Manjushri commited on
Commit
3459d34
1 Parent(s): b6b49fc

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +8 -9
app.py CHANGED
@@ -10,19 +10,18 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
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  pipe = DiffusionPipeline.from_pretrained("circulus/canvers-realistic-v3.6", torch_dtype=torch.float16, safety_checker=None)
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  pipe = pipe.to(device)
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  pipe.enable_xformers_memory_efficient_attention()
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- upscaler = StableDiffusionLatentUpscalePipeline.from_pretrained("stabilityai/sd-x2-latent-upscaler", torch_dtype=torch.float16, safety_checker=None)
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- upscaler = upscaler.to(device)
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- upscaler.enable_xformers_memory_efficient_attention()
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-
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  def genie (Prompt, negative_prompt, height, width, scale, steps, seed, upscale):
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-
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  generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed)
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-
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  if upscale == "Yes":
 
 
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  image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
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- upscaled = upscaler(Prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
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- return (image, upscaled)
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  else:
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  image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
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  return (image, image)
@@ -34,7 +33,7 @@ gr.Interface(fn=genie, inputs=[gr.Textbox(label='What you want the AI to generat
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  gr.Slider(1, maximum=15, value=7, step=.25, label='Guidance Scale'),
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  gr.Slider(25, maximum=100, value=50, step=25, label='Number of Iterations'),
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  gr.Slider(minimum=0, step=1, maximum=9999999999999999, randomize=True, label='Seed: 0 is Random'),
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- gr.Radio(["Yes", "No"], label='Upscale?', value='No'),
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  ],
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  outputs=[gr.Image(label='Generated Image'), gr.Image(label='Generated Image')],
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  title="PhotoReal V3.6 with SD x2 Upscaler - GPU",
 
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  pipe = DiffusionPipeline.from_pretrained("circulus/canvers-realistic-v3.6", torch_dtype=torch.float16, safety_checker=None)
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  pipe = pipe.to(device)
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  pipe.enable_xformers_memory_efficient_attention()
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+ refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True, torch_dtype=torch.float16, variant="fp16")
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+ refiner.enable_xformers_memory_efficient_attention()
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+ refiner = refiner.to(device)
 
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  def genie (Prompt, negative_prompt, height, width, scale, steps, seed, upscale):
 
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  generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed)
 
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  if upscale == "Yes":
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+ n_steps = 40
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+ high_noise_frac = 0.8
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  image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
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+ image = refiner(prompt=prompt, negative_prompt=negative_prompt, image=int_image, num_inference_steps=n_steps, denoising_start=high_noise_frac).images[0]
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+ return (image, refined)
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  else:
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  image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
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  return (image, image)
 
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  gr.Slider(1, maximum=15, value=7, step=.25, label='Guidance Scale'),
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  gr.Slider(25, maximum=100, value=50, step=25, label='Number of Iterations'),
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  gr.Slider(minimum=0, step=1, maximum=9999999999999999, randomize=True, label='Seed: 0 is Random'),
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+ gr.Radio(["Yes", "No"], label='SDXL 1.0 Refiner', value='No'),
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  ],
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  outputs=[gr.Image(label='Generated Image'), gr.Image(label='Generated Image')],
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  title="PhotoReal V3.6 with SD x2 Upscaler - GPU",