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Running
on
T4
Update app.py
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app.py
CHANGED
@@ -10,15 +10,22 @@ device = 'cuda' if torch.cuda.is_available() else 'cpu'
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pipe = DiffusionPipeline.from_pretrained("circulus/canvers-real-v3.8.1", torch_dtype=torch.float16, safety_checker=None) if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("circulus/canvers-real-v3.8.1")
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pipe = pipe.to(device)
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pipe.enable_xformers_memory_efficient_attention()
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anime = DiffusionPipeline.from_pretrained("circulus/canvers-anime-v3.8.1", torch_dtype=torch.float16, safety_checker=None) if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("circulus/canvers-anime-v3.8.1")
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anime = anime.to(device)
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anime.enable_xformers_memory_efficient_attention()
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disney = DiffusionPipeline.from_pretrained("circulus/canvers-disney-v3.8.1", torch_dtype=torch.float16, safety_checker=None) if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("circulus/canvers-disney-v3.8.1")
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disney = disney.to(device)
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disney.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") if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0")
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refiner.enable_xformers_memory_efficient_attention()
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refiner = refiner.to(device)
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def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, upscale, high_noise_frac):
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generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed)
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@@ -26,27 +33,32 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, up
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if upscale == "Yes":
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int_image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images
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image = refiner(Prompt, negative_prompt=negative_prompt, image=int_image, denoising_start=high_noise_frac).images[0]
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return image
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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
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if Model == "Anime":
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if upscale == "Yes":
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int_image = anime(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images
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image = refiner(Prompt, negative_prompt=negative_prompt, image=int_image, denoising_start=high_noise_frac).images[0]
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return image
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else:
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image = anime(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
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return image
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else:
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if upscale == "Yes":
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int_image = disney(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images
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image = refiner(Prompt, negative_prompt=negative_prompt, image=int_image, denoising_start=high_noise_frac).images[0]
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return image
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else:
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image = disney(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
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return image
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gr.Interface(fn=genie, inputs=[gr.Radio(['Real', 'Anime', 'Disney'], value='Real', label='Choose Canvers Model'),
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pipe = DiffusionPipeline.from_pretrained("circulus/canvers-real-v3.8.1", torch_dtype=torch.float16, safety_checker=None) if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("circulus/canvers-real-v3.8.1")
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pipe = pipe.to(device)
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pipe.enable_xformers_memory_efficient_attention()
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torch.cuda.empty_cache()
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anime = DiffusionPipeline.from_pretrained("circulus/canvers-anime-v3.8.1", torch_dtype=torch.float16, safety_checker=None) if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("circulus/canvers-anime-v3.8.1")
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anime = anime.to(device)
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anime.enable_xformers_memory_efficient_attention()
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torch.cuda.empty_cache()
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disney = DiffusionPipeline.from_pretrained("circulus/canvers-disney-v3.8.1", torch_dtype=torch.float16, safety_checker=None) if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("circulus/canvers-disney-v3.8.1")
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disney = disney.to(device)
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disney.enable_xformers_memory_efficient_attention()
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torch.cuda.empty_cache()
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refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True, torch_dtype=torch.float16, variant="fp16") if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0")
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refiner.enable_xformers_memory_efficient_attention()
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refiner = refiner.to(device)
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torch.cuda.empty_cache()
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def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, upscale, high_noise_frac):
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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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int_image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images
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image = refiner(Prompt, negative_prompt=negative_prompt, image=int_image, denoising_start=high_noise_frac).images[0]
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torch.cuda.empty_cache()
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return image
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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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torch.cuda.empty_cache()
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return image
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if Model == "Anime":
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if upscale == "Yes":
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int_image = anime(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images
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image = refiner(Prompt, negative_prompt=negative_prompt, image=int_image, denoising_start=high_noise_frac).images[0]
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torch.cuda.empty_cache()
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return image
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else:
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image = anime(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
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torch.cuda.empty_cache()
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return image
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else:
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if upscale == "Yes":
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int_image = disney(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images
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image = refiner(Prompt, negative_prompt=negative_prompt, image=int_image, denoising_start=high_noise_frac).images[0]
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torch.cuda.empty_cache()
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return image
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else:
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image = disney(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
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torch.cuda.empty_cache()
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return image
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gr.Interface(fn=genie, inputs=[gr.Radio(['Real', 'Anime', 'Disney'], value='Real', label='Choose Canvers Model'),
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