kyleandClaude Sonnet 5.5
497f026dc9
hermes_vision.calibrate collects 20 varied checkerboard views from the camera topic (rejecting repeats of a pose, which constrain nothing), solves with OpenCV and writes the camera_info YAML camera_ros loads, named with the resolution as it expects. Tested: the solver recovers a known synthetic camera (focal length within 1%), the YAML round-trips, and real board detection works on a rendered board. Not yet run on the real camera: it needs someone holding a board in front of it, with the focus set. docs/checkerboard-9x6.png is a 10x7-square board that can be shown on a screen. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01AFN8nRRCiDiMN7ChBpHJhs
28 lines
846 B
Python
28 lines
846 B
Python
from setuptools import find_packages, setup
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package_name = 'hermes_vision'
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setup(
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name=package_name,
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version='0.1.0',
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packages=find_packages(exclude=['test']),
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data_files=[
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('share/ament_index/resource_index/packages', ['resource/' + package_name]),
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('share/' + package_name, ['package.xml']),
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],
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install_requires=['setuptools'],
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zip_safe=True,
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maintainer='K. Isom',
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maintainer_email='noreply@example.com',
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description='Face detection for the Hermes robot.',
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license='UNLICENSED',
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entry_points={
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'console_scripts': [
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'face_detector = hermes_vision.face_detector_node:main',
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'detect_faces = hermes_vision.detect_cli:main',
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'people = hermes_vision.people:main',
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'calibrate = hermes_vision.calibrate:main',
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],
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},
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)
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