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run_image.py
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run_image.py
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from dataclasses import dataclass
from pathlib import Path
from typing import Annotated, Optional
import cv2
import typer
from sorters import SORTER_DICT, AbstractSorter, Sorters
app = typer.Typer()
@dataclass
class Scenario:
sorter: type[AbstractSorter]
detector: type[AbstractSorter]
thresh: int | float
file: Path
output: Path
def parse_scenario(s: Scenario):
img = cv2.imread(str(s.file), cv2.IMREAD_UNCHANGED)
s.output.parent.mkdir(parents=True, exist_ok=True)
im_sorted = s.sorter(0).apply(img, s.detector(s.thresh))
cv2.imwrite(str(s.output), im_sorted)
return s
@app.command()
def run_img(
input_img: Annotated[Path, typer.Argument(help="the input image to sort")],
output: Annotated[
Optional[Path], typer.Option(help="where to output to. if empty, appends `-pixelsorted` to input.")
] = None,
sorter: Annotated[Sorters, typer.Option(help="what sorter to actually sort sections with")] = Sorters.GRAY,
detector: Annotated[Sorters, typer.Option(help="how to detect sections")] = Sorters.CANNY,
detector_threshold: float = 1,
):
assert input_img.exists(), "Image does not exist"
output = output or input_img.with_stem(f"{input_img.stem}-pixelsorted")
parse_scenario(Scenario(SORTER_DICT[sorter], SORTER_DICT[detector], detector_threshold, input_img, output))
if __name__ == "__main__":
app()