lllyasviel/stable-diffusion-webui-forge
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lllyasviel
2024-01-28 00:07:10 -08:00
parent dcba2f77e9
commit fe8dbe2562
3 changed files with 10 additions and 5 deletions
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9
README.md
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@@ -392,6 +392,11 @@ class ControlNetExampleForge(scripts.Script):
model_dir = os.path.join(models_path, 'ControlNet')
os.makedirs(model_dir, exist_ok=True)
# controlnet_canny_path = load_file_from_url(
# url='https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/sai_xl_canny_256lora.safetensors',
# model_dir=model_dir,
# file_name='sai_xl_canny_256lora.safetensors'
# )
controlnet_canny_path = load_file_from_url(
url='https://huggingface.co/lllyasviel/fav_models/resolve/main/fav/control_v11p_sd15_canny_fp16.safetensors',
model_dir=model_dir,
@@ -399,7 +404,6 @@ class ControlNetExampleForge(scripts.Script):
)
print('The model [control_v11p_sd15_canny_fp16.safetensors] download finished.')
# Works for all controlnets, t2i adapters, control-loras, etc.
self.model = load_controlnet(controlnet_canny_path)
print('Controlnet loaded.')
@@ -432,7 +436,8 @@ class ControlNetExampleForge(scripts.Script):
unet = apply_controlnet_advanced(unet=unet, controlnet=self.model, image_bhwc=control_image,
strength=0.6, start_percent=0.0, end_percent=0.8,
positive_advanced_weighting=None, negative_advanced_weighting=None)
positive_advanced_weighting=None, negative_advanced_weighting=None,
frame_advanced_weighting=None)
p.sd_model.forge_objects.unet = unet

2
extensions-builtin/sd_forge_controlnet_example/scripts/sd_forge_controlnet_example.py
View File

@@ -89,7 +89,7 @@ class ControlNetExampleForge(scripts.Script):
unet = apply_controlnet_advanced(unet=unet, controlnet=self.model, image_bhwc=control_image,
strength=0.6, start_percent=0.0, end_percent=0.8,
positive_advanced_weighting=None, negative_advanced_weighting=None,
only_apply_to_one_frame_in_a_batch=None)
frame_advanced_weighting=None)
p.sd_model.forge_objects.unet = unet

4
modules_forge/controlnet.py
View File

@@ -7,13 +7,13 @@ def apply_controlnet_advanced(
end_percent,
positive_advanced_weighting=None,
negative_advanced_weighting=None,
only_apply_to_one_frame_in_a_batch=None,
frame_advanced_weighting=None,
):
cnet = controlnet.copy().set_cond_hint(image_bhwc.movedim(-1, 1), strength, (start_percent, end_percent))
cnet.positive_advanced_weighting = positive_advanced_weighting
cnet.negative_advanced_weighting = negative_advanced_weighting
cnet.only_apply_to_one_frame_in_a_batch = only_apply_to_one_frame_in_a_batch
cnet.frame_advanced_weighting = frame_advanced_weighting
m = unet.clone()
m.add_patched_controlnet(cnet)