loop
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@ -289,6 +289,7 @@ class ControlNetForForgeOfficial(scripts.Script):
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break
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if preprocessor_output_is_image:
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alignment_indices = [i % len(preprocessor_outputs) for i in range(p.batch_size)]
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params.control_cond = []
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params.control_cond_for_hr_fix = []
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@ -297,14 +298,14 @@ class ControlNetForForgeOfficial(scripts.Script):
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p.extra_result_images.append(external_code.visualize_inpaint_mask(control_cond))
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params.control_cond.append(numpy_to_pytorch(control_cond).movedim(-1, 1))
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params.control_cond = torch.cat(params.control_cond, dim=0)
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params.control_cond = torch.cat(params.control_cond, dim=0)[alignment_indices].contiguous()
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if has_high_res_fix:
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for preprocessor_output in preprocessor_outputs:
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control_cond_for_hr_fix = crop_and_resize_image(preprocessor_output, resize_mode, hr_y, hr_x)
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p.extra_result_images.append(external_code.visualize_inpaint_mask(control_cond_for_hr_fix))
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params.control_cond_for_hr_fix.append(numpy_to_pytorch(control_cond_for_hr_fix).movedim(-1, 1))
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params.control_cond_for_hr_fix = torch.cat(params.control_cond_for_hr_fix, dim=0)
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params.control_cond_for_hr_fix = torch.cat(params.control_cond_for_hr_fix, dim=0)[alignment_indices].contiguous()
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else:
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params.control_cond_for_hr_fix = params.control_cond
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else:
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