00001 """autogenerated by genmsg_py from ObjectSegmentationGuiActionGoal.msg. Do not edit."""
00002 import roslib.message
00003 import struct
00004
00005 import roslib.rostime
00006 import actionlib_msgs.msg
00007 import stereo_msgs.msg
00008 import sensor_msgs.msg
00009 import object_segmentation_gui.msg
00010 import std_msgs.msg
00011
00012 class ObjectSegmentationGuiActionGoal(roslib.message.Message):
00013 _md5sum = "c90d057a2cbad468bbf26bcf158e312e"
00014 _type = "object_segmentation_gui/ObjectSegmentationGuiActionGoal"
00015 _has_header = True
00016 _full_text = """# ====== DO NOT MODIFY! AUTOGENERATED FROM AN ACTION DEFINITION ======
00017
00018 Header header
00019 actionlib_msgs/GoalID goal_id
00020 ObjectSegmentationGuiGoal goal
00021
00022 ================================================================================
00023 MSG: std_msgs/Header
00024 # Standard metadata for higher-level stamped data types.
00025 # This is generally used to communicate timestamped data
00026 # in a particular coordinate frame.
00027 #
00028 # sequence ID: consecutively increasing ID
00029 uint32 seq
00030 #Two-integer timestamp that is expressed as:
00031 # * stamp.secs: seconds (stamp_secs) since epoch
00032 # * stamp.nsecs: nanoseconds since stamp_secs
00033 # time-handling sugar is provided by the client library
00034 time stamp
00035 #Frame this data is associated with
00036 # 0: no frame
00037 # 1: global frame
00038 string frame_id
00039
00040 ================================================================================
00041 MSG: actionlib_msgs/GoalID
00042 # The stamp should store the time at which this goal was requested.
00043 # It is used by an action server when it tries to preempt all
00044 # goals that were requested before a certain time
00045 time stamp
00046
00047 # The id provides a way to associate feedback and
00048 # result message with specific goal requests. The id
00049 # specified must be unique.
00050 string id
00051
00052
00053 ================================================================================
00054 MSG: object_segmentation_gui/ObjectSegmentationGuiGoal
00055 # ====== DO NOT MODIFY! AUTOGENERATED FROM AN ACTION DEFINITION ======
00056 sensor_msgs/Image image
00057 sensor_msgs/CameraInfo camera_info
00058 sensor_msgs/Image wide_field
00059 sensor_msgs/CameraInfo wide_camera_info
00060
00061 sensor_msgs/PointCloud2 point_cloud
00062 stereo_msgs/DisparityImage disparity_image
00063
00064
00065 ================================================================================
00066 MSG: sensor_msgs/Image
00067 # This message contains an uncompressed image
00068 # (0, 0) is at top-left corner of image
00069 #
00070
00071 Header header # Header timestamp should be acquisition time of image
00072 # Header frame_id should be optical frame of camera
00073 # origin of frame should be optical center of cameara
00074 # +x should point to the right in the image
00075 # +y should point down in the image
00076 # +z should point into to plane of the image
00077 # If the frame_id here and the frame_id of the CameraInfo
00078 # message associated with the image conflict
00079 # the behavior is undefined
00080
00081 uint32 height # image height, that is, number of rows
00082 uint32 width # image width, that is, number of columns
00083
00084 # The legal values for encoding are in file src/image_encodings.cpp
00085 # If you want to standardize a new string format, join
00086 # ros-users@lists.sourceforge.net and send an email proposing a new encoding.
00087
00088 string encoding # Encoding of pixels -- channel meaning, ordering, size
00089 # taken from the list of strings in src/image_encodings.cpp
00090
00091 uint8 is_bigendian # is this data bigendian?
00092 uint32 step # Full row length in bytes
00093 uint8[] data # actual matrix data, size is (step * rows)
00094
00095 ================================================================================
00096 MSG: sensor_msgs/CameraInfo
00097 # This message defines meta information for a camera. It should be in a
00098 # camera namespace on topic "camera_info" and accompanied by up to five
00099 # image topics named:
00100 #
00101 # image_raw - raw data from the camera driver, possibly Bayer encoded
00102 # image - monochrome, distorted
00103 # image_color - color, distorted
00104 # image_rect - monochrome, rectified
00105 # image_rect_color - color, rectified
00106 #
00107 # The image_pipeline contains packages (image_proc, stereo_image_proc)
00108 # for producing the four processed image topics from image_raw and
00109 # camera_info. The meaning of the camera parameters are described in
00110 # detail at http://www.ros.org/wiki/image_pipeline/CameraInfo.
00111 #
00112 # The image_geometry package provides a user-friendly interface to
00113 # common operations using this meta information. If you want to, e.g.,
00114 # project a 3d point into image coordinates, we strongly recommend
00115 # using image_geometry.
00116 #
00117 # If the camera is uncalibrated, the matrices D, K, R, P should be left
00118 # zeroed out. In particular, clients may assume that K[0] == 0.0
00119 # indicates an uncalibrated camera.
00120
00121 #######################################################################
00122 # Image acquisition info #
00123 #######################################################################
00124
00125 # Time of image acquisition, camera coordinate frame ID
00126 Header header # Header timestamp should be acquisition time of image
00127 # Header frame_id should be optical frame of camera
00128 # origin of frame should be optical center of camera
00129 # +x should point to the right in the image
00130 # +y should point down in the image
00131 # +z should point into the plane of the image
00132
00133
00134 #######################################################################
00135 # Calibration Parameters #
00136 #######################################################################
00137 # These are fixed during camera calibration. Their values will be the #
00138 # same in all messages until the camera is recalibrated. Note that #
00139 # self-calibrating systems may "recalibrate" frequently. #
00140 # #
00141 # The internal parameters can be used to warp a raw (distorted) image #
00142 # to: #
00143 # 1. An undistorted image (requires D and K) #
00144 # 2. A rectified image (requires D, K, R) #
00145 # The projection matrix P projects 3D points into the rectified image.#
00146 #######################################################################
00147
00148 # The image dimensions with which the camera was calibrated. Normally
00149 # this will be the full camera resolution in pixels.
00150 uint32 height
00151 uint32 width
00152
00153 # The distortion model used. Supported models are listed in
00154 # sensor_msgs/distortion_models.h. For most cameras, "plumb_bob" - a
00155 # simple model of radial and tangential distortion - is sufficent.
00156 string distortion_model
00157
00158 # The distortion parameters, size depending on the distortion model.
00159 # For "plumb_bob", the 5 parameters are: (k1, k2, t1, t2, k3).
00160 float64[] D
00161
00162 # Intrinsic camera matrix for the raw (distorted) images.
00163 # [fx 0 cx]
00164 # K = [ 0 fy cy]
00165 # [ 0 0 1]
00166 # Projects 3D points in the camera coordinate frame to 2D pixel
00167 # coordinates using the focal lengths (fx, fy) and principal point
00168 # (cx, cy).
00169 float64[9] K # 3x3 row-major matrix
00170
00171 # Rectification matrix (stereo cameras only)
00172 # A rotation matrix aligning the camera coordinate system to the ideal
00173 # stereo image plane so that epipolar lines in both stereo images are
00174 # parallel.
00175 float64[9] R # 3x3 row-major matrix
00176
00177 # Projection/camera matrix
00178 # [fx' 0 cx' Tx]
00179 # P = [ 0 fy' cy' Ty]
00180 # [ 0 0 1 0]
00181 # By convention, this matrix specifies the intrinsic (camera) matrix
00182 # of the processed (rectified) image. That is, the left 3x3 portion
00183 # is the normal camera intrinsic matrix for the rectified image.
00184 # It projects 3D points in the camera coordinate frame to 2D pixel
00185 # coordinates using the focal lengths (fx', fy') and principal point
00186 # (cx', cy') - these may differ from the values in K.
00187 # For monocular cameras, Tx = Ty = 0. Normally, monocular cameras will
00188 # also have R = the identity and P[1:3,1:3] = K.
00189 # For a stereo pair, the fourth column [Tx Ty 0]' is related to the
00190 # position of the optical center of the second camera in the first
00191 # camera's frame. We assume Tz = 0 so both cameras are in the same
00192 # stereo image plane. The first camera always has Tx = Ty = 0. For
00193 # the right (second) camera of a horizontal stereo pair, Ty = 0 and
00194 # Tx = -fx' * B, where B is the baseline between the cameras.
00195 # Given a 3D point [X Y Z]', the projection (x, y) of the point onto
00196 # the rectified image is given by:
00197 # [u v w]' = P * [X Y Z 1]'
00198 # x = u / w
00199 # y = v / w
00200 # This holds for both images of a stereo pair.
00201 float64[12] P # 3x4 row-major matrix
00202
00203
00204 #######################################################################
00205 # Operational Parameters #
00206 #######################################################################
00207 # These define the image region actually captured by the camera #
00208 # driver. Although they affect the geometry of the output image, they #
00209 # may be changed freely without recalibrating the camera. #
00210 #######################################################################
00211
00212 # Binning refers here to any camera setting which combines rectangular
00213 # neighborhoods of pixels into larger "super-pixels." It reduces the
00214 # resolution of the output image to
00215 # (width / binning_x) x (height / binning_y).
00216 # The default values binning_x = binning_y = 0 is considered the same
00217 # as binning_x = binning_y = 1 (no subsampling).
00218 uint32 binning_x
00219 uint32 binning_y
00220
00221 # Region of interest (subwindow of full camera resolution), given in
00222 # full resolution (unbinned) image coordinates. A particular ROI
00223 # always denotes the same window of pixels on the camera sensor,
00224 # regardless of binning settings.
00225 # The default setting of roi (all values 0) is considered the same as
00226 # full resolution (roi.width = width, roi.height = height).
00227 RegionOfInterest roi
00228
00229 ================================================================================
00230 MSG: sensor_msgs/RegionOfInterest
00231 # This message is used to specify a region of interest within an image.
00232 #
00233 # When used to specify the ROI setting of the camera when the image was
00234 # taken, the height and width fields should either match the height and
00235 # width fields for the associated image; or height = width = 0
00236 # indicates that the full resolution image was captured.
00237
00238 uint32 x_offset # Leftmost pixel of the ROI
00239 # (0 if the ROI includes the left edge of the image)
00240 uint32 y_offset # Topmost pixel of the ROI
00241 # (0 if the ROI includes the top edge of the image)
00242 uint32 height # Height of ROI
00243 uint32 width # Width of ROI
00244
00245 # True if a distinct rectified ROI should be calculated from the "raw"
00246 # ROI in this message. Typically this should be False if the full image
00247 # is captured (ROI not used), and True if a subwindow is captured (ROI
00248 # used).
00249 bool do_rectify
00250
00251 ================================================================================
00252 MSG: sensor_msgs/PointCloud2
00253 # This message holds a collection of N-dimensional points, which may
00254 # contain additional information such as normals, intensity, etc. The
00255 # point data is stored as a binary blob, its layout described by the
00256 # contents of the "fields" array.
00257
00258 # The point cloud data may be organized 2d (image-like) or 1d
00259 # (unordered). Point clouds organized as 2d images may be produced by
00260 # camera depth sensors such as stereo or time-of-flight.
00261
00262 # Time of sensor data acquisition, and the coordinate frame ID (for 3d
00263 # points).
00264 Header header
00265
00266 # 2D structure of the point cloud. If the cloud is unordered, height is
00267 # 1 and width is the length of the point cloud.
00268 uint32 height
00269 uint32 width
00270
00271 # Describes the channels and their layout in the binary data blob.
00272 PointField[] fields
00273
00274 bool is_bigendian # Is this data bigendian?
00275 uint32 point_step # Length of a point in bytes
00276 uint32 row_step # Length of a row in bytes
00277 uint8[] data # Actual point data, size is (row_step*height)
00278
00279 bool is_dense # True if there are no invalid points
00280
00281 ================================================================================
00282 MSG: sensor_msgs/PointField
00283 # This message holds the description of one point entry in the
00284 # PointCloud2 message format.
00285 uint8 INT8 = 1
00286 uint8 UINT8 = 2
00287 uint8 INT16 = 3
00288 uint8 UINT16 = 4
00289 uint8 INT32 = 5
00290 uint8 UINT32 = 6
00291 uint8 FLOAT32 = 7
00292 uint8 FLOAT64 = 8
00293
00294 string name # Name of field
00295 uint32 offset # Offset from start of point struct
00296 uint8 datatype # Datatype enumeration, see above
00297 uint32 count # How many elements in the field
00298
00299 ================================================================================
00300 MSG: stereo_msgs/DisparityImage
00301 # Separate header for compatibility with current TimeSynchronizer.
00302 # Likely to be removed in a later release, use image.header instead.
00303 Header header
00304
00305 # Floating point disparity image. The disparities are pre-adjusted for any
00306 # x-offset between the principal points of the two cameras (in the case
00307 # that they are verged). That is: d = x_l - x_r - (cx_l - cx_r)
00308 sensor_msgs/Image image
00309
00310 # Stereo geometry. For disparity d, the depth from the camera is Z = fT/d.
00311 float32 f # Focal length, pixels
00312 float32 T # Baseline, world units
00313
00314 # Subwindow of (potentially) valid disparity values.
00315 sensor_msgs/RegionOfInterest valid_window
00316
00317 # The range of disparities searched.
00318 # In the disparity image, any disparity less than min_disparity is invalid.
00319 # The disparity search range defines the horopter, or 3D volume that the
00320 # stereo algorithm can "see". Points with Z outside of:
00321 # Z_min = fT / max_disparity
00322 # Z_max = fT / min_disparity
00323 # could not be found.
00324 float32 min_disparity
00325 float32 max_disparity
00326
00327 # Smallest allowed disparity increment. The smallest achievable depth range
00328 # resolution is delta_Z = (Z^2/fT)*delta_d.
00329 float32 delta_d
00330
00331 """
00332 __slots__ = ['header','goal_id','goal']
00333 _slot_types = ['Header','actionlib_msgs/GoalID','object_segmentation_gui/ObjectSegmentationGuiGoal']
00334
00335 def __init__(self, *args, **kwds):
00336 """
00337 Constructor. Any message fields that are implicitly/explicitly
00338 set to None will be assigned a default value. The recommend
00339 use is keyword arguments as this is more robust to future message
00340 changes. You cannot mix in-order arguments and keyword arguments.
00341
00342 The available fields are:
00343 header,goal_id,goal
00344
00345 @param args: complete set of field values, in .msg order
00346 @param kwds: use keyword arguments corresponding to message field names
00347 to set specific fields.
00348 """
00349 if args or kwds:
00350 super(ObjectSegmentationGuiActionGoal, self).__init__(*args, **kwds)
00351
00352 if self.header is None:
00353 self.header = std_msgs.msg._Header.Header()
00354 if self.goal_id is None:
00355 self.goal_id = actionlib_msgs.msg.GoalID()
00356 if self.goal is None:
00357 self.goal = object_segmentation_gui.msg.ObjectSegmentationGuiGoal()
00358 else:
00359 self.header = std_msgs.msg._Header.Header()
00360 self.goal_id = actionlib_msgs.msg.GoalID()
00361 self.goal = object_segmentation_gui.msg.ObjectSegmentationGuiGoal()
00362
00363 def _get_types(self):
00364 """
00365 internal API method
00366 """
00367 return self._slot_types
00368
00369 def serialize(self, buff):
00370 """
00371 serialize message into buffer
00372 @param buff: buffer
00373 @type buff: StringIO
00374 """
00375 try:
00376 _x = self
00377 buff.write(_struct_3I.pack(_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs))
00378 _x = self.header.frame_id
00379 length = len(_x)
00380 buff.write(struct.pack('<I%ss'%length, length, _x))
00381 _x = self
00382 buff.write(_struct_2I.pack(_x.goal_id.stamp.secs, _x.goal_id.stamp.nsecs))
00383 _x = self.goal_id.id
00384 length = len(_x)
00385 buff.write(struct.pack('<I%ss'%length, length, _x))
00386 _x = self
00387 buff.write(_struct_3I.pack(_x.goal.image.header.seq, _x.goal.image.header.stamp.secs, _x.goal.image.header.stamp.nsecs))
00388 _x = self.goal.image.header.frame_id
00389 length = len(_x)
00390 buff.write(struct.pack('<I%ss'%length, length, _x))
00391 _x = self
00392 buff.write(_struct_2I.pack(_x.goal.image.height, _x.goal.image.width))
00393 _x = self.goal.image.encoding
00394 length = len(_x)
00395 buff.write(struct.pack('<I%ss'%length, length, _x))
00396 _x = self
00397 buff.write(_struct_BI.pack(_x.goal.image.is_bigendian, _x.goal.image.step))
00398 _x = self.goal.image.data
00399 length = len(_x)
00400
00401 if type(_x) in [list, tuple]:
00402 buff.write(struct.pack('<I%sB'%length, length, *_x))
00403 else:
00404 buff.write(struct.pack('<I%ss'%length, length, _x))
00405 _x = self
00406 buff.write(_struct_3I.pack(_x.goal.camera_info.header.seq, _x.goal.camera_info.header.stamp.secs, _x.goal.camera_info.header.stamp.nsecs))
00407 _x = self.goal.camera_info.header.frame_id
00408 length = len(_x)
00409 buff.write(struct.pack('<I%ss'%length, length, _x))
00410 _x = self
00411 buff.write(_struct_2I.pack(_x.goal.camera_info.height, _x.goal.camera_info.width))
00412 _x = self.goal.camera_info.distortion_model
00413 length = len(_x)
00414 buff.write(struct.pack('<I%ss'%length, length, _x))
00415 length = len(self.goal.camera_info.D)
00416 buff.write(_struct_I.pack(length))
00417 pattern = '<%sd'%length
00418 buff.write(struct.pack(pattern, *self.goal.camera_info.D))
00419 buff.write(_struct_9d.pack(*self.goal.camera_info.K))
00420 buff.write(_struct_9d.pack(*self.goal.camera_info.R))
00421 buff.write(_struct_12d.pack(*self.goal.camera_info.P))
00422 _x = self
00423 buff.write(_struct_6IB3I.pack(_x.goal.camera_info.binning_x, _x.goal.camera_info.binning_y, _x.goal.camera_info.roi.x_offset, _x.goal.camera_info.roi.y_offset, _x.goal.camera_info.roi.height, _x.goal.camera_info.roi.width, _x.goal.camera_info.roi.do_rectify, _x.goal.wide_field.header.seq, _x.goal.wide_field.header.stamp.secs, _x.goal.wide_field.header.stamp.nsecs))
00424 _x = self.goal.wide_field.header.frame_id
00425 length = len(_x)
00426 buff.write(struct.pack('<I%ss'%length, length, _x))
00427 _x = self
00428 buff.write(_struct_2I.pack(_x.goal.wide_field.height, _x.goal.wide_field.width))
00429 _x = self.goal.wide_field.encoding
00430 length = len(_x)
00431 buff.write(struct.pack('<I%ss'%length, length, _x))
00432 _x = self
00433 buff.write(_struct_BI.pack(_x.goal.wide_field.is_bigendian, _x.goal.wide_field.step))
00434 _x = self.goal.wide_field.data
00435 length = len(_x)
00436
00437 if type(_x) in [list, tuple]:
00438 buff.write(struct.pack('<I%sB'%length, length, *_x))
00439 else:
00440 buff.write(struct.pack('<I%ss'%length, length, _x))
00441 _x = self
00442 buff.write(_struct_3I.pack(_x.goal.wide_camera_info.header.seq, _x.goal.wide_camera_info.header.stamp.secs, _x.goal.wide_camera_info.header.stamp.nsecs))
00443 _x = self.goal.wide_camera_info.header.frame_id
00444 length = len(_x)
00445 buff.write(struct.pack('<I%ss'%length, length, _x))
00446 _x = self
00447 buff.write(_struct_2I.pack(_x.goal.wide_camera_info.height, _x.goal.wide_camera_info.width))
00448 _x = self.goal.wide_camera_info.distortion_model
00449 length = len(_x)
00450 buff.write(struct.pack('<I%ss'%length, length, _x))
00451 length = len(self.goal.wide_camera_info.D)
00452 buff.write(_struct_I.pack(length))
00453 pattern = '<%sd'%length
00454 buff.write(struct.pack(pattern, *self.goal.wide_camera_info.D))
00455 buff.write(_struct_9d.pack(*self.goal.wide_camera_info.K))
00456 buff.write(_struct_9d.pack(*self.goal.wide_camera_info.R))
00457 buff.write(_struct_12d.pack(*self.goal.wide_camera_info.P))
00458 _x = self
00459 buff.write(_struct_6IB3I.pack(_x.goal.wide_camera_info.binning_x, _x.goal.wide_camera_info.binning_y, _x.goal.wide_camera_info.roi.x_offset, _x.goal.wide_camera_info.roi.y_offset, _x.goal.wide_camera_info.roi.height, _x.goal.wide_camera_info.roi.width, _x.goal.wide_camera_info.roi.do_rectify, _x.goal.point_cloud.header.seq, _x.goal.point_cloud.header.stamp.secs, _x.goal.point_cloud.header.stamp.nsecs))
00460 _x = self.goal.point_cloud.header.frame_id
00461 length = len(_x)
00462 buff.write(struct.pack('<I%ss'%length, length, _x))
00463 _x = self
00464 buff.write(_struct_2I.pack(_x.goal.point_cloud.height, _x.goal.point_cloud.width))
00465 length = len(self.goal.point_cloud.fields)
00466 buff.write(_struct_I.pack(length))
00467 for val1 in self.goal.point_cloud.fields:
00468 _x = val1.name
00469 length = len(_x)
00470 buff.write(struct.pack('<I%ss'%length, length, _x))
00471 _x = val1
00472 buff.write(_struct_IBI.pack(_x.offset, _x.datatype, _x.count))
00473 _x = self
00474 buff.write(_struct_B2I.pack(_x.goal.point_cloud.is_bigendian, _x.goal.point_cloud.point_step, _x.goal.point_cloud.row_step))
00475 _x = self.goal.point_cloud.data
00476 length = len(_x)
00477
00478 if type(_x) in [list, tuple]:
00479 buff.write(struct.pack('<I%sB'%length, length, *_x))
00480 else:
00481 buff.write(struct.pack('<I%ss'%length, length, _x))
00482 _x = self
00483 buff.write(_struct_B3I.pack(_x.goal.point_cloud.is_dense, _x.goal.disparity_image.header.seq, _x.goal.disparity_image.header.stamp.secs, _x.goal.disparity_image.header.stamp.nsecs))
00484 _x = self.goal.disparity_image.header.frame_id
00485 length = len(_x)
00486 buff.write(struct.pack('<I%ss'%length, length, _x))
00487 _x = self
00488 buff.write(_struct_3I.pack(_x.goal.disparity_image.image.header.seq, _x.goal.disparity_image.image.header.stamp.secs, _x.goal.disparity_image.image.header.stamp.nsecs))
00489 _x = self.goal.disparity_image.image.header.frame_id
00490 length = len(_x)
00491 buff.write(struct.pack('<I%ss'%length, length, _x))
00492 _x = self
00493 buff.write(_struct_2I.pack(_x.goal.disparity_image.image.height, _x.goal.disparity_image.image.width))
00494 _x = self.goal.disparity_image.image.encoding
00495 length = len(_x)
00496 buff.write(struct.pack('<I%ss'%length, length, _x))
00497 _x = self
00498 buff.write(_struct_BI.pack(_x.goal.disparity_image.image.is_bigendian, _x.goal.disparity_image.image.step))
00499 _x = self.goal.disparity_image.image.data
00500 length = len(_x)
00501
00502 if type(_x) in [list, tuple]:
00503 buff.write(struct.pack('<I%sB'%length, length, *_x))
00504 else:
00505 buff.write(struct.pack('<I%ss'%length, length, _x))
00506 _x = self
00507 buff.write(_struct_2f4IB3f.pack(_x.goal.disparity_image.f, _x.goal.disparity_image.T, _x.goal.disparity_image.valid_window.x_offset, _x.goal.disparity_image.valid_window.y_offset, _x.goal.disparity_image.valid_window.height, _x.goal.disparity_image.valid_window.width, _x.goal.disparity_image.valid_window.do_rectify, _x.goal.disparity_image.min_disparity, _x.goal.disparity_image.max_disparity, _x.goal.disparity_image.delta_d))
00508 except struct.error as se: self._check_types(se)
00509 except TypeError as te: self._check_types(te)
00510
00511 def deserialize(self, str):
00512 """
00513 unpack serialized message in str into this message instance
00514 @param str: byte array of serialized message
00515 @type str: str
00516 """
00517 try:
00518 if self.header is None:
00519 self.header = std_msgs.msg._Header.Header()
00520 if self.goal_id is None:
00521 self.goal_id = actionlib_msgs.msg.GoalID()
00522 if self.goal is None:
00523 self.goal = object_segmentation_gui.msg.ObjectSegmentationGuiGoal()
00524 end = 0
00525 _x = self
00526 start = end
00527 end += 12
00528 (_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
00529 start = end
00530 end += 4
00531 (length,) = _struct_I.unpack(str[start:end])
00532 start = end
00533 end += length
00534 self.header.frame_id = str[start:end]
00535 _x = self
00536 start = end
00537 end += 8
00538 (_x.goal_id.stamp.secs, _x.goal_id.stamp.nsecs,) = _struct_2I.unpack(str[start:end])
00539 start = end
00540 end += 4
00541 (length,) = _struct_I.unpack(str[start:end])
00542 start = end
00543 end += length
00544 self.goal_id.id = str[start:end]
00545 _x = self
00546 start = end
00547 end += 12
00548 (_x.goal.image.header.seq, _x.goal.image.header.stamp.secs, _x.goal.image.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
00549 start = end
00550 end += 4
00551 (length,) = _struct_I.unpack(str[start:end])
00552 start = end
00553 end += length
00554 self.goal.image.header.frame_id = str[start:end]
00555 _x = self
00556 start = end
00557 end += 8
00558 (_x.goal.image.height, _x.goal.image.width,) = _struct_2I.unpack(str[start:end])
00559 start = end
00560 end += 4
00561 (length,) = _struct_I.unpack(str[start:end])
00562 start = end
00563 end += length
00564 self.goal.image.encoding = str[start:end]
00565 _x = self
00566 start = end
00567 end += 5
00568 (_x.goal.image.is_bigendian, _x.goal.image.step,) = _struct_BI.unpack(str[start:end])
00569 start = end
00570 end += 4
00571 (length,) = _struct_I.unpack(str[start:end])
00572 start = end
00573 end += length
00574 self.goal.image.data = str[start:end]
00575 _x = self
00576 start = end
00577 end += 12
00578 (_x.goal.camera_info.header.seq, _x.goal.camera_info.header.stamp.secs, _x.goal.camera_info.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
00579 start = end
00580 end += 4
00581 (length,) = _struct_I.unpack(str[start:end])
00582 start = end
00583 end += length
00584 self.goal.camera_info.header.frame_id = str[start:end]
00585 _x = self
00586 start = end
00587 end += 8
00588 (_x.goal.camera_info.height, _x.goal.camera_info.width,) = _struct_2I.unpack(str[start:end])
00589 start = end
00590 end += 4
00591 (length,) = _struct_I.unpack(str[start:end])
00592 start = end
00593 end += length
00594 self.goal.camera_info.distortion_model = str[start:end]
00595 start = end
00596 end += 4
00597 (length,) = _struct_I.unpack(str[start:end])
00598 pattern = '<%sd'%length
00599 start = end
00600 end += struct.calcsize(pattern)
00601 self.goal.camera_info.D = struct.unpack(pattern, str[start:end])
00602 start = end
00603 end += 72
00604 self.goal.camera_info.K = _struct_9d.unpack(str[start:end])
00605 start = end
00606 end += 72
00607 self.goal.camera_info.R = _struct_9d.unpack(str[start:end])
00608 start = end
00609 end += 96
00610 self.goal.camera_info.P = _struct_12d.unpack(str[start:end])
00611 _x = self
00612 start = end
00613 end += 37
00614 (_x.goal.camera_info.binning_x, _x.goal.camera_info.binning_y, _x.goal.camera_info.roi.x_offset, _x.goal.camera_info.roi.y_offset, _x.goal.camera_info.roi.height, _x.goal.camera_info.roi.width, _x.goal.camera_info.roi.do_rectify, _x.goal.wide_field.header.seq, _x.goal.wide_field.header.stamp.secs, _x.goal.wide_field.header.stamp.nsecs,) = _struct_6IB3I.unpack(str[start:end])
00615 self.goal.camera_info.roi.do_rectify = bool(self.goal.camera_info.roi.do_rectify)
00616 start = end
00617 end += 4
00618 (length,) = _struct_I.unpack(str[start:end])
00619 start = end
00620 end += length
00621 self.goal.wide_field.header.frame_id = str[start:end]
00622 _x = self
00623 start = end
00624 end += 8
00625 (_x.goal.wide_field.height, _x.goal.wide_field.width,) = _struct_2I.unpack(str[start:end])
00626 start = end
00627 end += 4
00628 (length,) = _struct_I.unpack(str[start:end])
00629 start = end
00630 end += length
00631 self.goal.wide_field.encoding = str[start:end]
00632 _x = self
00633 start = end
00634 end += 5
00635 (_x.goal.wide_field.is_bigendian, _x.goal.wide_field.step,) = _struct_BI.unpack(str[start:end])
00636 start = end
00637 end += 4
00638 (length,) = _struct_I.unpack(str[start:end])
00639 start = end
00640 end += length
00641 self.goal.wide_field.data = str[start:end]
00642 _x = self
00643 start = end
00644 end += 12
00645 (_x.goal.wide_camera_info.header.seq, _x.goal.wide_camera_info.header.stamp.secs, _x.goal.wide_camera_info.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
00646 start = end
00647 end += 4
00648 (length,) = _struct_I.unpack(str[start:end])
00649 start = end
00650 end += length
00651 self.goal.wide_camera_info.header.frame_id = str[start:end]
00652 _x = self
00653 start = end
00654 end += 8
00655 (_x.goal.wide_camera_info.height, _x.goal.wide_camera_info.width,) = _struct_2I.unpack(str[start:end])
00656 start = end
00657 end += 4
00658 (length,) = _struct_I.unpack(str[start:end])
00659 start = end
00660 end += length
00661 self.goal.wide_camera_info.distortion_model = str[start:end]
00662 start = end
00663 end += 4
00664 (length,) = _struct_I.unpack(str[start:end])
00665 pattern = '<%sd'%length
00666 start = end
00667 end += struct.calcsize(pattern)
00668 self.goal.wide_camera_info.D = struct.unpack(pattern, str[start:end])
00669 start = end
00670 end += 72
00671 self.goal.wide_camera_info.K = _struct_9d.unpack(str[start:end])
00672 start = end
00673 end += 72
00674 self.goal.wide_camera_info.R = _struct_9d.unpack(str[start:end])
00675 start = end
00676 end += 96
00677 self.goal.wide_camera_info.P = _struct_12d.unpack(str[start:end])
00678 _x = self
00679 start = end
00680 end += 37
00681 (_x.goal.wide_camera_info.binning_x, _x.goal.wide_camera_info.binning_y, _x.goal.wide_camera_info.roi.x_offset, _x.goal.wide_camera_info.roi.y_offset, _x.goal.wide_camera_info.roi.height, _x.goal.wide_camera_info.roi.width, _x.goal.wide_camera_info.roi.do_rectify, _x.goal.point_cloud.header.seq, _x.goal.point_cloud.header.stamp.secs, _x.goal.point_cloud.header.stamp.nsecs,) = _struct_6IB3I.unpack(str[start:end])
00682 self.goal.wide_camera_info.roi.do_rectify = bool(self.goal.wide_camera_info.roi.do_rectify)
00683 start = end
00684 end += 4
00685 (length,) = _struct_I.unpack(str[start:end])
00686 start = end
00687 end += length
00688 self.goal.point_cloud.header.frame_id = str[start:end]
00689 _x = self
00690 start = end
00691 end += 8
00692 (_x.goal.point_cloud.height, _x.goal.point_cloud.width,) = _struct_2I.unpack(str[start:end])
00693 start = end
00694 end += 4
00695 (length,) = _struct_I.unpack(str[start:end])
00696 self.goal.point_cloud.fields = []
00697 for i in range(0, length):
00698 val1 = sensor_msgs.msg.PointField()
00699 start = end
00700 end += 4
00701 (length,) = _struct_I.unpack(str[start:end])
00702 start = end
00703 end += length
00704 val1.name = str[start:end]
00705 _x = val1
00706 start = end
00707 end += 9
00708 (_x.offset, _x.datatype, _x.count,) = _struct_IBI.unpack(str[start:end])
00709 self.goal.point_cloud.fields.append(val1)
00710 _x = self
00711 start = end
00712 end += 9
00713 (_x.goal.point_cloud.is_bigendian, _x.goal.point_cloud.point_step, _x.goal.point_cloud.row_step,) = _struct_B2I.unpack(str[start:end])
00714 self.goal.point_cloud.is_bigendian = bool(self.goal.point_cloud.is_bigendian)
00715 start = end
00716 end += 4
00717 (length,) = _struct_I.unpack(str[start:end])
00718 start = end
00719 end += length
00720 self.goal.point_cloud.data = str[start:end]
00721 _x = self
00722 start = end
00723 end += 13
00724 (_x.goal.point_cloud.is_dense, _x.goal.disparity_image.header.seq, _x.goal.disparity_image.header.stamp.secs, _x.goal.disparity_image.header.stamp.nsecs,) = _struct_B3I.unpack(str[start:end])
00725 self.goal.point_cloud.is_dense = bool(self.goal.point_cloud.is_dense)
00726 start = end
00727 end += 4
00728 (length,) = _struct_I.unpack(str[start:end])
00729 start = end
00730 end += length
00731 self.goal.disparity_image.header.frame_id = str[start:end]
00732 _x = self
00733 start = end
00734 end += 12
00735 (_x.goal.disparity_image.image.header.seq, _x.goal.disparity_image.image.header.stamp.secs, _x.goal.disparity_image.image.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
00736 start = end
00737 end += 4
00738 (length,) = _struct_I.unpack(str[start:end])
00739 start = end
00740 end += length
00741 self.goal.disparity_image.image.header.frame_id = str[start:end]
00742 _x = self
00743 start = end
00744 end += 8
00745 (_x.goal.disparity_image.image.height, _x.goal.disparity_image.image.width,) = _struct_2I.unpack(str[start:end])
00746 start = end
00747 end += 4
00748 (length,) = _struct_I.unpack(str[start:end])
00749 start = end
00750 end += length
00751 self.goal.disparity_image.image.encoding = str[start:end]
00752 _x = self
00753 start = end
00754 end += 5
00755 (_x.goal.disparity_image.image.is_bigendian, _x.goal.disparity_image.image.step,) = _struct_BI.unpack(str[start:end])
00756 start = end
00757 end += 4
00758 (length,) = _struct_I.unpack(str[start:end])
00759 start = end
00760 end += length
00761 self.goal.disparity_image.image.data = str[start:end]
00762 _x = self
00763 start = end
00764 end += 37
00765 (_x.goal.disparity_image.f, _x.goal.disparity_image.T, _x.goal.disparity_image.valid_window.x_offset, _x.goal.disparity_image.valid_window.y_offset, _x.goal.disparity_image.valid_window.height, _x.goal.disparity_image.valid_window.width, _x.goal.disparity_image.valid_window.do_rectify, _x.goal.disparity_image.min_disparity, _x.goal.disparity_image.max_disparity, _x.goal.disparity_image.delta_d,) = _struct_2f4IB3f.unpack(str[start:end])
00766 self.goal.disparity_image.valid_window.do_rectify = bool(self.goal.disparity_image.valid_window.do_rectify)
00767 return self
00768 except struct.error as e:
00769 raise roslib.message.DeserializationError(e)
00770
00771
00772 def serialize_numpy(self, buff, numpy):
00773 """
00774 serialize message with numpy array types into buffer
00775 @param buff: buffer
00776 @type buff: StringIO
00777 @param numpy: numpy python module
00778 @type numpy module
00779 """
00780 try:
00781 _x = self
00782 buff.write(_struct_3I.pack(_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs))
00783 _x = self.header.frame_id
00784 length = len(_x)
00785 buff.write(struct.pack('<I%ss'%length, length, _x))
00786 _x = self
00787 buff.write(_struct_2I.pack(_x.goal_id.stamp.secs, _x.goal_id.stamp.nsecs))
00788 _x = self.goal_id.id
00789 length = len(_x)
00790 buff.write(struct.pack('<I%ss'%length, length, _x))
00791 _x = self
00792 buff.write(_struct_3I.pack(_x.goal.image.header.seq, _x.goal.image.header.stamp.secs, _x.goal.image.header.stamp.nsecs))
00793 _x = self.goal.image.header.frame_id
00794 length = len(_x)
00795 buff.write(struct.pack('<I%ss'%length, length, _x))
00796 _x = self
00797 buff.write(_struct_2I.pack(_x.goal.image.height, _x.goal.image.width))
00798 _x = self.goal.image.encoding
00799 length = len(_x)
00800 buff.write(struct.pack('<I%ss'%length, length, _x))
00801 _x = self
00802 buff.write(_struct_BI.pack(_x.goal.image.is_bigendian, _x.goal.image.step))
00803 _x = self.goal.image.data
00804 length = len(_x)
00805
00806 if type(_x) in [list, tuple]:
00807 buff.write(struct.pack('<I%sB'%length, length, *_x))
00808 else:
00809 buff.write(struct.pack('<I%ss'%length, length, _x))
00810 _x = self
00811 buff.write(_struct_3I.pack(_x.goal.camera_info.header.seq, _x.goal.camera_info.header.stamp.secs, _x.goal.camera_info.header.stamp.nsecs))
00812 _x = self.goal.camera_info.header.frame_id
00813 length = len(_x)
00814 buff.write(struct.pack('<I%ss'%length, length, _x))
00815 _x = self
00816 buff.write(_struct_2I.pack(_x.goal.camera_info.height, _x.goal.camera_info.width))
00817 _x = self.goal.camera_info.distortion_model
00818 length = len(_x)
00819 buff.write(struct.pack('<I%ss'%length, length, _x))
00820 length = len(self.goal.camera_info.D)
00821 buff.write(_struct_I.pack(length))
00822 pattern = '<%sd'%length
00823 buff.write(self.goal.camera_info.D.tostring())
00824 buff.write(self.goal.camera_info.K.tostring())
00825 buff.write(self.goal.camera_info.R.tostring())
00826 buff.write(self.goal.camera_info.P.tostring())
00827 _x = self
00828 buff.write(_struct_6IB3I.pack(_x.goal.camera_info.binning_x, _x.goal.camera_info.binning_y, _x.goal.camera_info.roi.x_offset, _x.goal.camera_info.roi.y_offset, _x.goal.camera_info.roi.height, _x.goal.camera_info.roi.width, _x.goal.camera_info.roi.do_rectify, _x.goal.wide_field.header.seq, _x.goal.wide_field.header.stamp.secs, _x.goal.wide_field.header.stamp.nsecs))
00829 _x = self.goal.wide_field.header.frame_id
00830 length = len(_x)
00831 buff.write(struct.pack('<I%ss'%length, length, _x))
00832 _x = self
00833 buff.write(_struct_2I.pack(_x.goal.wide_field.height, _x.goal.wide_field.width))
00834 _x = self.goal.wide_field.encoding
00835 length = len(_x)
00836 buff.write(struct.pack('<I%ss'%length, length, _x))
00837 _x = self
00838 buff.write(_struct_BI.pack(_x.goal.wide_field.is_bigendian, _x.goal.wide_field.step))
00839 _x = self.goal.wide_field.data
00840 length = len(_x)
00841
00842 if type(_x) in [list, tuple]:
00843 buff.write(struct.pack('<I%sB'%length, length, *_x))
00844 else:
00845 buff.write(struct.pack('<I%ss'%length, length, _x))
00846 _x = self
00847 buff.write(_struct_3I.pack(_x.goal.wide_camera_info.header.seq, _x.goal.wide_camera_info.header.stamp.secs, _x.goal.wide_camera_info.header.stamp.nsecs))
00848 _x = self.goal.wide_camera_info.header.frame_id
00849 length = len(_x)
00850 buff.write(struct.pack('<I%ss'%length, length, _x))
00851 _x = self
00852 buff.write(_struct_2I.pack(_x.goal.wide_camera_info.height, _x.goal.wide_camera_info.width))
00853 _x = self.goal.wide_camera_info.distortion_model
00854 length = len(_x)
00855 buff.write(struct.pack('<I%ss'%length, length, _x))
00856 length = len(self.goal.wide_camera_info.D)
00857 buff.write(_struct_I.pack(length))
00858 pattern = '<%sd'%length
00859 buff.write(self.goal.wide_camera_info.D.tostring())
00860 buff.write(self.goal.wide_camera_info.K.tostring())
00861 buff.write(self.goal.wide_camera_info.R.tostring())
00862 buff.write(self.goal.wide_camera_info.P.tostring())
00863 _x = self
00864 buff.write(_struct_6IB3I.pack(_x.goal.wide_camera_info.binning_x, _x.goal.wide_camera_info.binning_y, _x.goal.wide_camera_info.roi.x_offset, _x.goal.wide_camera_info.roi.y_offset, _x.goal.wide_camera_info.roi.height, _x.goal.wide_camera_info.roi.width, _x.goal.wide_camera_info.roi.do_rectify, _x.goal.point_cloud.header.seq, _x.goal.point_cloud.header.stamp.secs, _x.goal.point_cloud.header.stamp.nsecs))
00865 _x = self.goal.point_cloud.header.frame_id
00866 length = len(_x)
00867 buff.write(struct.pack('<I%ss'%length, length, _x))
00868 _x = self
00869 buff.write(_struct_2I.pack(_x.goal.point_cloud.height, _x.goal.point_cloud.width))
00870 length = len(self.goal.point_cloud.fields)
00871 buff.write(_struct_I.pack(length))
00872 for val1 in self.goal.point_cloud.fields:
00873 _x = val1.name
00874 length = len(_x)
00875 buff.write(struct.pack('<I%ss'%length, length, _x))
00876 _x = val1
00877 buff.write(_struct_IBI.pack(_x.offset, _x.datatype, _x.count))
00878 _x = self
00879 buff.write(_struct_B2I.pack(_x.goal.point_cloud.is_bigendian, _x.goal.point_cloud.point_step, _x.goal.point_cloud.row_step))
00880 _x = self.goal.point_cloud.data
00881 length = len(_x)
00882
00883 if type(_x) in [list, tuple]:
00884 buff.write(struct.pack('<I%sB'%length, length, *_x))
00885 else:
00886 buff.write(struct.pack('<I%ss'%length, length, _x))
00887 _x = self
00888 buff.write(_struct_B3I.pack(_x.goal.point_cloud.is_dense, _x.goal.disparity_image.header.seq, _x.goal.disparity_image.header.stamp.secs, _x.goal.disparity_image.header.stamp.nsecs))
00889 _x = self.goal.disparity_image.header.frame_id
00890 length = len(_x)
00891 buff.write(struct.pack('<I%ss'%length, length, _x))
00892 _x = self
00893 buff.write(_struct_3I.pack(_x.goal.disparity_image.image.header.seq, _x.goal.disparity_image.image.header.stamp.secs, _x.goal.disparity_image.image.header.stamp.nsecs))
00894 _x = self.goal.disparity_image.image.header.frame_id
00895 length = len(_x)
00896 buff.write(struct.pack('<I%ss'%length, length, _x))
00897 _x = self
00898 buff.write(_struct_2I.pack(_x.goal.disparity_image.image.height, _x.goal.disparity_image.image.width))
00899 _x = self.goal.disparity_image.image.encoding
00900 length = len(_x)
00901 buff.write(struct.pack('<I%ss'%length, length, _x))
00902 _x = self
00903 buff.write(_struct_BI.pack(_x.goal.disparity_image.image.is_bigendian, _x.goal.disparity_image.image.step))
00904 _x = self.goal.disparity_image.image.data
00905 length = len(_x)
00906
00907 if type(_x) in [list, tuple]:
00908 buff.write(struct.pack('<I%sB'%length, length, *_x))
00909 else:
00910 buff.write(struct.pack('<I%ss'%length, length, _x))
00911 _x = self
00912 buff.write(_struct_2f4IB3f.pack(_x.goal.disparity_image.f, _x.goal.disparity_image.T, _x.goal.disparity_image.valid_window.x_offset, _x.goal.disparity_image.valid_window.y_offset, _x.goal.disparity_image.valid_window.height, _x.goal.disparity_image.valid_window.width, _x.goal.disparity_image.valid_window.do_rectify, _x.goal.disparity_image.min_disparity, _x.goal.disparity_image.max_disparity, _x.goal.disparity_image.delta_d))
00913 except struct.error as se: self._check_types(se)
00914 except TypeError as te: self._check_types(te)
00915
00916 def deserialize_numpy(self, str, numpy):
00917 """
00918 unpack serialized message in str into this message instance using numpy for array types
00919 @param str: byte array of serialized message
00920 @type str: str
00921 @param numpy: numpy python module
00922 @type numpy: module
00923 """
00924 try:
00925 if self.header is None:
00926 self.header = std_msgs.msg._Header.Header()
00927 if self.goal_id is None:
00928 self.goal_id = actionlib_msgs.msg.GoalID()
00929 if self.goal is None:
00930 self.goal = object_segmentation_gui.msg.ObjectSegmentationGuiGoal()
00931 end = 0
00932 _x = self
00933 start = end
00934 end += 12
00935 (_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
00936 start = end
00937 end += 4
00938 (length,) = _struct_I.unpack(str[start:end])
00939 start = end
00940 end += length
00941 self.header.frame_id = str[start:end]
00942 _x = self
00943 start = end
00944 end += 8
00945 (_x.goal_id.stamp.secs, _x.goal_id.stamp.nsecs,) = _struct_2I.unpack(str[start:end])
00946 start = end
00947 end += 4
00948 (length,) = _struct_I.unpack(str[start:end])
00949 start = end
00950 end += length
00951 self.goal_id.id = str[start:end]
00952 _x = self
00953 start = end
00954 end += 12
00955 (_x.goal.image.header.seq, _x.goal.image.header.stamp.secs, _x.goal.image.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
00956 start = end
00957 end += 4
00958 (length,) = _struct_I.unpack(str[start:end])
00959 start = end
00960 end += length
00961 self.goal.image.header.frame_id = str[start:end]
00962 _x = self
00963 start = end
00964 end += 8
00965 (_x.goal.image.height, _x.goal.image.width,) = _struct_2I.unpack(str[start:end])
00966 start = end
00967 end += 4
00968 (length,) = _struct_I.unpack(str[start:end])
00969 start = end
00970 end += length
00971 self.goal.image.encoding = str[start:end]
00972 _x = self
00973 start = end
00974 end += 5
00975 (_x.goal.image.is_bigendian, _x.goal.image.step,) = _struct_BI.unpack(str[start:end])
00976 start = end
00977 end += 4
00978 (length,) = _struct_I.unpack(str[start:end])
00979 start = end
00980 end += length
00981 self.goal.image.data = str[start:end]
00982 _x = self
00983 start = end
00984 end += 12
00985 (_x.goal.camera_info.header.seq, _x.goal.camera_info.header.stamp.secs, _x.goal.camera_info.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
00986 start = end
00987 end += 4
00988 (length,) = _struct_I.unpack(str[start:end])
00989 start = end
00990 end += length
00991 self.goal.camera_info.header.frame_id = str[start:end]
00992 _x = self
00993 start = end
00994 end += 8
00995 (_x.goal.camera_info.height, _x.goal.camera_info.width,) = _struct_2I.unpack(str[start:end])
00996 start = end
00997 end += 4
00998 (length,) = _struct_I.unpack(str[start:end])
00999 start = end
01000 end += length
01001 self.goal.camera_info.distortion_model = str[start:end]
01002 start = end
01003 end += 4
01004 (length,) = _struct_I.unpack(str[start:end])
01005 pattern = '<%sd'%length
01006 start = end
01007 end += struct.calcsize(pattern)
01008 self.goal.camera_info.D = numpy.frombuffer(str[start:end], dtype=numpy.float64, count=length)
01009 start = end
01010 end += 72
01011 self.goal.camera_info.K = numpy.frombuffer(str[start:end], dtype=numpy.float64, count=9)
01012 start = end
01013 end += 72
01014 self.goal.camera_info.R = numpy.frombuffer(str[start:end], dtype=numpy.float64, count=9)
01015 start = end
01016 end += 96
01017 self.goal.camera_info.P = numpy.frombuffer(str[start:end], dtype=numpy.float64, count=12)
01018 _x = self
01019 start = end
01020 end += 37
01021 (_x.goal.camera_info.binning_x, _x.goal.camera_info.binning_y, _x.goal.camera_info.roi.x_offset, _x.goal.camera_info.roi.y_offset, _x.goal.camera_info.roi.height, _x.goal.camera_info.roi.width, _x.goal.camera_info.roi.do_rectify, _x.goal.wide_field.header.seq, _x.goal.wide_field.header.stamp.secs, _x.goal.wide_field.header.stamp.nsecs,) = _struct_6IB3I.unpack(str[start:end])
01022 self.goal.camera_info.roi.do_rectify = bool(self.goal.camera_info.roi.do_rectify)
01023 start = end
01024 end += 4
01025 (length,) = _struct_I.unpack(str[start:end])
01026 start = end
01027 end += length
01028 self.goal.wide_field.header.frame_id = str[start:end]
01029 _x = self
01030 start = end
01031 end += 8
01032 (_x.goal.wide_field.height, _x.goal.wide_field.width,) = _struct_2I.unpack(str[start:end])
01033 start = end
01034 end += 4
01035 (length,) = _struct_I.unpack(str[start:end])
01036 start = end
01037 end += length
01038 self.goal.wide_field.encoding = str[start:end]
01039 _x = self
01040 start = end
01041 end += 5
01042 (_x.goal.wide_field.is_bigendian, _x.goal.wide_field.step,) = _struct_BI.unpack(str[start:end])
01043 start = end
01044 end += 4
01045 (length,) = _struct_I.unpack(str[start:end])
01046 start = end
01047 end += length
01048 self.goal.wide_field.data = str[start:end]
01049 _x = self
01050 start = end
01051 end += 12
01052 (_x.goal.wide_camera_info.header.seq, _x.goal.wide_camera_info.header.stamp.secs, _x.goal.wide_camera_info.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
01053 start = end
01054 end += 4
01055 (length,) = _struct_I.unpack(str[start:end])
01056 start = end
01057 end += length
01058 self.goal.wide_camera_info.header.frame_id = str[start:end]
01059 _x = self
01060 start = end
01061 end += 8
01062 (_x.goal.wide_camera_info.height, _x.goal.wide_camera_info.width,) = _struct_2I.unpack(str[start:end])
01063 start = end
01064 end += 4
01065 (length,) = _struct_I.unpack(str[start:end])
01066 start = end
01067 end += length
01068 self.goal.wide_camera_info.distortion_model = str[start:end]
01069 start = end
01070 end += 4
01071 (length,) = _struct_I.unpack(str[start:end])
01072 pattern = '<%sd'%length
01073 start = end
01074 end += struct.calcsize(pattern)
01075 self.goal.wide_camera_info.D = numpy.frombuffer(str[start:end], dtype=numpy.float64, count=length)
01076 start = end
01077 end += 72
01078 self.goal.wide_camera_info.K = numpy.frombuffer(str[start:end], dtype=numpy.float64, count=9)
01079 start = end
01080 end += 72
01081 self.goal.wide_camera_info.R = numpy.frombuffer(str[start:end], dtype=numpy.float64, count=9)
01082 start = end
01083 end += 96
01084 self.goal.wide_camera_info.P = numpy.frombuffer(str[start:end], dtype=numpy.float64, count=12)
01085 _x = self
01086 start = end
01087 end += 37
01088 (_x.goal.wide_camera_info.binning_x, _x.goal.wide_camera_info.binning_y, _x.goal.wide_camera_info.roi.x_offset, _x.goal.wide_camera_info.roi.y_offset, _x.goal.wide_camera_info.roi.height, _x.goal.wide_camera_info.roi.width, _x.goal.wide_camera_info.roi.do_rectify, _x.goal.point_cloud.header.seq, _x.goal.point_cloud.header.stamp.secs, _x.goal.point_cloud.header.stamp.nsecs,) = _struct_6IB3I.unpack(str[start:end])
01089 self.goal.wide_camera_info.roi.do_rectify = bool(self.goal.wide_camera_info.roi.do_rectify)
01090 start = end
01091 end += 4
01092 (length,) = _struct_I.unpack(str[start:end])
01093 start = end
01094 end += length
01095 self.goal.point_cloud.header.frame_id = str[start:end]
01096 _x = self
01097 start = end
01098 end += 8
01099 (_x.goal.point_cloud.height, _x.goal.point_cloud.width,) = _struct_2I.unpack(str[start:end])
01100 start = end
01101 end += 4
01102 (length,) = _struct_I.unpack(str[start:end])
01103 self.goal.point_cloud.fields = []
01104 for i in range(0, length):
01105 val1 = sensor_msgs.msg.PointField()
01106 start = end
01107 end += 4
01108 (length,) = _struct_I.unpack(str[start:end])
01109 start = end
01110 end += length
01111 val1.name = str[start:end]
01112 _x = val1
01113 start = end
01114 end += 9
01115 (_x.offset, _x.datatype, _x.count,) = _struct_IBI.unpack(str[start:end])
01116 self.goal.point_cloud.fields.append(val1)
01117 _x = self
01118 start = end
01119 end += 9
01120 (_x.goal.point_cloud.is_bigendian, _x.goal.point_cloud.point_step, _x.goal.point_cloud.row_step,) = _struct_B2I.unpack(str[start:end])
01121 self.goal.point_cloud.is_bigendian = bool(self.goal.point_cloud.is_bigendian)
01122 start = end
01123 end += 4
01124 (length,) = _struct_I.unpack(str[start:end])
01125 start = end
01126 end += length
01127 self.goal.point_cloud.data = str[start:end]
01128 _x = self
01129 start = end
01130 end += 13
01131 (_x.goal.point_cloud.is_dense, _x.goal.disparity_image.header.seq, _x.goal.disparity_image.header.stamp.secs, _x.goal.disparity_image.header.stamp.nsecs,) = _struct_B3I.unpack(str[start:end])
01132 self.goal.point_cloud.is_dense = bool(self.goal.point_cloud.is_dense)
01133 start = end
01134 end += 4
01135 (length,) = _struct_I.unpack(str[start:end])
01136 start = end
01137 end += length
01138 self.goal.disparity_image.header.frame_id = str[start:end]
01139 _x = self
01140 start = end
01141 end += 12
01142 (_x.goal.disparity_image.image.header.seq, _x.goal.disparity_image.image.header.stamp.secs, _x.goal.disparity_image.image.header.stamp.nsecs,) = _struct_3I.unpack(str[start:end])
01143 start = end
01144 end += 4
01145 (length,) = _struct_I.unpack(str[start:end])
01146 start = end
01147 end += length
01148 self.goal.disparity_image.image.header.frame_id = str[start:end]
01149 _x = self
01150 start = end
01151 end += 8
01152 (_x.goal.disparity_image.image.height, _x.goal.disparity_image.image.width,) = _struct_2I.unpack(str[start:end])
01153 start = end
01154 end += 4
01155 (length,) = _struct_I.unpack(str[start:end])
01156 start = end
01157 end += length
01158 self.goal.disparity_image.image.encoding = str[start:end]
01159 _x = self
01160 start = end
01161 end += 5
01162 (_x.goal.disparity_image.image.is_bigendian, _x.goal.disparity_image.image.step,) = _struct_BI.unpack(str[start:end])
01163 start = end
01164 end += 4
01165 (length,) = _struct_I.unpack(str[start:end])
01166 start = end
01167 end += length
01168 self.goal.disparity_image.image.data = str[start:end]
01169 _x = self
01170 start = end
01171 end += 37
01172 (_x.goal.disparity_image.f, _x.goal.disparity_image.T, _x.goal.disparity_image.valid_window.x_offset, _x.goal.disparity_image.valid_window.y_offset, _x.goal.disparity_image.valid_window.height, _x.goal.disparity_image.valid_window.width, _x.goal.disparity_image.valid_window.do_rectify, _x.goal.disparity_image.min_disparity, _x.goal.disparity_image.max_disparity, _x.goal.disparity_image.delta_d,) = _struct_2f4IB3f.unpack(str[start:end])
01173 self.goal.disparity_image.valid_window.do_rectify = bool(self.goal.disparity_image.valid_window.do_rectify)
01174 return self
01175 except struct.error as e:
01176 raise roslib.message.DeserializationError(e)
01177
01178 _struct_I = roslib.message.struct_I
01179 _struct_IBI = struct.Struct("<IBI")
01180 _struct_6IB3I = struct.Struct("<6IB3I")
01181 _struct_12d = struct.Struct("<12d")
01182 _struct_2f4IB3f = struct.Struct("<2f4IB3f")
01183 _struct_9d = struct.Struct("<9d")
01184 _struct_BI = struct.Struct("<BI")
01185 _struct_3I = struct.Struct("<3I")
01186 _struct_B3I = struct.Struct("<B3I")
01187 _struct_B2I = struct.Struct("<B2I")
01188 _struct_2I = struct.Struct("<2I")
