Spaces:
Running
on
Zero
Running
on
Zero
Update raw.py
Browse files
raw.py
CHANGED
@@ -23,7 +23,7 @@ pipe = FluxControlNetPipeline.from_pretrained(
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pipe.to("cuda")
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@spaces.GPU
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-
def generate_image(prompt, scale, steps, control_image):
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# Load control image
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control_image = load_image(control_image)
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w, h = control_image.size
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@@ -33,9 +33,9 @@ def generate_image(prompt, scale, steps, control_image):
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image = pipe(
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prompt=prompt,
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control_image=control_image,
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-
controlnet_conditioning_scale=
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num_inference_steps=steps,
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-
guidance_scale=
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height=control_image.size[1],
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width=control_image.size[0]
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).images[0]
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@@ -49,6 +49,8 @@ iface = gr.Interface(
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gr.Slider(1, 3, value=1, label="Scale"),
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gr.Slider(6, 30, value=8, label="Steps"),
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gr.Image(type="pil", label="Control Image"),
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],
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outputs=[
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gr.Image(type="pil", label="Generated Image", format="png"),
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pipe.to("cuda")
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@spaces.GPU
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+
def generate_image(prompt, scale, steps, control_image, controlnet_conditioning_scale, guidance_scale):
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# Load control image
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control_image = load_image(control_image)
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w, h = control_image.size
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image = pipe(
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prompt=prompt,
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control_image=control_image,
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controlnet_conditioning_scale=controlnet_conditioning_scale,
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num_inference_steps=steps,
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guidance_scale=guidance_scale,
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height=control_image.size[1],
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width=control_image.size[0]
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).images[0]
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gr.Slider(1, 3, value=1, label="Scale"),
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gr.Slider(6, 30, value=8, label="Steps"),
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gr.Image(type="pil", label="Control Image"),
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gr.Slider(0, 1, value=0.6, label="ControlNet Scale"),
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gr.Slider(1, 20, value=3.5, label="Guidance Scale"),
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],
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outputs=[
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gr.Image(type="pil", label="Generated Image", format="png"),
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