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ccce713
1
Parent(s):
bb07a1e
chore: Integrate live preview functionality in image enhancement pipeline
Browse files
app.py
CHANGED
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@@ -3,7 +3,7 @@ from diffusers import FluxPriorReduxPipeline, FluxPipeline
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from diffusers.utils import load_image
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import gradio as gr
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import spaces
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pipe_prior_redux = FluxPriorReduxPipeline.from_pretrained("black-forest-labs/FLUX.1-Redux-dev", revision="refs/pr/8", torch_dtype=torch.bfloat16).to("cuda")
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pipe = FluxPipeline.from_pretrained(
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@@ -11,26 +11,36 @@ pipe = FluxPipeline.from_pretrained(
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text_encoder=None,
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text_encoder_2=None,
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torch_dtype=torch.bfloat16
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# pipe.enable_sequential_cpu_offload()
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@spaces.GPU
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def enhance_image(image_path, keep_aspect_ratio=False):
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print(image_path)
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image = load_image(image_path)
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print(image.size)
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width, height = image.size if keep_aspect_ratio else (None, None)
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pipe_prior_output = pipe_prior_redux(image)
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height=height,
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width=width,
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guidance_scale=2.5,
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num_inference_steps=50,
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generator=torch.Generator("cpu").manual_seed(0),
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with gr.Blocks(title="Flux.1 Dev Redux") as demo:
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from diffusers.utils import load_image
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import gradio as gr
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import spaces
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from live_preview_helpers import flux_pipe_call_that_returns_an_iterable_of_images
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pipe_prior_redux = FluxPriorReduxPipeline.from_pretrained("black-forest-labs/FLUX.1-Redux-dev", revision="refs/pr/8", torch_dtype=torch.bfloat16).to("cuda")
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pipe = FluxPipeline.from_pretrained(
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text_encoder=None,
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text_encoder_2=None,
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torch_dtype=torch.bfloat16
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).to("cuda")
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pipe.flux_pipe_call_that_returns_an_iterable_of_images = flux_pipe_call_that_returns_an_iterable_of_images.__get__(pipe)
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# pipe.enable_sequential_cpu_offload()
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@spaces.GPU
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def enhance_image(image_path, keep_aspect_ratio=False):
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print(image_path)
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image = load_image(image_path)
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print(image.size)
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width, height = image.size if keep_aspect_ratio else (None, None)
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pipe_prior_output = pipe_prior_redux(image)
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for img in pipe.flux_pipe_call_that_returns_an_iterable_of_images(
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guidance_scale=2.5,
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num_inference_steps=50,
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width=width,
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height=height,
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generator=torch.Generator("cpu").manual_seed(0),
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output_type="pil",
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**pipe_prior_output
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):
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yield img
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# images = pipe(
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# height=height,
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# width=width,
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# guidance_scale=2.5,
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# num_inference_steps=50,
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# generator=torch.Generator("cpu").manual_seed(0),
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# **pipe_prior_output,
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# ).images
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# return images[0]
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with gr.Blocks(title="Flux.1 Dev Redux") as demo:
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