Hama myScan Linux driver tools: scan mode, frame decoding, stitching

UVC extension-unit control (mouse/scan mode, LEDs, exposure), JPEG header
fix and embedded laser record decoding, session recorder, and a stitcher
that combines laser dead reckoning with phase correlation and ECC refinement.
FINDINGS.md holds the reverse-engineered protocol and laser calibration.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

tools/stitch.py

@@ -0,0 +1,44 @@
+#!/usr/bin/env python3
+"""Stitch a directory recorded by tools/record.py into a page image."""
+import argparse
+import csv
+import os
+import sys
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+import cv2  # noqa: E402
+import numpy as np  # noqa: E402
+
+from myscan.stitch import ROT_GAIN, Stitcher, laser_deltas  # noqa: E402
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("dir")
+    ap.add_argument("-o", "--out", help="output image (default <dir>/page.png)")
+    ap.add_argument("--no-refine", action="store_true", help="lasers only, no image registration")
+    ap.add_argument("--rot-gain", type=float, default=ROT_GAIN)
+    ap.add_argument("--start", type=int, default=0)
+    ap.add_argument("--end", type=int)
+    a = ap.parse_args()
+
+    rows = list(csv.DictReader(open(os.path.join(a.dir, "records.csv"))))
+    v = np.array([[int(r[f"v{k}"]) for k in range(6)] for r in rows])
+    deltas = laser_deltas(v)
+    frames = [int(r["frame"]) for r in rows]
+    rng = range(a.start, a.end if a.end is not None else len(rows))
+
+    st = None
+    for i in rng:
+        im = cv2.imread(os.path.join(a.dir, f"f{frames[i]:05d}.png"), cv2.IMREAD_GRAYSCALE)
+        if st is None:
+            st = Stitcher(im.shape, refine=not a.no_refine, rot_gain=a.rot_gain)
+        st.add(im, deltas[i])
+    out = a.out or os.path.join(a.dir, "page.png")
+    cv2.imwrite(out, st.image())
+    print(f"{st.n} frames -> {out}  {st.stats}")
+
+
+if __name__ == "__main__":
+    main()