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package sensor_msgs.msg.dds;
import us.ihmc.communication.packets.Packet;
import us.ihmc.euclid.interfaces.Settable;
import us.ihmc.euclid.interfaces.EpsilonComparable;
import java.util.function.Supplier;
import us.ihmc.pubsub.TopicDataType;
/**
* 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 #
* ######################################################################
* 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.#
* ######################################################################
* ######################################################################
* 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. #
* ######################################################################
*/
public class CameraInfo extends Packet implements Settable, EpsilonComparable
{
/**
* Time of image acquisition, camera coordinate frame ID
* Header timestamp should be acquisition time of image
*/
public std_msgs.msg.dds.Header header_;
/**
* The image dimensions with which the camera was calibrated.
* Normally this will be the full camera resolution in pixels.
*/
public long height_;
public long width_;
/**
* The distortion model used. Supported models are listed in
* sensor_msgs/distortion_models.hpp. For most cameras, "plumb_bob" - a
* simple model of radial and tangential distortion - is sufficent.
*/
public java.lang.StringBuilder distortion_model_;
/**
* The distortion parameters, size depending on the distortion model.
* For "plumb_bob", the 5 parameters are: (k1, k2, t1, t2, k3).
*/
public us.ihmc.idl.IDLSequence.Double 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).
* 3x3 row-major matrix
*/
public double[] k_;
/**
* 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.
* 3x3 row-major matrix
*/
public double[] r_;
/**
* 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.
* 3x4 row-major matrix
*/
public double[] p_;
/**
* 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).
*/
public long binning_x_;
public long 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).
*/
public sensor_msgs.msg.dds.RegionOfInterest roi_;
public CameraInfo()
{
header_ = new std_msgs.msg.dds.Header();
distortion_model_ = new java.lang.StringBuilder(255);
d_ = new us.ihmc.idl.IDLSequence.Double (100, "type_6");
k_ = new double[9];
r_ = new double[9];
p_ = new double[12];
roi_ = new sensor_msgs.msg.dds.RegionOfInterest();
}
public CameraInfo(CameraInfo other)
{
this();
set(other);
}
public void set(CameraInfo other)
{
std_msgs.msg.dds.HeaderPubSubType.staticCopy(other.header_, header_);
height_ = other.height_;
width_ = other.width_;
distortion_model_.setLength(0);
distortion_model_.append(other.distortion_model_);
d_.set(other.d_);
for(int i1 = 0; i1 < k_.length; ++i1)
{
k_[i1] = other.k_[i1];
}
for(int i3 = 0; i3 < r_.length; ++i3)
{
r_[i3] = other.r_[i3];
}
for(int i5 = 0; i5 < p_.length; ++i5)
{
p_[i5] = other.p_[i5];
}
binning_x_ = other.binning_x_;
binning_y_ = other.binning_y_;
sensor_msgs.msg.dds.RegionOfInterestPubSubType.staticCopy(other.roi_, roi_);
}
/**
* Time of image acquisition, camera coordinate frame ID
* Header timestamp should be acquisition time of image
*/
public std_msgs.msg.dds.Header getHeader()
{
return header_;
}
/**
* The image dimensions with which the camera was calibrated.
* Normally this will be the full camera resolution in pixels.
*/
public void setHeight(long height)
{
height_ = height;
}
/**
* The image dimensions with which the camera was calibrated.
* Normally this will be the full camera resolution in pixels.
*/
public long getHeight()
{
return height_;
}
public void setWidth(long width)
{
width_ = width;
}
public long getWidth()
{
return width_;
}
/**
* The distortion model used. Supported models are listed in
* sensor_msgs/distortion_models.hpp. For most cameras, "plumb_bob" - a
* simple model of radial and tangential distortion - is sufficent.
*/
public void setDistortionModel(java.lang.String distortion_model)
{
distortion_model_.setLength(0);
distortion_model_.append(distortion_model);
}
/**
* The distortion model used. Supported models are listed in
* sensor_msgs/distortion_models.hpp. For most cameras, "plumb_bob" - a
* simple model of radial and tangential distortion - is sufficent.
*/
public java.lang.String getDistortionModelAsString()
{
return getDistortionModel().toString();
}
/**
* The distortion model used. Supported models are listed in
* sensor_msgs/distortion_models.hpp. For most cameras, "plumb_bob" - a
* simple model of radial and tangential distortion - is sufficent.
*/
public java.lang.StringBuilder getDistortionModel()
{
return distortion_model_;
}
/**
* The distortion parameters, size depending on the distortion model.
* For "plumb_bob", the 5 parameters are: (k1, k2, t1, t2, k3).
*/
public us.ihmc.idl.IDLSequence.Double getD()
{
return 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).
* 3x3 row-major matrix
*/
public double[] getK()
{
return k_;
}
/**
* 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.
* 3x3 row-major matrix
*/
public double[] getR()
{
return r_;
}
/**
* 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.
* 3x4 row-major matrix
*/
public double[] getP()
{
return p_;
}
/**
* 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).
*/
public void setBinningX(long binning_x)
{
binning_x_ = binning_x;
}
/**
* 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).
*/
public long getBinningX()
{
return binning_x_;
}
public void setBinningY(long binning_y)
{
binning_y_ = binning_y;
}
public long getBinningY()
{
return 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).
*/
public sensor_msgs.msg.dds.RegionOfInterest getRoi()
{
return roi_;
}
public static Supplier getPubSubType()
{
return CameraInfoPubSubType::new;
}
@Override
public Supplier getPubSubTypePacket()
{
return CameraInfoPubSubType::new;
}
@Override
public boolean epsilonEquals(CameraInfo other, double epsilon)
{
if(other == null) return false;
if(other == this) return true;
if (!this.header_.epsilonEquals(other.header_, epsilon)) return false;
if (!us.ihmc.idl.IDLTools.epsilonEqualsPrimitive(this.height_, other.height_, epsilon)) return false;
if (!us.ihmc.idl.IDLTools.epsilonEqualsPrimitive(this.width_, other.width_, epsilon)) return false;
if (!us.ihmc.idl.IDLTools.epsilonEqualsStringBuilder(this.distortion_model_, other.distortion_model_, epsilon)) return false;
if (!us.ihmc.idl.IDLTools.epsilonEqualsDoubleSequence(this.d_, other.d_, epsilon)) return false;
for(int i7 = 0; i7 < k_.length; ++i7)
{
if (!us.ihmc.idl.IDLTools.epsilonEqualsPrimitive(this.k_[i7], other.k_[i7], epsilon)) return false;
}
for(int i9 = 0; i9 < r_.length; ++i9)
{
if (!us.ihmc.idl.IDLTools.epsilonEqualsPrimitive(this.r_[i9], other.r_[i9], epsilon)) return false;
}
for(int i11 = 0; i11 < p_.length; ++i11)
{
if (!us.ihmc.idl.IDLTools.epsilonEqualsPrimitive(this.p_[i11], other.p_[i11], epsilon)) return false;
}
if (!us.ihmc.idl.IDLTools.epsilonEqualsPrimitive(this.binning_x_, other.binning_x_, epsilon)) return false;
if (!us.ihmc.idl.IDLTools.epsilonEqualsPrimitive(this.binning_y_, other.binning_y_, epsilon)) return false;
if (!this.roi_.epsilonEquals(other.roi_, epsilon)) return false;
return true;
}
@Override
public boolean equals(Object other)
{
if(other == null) return false;
if(other == this) return true;
if(!(other instanceof CameraInfo)) return false;
CameraInfo otherMyClass = (CameraInfo) other;
if (!this.header_.equals(otherMyClass.header_)) return false;
if(this.height_ != otherMyClass.height_) return false;
if(this.width_ != otherMyClass.width_) return false;
if (!us.ihmc.idl.IDLTools.equals(this.distortion_model_, otherMyClass.distortion_model_)) return false;
if (!this.d_.equals(otherMyClass.d_)) return false;
for(int i13 = 0; i13 < k_.length; ++i13)
{
if(this.k_[i13] != otherMyClass.k_[i13]) return false;
}
for(int i15 = 0; i15 < r_.length; ++i15)
{
if(this.r_[i15] != otherMyClass.r_[i15]) return false;
}
for(int i17 = 0; i17 < p_.length; ++i17)
{
if(this.p_[i17] != otherMyClass.p_[i17]) return false;
}
if(this.binning_x_ != otherMyClass.binning_x_) return false;
if(this.binning_y_ != otherMyClass.binning_y_) return false;
if (!this.roi_.equals(otherMyClass.roi_)) return false;
return true;
}
@Override
public java.lang.String toString()
{
StringBuilder builder = new StringBuilder();
builder.append("CameraInfo {");
builder.append("header=");
builder.append(this.header_); builder.append(", ");
builder.append("height=");
builder.append(this.height_); builder.append(", ");
builder.append("width=");
builder.append(this.width_); builder.append(", ");
builder.append("distortion_model=");
builder.append(this.distortion_model_); builder.append(", ");
builder.append("d=");
builder.append(this.d_); builder.append(", ");
builder.append("k=");
builder.append(java.util.Arrays.toString(this.k_)); builder.append(", ");
builder.append("r=");
builder.append(java.util.Arrays.toString(this.r_)); builder.append(", ");
builder.append("p=");
builder.append(java.util.Arrays.toString(this.p_)); builder.append(", ");
builder.append("binning_x=");
builder.append(this.binning_x_); builder.append(", ");
builder.append("binning_y=");
builder.append(this.binning_y_); builder.append(", ");
builder.append("roi=");
builder.append(this.roi_);
builder.append("}");
return builder.toString();
}
}
