kyleandClaude Sonnet 5.5
5e48b6fa03
Stock libcamera 0.2.0 (Ubuntu) and ROS Jazzy's 0.7.2 both detect the OV5647 but crash in the Pi IPA when capturing, for every stream format and size. The Raspberry Pi fork, built into /opt/libcamera-rpi, captures 1296x972 frames. capture_still.py takes a still with it, and detect_faces.py runs OpenCV YuNet (Haar fallback) on images. YuNet needs OpenCV 4.8+ and input sides in multiples of 32, so the venv carries opencv-python-headless 4.10 pinned with numpy<2. camera_ros still has to be built against the fork. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01AFN8nRRCiDiMN7ChBpHJhs
44 lines
1.7 KiB
Python
44 lines
1.7 KiB
Python
#!/usr/bin/env python3
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"""Capture one still from the camera with the Raspberry Pi libcamera fork, as a JPEG.
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capture_still.py OUT.jpg [--frames N] [--width W --height H]
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Runs `cam` from /opt/libcamera-rpi for N frames (so auto-exposure settles) and keeps the last.
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Run it with the venv's python so OpenCV is the newer one: ~/venv/bin/python capture_still.py ...
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"""
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import argparse
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import glob
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import os
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import subprocess
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import tempfile
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import cv2
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import numpy as np
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PREFIX = '/opt/libcamera-rpi'
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def main():
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p = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
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p.add_argument('out')
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p.add_argument('--frames', type=int, default=45)
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p.add_argument('--width', type=int, default=1296)
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p.add_argument('--height', type=int, default=972)
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a = p.parse_args()
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env = dict(os.environ, LD_LIBRARY_PATH=f'{PREFIX}/lib/aarch64-linux-gnu')
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with tempfile.TemporaryDirectory() as tmp:
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subprocess.run([f'{PREFIX}/bin/cam', '-c', '1', '--stream',
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f'pixelformat=RGB888,width={a.width},height={a.height}',
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f'--capture={a.frames}', f'--file={tmp}/f-#.bin'],
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env=env, check=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, timeout=90)
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last = sorted(glob.glob(f'{tmp}/f-*.bin'))[-1]
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raw = np.fromfile(last, np.uint8)
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stride = raw.size // a.height # rows are padded
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img = raw.reshape(a.height, stride)[:, :a.width * 3].reshape(a.height, a.width, 3) # B,G,R in memory
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cv2.imwrite(a.out, img)
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print(f'{a.out}: {a.width}x{a.height}, mean brightness {img.mean():.1f}/255')
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if __name__ == '__main__':
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main()
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