mirror of
https://github.com/openvinotoolkit/stable-diffusion-webui.git
synced 2024-12-14 14:45:06 +03:00
deepbooru: added option to use spaces or underscores
deepbooru: added option to quote (\) in tags deepbooru/BLIP: write caption to file instead of image filename deepbooru/BLIP: now possible to use both for captions deepbooru: process is stopped even if an exception occurs
This commit is contained in:
AUTOMATIC
parent
c3c8eef9fd
commit
698d303b04
@ -2,33 +2,44 @@ import os.path
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from concurrent.futures import ProcessPoolExecutor
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import multiprocessing
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import time
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import re
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re_special = re.compile(r'([\\()])')
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def get_deepbooru_tags(pil_image):
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"""
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This method is for running only one image at a time for simple use. Used to the img2img interrogate.
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"""
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from modules import shared # prevents circular reference
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create_deepbooru_process(shared.opts.interrogate_deepbooru_score_threshold, shared.opts.deepbooru_sort_alpha)
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shared.deepbooru_process_return["value"] = -1
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shared.deepbooru_process_queue.put(pil_image)
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while shared.deepbooru_process_return["value"] == -1:
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time.sleep(0.2)
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tags = shared.deepbooru_process_return["value"]
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release_process()
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return tags
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try:
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create_deepbooru_process(shared.opts.interrogate_deepbooru_score_threshold, create_deepbooru_opts())
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return get_tags_from_process(pil_image)
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finally:
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release_process()
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def deepbooru_process(queue, deepbooru_process_return, threshold, alpha_sort):
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def create_deepbooru_opts():
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from modules import shared
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return {
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"use_spaces": shared.opts.deepbooru_use_spaces,
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"use_escape": shared.opts.deepbooru_escape,
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"alpha_sort": shared.opts.deepbooru_sort_alpha,
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}
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def deepbooru_process(queue, deepbooru_process_return, threshold, deepbooru_opts):
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model, tags = get_deepbooru_tags_model()
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while True: # while process is running, keep monitoring queue for new image
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pil_image = queue.get()
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if pil_image == "QUIT":
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break
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else:
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deepbooru_process_return["value"] = get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort)
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deepbooru_process_return["value"] = get_deepbooru_tags_from_model(model, tags, pil_image, threshold, deepbooru_opts)
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def create_deepbooru_process(threshold, alpha_sort):
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def create_deepbooru_process(threshold, deepbooru_opts):
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"""
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Creates deepbooru process. A queue is created to send images into the process. This enables multiple images
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to be processed in a row without reloading the model or creating a new process. To return the data, a shared
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@ -41,10 +52,23 @@ def create_deepbooru_process(threshold, alpha_sort):
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shared.deepbooru_process_queue = shared.deepbooru_process_manager.Queue()
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shared.deepbooru_process_return = shared.deepbooru_process_manager.dict()
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shared.deepbooru_process_return["value"] = -1
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shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold, alpha_sort))
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shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold, deepbooru_opts))
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shared.deepbooru_process.start()
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def get_tags_from_process(image):
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from modules import shared
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shared.deepbooru_process_return["value"] = -1
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shared.deepbooru_process_queue.put(image)
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while shared.deepbooru_process_return["value"] == -1:
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time.sleep(0.2)
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caption = shared.deepbooru_process_return["value"]
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shared.deepbooru_process_return["value"] = -1
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return caption
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def release_process():
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"""
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Stops the deepbooru process to return used memory
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@ -81,10 +105,15 @@ def get_deepbooru_tags_model():
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return model, tags
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def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort):
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def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, deepbooru_opts):
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import deepdanbooru as dd
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import tensorflow as tf
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import numpy as np
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alpha_sort = deepbooru_opts['alpha_sort']
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use_spaces = deepbooru_opts['use_spaces']
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use_escape = deepbooru_opts['use_escape']
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width = model.input_shape[2]
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height = model.input_shape[1]
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image = np.array(pil_image)
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@ -129,4 +158,12 @@ def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort)
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print('\n'.join(sorted(result_tags_print, reverse=True)))
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return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ')
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tags_text = ', '.join(result_tags_out)
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if use_spaces:
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tags_text = tags_text.replace('_', ' ')
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if use_escape:
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tags_text = re.sub(re_special, r'\\\1', tags_text)
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return tags_text.replace(':', ' ')
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@ -260,6 +260,8 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"),
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"interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
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"interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
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"deepbooru_sort_alpha": OptionInfo(True, "Interrogate: deepbooru sort alphabetically"),
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"deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"),
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"deepbooru_escape": OptionInfo(True, "escape (\\) brackets in deepbooru (so they are used as literal brackets and not for emphasis)"),
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}))
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options_templates.update(options_section(('ui', "User interface"), {
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@ -10,7 +10,28 @@ from modules.shared import opts, cmd_opts
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if cmd_opts.deepdanbooru:
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import modules.deepbooru as deepbooru
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def preprocess(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False):
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try:
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if process_caption:
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shared.interrogator.load()
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if process_caption_deepbooru:
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deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, deepbooru.create_deepbooru_opts())
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preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru)
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finally:
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if process_caption:
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shared.interrogator.send_blip_to_ram()
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if process_caption_deepbooru:
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deepbooru.release_process()
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def preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False):
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width = process_width
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height = process_height
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src = os.path.abspath(process_src)
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@ -25,30 +46,28 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
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shared.state.textinfo = "Preprocessing..."
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shared.state.job_count = len(files)
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if process_caption:
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shared.interrogator.load()
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if process_caption_deepbooru:
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deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, opts.deepbooru_sort_alpha)
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def save_pic_with_caption(image, index):
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if process_caption:
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caption = "-" + shared.interrogator.generate_caption(image)
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caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png")
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elif process_caption_deepbooru:
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shared.deepbooru_process_return["value"] = -1
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shared.deepbooru_process_queue.put(image)
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while shared.deepbooru_process_return["value"] == -1:
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time.sleep(0.2)
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caption = "-" + shared.deepbooru_process_return["value"]
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caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png")
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shared.deepbooru_process_return["value"] = -1
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else:
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caption = filename
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caption = os.path.splitext(caption)[0]
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caption = os.path.basename(caption)
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caption = ""
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if process_caption:
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caption += shared.interrogator.generate_caption(image)
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if process_caption_deepbooru:
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if len(caption) > 0:
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caption += ", "
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caption += deepbooru.get_tags_from_process(image)
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filename_part = filename
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filename_part = os.path.splitext(filename_part)[0]
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filename_part = os.path.basename(filename_part)
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basename = f"{index:05}-{subindex[0]}-{filename_part}"
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image.save(os.path.join(dst, f"{basename}.png"))
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if len(caption) > 0:
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with open(os.path.join(dst, f"{basename}.txt"), "w", encoding="utf8") as file:
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file.write(caption)
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image.save(os.path.join(dst, f"{index:05}-{subindex[0]}{caption}.png"))
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subindex[0] += 1
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def save_pic(image, index):
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@ -93,34 +112,3 @@ def preprocess(process_src, process_dst, process_width, process_height, process_
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save_pic(img, index)
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shared.state.nextjob()
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if process_caption:
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shared.interrogator.send_blip_to_ram()
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if process_caption_deepbooru:
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deepbooru.release_process()
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def sanitize_caption(base_path, original_caption, suffix):
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operating_system = platform.system().lower()
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if (operating_system == "windows"):
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invalid_path_characters = "\\/:*?\"<>|"
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max_path_length = 259
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else:
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invalid_path_characters = "/" #linux/macos
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max_path_length = 1023
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caption = original_caption
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for invalid_character in invalid_path_characters:
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caption = caption.replace(invalid_character, "")
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fixed_path_length = len(base_path) + len(suffix)
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if fixed_path_length + len(caption) <= max_path_length:
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return caption
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caption_tokens = caption.split()
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new_caption = ""
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for token in caption_tokens:
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last_caption = new_caption
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new_caption = new_caption + token + " "
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if (len(new_caption) + fixed_path_length - 1 > max_path_length):
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break
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print(f"\nPath will be too long. Truncated caption: {original_caption}\nto: {last_caption}", file=sys.stderr)
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return last_caption.strip()
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@ -1074,11 +1074,8 @@ def create_ui(wrap_gradio_gpu_call):
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with gr.Row():
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process_flip = gr.Checkbox(label='Create flipped copies')
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process_split = gr.Checkbox(label='Split oversized images into two')
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process_caption = gr.Checkbox(label='Use BLIP caption as filename')
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if cmd_opts.deepdanbooru:
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process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename')
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else:
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process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename', visible=False)
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process_caption = gr.Checkbox(label='Use BLIP for caption')
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process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True if cmd_opts.deepdanbooru else False)
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with gr.Row():
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with gr.Column(scale=3):
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