update

app.py

@@ -6,9 +6,10 @@ from io import BytesIO
 from diffusers import StableDiffusionUpscalePipeline
 import torch
 import os
+import requests
 
 HF_TOKEN = os.environ.get('HF_TOKEN')
-client_if = Client("huggingface-projects/IF", hf_token=HF_TOKEN)
+client_if = Client("ysharma/IF", hf_token=HF_TOKEN)
 client_pick = Client("yuvalkirstain/PickScore") 
 
 # load upscaling model and scheduler
@@ -22,7 +23,8 @@ def get_IF_op(prompt, neg_prompt):
   folder_path = filepaths[0]
   file_list = os.listdir(folder_path)
   file_list = [os.path.join(folder_path, f) for f in file_list if f != 'captions.json']
-  return file_list    
+  print(f"^^file list is: {file_list}")
+  return file_list   
 
 def get_pickscores(prompt, file_list):
   print("inside get_pickscores")
@@ -37,6 +39,7 @@ def get_pickscores(prompt, file_list):
 
 def get_upscale_op(prompt, gallery_if):
   print("inside get_upscale_op")
+  print(f"^^gallery_if is: {gallery_if}")
   # get pickscores
   best_match_image = get_pickscores(prompt, gallery_if)
   # let's get the best pick! 
@@ -47,18 +50,18 @@ def get_upscale_op(prompt, gallery_if):
   #upscaled_image.save("upsampled.png")
   return upscaled_image
 
-
 with gr.Blocks() as demo:
   with gr.Row():
     with gr.Column():
       prompt = gr.Textbox(label='Prompt')
       neg_prompt = gr.Textbox(label='Negative Prompt')
     b1 = gr.Button('Generate')
-  gallery_if = gr.Gallery(label='IF Space outputs')
+  with gr.Row():
+      gallery_if = gr.Gallery(label='IF Space outputs')
   b2 = gr.Button("Get the best generation using Pick-A-Pic")
   image_picakapic = gr.Image(label="PickAPic Evaluated Output") 
 
   b1.click(get_IF_op,[prompt, neg_prompt], gallery_if)
-  b1.click(get_upscale_op,[prompt, gallery_if], image_picakapic)
+  b2.click(get_upscale_op,[prompt, gallery_if], image_picakapic)
 
 demo.launch(debug=True)