Loading modules/processing.py +22 −21 Original line number Diff line number Diff line Loading @@ -516,25 +516,25 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: else: p.all_negative_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_negative_styles_to_prompt(p.negative_prompt, p.styles)] if type(p) == StableDiffusionProcessingTxt2Img: if p.enable_hr and p.is_hr_pass: logging.info("Running hr pass with custom prompt") if p.hr_prompt: if type(p.prompt) == list: p.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, p.styles) for x in p.hr_prompt] else: p.all_prompts = p.batch_size * p.n_iter * [ shared.prompt_styles.apply_styles_to_prompt(p.hr_prompt, p.styles)] logging.info(p.all_prompts) if p.hr_negative_prompt: if type(p.negative_prompt) == list: p.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, p.styles) for x in p.hr_negative_prompt] else: p.all_negative_prompts = p.batch_size * p.n_iter * [ shared.prompt_styles.apply_negative_styles_to_prompt(p.hr_negative_prompt, p.styles)] logging.info(p.all_negative_prompts) # if type(p) == StableDiffusionProcessingTxt2Img: # if p.enable_hr and p.is_hr_pass: # logging.info("Running hr pass with custom prompt") # if p.hr_prompt: # if type(p.prompt) == list: # p.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, p.styles) for x in p.hr_prompt] # else: # p.all_prompts = p.batch_size * p.n_iter * [ # shared.prompt_styles.apply_styles_to_prompt(p.hr_prompt, p.styles)] # logging.info(p.all_prompts) # # if p.hr_negative_prompt: # if type(p.negative_prompt) == list: # p.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, p.styles) for x in # p.hr_negative_prompt] # else: # p.all_negative_prompts = p.batch_size * p.n_iter * [ # shared.prompt_styles.apply_negative_styles_to_prompt(p.hr_negative_prompt, p.styles)] # logging.info(p.all_negative_prompts) if type(seed) == list: p.all_seeds = seed Loading Loading @@ -744,7 +744,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.hr_sampler = hr_sampler self.hr_prompt = hr_prompt if hr_prompt != '' else self.prompt self.hr_negative_prompt = hr_negative_prompt if hr_negative_prompt != '' else self.negative_prompt self.is_hr_pass = False if firstphase_width != 0 or firstphase_height != 0: self.hr_upscale_to_x = self.width Loading Loading @@ -831,7 +830,9 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): if not self.enable_hr: return samples self.is_hr_pass = True self.prompt = self.hr_prompt self.negative_prompt = self.hr_negative_prompt target_width = self.hr_upscale_to_x target_height = self.hr_upscale_to_y Loading Loading
modules/processing.py +22 −21 Original line number Diff line number Diff line Loading @@ -516,25 +516,25 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: else: p.all_negative_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_negative_styles_to_prompt(p.negative_prompt, p.styles)] if type(p) == StableDiffusionProcessingTxt2Img: if p.enable_hr and p.is_hr_pass: logging.info("Running hr pass with custom prompt") if p.hr_prompt: if type(p.prompt) == list: p.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, p.styles) for x in p.hr_prompt] else: p.all_prompts = p.batch_size * p.n_iter * [ shared.prompt_styles.apply_styles_to_prompt(p.hr_prompt, p.styles)] logging.info(p.all_prompts) if p.hr_negative_prompt: if type(p.negative_prompt) == list: p.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, p.styles) for x in p.hr_negative_prompt] else: p.all_negative_prompts = p.batch_size * p.n_iter * [ shared.prompt_styles.apply_negative_styles_to_prompt(p.hr_negative_prompt, p.styles)] logging.info(p.all_negative_prompts) # if type(p) == StableDiffusionProcessingTxt2Img: # if p.enable_hr and p.is_hr_pass: # logging.info("Running hr pass with custom prompt") # if p.hr_prompt: # if type(p.prompt) == list: # p.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, p.styles) for x in p.hr_prompt] # else: # p.all_prompts = p.batch_size * p.n_iter * [ # shared.prompt_styles.apply_styles_to_prompt(p.hr_prompt, p.styles)] # logging.info(p.all_prompts) # # if p.hr_negative_prompt: # if type(p.negative_prompt) == list: # p.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, p.styles) for x in # p.hr_negative_prompt] # else: # p.all_negative_prompts = p.batch_size * p.n_iter * [ # shared.prompt_styles.apply_negative_styles_to_prompt(p.hr_negative_prompt, p.styles)] # logging.info(p.all_negative_prompts) if type(seed) == list: p.all_seeds = seed Loading Loading @@ -744,7 +744,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.hr_sampler = hr_sampler self.hr_prompt = hr_prompt if hr_prompt != '' else self.prompt self.hr_negative_prompt = hr_negative_prompt if hr_negative_prompt != '' else self.negative_prompt self.is_hr_pass = False if firstphase_width != 0 or firstphase_height != 0: self.hr_upscale_to_x = self.width Loading Loading @@ -831,7 +830,9 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): if not self.enable_hr: return samples self.is_hr_pass = True self.prompt = self.hr_prompt self.negative_prompt = self.hr_negative_prompt target_width = self.hr_upscale_to_x target_height = self.hr_upscale_to_y Loading
