Update app.py

app.py

@@ -19,11 +19,18 @@ model_id = "CompVis/stable-diffusion-v1-4"
 # register_free_crossattn_upblock2d(pip_freeu, b1=1.2, b2=1.4, s1=0.9, s2=0.2)
 # # -------- freeu block registration
 
-def infer(prompt):
- 
+def infer(prompt, pip_sd, pip_freeu, seed, b1, b2, s1, s2):
+
+ # # -------- freeu block registration
+ # register_free_upblock2d(pip_freeu, b1=b1, b2=b2, s1=s1, s2=s1)
+ # register_free_crossattn_upblock2d(pip_freeu, b1=b1, b2=b2, s1=s1, s2=s1)
+ # # -------- freeu block registration
+
+ torch.manual_seed(seed)
  print("Generating SD:")
  sd_image = pip_sd(prompt).images[0] 
 
+ torch.manual_seed(seed)
  print("Generating FreeU:")
  freeu_image = pip_freeu(prompt).images[0] 
 
@@ -99,8 +106,21 @@ with block:
  with gr.Group():
  with gr.Row(): 
  sd_options = gr.Dropdown(['SD1.4', 'SD1.5', 'SD2.1'], value='SD1.4', label="SD options")
+
+ if sd_options == 'SD1.5':
+ model_id = "runwayml/stable-diffusion-v1-5"
+ elif sd_options == 'SD2.1':
+ model_id = "stabilityai/stable-diffusion-2-1"
+ else:
+ model_id = "CompVis/stable-diffusion-v1-4"
  
- with gr.Column():
+ pip_sd = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+ pip_sd = pip_sd.to("cuda")
+ 
+ pip_freeu = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+ pip_freeu = pip_freeu.to("cuda")
+ 
+ with gr.Row():
  text = gr.Textbox(
  label="Enter your prompt",
  show_label=False,
@@ -114,7 +134,7 @@ with block:
  step=1,
  value=42)
 
-
+ 
  with gr.Group():
  with gr.Row():
  with gr.Accordion('FreeU Parameters: b', open=True):
@@ -138,9 +158,7 @@ with block:
  minimum=0,
  maximum=1,
  step=0.1,
- value=1)
- 
- 
+ value=1) 
  
  with gr.Row():
  with gr.Group():
@@ -159,56 +177,11 @@ with block:
  image_2_label = gr.Markdown("FreeU")
  
  
- # with gr.Column():
- # sd_options = gr.Dropdown(options, value='SD1.4', label="SD options")
- # model_id = "CompVis/stable-diffusion-v1-4"
- # with gr.Accordion('FreeU Parameters', open=False):
- # b1 = gr.Slider(label='b1: backbone factor of the first stage block of decoder',
- # minimum=1,
- # maximum=1.6,
- # step=0.1,
- # value=1)
- # b2 = gr.Slider(label='b2: backbone factor of the second stage block of decoder',
- # minimum=1,
- # maximum=1.6,
- # step=0.1,
- # value=1)
- # s1 = gr.Slider(label='s1: skip factor of the first stage block of decoder',
- # minimum=0,
- # maximum=1,
- # step=0.1,
- # value=1)
- # s2 = gr.Slider(label='s2: skip factor of the second stage block of decoder',
- # minimum=0,
- # maximum=1,
- # step=0.1,
- # value=1)
- # with gr.Group():
- # with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True):
- # with gr.Column():
- # text = gr.Textbox(
- # label="Enter your prompt",
- # show_label=False,
- # max_lines=1,
- # placeholder="Enter your prompt",
- # container=False,
- # )
- # btn = gr.Button("Generate image", scale=0)
- 
- # with gr.Row():
- # with gr.Column(min_width=256) as c1:
- # image_1 = gr.Image(interactive=False)
- # image_1_label = gr.Markdown("SD")
- # with gr.Column(min_width=256) as c2:
- # image_2 = gr.Image(interactive=False)
- # image_2_label = gr.Markdown("FreeU")
- 
-
- ex = gr.Examples(examples=examples, fn=infer, inputs=[text], outputs=[image_1, image_2], cache_examples=False)
+ ex = gr.Examples(examples=examples, fn=infer, inputs=[text, pip_sd, pip_freeu, seed, b1, b2, s1, s2], outputs=[image_1, image_2], cache_examples=False)
  ex.dataset.headers = [""]
 
- text.submit(infer, inputs=[text], outputs=[image_1, image_2])
- btn.click(infer, inputs=[text], outputs=[image_1, image_2])
+ text.submit(infer, inputs=[text, pip_sd, pip_freeu, seed, b1, b2, s1, s2], outputs=[image_1, image_2])
+ btn.click(infer, inputs=[text, pip_sd, pip_freeu, seed, b1, b2, s1, s2], outputs=[image_1, image_2])
 
 block.launch()
 # block.queue(default_enabled=False).launch(share=False)