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tracker_config.yaml
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debug: true
undistort: true
# Pickle file that contains fields
fields_path: "./saved_fields.pickle"
# video_source: 0
# video_source: 'ROBO_7.mp4'
video_source: 'http://192.168.0.100/mjpg/video.mjpg'
object_timeout: 30
pos_limit_x: [-50, 3600]
pos_limit_y: [-50, 2100]
map_virtual_corners: [
[0, 0],
[3600, 0],
[3600, 2100],
[0, 2100]
]
# Kalman filter
kalman_filter:
# Sampling rate
dt: 1
# Acceleration magnitude
u: 0.0
acc_noise_mag: 0.003
measurement_noise_x: 0.6
measurement_noise_y: 0.6
# AruCo detector
aruco_detector:
# Minimum window for binarization
# Too small a window makes whole tags the same color
adaptive_thresh_win_size_min: 10
# Maximum window for binarization
# Too large a window rounds the corners of the bits on the tag
adaptive_thresh_win_size_max: 23
# Bottom for thresholding
# Too low a bottom causes too many candidates, too high distorts tags (probably also dependent on contrast)
adaptive_thresh_constant: 7
# Minimum size of candidates for tags
# Too low checks too many candidates and affects performance
min_marker_perimeter_rate: 0.04
# Maximum size of candidates for tags
# Slightly affects performance, but there are usually not too many large candidates
max_marker_perimeter_rate: 0.1
# Algorithm crops tag and upsamples it to x pixels per cell
# Affects performance
perspective_remove_pixel_per_cell: 30
# Algorithm crops each cell and looks only at the center
# Larger factor crops more
perspective_remove_ignored_margin_per_cell: 0.30
# Limit how close two tags can be
# Because ours can be very close, we have to set this low, which can mean that
# the same tag is detected twice, which we can filter out later
min_marker_distance_rate: 0.001
# Camera
camera:
# Camera parameters for removing distortion
# These are the parameters for the camera used in the lab
k1: -0.4077
k2: 0.2827
k3: -0.1436
p1: 6.6668e-4
p2: -0.0025
fx: 1443
fy: 1.509243126646947e+03
cx: 9.678725207348843e+02
cy: 5.356599023732050e+02
# Scaling factors
scale0: 0.954
scale1: 0.00001