Update app.py

app.py

@@ -43,7 +43,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 upscaler.enable_xformers_memory_efficient_attention()
                 upscaler = upscaler.to(device)
                 torch.cuda.empty_cache()
-                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -69,7 +69,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 refiner.enable_xformers_memory_efficient_attention()
                 refiner = refiner.to(device)
                 torch.cuda.empty_cache()
-                upscaled = refiner(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = refiner(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -81,7 +81,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 upscaler.enable_xformers_memory_efficient_attention()
                 upscaler = upscaler.to(device)
                 torch.cuda.empty_cache()
-                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -108,7 +108,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 refiner.enable_xformers_memory_efficient_attention()
                 refiner = refiner.to(device)
                 torch.cuda.empty_cache()
-                upscaled = refiner(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = refiner(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -120,7 +120,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 upscaler.enable_xformers_memory_efficient_attention()
                 upscaler = upscaler.to(device)
                 torch.cuda.empty_cache()
-                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else: 
@@ -147,7 +147,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 refiner.enable_xformers_memory_efficient_attention()
                 refiner = refiner.to(device)
                 torch.cuda.empty_cache()
-                upscaled = refiner(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = refiner(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -160,7 +160,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 upscaler.enable_xformers_memory_efficient_attention()
                 upscaler = upscaler.to(device)
                 torch.cuda.empty_cache()
-                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -188,7 +188,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 refiner.enable_xformers_memory_efficient_attention()
                 refiner = refiner.to(device)
                 torch.cuda.empty_cache()
-                upscaled = refiner(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = refiner(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -201,7 +201,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 upscaler.enable_xformers_memory_efficient_attention()
                 upscaler = upscaler.to(device)
                 torch.cuda.empty_cache()
-                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -232,7 +232,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 animagine.enable_xformers_memory_efficient_attention()
                 animagine = animagine.to(device)
                 torch.cuda.empty_cache()
-                upscaled = animagine(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = animagine(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -245,7 +245,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 upscaler.enable_xformers_memory_efficient_attention()
                 upscaler = upscaler.to(device)
                 torch.cuda.empty_cache()
-                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -280,7 +280,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 sdxl.enable_xformers_memory_efficient_attention()
                 sdxl = sdxl.to(device)
                 torch.cuda.empty_cache()
-                upscaled = sdxl(prompt=Prompt, negative_prompt=negative_prompt, image=refined, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = sdxl(prompt=Prompt, negative_prompt=negative_prompt, image=refined, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -294,7 +294,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 upscaler.enable_xformers_memory_efficient_attention()
                 upscaler = upscaler.to(device)
                 torch.cuda.empty_cache()
-                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -326,7 +326,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 pipe.enable_xformers_memory_efficient_attention()
                 pipe = pipe.to(device)
                 torch.cuda.empty_cache()
-                upscaled = pipe(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = pipe(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -342,7 +342,7 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                 pipe.enable_xformers_memory_efficient_attention()
                 pipe = pipe.to(device)
                 torch.cuda.empty_cache()
-                upscaled = pipe(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                upscaled = pipe(prompt=Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
                 torch.cuda.empty_cache()
                 return upscaled
             else:
@@ -355,8 +355,8 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
 gr.Interface(fn=genie, inputs=[gr.Radio(['PhotoReal', 'Anime', 'Disney', 'StoryBook', 'SemiReal', 'Animagine XL 3.0', 'SDXL 1.0', 'FusionXL'], value='PhotoReal', label='Choose Model'),
                                gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'), 
                                gr.Textbox(label='What you Do Not want the AI to generate. 77 Token Limit'),
-                               gr.Slider(512, 1536, 768, step=128, label='Height'),
-                               gr.Slider(512, 1536, 768, step=128, label='Width'),
+                               gr.Slider(512, 1280, 768, step=128, label='Height'),
+                               gr.Slider(512, 1280, 768, step=128, label='Width'),
                                gr.Slider(1, maximum=15, value=5, step=.25, label='Guidance Scale'), 
                                gr.Slider(5, maximum=100, value=50, step=5, label='Number of Iterations'), 
                                gr.Slider(minimum=0, step=1, maximum=9999999999999999, randomize=True, label='Seed: 0 is Random'),