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DeeJanuzandClaude Opus 5.5
1a76d1560b
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>
80 lines
3.1 KiB
Python
80 lines
3.1 KiB
Python
"""Calibration crops for quantizing the models to int8 (ncnn2table).
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Takes the frames of an fh-camprobe capture, cuts the crops the tracker would feed
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the models (CLAHE-equalized, as tracker/models.py prepares them), and writes them
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as PNGs plus a list per model:
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palm: every search tile of every frame (a sample of them)
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hand: the hands found in them, each also shifted, scaled and turned a little
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usage: python tools/make_int8_calib.py CAPTURE_DIR OUT_DIR
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"""
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import glob
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import os
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import random
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import sys
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import cv2
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import numpy as np
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sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), '..', 'tracker'))
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import calib # noqa: E402
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import hands # noqa: E402
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import models # noqa: E402
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NODES = {'video9': 'slam_left', 'video13': 'slam_right', 'video6': 'upper_left', 'video7': 'upper_right'}
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def save(path, patch):
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cv2.imwrite(path, cv2.cvtColor(patch, cv2.COLOR_GRAY2BGR))
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def main():
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cap, out = sys.argv[1], sys.argv[2]
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random.seed(1)
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cams = calib.load()
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eng = models.Engine()
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palm, hm = models.PalmDetector(), models.HandLandmarker()
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tracker = hands.Tracker(cams, eng)
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for d in ('palm', 'hand'):
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os.makedirs(os.path.join(out, d), exist_ok=True)
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palm_files, hand_files = [], []
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for node, name in NODES.items():
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tiles = [t for t in tracker.tiles if t.cam.name == name]
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for f in sorted(glob.glob(os.path.join(cap, '*_%s.pgm' % node))):
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g = cv2.imread(f, cv2.IMREAD_GRAYSCALE)
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base = os.path.basename(f)[:-4]
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prep = [palm.prepare(g, t.center, t.size, t.rotation) for t in tiles]
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outs = eng.run([('palm', p) for p, _ in prep])
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rois = []
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for k, ((p, ctx), o) in enumerate(zip(prep, outs)):
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if random.random() < 0.3:
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path = os.path.join(out, 'palm', '%s_t%02d.png' % (base, k))
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save(path, p)
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palm_files.append(path)
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for d in palm.decode(o, ctx):
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r = d.roi()
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if all(np.linalg.norm(r[0] - q[0]) > 0.5 * r[1] for q in rois):
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rois.append(r)
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for j, r in enumerate(rois):
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p, ctx = hm.prepare(g, r)
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if hm.decode(eng.run([('hand', p)])[0], ctx).presence < 0.5:
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continue
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for v in range(5):
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c, s, rot = r
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if v:
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c = np.asarray(c) + np.random.uniform(-0.08, 0.08, 2) * s
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s = s * np.random.uniform(0.87, 1.15)
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rot = rot + np.radians(np.random.uniform(-20, 20))
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p, _ = hm.prepare(g, (c, s, rot))
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path = os.path.join(out, 'hand', '%s_h%d_%d.png' % (base, j, v))
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save(path, p)
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hand_files.append(path)
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for name, files in (('palm', palm_files), ('hand', hand_files)):
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with open(os.path.join(out, name + '.txt'), 'w') as fh:
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fh.write('\n'.join(files) + '\n')
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print(name, len(files), 'crops')
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if __name__ == '__main__':
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main()
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