create app.py

app.py

@@ -0,0 +1,41 @@
+import pandas as pd
+import gradio as gr
+ 
+df = pd.read_csv("liked_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))
+df['height'] = df['height'].apply(lambda x: str(x))
+df['steps'] = df['steps'].apply(lambda x: str(x))
+df['source'] = df['source'].apply(lambda x: str(x))
+df = df[[ 'url', 'prompt', 'seed', 'width', 'height', 'steps', 'source']]
+
+def display_df():
+  df_images = df.head()
+  return df_images
+
+def display_next10(dataframe, end):
+  start = (end  or dataframe.index[-1]) + 1
+  end = start + 9
+  df_images = df.loc[start:end]
+  return df_images, 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:<br>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>""")
+
+  with gr.Row():
+    num_end = gr.Number(visible=False)
+    b1 = gr.Button("Get Initial dataframe")
+    b2 = gr.Button("Next 10 Rows")
+    
+  with gr.Row():
+    out_dataframe = gr.Dataframe(wrap=True, max_rows=10, overflow_row_behaviour= "paginate", datatype = ["markdown", "markdown", "str", "str", "str", "str", "str", "str"])
+    
+  b1.click(fn=display_df, outputs=out_dataframe) 
+  b2.click(fn=display_next10, inputs= [out_dataframe, num_end ], outputs=[out_dataframe, num_end])
+  
+demo.launch(debug=True, show_error=True)