evazion
d43ce9c4e7
Add an option for taking the list of input files from a text file: ./autotag -i files.txt This is useful in conjunction with the `find` command: find ~/images/ -name '*.jpg' | ./autotag -i -
65 lines
3.0 KiB
Python
Executable File
65 lines
3.0 KiB
Python
Executable File
#!/usr/bin/env python
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import json
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import click
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import itertools
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from autotagger import Autotagger
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from pathlib import Path
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from more_itertools import ichunked
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@click.command(help="Automatically generate tags for a list of images.", context_settings=dict(max_content_width=140))
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@click.option("-t", "--threshold", default=0.01, type=float, show_default=True, help="The minimum tag confidence level.")
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@click.option("-n", "--limit", default=50, type=int, show_default=True, help="The maximum number of tags to return per image.")
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@click.option("-b", "--batch", "bs", default=128, type=int, show_default=True, help="The number of images to process per batch.")
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@click.option("-c", "--csv", is_flag=True, help="Output CSV instead of JSON.")
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@click.option("-i", "--input-file", type=click.File(), help="Read list of image filenames from text file.")
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@click.option("-g/-f", "--group-tags/--flatten-tags", default=True, show_default=True, help="Output rows in {filename, tags} format or {filename, tag, score} format.")
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@click.option("-N", "--name-only", is_flag=True, help="Output only the filename without the full path or extension.")
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@click.option("-m", "--model", default="models/model.pth", type=click.Path(exists=True), show_default=True, help="The model to use.")
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@click.argument("files", nargs=-1, type=click.Path(exists=True, allow_dash=True, path_type=Path))
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def main(files, threshold, limit, bs, csv, input_file, group_tags, name_only, model):
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autotagger = Autotagger(model)
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if input_file:
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paths = (Path(line.rstrip()) for line in input_file)
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elif len(files) > 0:
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paths = get_filepaths(files)
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else:
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click.echo(click.get_current_context().get_help())
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click.get_current_context().exit()
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for filepaths in ichunked(paths, bs):
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filepaths = list(filepaths)
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files = [click.open_file(filepath, "rb") for filepath in filepaths]
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predictions = autotagger.predict(files, threshold=threshold, limit=limit, bs=bs)
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for filepath, tags in zip(filepaths, predictions):
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output_result(filepath, tags, csv, group_tags, name_only)
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def output_result(filepath, tags, csv, group_tags, name_only):
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name = filepath.stem if name_only else str(filepath)
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if csv and group_tags:
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tag_names = " ".join(sorted(tags.keys()))
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click.echo(f"{name},{tag_names}")
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elif csv and not group_tags:
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for tag, score in tags.items():
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click.echo(f"{name},{tag},{score}")
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elif group_tags:
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data = { "filename": name, "tags": tags }
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click.echo(json.dumps(data))
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else:
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for tag, score in tags.items():
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data = { "filename": name, "tag": tag, "score": score }
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click.echo(json.dumps(data))
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def get_filepaths(paths):
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files = (recurse_dir(path) if path.is_dir() else iter([path]) for path in paths)
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return itertools.chain(*files)
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def recurse_dir(directory):
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return (path for path in directory.glob("**/*") if not path.is_dir())
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if __name__ == "__main__":
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main()
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