 Setup program look older than the rest?
SerenityOS replicates that look and feel. It is also implemented in a dialect of C++ that adheres to some of the good parts of C++98: https://serenityos.org
- SerenityOS
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XZ: A Microcosm of the interactions in Open Source projects
One example of a useful technique
https://serenityos.org/ apparently only makes source code available. There are no binary images of the OS to install
I think Andreas said this functions like a little test -- if you're not willing to build it from source, then you probably wouldn't be a good contributor anyway.
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Likewise, my shell project provides source tarballs only, right now - https://www.oilshell.org/release/0.21.0/
It is packaged in a number of places, which I appreciate. That means some other people are willing to do some work.
And they provide good feedback.
I would like it to be more widely available, but yeah I definitely see that you need to "gate" peanut gallery feedback a bit, because it takes up a lot of time.
Of course, it's a tricky balance, because you also want feedback from casual users, to make the project better.
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Fuzzing Ladybird with tools from Google Project Zero
Indeed, given the existence of `JS::NonnullGCPtr`, `JS::GcPtr` intentionally corresponds to a nullable pointer, so it seems dangerous to convert one to a reference without a null-check.
That said, a naive code search finds what *may* be more cases of this pattern:
https://github.com/search?q=repo%3ASerenityOS%2Fserenity+%2F...
Eg: https://github.com/SerenityOS/serenity/blob/a68b134e6dea5065... -> https://github.com/SerenityOS/serenity/blob/a68b134e6dea5065...
In some of those search results, it is fine because there is a preceding null-check, and obviously I know nothing about this code other than this naive search result, but perhaps it would be prudent to vet all of them.
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The Ladybird Browser Project
It is a SerenityOS project. You can find the answer to that question in their primary project's FAQ[1].
1. https://github.com/SerenityOS/serenity/blob/master/Documenta...
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Sane C++ Libraries
https://github.com/SerenityOS/serenity
The best way to write proper exception free C++ is not to use the C++ Standard Library.
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Serenum: OS from scratch to save computers [video]
I initially confused it with Serenity OS prior to watching the video: https://github.com/SerenityOS/serenity
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Ask HN: What side projects landed you a job?
My contributions to SerenityOS[0] helped me get my current job. My team lead (who was also my interviewer) was interested in what I did since I listed some of it in my CV, and I showed him some PRs I made and explained what went into each of them. It was really exciting because I didn't have professional experience with low-level development, and basically got the job due to hobby programming.
[0]: https://github.com/SerenityOS/serenity/pulls?q=is%3Apr+autho...
- SerenityOS – a love letter to '90s user interfaces with a custom Unix-like core
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Bring garbage collected programming languages efficiently to WebAssembly
Definitely not "literally impossible", just a great deal of work. https://github.com/SerenityOS/serenity/tree/master/Ladybird
What are some alternatives?
imgaug - Image augmentation for machine learning experiments.
Chicago95 - A rendition of everyone's favorite 1995 Microsoft operating system for Linux.
YOLO-Mosaic - Perform mosaic image augmentation on data for training a YOLO model
rust-raspberrypi-OS-tutorials - :books: Learn to write an embedded OS in Rust :crab:
labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.
haiku - The Haiku operating system. (Pull requests will be ignored; patches may be sent to https://review.haiku-os.org).
autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
linux - Linux kernel source tree
Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
reactos - A free Windows-compatible Operating System
BlenderProc - A procedural Blender pipeline for photorealistic training image generation
redox - Mirror of https://gitlab.redox-os.org/redox-os/redox