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README.md
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<div align="center">
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[\[🏠Homepage\]](https://
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</div>
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## Overview
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For generating single-step actions in GUI agent tasks, you can use:
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- [OS-Atlas-Pro-7B](https://huggingface.co/OS-Copilot/OS-Atlas-Pro-7B)
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- [OS-Atlas-Pro-4B](https://huggingface.co/OS-Copilot/OS-Atlas-Pro-4B)
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**Notes:** Our models accept images of any size as input. The model outputs are normalized to relative coordinates within a 0-1000 range (either a center point or a bounding box defined by top-left and bottom-right coordinates). For visualization, please remember to convert these relative coordinates back to the original image dimensions.
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### Inference Example
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First, ensure that the necessary dependencies are installed:
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pip install transformers
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pip install qwen-vl-utils
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```
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Inference code example:
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```python
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"type": "image",
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"image": "./web_6f93090a-81f6-489e-bb35-1a2838b18c01.png",
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},
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{"type": "text", "text": "
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],
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}
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]
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<div align="center">
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[\[🏠Homepage\]](https://qiushisun.github.io/OS-Genesis-Home/) [\[💻Code\]](https://github.com/OS-Copilot/OS-Genesis) [\[📝Paper\]](https://arxiv.org/abs/2412.19723) [\[🤗Models\]](https://huggingface.co/collections/OS-Copilot/os-genesis-6768d4b6fffc431dbf624c2d)[\[🤗Data\]](https://huggingface.co/collections/OS-Copilot/os-genesis-6768d4b6fffc431dbf624c2d)
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</div>
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## Overview
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We introduce OS-Genesis, an interaction-driven pipeline that synthesizes high-quality and diverse GUI agent trajectory data without human supervision. By leveraging reverse task synthesis, OS-Genesis enables effective training of GUI agents to achieve superior performance on dynamic benchmarks such as AndroidWorld and WebArena.
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## Quick Start
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OS-Genesis-7B-AC is a mobile action model finetuned from [Qwen2-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct).
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### OS-Genesis AC Family Models
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In the following table, we provide an overview of the OS-Genesis AC Family Models used for evaluating the AndroidControl Benchmark.
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| Model Name | Base Model | Training Data | HF Link |
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| :-------------: | :-------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------: | :---------------------------------------------------------: |
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| OS-Genesis-4B-AC | [InternVL2-4B](https://huggingface.co/OpenGVLab/InternVL2-4B) | [OS-Genesis-mobile-data](https://huggingface.co/datasets/OS-Copilot/OS-Genesis-mobile-data) | [🤗 link](https://huggingface.co/OS-Copilot/OS-Genesis-4B-AC) |
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| OS-Genesis-7B-AC | [Qwen2-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct) | [OS-Genesis-mobile-data](https://huggingface.co/datasets/OS-Copilot/OS-Genesis-mobile-data) | [🤗 link](https://huggingface.co/OS-Copilot/OS-Genesis-7B-AC) |
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| OS-Genesis-8B-AC | [InternVL2-8B](https://huggingface.co/OpenGVLab/InternVL2-8B) | [OS-Genesis-mobile-data](https://huggingface.co/datasets/OS-Copilot/OS-Genesis-mobile-data) | [🤗 link](https://huggingface.co/OS-Copilot/OS-Genesis-8B-AC) |
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### Inference Example
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First, ensure that the necessary dependencies are installed:
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pip install transformers
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pip install qwen-vl-utils
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```
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For evaluating the AndroidControl Benchmark, please refer to the [**evaluation code**](https://github.com/OS-Copilot/OS-Genesis/tree/main/evaluation/android_control).
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Inference code example:
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```python
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"type": "image",
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"image": "./web_6f93090a-81f6-489e-bb35-1a2838b18c01.png",
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},
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{"type": "text", "text": "You are a GUI task expert, I will provide you with a high-level instruction, an action history, a screenshot with its corresponding accessibility tree.\n High-level instruction: {high_level_instruction}\n Action history: {action_history}\n Accessibility tree: {a11y_tree}\n Please generate the low-level thought and action for the next step."},
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],
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}
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]
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