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Updated readme to reflect AlbumentationsX #2570

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Updated readme to reflect AlbumentationsX #2570

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1 change: 1 addition & 0 deletions .cursor/rules/albumentations-rules.mdc
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Original file line number Diff line number Diff line change
Expand Up @@ -12,3 +12,4 @@ alwaysApply: true
- We do not have ANY default values in the InitSchema class
- Use pytest.mark.parametrize for parameterized tests
- In the code, when need default value use 137, not 42
- If you want to create tests - create it in the tests folder.
111 changes: 76 additions & 35 deletions README.md
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Expand Up @@ -12,52 +12,98 @@

[Docs](https://albumentations.ai/docs/) | [Discord](https://discord.gg/AKPrrDYNAt) | [Twitter](https://twitter.com/albumentations) | [LinkedIn](https://www.linkedin.com/company/100504475/)

## GitAds Sponsored
[![Sponsored by GitAds](https://gitads.dev/v1/ad-serve?source=albumentations-team/albumentations@github)](https://gitads.dev/v1/ad-track?source=albumentations-team/albumentations@github)
## ⚠️ Important Notice: Albumentations is No Longer Maintained

**This repository is no longer actively maintained.** The last update was in June 2025, and no further bug fixes, features, or compatibility updates will be provided.

Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to increase the quality of trained models. The purpose of image augmentation is to create new training samples from the existing data.
### 🚀 Introducing AlbumentationsX - The Future of Albumentations

Here is an example of how you can apply some [pixel-level](#pixel-level-transforms) augmentations from Albumentations to create new images from the original one:
![parrot](https://habrastorage.org/webt/bd/ne/rv/bdnerv5ctkudmsaznhw4crsdfiw.jpeg)
All development has moved to **[AlbumentationsX](https://github.com/albumentations-team/AlbumentationsX)**, the next-generation successor to Albumentations.

## Why Albumentations
> **Note:** AlbumentationsX uses dual licensing (AGPL-3.0 / Commercial). The AGPL license has strict copyleft requirements - see details below.

- **Complete Computer Vision Support**: Works with [all major CV tasks](#i-want-to-use-albumentations-for-the-specific-task-such-as-classification-or-segmentation) including classification, segmentation (semantic & instance), object detection, and pose estimation.
- **Simple, Unified API**: [One consistent interface](#a-simple-example) for all data types - RGB/grayscale/multispectral images, masks, bounding boxes, and keypoints.
- **Rich Augmentation Library**: [70+ high-quality augmentations](https://albumentations.ai/docs/api_reference/augmentations/transforms/) to enhance your training data.
- **Fast**: Consistently benchmarked as the [fastest augmentation library](https://albumentations.ai/docs/benchmarking_results/#performance-comparison) also shown [below section](#performance-comparison), with optimizations for production use.
- **Deep Learning Integration**: Works with [PyTorch](https://pytorch.org/), [TensorFlow](https://www.tensorflow.org/), and other frameworks. Part of the [PyTorch ecosystem](https://pytorch.org/ecosystem/).
- **Created by Experts**: Built by [developers with deep experience in computer vision and machine learning competitions](#authors).
### Your Options Moving Forward

#### 1. **Continue Using Albumentations (MIT License)**

- ✅ **Forever free** for all uses including commercial
- ✅ **No licensing fees or restrictions**
- ❌ **No bug fixes** - Even critical bugs won't be addressed
- ❌ **No new features** - Missing out on performance improvements
- ❌ **No support** - Issues and questions go unanswered
- ❌ **No compatibility updates** - May break with new Python/PyTorch versions

## Community-Driven Project, Supported By
**Best for:** Projects that work fine with the current version and don't need updates

Albumentations thrives on developer contributions. We appreciate our sponsors who help sustain the project's infrastructure.
#### 2. **Upgrade to AlbumentationsX (Dual Licensed)**

- ✅ **Drop-in replacement** - Same API, just `pip install albumentationsx`
- ✅ **Active development** - Regular updates and new features
- ✅ **Bug fixes** - Issues are actively addressed
- ✅ **Performance improvements** - Faster execution
- ✅ **Community support** - Active Discord and issue tracking
- ⚠️ **Dual licensed:**
- **AGPL-3.0**: Free ONLY for projects licensed under AGPL-3.0 (not compatible with MIT, Apache, BSD, etc.)
- **Commercial License**: Required for proprietary use AND permissive open-source projects

**Best for:** Projects that need ongoing support, updates, and new features

> ⚠️ **AGPL License Warning**: The AGPL-3.0 license is NOT compatible with permissive licenses like MIT, Apache 2.0, or BSD. If your project uses any of these licenses, you CANNOT use the AGPL version of AlbumentationsX - you'll need a commercial license.

### Migration is Simple

```bash
# Uninstall original
pip uninstall albumentations

# Install AlbumentationsX
pip install albumentationsx
```

That's it! Your existing code continues to work without any changes:

```python
import albumentations as A # Same import!

| 🟠 Exclusive Partner |
|-------------------|
| Your company could be here |
transform = A.Compose([
A.RandomCrop(width=256, height=256),
A.HorizontalFlip(p=0.5),
A.RandomBrightnessContrast(p=0.2),
])
```

| 🟡 Integration Partner |
|-------------------|
| Your company could be here |
### Learn More

| 🟢 Community Sponsor |
|-----------------|
| <a href="https://datature.io" target="_blank"><img src="https://albumentations.ai/assets/sponsors/datature-full.png" width="100" alt="Datature"/></a> |
- 📦 **AlbumentationsX Repository**: <https://github.com/albumentations-team/AlbumentationsX>
- 💰 **Commercial Licensing**: <https://albumentations.ai/pricing>
- 💬 **Discord Community**: <https://discord.gg/AKPrrDYNAt>

---

### 💝 Become a Sponsor
## Original Albumentations README

Your sponsorship is a way to say "thank you" to the maintainers and contributors who spend their free time building and maintaining Albumentations. Sponsors are featured on our website and README. View sponsorship tiers on [our support page](https://albumentations.ai/support/)
## GitAds Sponsored

[![Sponsored by GitAds](https://gitads.dev/v1/ad-serve?source=albumentations-team/albumentations@github)](https://gitads.dev/v1/ad-track?source=albumentations-team/albumentations@github)

Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to increase the quality of trained models. The purpose of image augmentation is to create new training samples from the existing data.

Here is an example of how you can apply some [pixel-level](#pixel-level-transforms) augmentations from Albumentations to create new images from the original one:
![parrot](https://habrastorage.org/webt/bd/ne/rv/bdnerv5ctkudmsaznhw4crsdfiw.jpeg)

## Why Albumentations

- **Complete Computer Vision Support**: Works with [all major CV tasks](#i-want-to-use-albumentations-for-the-specific-task-such-as-classification-or-segmentation) including classification, segmentation (semantic & instance), object detection, and pose estimation.
- **Simple, Unified API**: [One consistent interface](#a-simple-example) for all data types - RGB/grayscale/multispectral images, masks, bounding boxes, and keypoints.
- **Rich Augmentation Library**: [70+ high-quality augmentations](https://albumentations.ai/docs/reference/supported-targets-by-transform/) to enhance your training data.
- **Fast**: Consistently benchmarked as the [fastest augmentation library](https://albumentations.ai/docs/benchmarks/image-benchmarks/), with optimizations for production use.
- **Deep Learning Integration**: Works with [PyTorch](https://pytorch.org/), [TensorFlow](https://www.tensorflow.org/), and other frameworks. Part of the [PyTorch ecosystem](https://pytorch.org/ecosystem/).
- **Created by Experts**: Built by [developers with deep experience in computer vision and machine learning competitions](#authors).

## Table of contents

- [Albumentations](#albumentations)
- [Why Albumentations](#why-albumentations)
- [Community-Driven Project, Supported By](#community-driven-project-supported-by)
- [💝 Become a Sponsor](#-become-a-sponsor)
- [Table of contents](#table-of-contents)
- [Authors](#authors)
- [Current Maintainer](#current-maintainer)
Expand All @@ -68,7 +114,6 @@ Your sponsorship is a way to say "thank you" to the maintainers and contributors
- [Getting started](#getting-started)
- [I am new to image augmentation](#i-am-new-to-image-augmentation)
- [I want to use Albumentations for the specific task such as classification or segmentation](#i-want-to-use-albumentations-for-the-specific-task-such-as-classification-or-segmentation)
- [I want to know how to use Albumentations with deep learning frameworks](#i-want-to-know-how-to-use-albumentations-with-deep-learning-frameworks)
- [I want to explore augmentations and see Albumentations in action](#i-want-to-explore-augmentations-and-see-albumentations-in-action)
- [Who is using Albumentations](#who-is-using-albumentations)
- [See also](#see-also)
Expand Down Expand Up @@ -113,7 +158,7 @@ Albumentations requires Python 3.9 or higher. To install the latest version from
pip install -U albumentations
```

Other installation options are described in the [documentation](https://albumentations.ai/docs/getting_started/installation/).
Other installation options are described in the [documentation](https://albumentations.ai/docs/1-introduction/installation/).

## Documentation

Expand Down Expand Up @@ -149,15 +194,11 @@ Please start with the [introduction articles](https://albumentations.ai/docs/#le

### I want to use Albumentations for the specific task such as classification or segmentation

If you want to use Albumentations for a specific task such as classification, segmentation, or object detection, refer to the [set of articles](https://albumentations.ai/docs/#quick-start-guide) that has an in-depth description of this task. We also have a [list of examples](https://albumentations.ai/docs/examples/) on applying Albumentations for different use cases.

### I want to know how to use Albumentations with deep learning frameworks

We have [examples of using Albumentations](https://albumentations.ai/docs/#examples-of-how-to-use-albumentations-with-different-deep-learning-frameworks) along with PyTorch and TensorFlow.
If you want to use Albumentations for a specific task such as classification, segmentation, or object detection, refer to the [set of articles](https://albumentations.ai/docs/1-introduction/what-are-image-augmentations/) that has an in-depth description of this task. We also have a [list of examples](https://albumentations.ai/docs/examples/) on applying Albumentations for different use cases.

### I want to explore augmentations and see Albumentations in action

Check the [online demo of the library](https://albumentations-demo.herokuapp.com/). With it, you can apply augmentations to different images and see the result. Also, we have a [list of all available augmentations and their targets](#list-of-augmentations).
Check the [online demo of the library](https://explore.albumentations.ai/). With it, you can apply augmentations to different images and see the result. Also, we have a [list of all available augmentations and their targets](#list-of-augmentations).

## Who is using Albumentations

Expand Down