diff options
| -rw-r--r-- | modules/deepbooru.py | 65 | ||||
| -rw-r--r-- | modules/shared.py | 2 | ||||
| -rw-r--r-- | modules/textual_inversion/preprocess.py | 92 | ||||
| -rw-r--r-- | modules/ui.py | 7 |
4 files changed, 95 insertions, 71 deletions
diff --git a/modules/deepbooru.py b/modules/deepbooru.py index 29529949..419e6a9c 100644 --- a/modules/deepbooru.py +++ b/modules/deepbooru.py @@ -2,33 +2,44 @@ import os.path from concurrent.futures import ProcessPoolExecutor import multiprocessing import time +import re + +re_special = re.compile(r'([\\()])') def get_deepbooru_tags(pil_image): """ This method is for running only one image at a time for simple use. Used to the img2img interrogate. """ from modules import shared # prevents circular reference - create_deepbooru_process(shared.opts.interrogate_deepbooru_score_threshold, shared.opts.deepbooru_sort_alpha) - shared.deepbooru_process_return["value"] = -1 - shared.deepbooru_process_queue.put(pil_image) - while shared.deepbooru_process_return["value"] == -1: - time.sleep(0.2) - tags = shared.deepbooru_process_return["value"] - release_process() - return tags + try: + create_deepbooru_process(shared.opts.interrogate_deepbooru_score_threshold, create_deepbooru_opts()) + return get_tags_from_process(pil_image) + finally: + release_process() + + +def create_deepbooru_opts(): + from modules import shared -def deepbooru_process(queue, deepbooru_process_return, threshold, alpha_sort): + return { + "use_spaces": shared.opts.deepbooru_use_spaces, + "use_escape": shared.opts.deepbooru_escape, + "alpha_sort": shared.opts.deepbooru_sort_alpha, + } + + +def deepbooru_process(queue, deepbooru_process_return, threshold, deepbooru_opts): model, tags = get_deepbooru_tags_model() while True: # while process is running, keep monitoring queue for new image pil_image = queue.get() if pil_image == "QUIT": break else: - deepbooru_process_return["value"] = get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort) + deepbooru_process_return["value"] = get_deepbooru_tags_from_model(model, tags, pil_image, threshold, deepbooru_opts) -def create_deepbooru_process(threshold, alpha_sort): +def create_deepbooru_process(threshold, deepbooru_opts): """ Creates deepbooru process. A queue is created to send images into the process. This enables multiple images to be processed in a row without reloading the model or creating a new process. To return the data, a shared @@ -41,10 +52,23 @@ def create_deepbooru_process(threshold, alpha_sort): shared.deepbooru_process_queue = shared.deepbooru_process_manager.Queue() shared.deepbooru_process_return = shared.deepbooru_process_manager.dict() shared.deepbooru_process_return["value"] = -1 - shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold, alpha_sort)) + shared.deepbooru_process = multiprocessing.Process(target=deepbooru_process, args=(shared.deepbooru_process_queue, shared.deepbooru_process_return, threshold, deepbooru_opts)) shared.deepbooru_process.start() +def get_tags_from_process(image): + from modules import shared + + shared.deepbooru_process_return["value"] = -1 + shared.deepbooru_process_queue.put(image) + while shared.deepbooru_process_return["value"] == -1: + time.sleep(0.2) + caption = shared.deepbooru_process_return["value"] + shared.deepbooru_process_return["value"] = -1 + + return caption + + def release_process(): """ Stops the deepbooru process to return used memory @@ -81,10 +105,15 @@ def get_deepbooru_tags_model(): return model, tags -def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort): +def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, deepbooru_opts): import deepdanbooru as dd import tensorflow as tf import numpy as np + + alpha_sort = deepbooru_opts['alpha_sort'] + use_spaces = deepbooru_opts['use_spaces'] + use_escape = deepbooru_opts['use_escape'] + width = model.input_shape[2] height = model.input_shape[1] image = np.array(pil_image) @@ -129,4 +158,12 @@ def get_deepbooru_tags_from_model(model, tags, pil_image, threshold, alpha_sort) print('\n'.join(sorted(result_tags_print, reverse=True))) - return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ') + tags_text = ', '.join(result_tags_out) + + if use_spaces: + tags_text = tags_text.replace('_', ' ') + + if use_escape: + tags_text = re.sub(re_special, r'\\\1', tags_text) + + return tags_text.replace(':', ' ') diff --git a/modules/shared.py b/modules/shared.py index e64e69fc..78b73aae 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -260,6 +260,8 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"), "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
"interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
"deepbooru_sort_alpha": OptionInfo(True, "Interrogate: deepbooru sort alphabetically"),
+ "deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"),
+ "deepbooru_escape": OptionInfo(True, "escape (\\) brackets in deepbooru (so they are used as literal brackets and not for emphasis)"),
}))
options_templates.update(options_section(('ui', "User interface"), {
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index 113cecf1..3047bede 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -10,7 +10,28 @@ from modules.shared import opts, cmd_opts if cmd_opts.deepdanbooru:
import modules.deepbooru as deepbooru
+
def preprocess(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False):
+ try:
+ if process_caption:
+ shared.interrogator.load()
+
+ if process_caption_deepbooru:
+ deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, deepbooru.create_deepbooru_opts())
+
+ preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru)
+
+ finally:
+
+ if process_caption:
+ shared.interrogator.send_blip_to_ram()
+
+ if process_caption_deepbooru:
+ deepbooru.release_process()
+
+
+
+def preprocess_work(process_src, process_dst, process_width, process_height, process_flip, process_split, process_caption, process_caption_deepbooru=False):
width = process_width
height = process_height
src = os.path.abspath(process_src)
@@ -25,30 +46,28 @@ def preprocess(process_src, process_dst, process_width, process_height, process_ shared.state.textinfo = "Preprocessing..."
shared.state.job_count = len(files)
- if process_caption:
- shared.interrogator.load()
-
- if process_caption_deepbooru:
- deepbooru.create_deepbooru_process(opts.interrogate_deepbooru_score_threshold, opts.deepbooru_sort_alpha)
-
def save_pic_with_caption(image, index):
+ caption = ""
+
if process_caption:
- caption = "-" + shared.interrogator.generate_caption(image)
- caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png")
- elif process_caption_deepbooru:
- shared.deepbooru_process_return["value"] = -1
- shared.deepbooru_process_queue.put(image)
- while shared.deepbooru_process_return["value"] == -1:
- time.sleep(0.2)
- caption = "-" + shared.deepbooru_process_return["value"]
- caption = sanitize_caption(os.path.join(dst, f"{index:05}-{subindex[0]}"), caption, ".png")
- shared.deepbooru_process_return["value"] = -1
- else:
- caption = filename
- caption = os.path.splitext(caption)[0]
- caption = os.path.basename(caption)
+ caption += shared.interrogator.generate_caption(image)
+
+ if process_caption_deepbooru:
+ if len(caption) > 0:
+ caption += ", "
+ caption += deepbooru.get_tags_from_process(image)
+
+ filename_part = filename
+ filename_part = os.path.splitext(filename_part)[0]
+ filename_part = os.path.basename(filename_part)
+
+ basename = f"{index:05}-{subindex[0]}-{filename_part}"
+ image.save(os.path.join(dst, f"{basename}.png"))
+
+ if len(caption) > 0:
+ with open(os.path.join(dst, f"{basename}.txt"), "w", encoding="utf8") as file:
+ file.write(caption)
- image.save(os.path.join(dst, f"{index:05}-{subindex[0]}{caption}.png"))
subindex[0] += 1
def save_pic(image, index):
@@ -93,34 +112,3 @@ def preprocess(process_src, process_dst, process_width, process_height, process_ save_pic(img, index)
shared.state.nextjob()
-
- if process_caption:
- shared.interrogator.send_blip_to_ram()
-
- if process_caption_deepbooru:
- deepbooru.release_process()
-
-
-def sanitize_caption(base_path, original_caption, suffix):
- operating_system = platform.system().lower()
- if (operating_system == "windows"):
- invalid_path_characters = "\\/:*?\"<>|"
- max_path_length = 259
- else:
- invalid_path_characters = "/" #linux/macos
- max_path_length = 1023
- caption = original_caption
- for invalid_character in invalid_path_characters:
- caption = caption.replace(invalid_character, "")
- fixed_path_length = len(base_path) + len(suffix)
- if fixed_path_length + len(caption) <= max_path_length:
- return caption
- caption_tokens = caption.split()
- new_caption = ""
- for token in caption_tokens:
- last_caption = new_caption
- new_caption = new_caption + token + " "
- if (len(new_caption) + fixed_path_length - 1 > max_path_length):
- break
- print(f"\nPath will be too long. Truncated caption: {original_caption}\nto: {last_caption}", file=sys.stderr)
- return last_caption.strip()
diff --git a/modules/ui.py b/modules/ui.py index c42535c8..e07ee0e1 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1074,11 +1074,8 @@ def create_ui(wrap_gradio_gpu_call): with gr.Row():
process_flip = gr.Checkbox(label='Create flipped copies')
process_split = gr.Checkbox(label='Split oversized images into two')
- process_caption = gr.Checkbox(label='Use BLIP caption as filename')
- if cmd_opts.deepdanbooru:
- process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename')
- else:
- process_caption_deepbooru = gr.Checkbox(label='Use deepbooru caption as filename', visible=False)
+ process_caption = gr.Checkbox(label='Use BLIP for caption')
+ process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True if cmd_opts.deepdanbooru else False)
with gr.Row():
with gr.Column(scale=3):
|