Update app.py

app.py

@@ -1,7 +1,7 @@
 import pandas as pd
 import gradio as gr
  
-df = pd.read_csv("liked_images.csv")
+df = pd.read_csv("images.csv")
 df['url'] = df['url'].apply(lambda x: '<a href= "' + str(x) + '" target="_blank"> <img src= "' + str(x) + '"/> </a>') #'<img src= "' + str(x) + '"/> </a>')
 df['seed'] = df['seed'].apply(lambda x: str(x))
 df['width'] = df['width'].apply(lambda x: str(x))
@@ -23,7 +23,6 @@ def display_next10(dataframe, end):
 #Gradio Blocks
 with gr.Blocks() as demo:
   gr.Markdown("<h1><center>Utility Gradio Space for viewing PlaygroundAI Images</center></h1>")
-  gr.Markdown("""<img src='https://xxxxxxxx.jpg' class='center'> <br>  """) 
   gr.Markdown(
         """<div align="center">This Tool helps you to analyze and inspect the images and corresponding prompts from <a href = "https://playgroundai.com/">Playground AI</a> Images.<br><a href="https://twitter.com/Suhail">Suhail</a> has recently shared an open dataset of all the liked images and their prompts from PlaygroundAI on <a href="https://github.com/playgroundai/liked_images">Github here</a>. This is an attempt to explore this dataset beautifully using the power and flexibility of Gradio!<br><b>To use the tool:</b>First, click on the 'Initial' button, and then iteratively on the 'Next 10' button.<br><b>Bonus:</b>Click on images to get the original PlaygroundAI image displayed on next tab</div>""")