uav.vision_nodes.payload_perception_common#

Attributes#

`apriltag`
`DEFAULT_TAG_FAMILY`
`VTOL_TAG_POSES`
`USAGE`

Classes#

`AprilTagObservation`
`AprilTagDetectorCache`

Functions#

`_iter_detections`(gray, detector, backend)
`camera_model_from_info`(→ tuple[numpy.ndarray, ...)
`back_view_angle_deg`(→ Optional[float])
`compute_edge_metrics`(→ tuple[float, int, int])
`compute_edge_follow_control`(→ tuple[bool, float, float])
`_rpy_to_rot`(→ numpy.ndarray)
`_make_transform`(→ numpy.ndarray)
`_invert_transform`(→ numpy.ndarray)
`_yaw_from_rotation`(→ float)
`_object_points_for_tag_size`(→ numpy.ndarray)
`_estimate_camera_pose_in_vtol`(→ Optional[tuple[float, ...)
`_yaw_error_from_rvec`(→ float)
`_solve_detection_pose`(→ Optional[tuple[int, ...)
`detect_payload_apriltags`(→ list[AprilTagObservation])
`solve_payload_apriltags`(→ list[AprilTagObservation])
`detect_payload_unreeled`(image[, lower_hsv, upper_hsv, ...])
`_make_camera_info`(→ sensor_msgs.msg.CameraInfo)	Synthesise a plausible pinhole CameraInfo from image dimensions.

Module Contents#

apriltag = None#

DEFAULT_TAG_FAMILY = 'tag36h11'#

VTOL_TAG_POSES#

class AprilTagObservation#

tag_id: int#

center_x: float#

center_y: float#

tvec_x: float#

tvec_y: float#

tvec_z: float#

yaw_error: float#

area: float#

pose_x: float | None = None#

pose_y: float | None = None#

pose_yaw: float | None = None#

class AprilTagDetectorCache#

_family: str | None = None#

_detector = None#

_backend: str | None = None#

get(family: str | None)#

property backend: str | None#

_iter_detections(gray: numpy.ndarray, detector, backend: str | None)#

camera_model_from_info(camera_info: sensor_msgs.msg.CameraInfo) → tuple[numpy.ndarray, numpy.ndarray]#

back_view_angle_deg(tvec_x: float, tvec_y: float, tvec_z: float) → float | None#

compute_edge_metrics(bgr: numpy.ndarray, lower_pink: numpy.ndarray, upper_pink: numpy.ndarray, lower_green: numpy.ndarray, upper_green: numpy.ndarray) → tuple[float, int, int]#

compute_edge_follow_control(bgr: numpy.ndarray, lower_pink: numpy.ndarray, upper_pink: numpy.ndarray, lower_green: numpy.ndarray, upper_green: numpy.ndarray, orbit_dir: int = 1) → tuple[bool, float, float]#

_rpy_to_rot(roll: float, pitch: float, yaw: float) → numpy.ndarray#

_make_transform(rotation: numpy.ndarray, translation: numpy.ndarray) → numpy.ndarray#

_invert_transform(transform: numpy.ndarray) → numpy.ndarray#

_yaw_from_rotation(rotation_v_c: numpy.ndarray) → float#

_object_points_for_tag_size(tag_size_m: float) → numpy.ndarray#

_estimate_camera_pose_in_vtol(tag_id: int, rvec: numpy.ndarray, tvec: numpy.ndarray) → tuple[float, float, float] | None#

_yaw_error_from_rvec(rvec: numpy.ndarray) → float#

_solve_detection_pose(detection, object_points: numpy.ndarray, camera_matrix: numpy.ndarray, dist_coeffs: numpy.ndarray, *, flags: int | None = None, min_forward_distance_m: float | None = None) → tuple[int, numpy.ndarray, numpy.ndarray, float, float, float, float, float] | None#

detect_payload_apriltags(gray: numpy.ndarray, camera_info: sensor_msgs.msg.CameraInfo, detector, detector_backend: str | None, tag_size_m: float) → list[AprilTagObservation]#

solve_payload_apriltags(gray: numpy.ndarray, camera_info: sensor_msgs.msg.CameraInfo, detector, detector_backend: str | None, tag_size_m: float) → list[AprilTagObservation]#

detect_payload_unreeled(image, lower_hsv: tuple[int, int, int] = (0, 0, 180), upper_hsv: tuple[int, int, int] = (180, 20, 255), debug: bool = False)#

_make_camera_info(image: numpy.ndarray) → sensor_msgs.msg.CameraInfo#: Synthesise a plausible pinhole CameraInfo from image dimensions.

USAGE = Multiline-String#

Show Value

"""
Usage:
  python payload_perception_common.py unreeled <image>
  python payload_perception_common.py apriltag  <image> [tag_size_m] [tag_family]

Examples:
  python payload_perception_common.py unreeled frame.jpg
  python payload_perception_common.py apriltag frame.jpg 0.1 tag36h11
"""