Update app.py

app.py

@@ -14,13 +14,12 @@ refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-ref
 refiner.enable_xformers_memory_efficient_attention()
 refiner = refiner.to(device)
 
-def genie (Prompt, negative_prompt, height, width, scale, steps, seed, upscale):
+def genie (Prompt, negative_prompt, height, width, scale, steps, seed, upscale, high_noise_frac):
     generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed)
     if upscale == "Yes":
         #n_steps = 30
-        #high_noise_frac = 0.95
         int_image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
-        image = refiner(Prompt, negative_prompt=negative_prompt, image=int_image).images[0]
+        image = refiner(Prompt, negative_prompt=negative_prompt, image=int_image, denoising_start=high_noise_frac).images[0]
         return (int_image, image)
     else:
         image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
@@ -34,7 +33,7 @@ gr.Interface(fn=genie, inputs=[gr.Textbox(label='What you want the AI to generat
                                gr.Slider(25, maximum=100, value=50, step=25, label='Number of Iterations'), 
                                gr.Slider(minimum=0, step=1, maximum=9999999999999999, randomize=True, label='Seed: 0 is Random'), 
                                gr.Radio(["Yes", "No"], label='SDXL 1.0 Refiner', value='No'),
-                              ],
+                               gr.Slider(minimum=.7, maximum=.99, value=.8, step=.01, label='Refiner Denoise %')],
              outputs=[gr.Image(label='Generated Image'), gr.Image(label='Generated Image')], 
              title="PhotoReal V3.6 with SD x2 Upscaler - GPU", 
              description="<br><br><b/>Warning: This Demo is capable of producing NSFW content.",