Update README.md

README.md

@@ -69,11 +69,8 @@ You can see details in our [paper](https://arxiv.org/abs/2409.11340).
 OmniGen is a unified image generation model that you can use to perform various tasks, including but not limited to text-to-image generation, subject-driven generation, Identity-Preserving Generation, image editing, and image-conditioned generation. **OmniGen doesn't need additional plugins or operations, it can automatically identify the features (e.g., required object, human pose, depth mapping) in input images according to the text prompt.**
 We showcase some examples in [inference.ipynb](inference.ipynb). And in [inference_demo.ipynb](inference_demo.ipynb), we show an interesting pipeline to generate and modify an image.
 
-Here are the illustrations of OmniGen's capabilities: 
-- You can control the image generation flexibly via OmniGen
-![demo](./imgs/demo_cases.png)
-- Referring Expression Generation: You can input multiple images and use simple, general language to refer to the objects within those images. OmniGen can automatically recognize the necessary objects in each image and generate new images based on them. No additional operations, such as image cropping or face detection, are required.
-![demo](./imgs/referring.png)
+You can control the image generation flexibly via OmniGen
+![demo](demo_cases.png)
 
 If you are not entirely satisfied with certain functionalities or wish to add new capabilities, you can try [fine-tuning OmniGen](#6-finetune).