fix: correctly initialize inpaint_mask var, rename task styles index
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dd866616bc
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@ -693,10 +693,10 @@ def worker():
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task_styles = async_task.style_selections.copy()
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if use_style:
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for i, s in enumerate(task_styles):
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for j, s in enumerate(task_styles):
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if s == random_style_name:
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s = get_random_style(task_rng)
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task_styles[i] = s
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task_styles[j] = s
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p, n = apply_style(s, positive=task_prompt)
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positive_basic_workloads = positive_basic_workloads + p
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negative_basic_workloads = negative_basic_workloads + n
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@ -847,9 +847,9 @@ def worker():
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return current_progress
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def apply_image_input(async_task, base_model_additional_loras, clip_vision_path, controlnet_canny_path,
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controlnet_cpds_path, goals, inpaint_head_model_path, inpaint_mask, inpaint_parameterized,
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ip_adapter_face_path, ip_adapter_path, ip_negative_path, skip_prompt_processing,
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use_synthetic_refiner):
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controlnet_cpds_path, goals, inpaint_head_model_path, inpaint_image, inpaint_mask,
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inpaint_parameterized, ip_adapter_face_path, ip_adapter_path, ip_negative_path,
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skip_prompt_processing, use_synthetic_refiner):
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if (async_task.current_tab == 'uov' or (
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async_task.current_tab == 'ip' and async_task.mixing_image_prompt_and_vary_upscale)) \
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and async_task.uov_method != flags.disabled and async_task.uov_input_image is not None:
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@ -1024,9 +1024,8 @@ def worker():
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if async_task.input_image_checkbox:
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base_model_additional_loras, clip_vision_path, controlnet_canny_path, controlnet_cpds_path, inpaint_head_model_path, inpaint_image, inpaint_mask, ip_adapter_face_path, ip_adapter_path, ip_negative_path, skip_prompt_processing, use_synthetic_refiner = apply_image_input(
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async_task, base_model_additional_loras, clip_vision_path, controlnet_canny_path, controlnet_cpds_path,
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goals, inpaint_head_model_path, inpaint_mask, inpaint_parameterized, ip_adapter_face_path, ip_adapter_path,
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ip_negative_path, skip_prompt_processing, use_synthetic_refiner)
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goals, inpaint_head_model_path, inpaint_image, inpaint_mask, inpaint_parameterized, ip_adapter_face_path,
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ip_adapter_path, ip_negative_path, skip_prompt_processing, use_synthetic_refiner)
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# Load or unload CNs
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progressbar(async_task, current_progress, 'Loading control models ...')
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