Bring in frame-hands' hand tracking under hands/

The history of frame-hands (~/Desktop/Projects/frame-hands on the
Frame), filtered to what moves: the camera broker (camd/), the tracker
and its offline tools (trackd/), the shared file layouts (include/), the
ncnn models, the analysis tools, and the calibration and model helpers
they import from the Python prototype. The reverse-engineering notes,
probes, camprobe, and the rest of the prototype stay in frame-hands.
Unchanged here: the renames to ft- names and Frametop paths follow.

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

hands/tools/check_color.py

@@ -0,0 +1,65 @@
+"""Which color camera is which, and how their calibration maps onto fh-camd's images.
+
+usage: python tools/check_color.py REC_DIR [--sets N]
+
+A recording made with fh-camd --with-color holds color_video<N> frames with each set.
+This matches features between the two color images and scores every reading of the
+calibration: which video node is passthrough_left, and whether the calibration's
+cropRegion is subtracted from x ('subtract') or not ('none'). Only the right reading
+makes true matches' rays meet in front of both cameras. Then it checks the winner against
+the side tracking cameras, which tests the CAD-to-head chain shared with them.
+"""
+import argparse
+import itertools
+import os
+import sys
+
+import numpy as np
+
+sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), '..'))
+from tools.check_sides import load_cams, matches, score  # noqa: E402
+from tools.show_set import index, read_set  # noqa: E402
+from tracker import calib  # noqa: E402
+
+
+def load_color(crop):
+    root = os.environ.get('FRAME_JOB_DEVICE_ROOT', '')   # frame-job's copy of the device files
+    return calib.load_color(root + calib.ARCTURUS_EEPROM, root + calib.DEVICE_JSON, crop=crop)
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument('rec')
+    ap.add_argument('--sets', type=int, default=8)
+    a = ap.parse_args()
+    path = os.path.join(a.rec, 'sets.bin')
+    offs = index(path)
+    sets = [read_set(path, offs[n]) for n in np.linspace(0, len(offs) - 1, a.sets).astype(int)]
+    nodes = sorted(k for k in sets[0] if k.startswith('color_video'))
+    if len(nodes) != 2:
+        sys.exit('need two color_video<N> cameras in the recording (fh-camd --with-color); found %s' % nodes)
+    pairs = [matches(s[nodes[0]][0], s[nodes[1]][0]) for s in sets]
+    print('%d sets, %d matches between %s and %s' % (len(sets), sum(len(p[0]) for p in pairs), *nodes))
+
+    best = None
+    for crop, left in itertools.product(['subtract', 'none'], nodes):
+        cams = load_color(crop)
+        right = nodes[1] if left == nodes[0] else nodes[0]
+        cam = {left: cams['passthrough_left'], right: cams['passthrough_right']}
+        s = np.mean([score(cam[nodes[0]], cam[nodes[1]], ua, ub) for ua, ub in pairs])
+        print('  %s = passthrough_left, crop %-8s: %3.0f%% of matches meet' % (left, crop, 100 * s))
+        if best is None or s > best[0]:
+            best = (s, crop, left, cam)
+    s, crop, left, cam = best
+    print('best: %s = passthrough_left, crop %s (%.0f%%)' % (left, crop, 100 * s))
+
+    mono = load_cams()
+    for node in nodes:
+        for side in ['slam_left', 'slam_right']:
+            ms = [matches(st[node][0], st[side][0]) for st in sets if side in st]
+            sc = np.mean([score(cam[node], mono[side], ua, ub) for ua, ub in ms]) if ms else 0
+            print('  %s vs %-10s: %4d matches, %3.0f%% meet' % (node, side, sum(len(m[0]) for m in ms), 100 * sc))
+
+
+if __name__ == '__main__':
+    main()