Update app.py

app.py

@@ -153,18 +153,37 @@ def run_image(runner,
     return image
 
 
+MARKDOWN = """
+# YOLO-World-Image 👀: YOLO-World with Image Prompts
+
+Now everyone can use YOLO-World and some image prompts to detect corresponding objects in images, no longer relying on text prompts!
+
+This demo is actively under construction and the YOLO-World-Image is an initial (**beta**) version!
+
+<div style='display:flex; gap: 0.25rem; align-items: center'>
+<a href="https://yoloworld.cc"><img src="https://img.shields.io/badge/Project-Page-green"></a>
+<a href="https://arxiv.org/abs/2401.17270"><img src="https://img.shields.io/badge/arXiv-Paper-red"></a>
+<a href="https://github.com/AILab-CVC/YOLO-World"><img src="https://img.shields.io/badge/GitHub-Code-blue"></a>
+<a href="https://huggingface.co/spaces/stevengrove/YOLO-World"><img src="https://img.shields.io/badge/🤗HugginngFace-Spaces-orange"></a>
+</div>
+
+### Simple guide:
+
+* upload the image prompts  
+* adjust the hyperparameters:  
+    - score threshold   
+    - nms threshold   
+    - max number of detections   
+    - whether using padding: adding padding might improve the confidence scores of the predictions. It will be removed in the coming updates.    
+* run with 'submit'!
+"""
 
 
 
 def demo(runner, vision_encoder, vision_processor, padding_embed):
     with gr.Blocks(title="YOLO-World") as demo:
         with gr.Row():
-            gr.Markdown('<h1><center>YOLO-World-Image: YOLO-World with Image Prompts</center></h1>')
-            gr.Markdown('<center> This demo is actively under construction and the YOLO-World-Image is an initial version!')
-            gr.Markdown("""<center>
-            [![project page](https://img.shields.io/badge/Project-Page-green)](https://yoloworld.cc)
-            [![arxiv paper](https://img.shields.io/badge/arXiv-Paper-red)](https://arxiv.org/abs/2401.17270)
-            [![demo](https://img.shields.io/badge/🤗HugginngFace-Spaces-orange)](https://huggingface.co/spaces/stevengrove/YOLO-World)</center>""")
+            gr.Markdown(MARKDOWN)
         with gr.Row():
             image = gr.Image(type='pil', label='input image')
             output_image = gr.Image(type='pil', label='output image')