我运行OK的voxblox工作空间下的src文件夹，包含voxblox安装包以及所需包

image_undistort exists to handle all the odd situations image_proc doesn't quite cover. Some examples of this are * working with images that don't have a camera_info topic * undistortion of images using equidistant or other less common camera models * turning a location in a distorted image into a bearing vector If you have an image undistortion / stereo imaging problem that the library doesn't cover, create an issue and I'll look at adding it. Note that the automatic image size approach used will fail for cameras with a fov greater than 180 degrees. This repo contains six related ros nodes- * **[image_undistort_node](#image_undistort_node):** Undistorts and changes images intrinsics and resolution. * **[stereo_info_node](#stereo_info_node):** Calculates the camera information needed for stereo rectification. * **[stereo_undistort_node](#stereo_undistort_node):** Combines the functionality of the above two nodes to perform stereo image rectification. * **[depth_node](#depth_node):** Converts two undistorted images and their camera information into a disparity image and a pointcloud. * **[dense_stereo_node](#dense_stereo_node):** Performs the full dense stereo estimation (internally this node is just the stereo_undistort nodelet and the depth nodelet). * **[point_to_bearing_node](#point_to_bearing_node):** Takes in a 2D image location and transforms it into a bearing vector. ## Dependencies Image undistort depends on ROS, OpenCV and Eigen. The point to bearing node also depends on NLopt (installed with `apt install libnlopt-dev`) and will only be built if it is found. ## Supported Camera and Distortion Models The only supported output is the pinhole camera model with no distortion. Supported input models: * Pinhole with no distortion * Pinhole with radial-tangential distortion * Pinhole with equidistant distortion * Omnidirectional with no distortion * Omindirectional with rad-tan distortion * FOV * Unified * Extended Unified * Double Sphere # image_undistort_node: A simple node for undistorting images. Handles plumb bob (aka radial-tangential), fov and equidistant distortion models. It can either use standard ros camera_info topics or load camera models in a form that is compatible with the camchain.yaml files produced by [Kalibr](https://github.com/ethz-asl/kalibr). Note this node can also be run as a nodelet named `image_undistort/ImageUndistortNodelet`. ## The node has several possible use cases: * **Undistort images.** The default usage of the node, outputting an undistorted version of an input image. * **Modify the image resolution and intrinsics.** The node supports projecting from and to any valid projection matrix and resolution. * **Provide a camera_info topic for an image.** In this mode ros params are used to build a camera info message that is published in sync with the image messages. This allows the use of ros nodes that require camera info with devices and bags that do not provide it. ## Parameters: * **queue size** The length of the queues the node uses for topics (default: 10). * **input_camera_info_from_ros_params** If false the node will subscribe to a camera_info ros topic named input/camera_info to obtain the input camera parameters. If true the input camera parameters will be loaded from ros parameters. See the parameters format section for further details. (default: false). * **output_camera_info_source** The source to use when obtaining the output camera parameters. The possible case-insensitive options are, * *"auto_generated"* The default value. In this mode "good" output parameters are automatically generated based on the input image. focal length is the average of fx and fy of the input, the center point is in the center of the image, R=I and translation is preserved. Resolution is set to the largest area that contains no empty pixels. The size of the output can also be modified with the *scale* parameter. * *"match_input"* The output projection matrix and resolution, exactly match the inputs. * *"ros_params"* The output camera parameters are loaded from ros parameters. See the parameters format section for further details. * *"camera_info"* The output parameters are found through subscribing to a camera_info ros topic named output/camera_info * **input_camera_namespace** If the input camera parameters are loaded from ros parameters this is the namespace that will be searched. This is needed to allow both input and output to be loaded from parameters. (default: "input_camera") * **output_camera_namespace** If the output camera parameters are loaded from ros parameters this is the namespace that will be searched. (default: "output_camera"). * **process_image** True to output a processed image, false if only a camera_info topic should be generated. (default: true). * **undistort_image** True to undistort the images, false to keep the distortion. (default: true). * **process_every_nth_frame** Used to temporarily down-sample the images, if it is <= 1 every frame will be processed. (default: 1). * **output_image_type** Converts the output image to the specified format, set to the empty string "" to preserve the input type. See [the cv_bridge tutorial](http://wiki.ros.org/cv_bridge/Tutorials/UsingCvBridgeToConvertBetweenROSImagesAndOpenCVImages) for possible format strings. (default: ""). * **scale** Only used if **output_camera_info_source** is set to "auto_generated" or "match_input". The output focal length will be multiplied by this value. If "auto_generated" is set the image size will also be increased by this factor. (default: 1.0). * **publish_tf** True to publish the tf between the input and output image. If the undistortion involves changes to the rotation matrix the frame that the image is in will change. This tf gives that change. (default: true) * **output_frame** The name of the frame of the output images. (default: "output_camera") * **rename_input_frame** If the input frame should be renamed in the published topics and tf tree. (default: false) * **input_frame** Only used if **rename_input_frame** is true. The name of the frame of the input images. (default: "input_camera") * **rename_radtan_plumb_bob** If true the radial-tangential distortion model will be called "plumb_bob" in the output camera_info, this is needed by some ros image processing nodes. If false it will be called "radtan". (default: false). ## Input/Output Topics Many of these topics are dependent on the parameters set above and may not appear or may be renamed under some settings. * **input/image** input image topic * **input/camera_info** input camera info topic * **output/image** output image topic * **output/camera_info** output camera info topic ## Loading Camera Information from ROS Parameters: Camera information can be loaded from ROS parameters. These parameters are typically set using <rosparam file="path_to_yaml_file"/>. The format used by this node is compatible with the camchains generated by [Kalibr](https://github.com/ethz-asl/kalibr). The follow steps are used when loading this information. 1. A 3x3 intrinscs matrix named **K** is searched for. If it is found it is loaded. If it is not found a 1x4 vector named **intrinsics** is loaded, this contains the parameters (fx, fy, cx, cy). If neither parameters are given the node displays an error and terminates. 2. A 1x2 vector named **resolution** is loaded which contains the parameters (width, height). Again, if not given the node displays an error and terminates. 3. A 4x4 transformation matrix **T_cn_cnm1** is searched for. If it is found it is loaded. Otherwise it is searched for under the name **T** and if found loaded. If neither are found the node continues. 4. A 4x3 projection matrix **P** is searched for. If it is found it is loaded. If **P** was found but **T** was not, **P** and **K** are used to construct **T**, otherwise **T** is set to identity. If **P** was not found it is constructed from **K** and **T**. 5. If an output is being loaded, the loading