scripts/make_example.py

"""Bake a synthetic noisy image + clean ground-truth sidecar into APP_TMP_DIR.

The clean image is the ground truth so the blind-spot denoiser can be scored with
PSNR / SSIM. Noise2Void itself never sees the clean image — it denoises the noisy
input alone — but we keep the clean copy for evaluation.
"""
from __future__ import annotations

import sys

import numpy as np
import tifffile

from core.io import APP_TMP_DIR, register_protected
from core.synth import add_noise, clean_image


def main() -> int:
    clean = clean_image(H=256, W=256, seed=7)
    noisy = add_noise(clean, sigma=0.13, seed=7)
    out = APP_TMP_DIR / "example.tif"
    # Single-page noisy TIFF the user/API sees. The clean ground truth is kept as a
    # hidden sidecar (leading dot) so it isn't picked up as an input but is still
    # available for PSNR/SSIM scoring.
    tifffile.imwrite(out, (noisy * 255).astype("uint8"))
    np.save(APP_TMP_DIR / ".example_clean.npy", clean)              # ground-truth sidecar
    register_protected(out)
    register_protected(APP_TMP_DIR / ".example_clean.npy")
    print(f"wrote {out}  shape={noisy.shape}")
    return 0


if __name__ == "__main__":
    sys.exit(main())