126 lines
3.6 KiB
Python
126 lines
3.6 KiB
Python
import sys
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from typing import Generator, Iterable
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from tagger.interrogator.interrogator import AbsInterrogator
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from PIL import Image
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from pathlib import Path
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import argparse
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from tagger.interrogators import interrogators
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parser = argparse.ArgumentParser()
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group = parser.add_mutually_exclusive_group(required=True)
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group.add_argument('--dir', help='Predictions for all images in the directory')
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group.add_argument('--file', help='Predictions for one file')
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parser.add_argument(
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'--threshold',
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type=float,
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default=0.35,
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help='Prediction threshold (default is 0.35)')
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parser.add_argument(
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'--ext',
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default='.txt',
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help='Extension to add to caption file in case of dir option (default is .txt)')
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parser.add_argument(
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'--overwrite',
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action='store_true',
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help='Overwrite caption file if it exists')
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parser.add_argument(
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'--cpu',
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action='store_true',
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help='Use CPU only')
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parser.add_argument(
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'--rawtag',
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action='store_true',
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help='Use the raw output of the model')
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parser.add_argument(
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'--recursive',
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action='store_true',
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help='Enable recursive file search')
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parser.add_argument(
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'--exclude-tag',
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dest='exclude_tags',
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action='append',
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metavar='t1,t2,t3',
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help='Specify tags to exclude (Need comma-separated list)')
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parser.add_argument(
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'--model',
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default='wd14-convnextv2.v1',
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metavar='MODELNAME',
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help='modelname to use for prediction (default is wd14-convnextv2.v1)')
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args = parser.parse_args()
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# get interrogator configs
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interrogator = interrogators[args.model]
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if args.cpu:
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interrogator.use_cpu()
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def parse_exclude_tags() -> set[str]:
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if args.exclude_tags is None:
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return set()
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tags = []
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for str in args.exclude_tags:
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for tag in str.split(','):
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tags.append(tag.strip())
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# reverse escape (nai tag to danbooru tag)
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reverse_escaped_tags = []
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for tag in tags:
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tag = tag.replace(' ', '_').replace(r'\(', '(').replace(r'\)', ')')
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reverse_escaped_tags.append(tag)
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return set([*tags, *reverse_escaped_tags]) # reduce duplicates
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def image_interrogate(image_path: Path, tag_escape: bool, exclude_tags: Iterable[str]) -> dict[str, float]:
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"""
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Predictions from a image path
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"""
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im = Image.open(image_path)
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result = interrogator.interrogate(im)
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return AbsInterrogator.postprocess_tags(
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result[1],
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threshold=args.threshold,
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escape_tag=tag_escape,
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replace_underscore=tag_escape,
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exclude_tags=exclude_tags)
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def explore_image_files(folder_path: Path) -> Generator[Path, None, None]:
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"""
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Explore files by folder path
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"""
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for path in folder_path.iterdir():
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if path.is_file() and path.suffix in ['.png', '.jpg', '.jpeg', '.webp']:
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yield path
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elif args.recursive and path.is_dir():
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yield from explore_image_files(path)
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if args.dir:
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root_path = Path(args.dir)
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for image_path in explore_image_files(root_path):
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caption_path = image_path.parent / f'{image_path.stem}{args.ext}'
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if caption_path.is_file() and not args.overwrite:
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# skip if caption exists
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print('skip:', image_path)
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continue
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print('processing:', image_path)
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tags = image_interrogate(image_path, not args.rawtag, parse_exclude_tags())
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tags_str = ', '.join(tags.keys())
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with open(caption_path, 'w') as fp:
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fp.write(tags_str)
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if args.file:
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tags = image_interrogate(Path(args.file), not args.rawtag, parse_exclude_tags())
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print(file=sys.stderr)
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tags_str = ', '.join(tags.keys())
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print(tags_str)
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