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Update app.py
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app.py
CHANGED
@@ -21,12 +21,12 @@ else:
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if torch.cuda.is_available():
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torch.cuda.max_memory_allocated(device=device)
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pipe = StableDiffusionImg2ImgPipeline.from_pretrained("Envvi/Inkpunk-Diffusion", torch_dtype=torch_dtype)
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#pipe = DiffusionPipeline.from_pretrained("Envvi/Inkpunk-Diffusion", torch_dtype=torch.float16, variant="fp16")
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pipe.enable_xformers_memory_efficient_attention()
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pipe = pipe.to(device)
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else:
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pipe = StableDiffusionImg2ImgPipeline.from_pretrained("Envvi/Inkpunk-Diffusion", torch_dtype=torch_dtype)
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pipe = pipe.to(device)
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MAX_SEED = np.iinfo(np.int32).max
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@@ -79,7 +79,7 @@ with gr.Blocks(css=css) as demo:
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with gr.Column(elem_id="col-container"):
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gr.Markdown(f"""
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#
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Currently running on {power_device}.
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""")
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@@ -110,15 +110,16 @@ with gr.Blocks(css=css) as demo:
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visible=False,
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)
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with gr.Row():
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@@ -145,7 +146,7 @@ with gr.Blocks(css=css) as demo:
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minimum=0.0,
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maximum=10.0,
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step=0.1,
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value=0
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)
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strength = gr.Slider(
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@@ -153,7 +154,7 @@ with gr.Blocks(css=css) as demo:
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minimum=0.0,
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maximum=1.0,
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step=0.1,
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value=0.
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)
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gr.Examples(
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if torch.cuda.is_available():
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torch.cuda.max_memory_allocated(device=device)
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pipe = StableDiffusionImg2ImgPipeline.from_pretrained("Envvi/Inkpunk-Diffusion", torch_dtype=torch_dtype, safety_checker = None, requires_safety_checker = False)
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#pipe = DiffusionPipeline.from_pretrained("Envvi/Inkpunk-Diffusion", torch_dtype=torch.float16, variant="fp16")
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pipe.enable_xformers_memory_efficient_attention()
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pipe = pipe.to(device)
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else:
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pipe = StableDiffusionImg2ImgPipeline.from_pretrained("Envvi/Inkpunk-Diffusion", torch_dtype=torch_dtype, safety_checker = None, requires_safety_checker = False)
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pipe = pipe.to(device)
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MAX_SEED = np.iinfo(np.int32).max
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with gr.Column(elem_id="col-container"):
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gr.Markdown(f"""
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# Image-to-Image Demo
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Currently running on {power_device}.
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""")
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visible=False,
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)
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with gr.Row():
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seed = gr.Slider(
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label="Seed",
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minimum=0,
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maximum=MAX_SEED,
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step=1,
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value=0,
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)
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randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
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with gr.Row():
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minimum=0.0,
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maximum=10.0,
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step=0.1,
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value=5.0,
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)
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strength = gr.Slider(
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minimum=0.0,
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maximum=1.0,
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step=0.1,
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value=0.5,
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)
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gr.Examples(
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