File size: 1,808 Bytes
1c0c94d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | """Queue integration: quality thresholds should be configurable from settings."""
from __future__ import annotations
from pathlib import Path
from core import queue
from core.config import Settings
from core.schemas import ImageMeta, ImageStatus
def test_process_and_store_respects_quality_threshold_settings(
monkeypatch, tmp_path: Path
) -> None:
image = tmp_path / "sample.jpg"
image.write_bytes(b"fake")
meta = ImageMeta(id="img_cfg", filename="sample.jpg")
statuses: list[ImageStatus] = []
monkeypatch.setattr(queue.storage, "get_image", lambda image_id: meta)
monkeypatch.setattr(queue.storage, "original_path", lambda image_id: str(image))
monkeypatch.setattr(
queue.storage, "set_status", lambda image_id, status: statuses.append(status)
)
assessed: dict[str, float] = {}
class _Report:
ok = False
def fake_assess(
path: str, *, min_side: int, blur_threshold: float, dark: float, bright: float
):
assessed.update(
{
"min_side": min_side,
"blur_threshold": blur_threshold,
"dark": dark,
"bright": bright,
}
)
return _Report()
monkeypatch.setattr(queue.quality, "assess", fake_assess)
monkeypatch.setattr(
queue,
"get_settings",
lambda: Settings(
quality_min_side=80,
quality_blur_threshold=7.5,
quality_dark_threshold=10.0,
quality_bright_threshold=250.0,
),
)
queue.process_and_store("img_cfg")
assert assessed == {
"min_side": 80,
"blur_threshold": 7.5,
"dark": 10.0,
"bright": 250.0,
}
assert statuses == [ImageStatus.processing, ImageStatus.undeterminable]
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