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Update app.py
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app.py
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@@ -28,6 +28,7 @@ from pipeline_stable_diffusion_xl_instantid_img2img import StableDiffusionXLInst
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from controlnet_aux import ZoeDetector
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from compel import Compel, ReturnedEmbeddingsType
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#from gradio_imageslider import ImageSlider
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with open("sdxl_loras.json", "r") as file:
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@@ -204,7 +205,7 @@ def merge_incompatible_lora(full_path_lora, lora_scale):
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del weights_sd
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del lora_model
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gc.collect()
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-
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def run_lora(face_image, prompt, negative, lora_scale, selected_state, face_strength, image_strength, guidance_scale, depth_control_scale, sdxl_loras, progress=gr.Progress(track_tqdm=True)):
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global last_lora, last_merged, last_fused, pipe
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@@ -262,7 +263,7 @@ def run_lora(face_image, prompt, negative, lora_scale, selected_state, face_stre
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pipe.unfuse_lora()
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pipe.unload_lora_weights()
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pipe.load_lora_weights(loaded_state_dict)
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pipe.fuse_lora()
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last_fused = True
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is_pivotal = sdxl_loras[selected_state.index]["is_pivotal"]
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if(is_pivotal):
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from controlnet_aux import ZoeDetector
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from compel import Compel, ReturnedEmbeddingsType
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import spaces
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#from gradio_imageslider import ImageSlider
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with open("sdxl_loras.json", "r") as file:
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del weights_sd
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del lora_model
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gc.collect()
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@spaces.GPU
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def run_lora(face_image, prompt, negative, lora_scale, selected_state, face_strength, image_strength, guidance_scale, depth_control_scale, sdxl_loras, progress=gr.Progress(track_tqdm=True)):
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global last_lora, last_merged, last_fused, pipe
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pipe.unfuse_lora()
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pipe.unload_lora_weights()
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pipe.load_lora_weights(loaded_state_dict)
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pipe.fuse_lora(lora_scale)
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last_fused = True
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is_pivotal = sdxl_loras[selected_state.index]["is_pivotal"]
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if(is_pivotal):
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