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_ImagePercept.py

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"""autogenerated by genmsg_py from ImagePercept.msg. Do not edit."""
import roslib.message
import struct

import sensor_msgs.msg
import worldmodel_msgs.msg
import std_msgs.msg

class ImagePercept(roslib.message.Message):
  _md5sum = "cfe1ba9ccbb3e43950b420f7336a3c6c"
  _type = "worldmodel_msgs/ImagePercept"
  _has_header = True #flag to mark the presence of a Header object
  _full_text = """# worldmodel_msgs/ImagePercept
# This message represents an observation of an object in a single image.

# The header should equal the header of the corresponding image.
Header header

# The camera info which is needed to project from image coordinates to world coordinates
sensor_msgs/CameraInfo camera_info

# Center coordinates of the percept in image coordinates
# x: axis points to the right in the image
# y: axis points downward in the image
float32 x
float32 y

# Normalized size of the percept in image coordinates (or 0.0)
float32 width
float32 height

# Distance estimate (slope distance) (or 0.0)
float32 distance

# Additional information about the percept
worldmodel_msgs/PerceptInfo info

================================================================================
MSG: std_msgs/Header
# Standard metadata for higher-level stamped data types.
# This is generally used to communicate timestamped data 
# in a particular coordinate frame.
# 
# sequence ID: consecutively increasing ID 
uint32 seq
#Two-integer timestamp that is expressed as:
# * stamp.secs: seconds (stamp_secs) since epoch
# * stamp.nsecs: nanoseconds since stamp_secs
# time-handling sugar is provided by the client library
time stamp
#Frame this data is associated with
# 0: no frame
# 1: global frame
string frame_id

================================================================================
MSG: sensor_msgs/CameraInfo
# This message defines meta information for a camera. It should be in a
# camera namespace on topic "camera_info" and accompanied by up to five
# image topics named:
#
#   image_raw - raw data from the camera driver, possibly Bayer encoded
#   image            - monochrome, distorted
#   image_color      - color, distorted
#   image_rect       - monochrome, rectified
#   image_rect_color - color, rectified
#
# The image_pipeline contains packages (image_proc, stereo_image_proc)
# for producing the four processed image topics from image_raw and
# camera_info. The meaning of the camera parameters are described in
# detail at http://www.ros.org/wiki/image_pipeline/CameraInfo.
#
# The image_geometry package provides a user-friendly interface to
# common operations using this meta information. If you want to, e.g.,
# project a 3d point into image coordinates, we strongly recommend
# using image_geometry.
#
# If the camera is uncalibrated, the matrices D, K, R, P should be left
# zeroed out. In particular, clients may assume that K[0] == 0.0
# indicates an uncalibrated camera.

#######################################################################
#                     Image acquisition info                          #
#######################################################################

# Time of image acquisition, camera coordinate frame ID
Header header    # Header timestamp should be acquisition time of image
                 # Header frame_id should be optical frame of camera
                 # origin of frame should be optical center of camera
                 # +x should point to the right in the image
                 # +y should point down in the image
                 # +z should point into the plane of the image


#######################################################################
#                      Calibration Parameters                         #
#######################################################################
# These are fixed during camera calibration. Their values will be the #
# same in all messages until the camera is recalibrated. Note that    #
# self-calibrating systems may "recalibrate" frequently.              #
#                                                                     #
# The internal parameters can be used to warp a raw (distorted) image #
# to:                                                                 #
#   1. An undistorted image (requires D and K)                        #
#   2. A rectified image (requires D, K, R)                           #
# The projection matrix P projects 3D points into the rectified image.#
#######################################################################

# The image dimensions with which the camera was calibrated. Normally
# this will be the full camera resolution in pixels.
uint32 height
uint32 width

# The distortion model used. Supported models are listed in
# sensor_msgs/distortion_models.h. For most cameras, "plumb_bob" - a
# simple model of radial and tangential distortion - is sufficent.
string distortion_model

# The distortion parameters, size depending on the distortion model.
# For "plumb_bob", the 5 parameters are: (k1, k2, t1, t2, k3).
float64[] D

# Intrinsic camera matrix for the raw (distorted) images.
#     [fx  0 cx]
# K = [ 0 fy cy]
#     [ 0  0  1]
# Projects 3D points in the camera coordinate frame to 2D pixel
# coordinates using the focal lengths (fx, fy) and principal point
# (cx, cy).
float64[9]  K # 3x3 row-major matrix

# Rectification matrix (stereo cameras only)
# A rotation matrix aligning the camera coordinate system to the ideal
# stereo image plane so that epipolar lines in both stereo images are
# parallel.
float64[9]  R # 3x3 row-major matrix

# Projection/camera matrix
#     [fx'  0  cx' Tx]
# P = [ 0  fy' cy' Ty]
#     [ 0   0   1   0]
# By convention, this matrix specifies the intrinsic (camera) matrix
#  of the processed (rectified) image. That is, the left 3x3 portion
#  is the normal camera intrinsic matrix for the rectified image.
# It projects 3D points in the camera coordinate frame to 2D pixel
#  coordinates using the focal lengths (fx', fy') and principal point
#  (cx', cy') - these may differ from the values in K.
# For monocular cameras, Tx = Ty = 0. Normally, monocular cameras will
#  also have R = the identity and P[1:3,1:3] = K.
# For a stereo pair, the fourth column [Tx Ty 0]' is related to the
#  position of the optical center of the second camera in the first
#  camera's frame. We assume Tz = 0 so both cameras are in the same
#  stereo image plane. The first camera always has Tx = Ty = 0. For
#  the right (second) camera of a horizontal stereo pair, Ty = 0 and
#  Tx = -fx' * B, where B is the baseline between the cameras.
# Given a 3D point [X Y Z]', the projection (x, y) of the point onto
#  the rectified image is given by:
#  [u v w]' = P * [X Y Z 1]'
#         x = u / w
#         y = v / w
#  This holds for both images of a stereo pair.
float64[12] P # 3x4 row-major matrix


#######################################################################
#                      Operational Parameters                         #
#######################################################################
# These define the image region actually captured by the camera       #
# driver. Although they affect the geometry of the output image, they #
# may be changed freely without recalibrating the camera.             #
#######################################################################

# Binning refers here to any camera setting which combines rectangular
#  neighborhoods of pixels into larger "super-pixels." It reduces the
#  resolution of the output image to
#  (width / binning_x) x (height / binning_y).
# The default values binning_x = binning_y = 0 is considered the same
#  as binning_x = binning_y = 1 (no subsampling).
uint32 binning_x
uint32 binning_y

# Region of interest (subwindow of full camera resolution), given in
#  full resolution (unbinned) image coordinates. A particular ROI
#  always denotes the same window of pixels on the camera sensor,
#  regardless of binning settings.
# The default setting of roi (all values 0) is considered the same as
#  full resolution (roi.width = width, roi.height = height).
RegionOfInterest roi

================================================================================
MSG: sensor_msgs/RegionOfInterest
# This message is used to specify a region of interest within an image.
#
# When used to specify the ROI setting of the camera when the image was
# taken, the height and width fields should either match the height and
# width fields for the associated image; or height = width = 0
# indicates that the full resolution image was captured.

uint32 x_offset  # Leftmost pixel of the ROI
                 # (0 if the ROI includes the left edge of the image)
uint32 y_offset  # Topmost pixel of the ROI
                 # (0 if the ROI includes the top edge of the image)
uint32 height    # Height of ROI
uint32 width     # Width of ROI

# True if a distinct rectified ROI should be calculated from the "raw"
# ROI in this message. Typically this should be False if the full image
# is captured (ROI not used), and True if a subwindow is captured (ROI
# used).
bool do_rectify

================================================================================
MSG: worldmodel_msgs/PerceptInfo
# This message contains information about the estimated class and object identity 

# A string identifying the object's class (all objects of a class look the same)
string class_id

# The class association support of the observation
# The support is the log odd likelihood ratio given by log(p(y/observation y belongs to object of class class_id) / p(y/observation y is a false positive))
float32 class_support

# A string identifying a specific object
string object_id

# The object association support of the observation
# The support is the log odd likelihood ratio given by log(p(observation belongs to object object_id) / p(observation is false positive or belongs to another object))
float32 object_support

# A string that contains the name or a description of the specific object
string name

"""
  __slots__ = ['header','camera_info','x','y','width','height','distance','info']
  _slot_types = ['Header','sensor_msgs/CameraInfo','float32','float32','float32','float32','float32','worldmodel_msgs/PerceptInfo']

  def __init__(self, *args, **kwds):
    """
    Constructor. Any message fields that are implicitly/explicitly
    set to None will be assigned a default value. The recommend
    use is keyword arguments as this is more robust to future message
    changes.  You cannot mix in-order arguments and keyword arguments.
    
    The available fields are:
       header,camera_info,x,y,width,height,distance,info
    
    @param args: complete set of field values, in .msg order
    @param kwds: use keyword arguments corresponding to message field names
    to set specific fields. 
    """
    if args or kwds:
      super(ImagePercept, self).__init__(*args, **kwds)
      #message fields cannot be None, assign default values for those that are
      if self.header is None:
        self.header = std_msgs.msg._Header.Header()
      if self.camera_info is None:
        self.camera_info = sensor_msgs.msg.CameraInfo()
      if self.x is None:
        self.x = 0.
      if self.y is None:
        self.y = 0.
      if self.width is None:
        self.width = 0.
      if self.height is None:
        self.height = 0.
      if self.distance is None:
        self.distance = 0.
      if self.info is None:
        self.info = worldmodel_msgs.msg.PerceptInfo()
    else:
      self.header = std_msgs.msg._Header.Header()
      self.camera_info = sensor_msgs.msg.CameraInfo()
      self.x = 0.
      self.y = 0.
      self.width = 0.
      self.height = 0.
      self.distance = 0.
      self.info = worldmodel_msgs.msg.PerceptInfo()

  def _get_types(self):
    """
    internal API method
    """
    return self._slot_types

  def serialize(self, buff):
    """
    serialize message into buffer
    @param buff: buffer
    @type  buff: StringIO
    """
    try:
      _x = self
      buff.write(_struct_3I.pack(_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs))
      _x = self.header.frame_id
      length = len(_x)
      buff.write(struct.pack('<I%ss'%length, length, _x))
      _x = self
      buff.write(_struct_3I.pack(_x.camera_info.header.seq, _x.camera_info.header.stamp.secs, _x.camera_info.header.stamp.nsecs))
      _x = self.camera_info.header.frame_id
      length = len(_x)
      buff.write(struct.pack('<I%ss'%length, length, _x))
      _x = self
      buff.write(_struct_2I.pack(_x.camera_info.height, _x.camera_info.width))
      _x = self.camera_info.distortion_model
      length = len(_x)
      buff.write(struct.pack('<I%ss'%length, length, _x))
      length = len(self.camera_info.D)
      buff.write(_struct_I.pack(length))
      pattern = '<%sd'%length
      buff.write(struct.pack(pattern, *self.camera_info.D))
      buff.write(_struct_9d.pack(*self.camera_info.K))
      buff.write(_struct_9d.pack(*self.camera_info.R))
      buff.write(_struct_12d.pack(*self.camera_info.P))
      _x = self
      buff.write(_struct_6IB5f.pack(_x.camera_info.binning_x, _x.camera_info.binning_y, _x.camera_info.roi.x_offset, _x.camera_info.roi.y_offset, _x.camera_info.roi.height, _x.camera_info.roi.width, _x.camera_info.roi.do_rectify, _x.x, _x.y, _x.width, _x.height, _x.distance))
      _x = self.info.class_id
      length = len(_x)
      buff.write(struct.pack('<I%ss'%length, length, _x))
      buff.write(_struct_f.pack(self.info.class_support))
      _x = self.info.object_id
      length = len(_x)
      buff.write(struct.pack('<I%ss'%length, length, _x))
      buff.write(_struct_f.pack(self.info.object_support))
      _x = self.info.name
      length = len(_x)
      buff.write(struct.pack('<I%ss'%length, length, _x))
    except struct.error as se: self._check_types(se)
    except TypeError as te: self._check_types(te)

  def deserialize(self, str):
    """
    unpack serialized message in str into this message instance
    @param str: byte array of serialized message
    @type  str: str
    """
    try:
      if self.header is None:
        self.header = std_msgs.msg._Header.Header()
      if self.camera_info is None:
        self.camera_info = sensor_msgs.msg.CameraInfo()
      if self.info is None:
        self.info = worldmodel_msgs.msg.PerceptInfo()
      end = 0
      _x = self
      start = end
      end += 12
      (_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      start = end
      end += length
      self.header.frame_id = str[start:end]
      _x = self
      start = end
      end += 12
      (_x.camera_info.header.seq, _x.camera_info.header.stamp.secs, _x.camera_info.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      start = end
      end += length
      self.camera_info.header.frame_id = str[start:end]
      _x = self
      start = end
      end += 8
      (_x.camera_info.height, _x.camera_info.width,) = _struct_2I.unpack(str[start:end])
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      start = end
      end += length
      self.camera_info.distortion_model = str[start:end]
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      pattern = '<%sd'%length
      start = end
      end += struct.calcsize(pattern)
      self.camera_info.D = struct.unpack(pattern, str[start:end])
      start = end
      end += 72
      self.camera_info.K = _struct_9d.unpack(str[start:end])
      start = end
      end += 72
      self.camera_info.R = _struct_9d.unpack(str[start:end])
      start = end
      end += 96
      self.camera_info.P = _struct_12d.unpack(str[start:end])
      _x = self
      start = end
      end += 45
      (_x.camera_info.binning_x, _x.camera_info.binning_y, _x.camera_info.roi.x_offset, _x.camera_info.roi.y_offset, _x.camera_info.roi.height, _x.camera_info.roi.width, _x.camera_info.roi.do_rectify, _x.x, _x.y, _x.width, _x.height, _x.distance,) = _struct_6IB5f.unpack(str[start:end])
      self.camera_info.roi.do_rectify = bool(self.camera_info.roi.do_rectify)
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      start = end
      end += length
      self.info.class_id = str[start:end]
      start = end
      end += 4
      (self.info.class_support,) = _struct_f.unpack(str[start:end])
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      start = end
      end += length
      self.info.object_id = str[start:end]
      start = end
      end += 4
      (self.info.object_support,) = _struct_f.unpack(str[start:end])
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      start = end
      end += length
      self.info.name = str[start:end]
      return self
    except struct.error as e:
      raise roslib.message.DeserializationError(e) #most likely buffer underfill


  def serialize_numpy(self, buff, numpy):
    """
    serialize message with numpy array types into buffer
    @param buff: buffer
    @type  buff: StringIO
    @param numpy: numpy python module
    @type  numpy module
    """
    try:
      _x = self
      buff.write(_struct_3I.pack(_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs))
      _x = self.header.frame_id
      length = len(_x)
      buff.write(struct.pack('<I%ss'%length, length, _x))
      _x = self
      buff.write(_struct_3I.pack(_x.camera_info.header.seq, _x.camera_info.header.stamp.secs, _x.camera_info.header.stamp.nsecs))
      _x = self.camera_info.header.frame_id
      length = len(_x)
      buff.write(struct.pack('<I%ss'%length, length, _x))
      _x = self
      buff.write(_struct_2I.pack(_x.camera_info.height, _x.camera_info.width))
      _x = self.camera_info.distortion_model
      length = len(_x)
      buff.write(struct.pack('<I%ss'%length, length, _x))
      length = len(self.camera_info.D)
      buff.write(_struct_I.pack(length))
      pattern = '<%sd'%length
      buff.write(self.camera_info.D.tostring())
      buff.write(self.camera_info.K.tostring())
      buff.write(self.camera_info.R.tostring())
      buff.write(self.camera_info.P.tostring())
      _x = self
      buff.write(_struct_6IB5f.pack(_x.camera_info.binning_x, _x.camera_info.binning_y, _x.camera_info.roi.x_offset, _x.camera_info.roi.y_offset, _x.camera_info.roi.height, _x.camera_info.roi.width, _x.camera_info.roi.do_rectify, _x.x, _x.y, _x.width, _x.height, _x.distance))
      _x = self.info.class_id
      length = len(_x)
      buff.write(struct.pack('<I%ss'%length, length, _x))
      buff.write(_struct_f.pack(self.info.class_support))
      _x = self.info.object_id
      length = len(_x)
      buff.write(struct.pack('<I%ss'%length, length, _x))
      buff.write(_struct_f.pack(self.info.object_support))
      _x = self.info.name
      length = len(_x)
      buff.write(struct.pack('<I%ss'%length, length, _x))
    except struct.error as se: self._check_types(se)
    except TypeError as te: self._check_types(te)

  def deserialize_numpy(self, str, numpy):
    """
    unpack serialized message in str into this message instance using numpy for array types
    @param str: byte array of serialized message
    @type  str: str
    @param numpy: numpy python module
    @type  numpy: module
    """
    try:
      if self.header is None:
        self.header = std_msgs.msg._Header.Header()
      if self.camera_info is None:
        self.camera_info = sensor_msgs.msg.CameraInfo()
      if self.info is None:
        self.info = worldmodel_msgs.msg.PerceptInfo()
      end = 0
      _x = self
      start = end
      end += 12
      (_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      start = end
      end += length
      self.header.frame_id = str[start:end]
      _x = self
      start = end
      end += 12
      (_x.camera_info.header.seq, _x.camera_info.header.stamp.secs, _x.camera_info.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      start = end
      end += length
      self.camera_info.header.frame_id = str[start:end]
      _x = self
      start = end
      end += 8
      (_x.camera_info.height, _x.camera_info.width,) = _struct_2I.unpack(str[start:end])
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      start = end
      end += length
      self.camera_info.distortion_model = str[start:end]
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      pattern = '<%sd'%length
      start = end
      end += struct.calcsize(pattern)
      self.camera_info.D = numpy.frombuffer(str[start:end], dtype=numpy.float64, count=length)
      start = end
      end += 72
      self.camera_info.K = numpy.frombuffer(str[start:end], dtype=numpy.float64, count=9)
      start = end
      end += 72
      self.camera_info.R = numpy.frombuffer(str[start:end], dtype=numpy.float64, count=9)
      start = end
      end += 96
      self.camera_info.P = numpy.frombuffer(str[start:end], dtype=numpy.float64, count=12)
      _x = self
      start = end
      end += 45
      (_x.camera_info.binning_x, _x.camera_info.binning_y, _x.camera_info.roi.x_offset, _x.camera_info.roi.y_offset, _x.camera_info.roi.height, _x.camera_info.roi.width, _x.camera_info.roi.do_rectify, _x.x, _x.y, _x.width, _x.height, _x.distance,) = _struct_6IB5f.unpack(str[start:end])
      self.camera_info.roi.do_rectify = bool(self.camera_info.roi.do_rectify)
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      start = end
      end += length
      self.info.class_id = str[start:end]
      start = end
      end += 4
      (self.info.class_support,) = _struct_f.unpack(str[start:end])
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      start = end
      end += length
      self.info.object_id = str[start:end]
      start = end
      end += 4
      (self.info.object_support,) = _struct_f.unpack(str[start:end])
      start = end
      end += 4
      (length,) = _struct_I.unpack(str[start:end])
      start = end
      end += length
      self.info.name = str[start:end]
      return self
    except struct.error as e:
      raise roslib.message.DeserializationError(e) #most likely buffer underfill

_struct_I = roslib.message.struct_I
_struct_12d = struct.Struct("<12d")
_struct_f = struct.Struct("<f")
_struct_9d = struct.Struct("<9d")
_struct_3I = struct.Struct("<3I")
_struct_6IB5f = struct.Struct("<6IB5f")
_struct_2I = struct.Struct("<2I")

---

worldmodel_msgs
Author(s): Johannes Meyer
autogenerated on Tue Mar 5 12:33:16 2013