Spaces:
Running
Running
Commit
•
97ebe70
1
Parent(s):
43230a0
app.py: fixed controlnet options.
Browse files
app.py
CHANGED
@@ -136,7 +136,7 @@ CONTROLNET_DICT = dict(
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'preprocessor': 'canny',
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},
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lineart={
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-
'model_name': 'controlnet-softedge-
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'strength': 1,
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'preprocessor': 'lineart',
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},
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@@ -269,7 +269,7 @@ def generate_image (
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num_steps,
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identitynet_strength_ratio,
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adapter_strength_ratio,
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-
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controlnet_selection,
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guidance_scale,
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seed,
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@@ -313,7 +313,7 @@ def generate_image (
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CONTROLNET_DICT['canny']['strength'],
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CONTROLNET_DICT['depth']['strength'],
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CONTROLNET_DICT['lineart']['strength'],
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-
) =
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face_image_uploaded, ref_image_uploaded = upload_assets_with_cache(client, [face_image_path, ref_image_path])
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@@ -474,7 +474,7 @@ with gr.Blocks(css=css) as demo:
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)
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with gr.Accordion('Controlnet'):
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controlnet_selection = gr.CheckboxGroup(
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-
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info='Use pose for skeleton inference, canny for edge detection, and depth for depth map estimation. You can try all three to control the generation process'
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)
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pose_strength = gr.Slider(
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@@ -580,12 +580,12 @@ with gr.Blocks(css=css) as demo:
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num_steps,
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identitynet_strength_ratio,
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adapter_strength_ratio,
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-
[
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pose_strength,
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canny_strength,
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depth_strength,
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lineart_strength,
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-
],
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controlnet_selection,
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guidance_scale,
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seed,
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'preprocessor': 'canny',
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},
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lineart={
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+
'model_name': 'controlnet-softedge-sdxl-1.0',
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'strength': 1,
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'preprocessor': 'lineart',
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},
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num_steps,
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identitynet_strength_ratio,
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adapter_strength_ratio,
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+
controlnet_strength_1, controlnet_strength_2, controlnet_strength_3, controlnet_strength_4,
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controlnet_selection,
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guidance_scale,
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seed,
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CONTROLNET_DICT['canny']['strength'],
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CONTROLNET_DICT['depth']['strength'],
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CONTROLNET_DICT['lineart']['strength'],
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+
) = [controlnet_strength_1, controlnet_strength_2, controlnet_strength_3, controlnet_strength_4]
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face_image_uploaded, ref_image_uploaded = upload_assets_with_cache(client, [face_image_path, ref_image_path])
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)
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with gr.Accordion('Controlnet'):
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controlnet_selection = gr.CheckboxGroup(
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+
CONTROLNET_DICT.keys(), label='Controlnet', value=['pose'],
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info='Use pose for skeleton inference, canny for edge detection, and depth for depth map estimation. You can try all three to control the generation process'
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)
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pose_strength = gr.Slider(
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num_steps,
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identitynet_strength_ratio,
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adapter_strength_ratio,
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+
#[
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pose_strength,
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canny_strength,
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depth_strength,
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lineart_strength,
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+
#],
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controlnet_selection,
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guidance_scale,
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seed,
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