Update README.md

README.md

@@ -1,3 +1,64 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+task_categories:
+- text-to-image
+- image-to-image
+language:
+- en
+size_categories:
+- 100K<n<1M
+---
+
+# X2I Dataset
+
+* Project Page: [https://vectorspacelab.github.io/OmniGen/](https://vectorspacelab.github.io/OmniGen/)
+* Github: [https://github.com/VectorSpaceLab/OmniGen](https://github.com/VectorSpaceLab/OmniGen)
+* Paper: [https://arxiv.org/abs/2409.11340](https://arxiv.org/abs/2409.11340)
+* Model: [https://huggingface.co/Shitao/OmniGen-v1](https://huggingface.co/Shitao/OmniGen-v1)
+
+
+To achieve robust multi-task processing capabilities, it is essential to train the **OmniGen** on large-scale and diverse datasets. However, in the field of unified image generation, a readily available dataset has yet to emerge. For this reason, we have curated a large-scale **unified image generation** dataset with unified format for the **first time**, which we refer to as the **X2I dataset**, meaning **"anything to image"**. 
+
+
+| Task| Datastet|
+| :--------  | :--------  |
+| Multi-modal Instruction| [X2I-mm-instruction](https://huggingface.co/datasets/yzwang/X2I-mm-instruction) |
+| Subject-driven Editing | [X2I-subject-driven](https://huggingface.co/datasets/yzwang/X2I-subject-driven) |
+| In-context Learning | [X2I-in-context-learning](https://huggingface.co/datasets/yzwang/X2I-in-context-learning) |
+| Computer Vision | [X2I-computer-vision](https://huggingface.co/datasets/yzwang/X2I-computer-vision) |
+| Text to Image Generation| [X2I-text-to-image](https://huggingface.co/datasets/yzwang/X2I-text-to-image) |
+
+
+## X2I-in-context-learning
+
+
+- **Derain & Enhance & GoPro**
+
+A set of image derain, enhance and deblur datasets with 859 & 485 & 2,103 samples. 
+
+```python
+## meta file: derain.jsonl
+cd derain
+tar -xzvf derain.tar.gz
+## meta file: enhance.jsonl
+cd enhance
+tar -xzvf enhance.tar.gz
+## meta file: gopro.jsonl
+cd gopro
+tar -xzvf gopro.tar.gz
+```
+
+
+- **ADE**
+
+A image segementation dataset with 297,472 samples.
+
+download images from [here](https://huggingface.co/datasets/yzwang/X2I-computer-vision/tree/main/ade)
+
+```python
+## meta file: ade.jsonl
+cd ade
+tar -xzvf ade.tar.gz
+```
+
+- [MultiGen](https://github.com/salesforce/UniControl)