1300 results about "Parallax" patented technology

The invention relates to the technical field of three-dimensional model adjustment, in particular to a three-dimensional model adjustment method and system and a medium. The method comprises the following steps: obtaining a multi-angle image of an original model, carrying out multi-view normalization on the multi-angle image, generating a normalized view image set, extracting feature points of the original model, carrying out parallax correction on the feature points, reconstructing a simulation three-dimensional model, collecting basic purpose data of the model, carrying out ideal demand mapping through the data, and carrying out ideal demand mapping. The method comprises the following steps: determining an ideal three-dimensional model structure, carrying out core region segmentation on a reconstruction model according to basic purpose data to obtain key region model slices, carrying out highlight region comparison with the ideal model structure, analyzing model differences, determining a structure adjustment amplitude interval according to a comparison result, and carrying out cyclic fine adjustment correction on the key region model slices to obtain a three-dimensional model. And the three-dimensional model is consistent with the ideal three-dimensional model in structure, so that the optimized three-dimensional model is generated. According to the invention, efficient and accurate three-dimensional model adjustment and optimization are realized.

The invention discloses an automobile leather defect detection method and system based on visual inspection, and relates to the technical field of industrial visual inspection, and the method comprises the steps: reconstructing the three-dimensional shape of a leather surface and generating a three-dimensional point cloud picture by analyzing the parallax relation and illumination direction reflection characteristics among multi-view automobile leather images; automobile leather surface curvature change characteristics of the three-dimensional point cloud picture are extracted, multi-scale texture analysis is carried out, and potential defect areas are identified and marked; through a three-dimensional shape measurement method, defect three-dimensional shape characteristics of the potential defect area are extracted, and defect three-dimensional geometric parameters are calculated; by analyzing defect geometrical characteristics and spatial distribution rules of the defect three-dimensional geometrical parameters and utilizing a preset grading judgment rule to divide defect grades, an automobile leather quality evaluation report containing defect three-dimensional coordinates is generated; according to the method, through combination of curvature-texture multi-scale fusion detection, the recognition capability of complex surface defects is remarkably enhanced.

The invention discloses a cradle head tracking method and device based on a binocular camera and a storage medium, and relates to the technical field of computer vision, and the method comprises the steps: processing image data based on a binocular parallax principle, and generating a three-dimensional coordinate of a center point of a tracking target; based on the three-dimensional coordinates of the camera coordinate system and the offset from the optical center of the camera to the rotation center of the holder, generating three-dimensional holder coordinates through coordinate transformation solution; determining a historical track based on the tracking target feature information and a historical target feature matching result, and outputting an identifier and a three-dimensional position observation value through correlation verification of a three-dimensional holder coordinate and the historical track; inputting an observation updating equation correction state through the identifier and the three-dimensional position observation value, and outputting a three-dimensional prediction position; based on the three-dimensional prediction position and a deviation formula, calculating the angle deviation with the camera image center under the holder coordinate system, and driving the holder to center the target in the picture center according to the angle deviation. The problem that the target tracking effect is poor is solved, and the robustness of target tracking in a complex scene is improved.

The invention relates to the technical field of image processing, and discloses a vehicle surface defect identification method and system based on artificial intelligence. The method comprises the following steps: acquiring a vehicle surface image through polarization filtering multi-angle imaging; processing the standardized image by applying HSV color conversion and texture equalization; constructing three-dimensional deformation features in combination with parallax analysis, and extracting defect feature vectors; and identifying defects by using the position-aware convolutional neural network, and outputting a severity thermodynamic diagram. According to the invention, in a complex illumination environment, tiny defects of vehicle surfaces with various colors and materials are accurately identified and evaluated, and accurate three-dimensional positioning and severity quantification of the defects are realized at the same time.

The invention provides an interaction method and system based on deep learning, and relates to the technical field of computer vision, and the method comprises the steps: collecting a continuous image sequence, extracting feature points, calculating the position variation and gradient variation of the feature points, constructing a two-dimensional feature vector, and carrying out the clustering through a Gaussian mixture model, thereby obtaining a stable feature class. And weighting the feature points based on a feature weight distribution function, calculating feature similarity and constructing a matching relationship. And calculating a dynamic parallax threshold in combination with the vehicle movement speed, screening reliable matching feature pairs, and solving pose transformation parameters. A feature change sequence is extracted through a feature detection network, a motion feature mapping matrix is constructed, and a compensation depth map is generated in combination with depth information. And scene reconstruction is carried out based on the compensation depth map and the pose transformation parameters, the scene confidence score is calculated, the pose parameters are calibrated, a high-precision pose parameter sequence is obtained, and the robustness of feature matching and the accuracy of pose estimation can be improved.

A highly reliable and high-precision navigation and positioning method and system for UAV under GPS-DENIED conditions includes: obtaining measurements of inertial sensor and image of binocular camera, extracting and tracking point features of the image, and obtaining altitude value; calculating position and attitude of camera and depth of landmark point based on the parallax and baseline of the binocular camera; fusing the measurement data of the inertial sensor and the binocular camera, and optimizing the data to obtain high-precision position and attitude data; obtaining the altitude value of the ranging radar and performing four-degree-of-freedom position and attitude graph optimization after adding the detected keyframes when repeated occurrence of the UAV at the same location is detected; encapsulating optimized position and attitude data to form a pseudo-GPS signal, inputting the pseudo-GPS signal to the UAV for positioning.

The invention discloses a shock wave overpressure field global measurement method based on multi-view image fusion, belongs to the technical field of explosive shock wave measurement, and is suitable for weapon equipment power evaluation and blasting safety analysis. The method comprises the following steps of: synchronously acquiring a time sequence image of the whole explosion process through a distributed multi-view high-speed imaging system, preprocessing the image by adopting pixel-by-pixel comparison, square operation enhancement and normalization processing, and positioning a shock wave edge contour; the blasting center coordinate is positioned through binocular parallax, the shock wave initial radius is determined by combining spatial domain analysis, and the key feature points of the front and rear edges of the wavefront are detected by using a dynamic search window and a radial gradient field. Based on multi-view constraints, a three-dimensional point cloud is generated through direct linear triangulation, and a three-dimensional wave front form is reconstructed in combination with least square spherical fitting. And finally, constructing a wavefront radius-time evolution model, and deducing a quantitative relationship between the instantaneous propagation velocity and the peak overpressure in combination with a Ranki ne-Huton iot relationship, thereby realizing the global high-precision calculation of the overpressure field.

The invention discloses an eVTOL multi-camera cooperative video compression coding method based on multi-source perception and intelligent partitioning. The method comprises the following steps: constructing a scene three-dimensional perception model by fusing multi-source data of visible light, infrared and depth sensors; the method comprises the following steps: realizing dynamic video partitioning based on motion vectors and semantic analysis, and dividing a picture into a core region, a secondary region and a background region; establishing a parallax compensation motion prediction model by adopting a cross-camera reference frame sharing mechanism; and high-fidelity compression of the key area is realized through layered entropy coding and a dynamic quantization parameter distribution strategy. And the decoding end reversely executes multi-source data fusion and partition reconstruction according to the coding metadata. The method is suitable for eVTOL multi-camera video real-time transmission scenes such as polling, surveying and mapping.

The invention discloses a robot obstacle avoidance method and system based on millimeter wave radar sparse point cloud, and relates to the technical field of obstacle avoidance recognition. A robot obstacle avoidance system based on millimeter wave radar sparse point cloud comprises a point cloud acquisition module, a negative obstacle identification module, a weak obstacle identification module, a point cluster identification module, a risk map module, a tentative verification module and an obstacle avoidance decision module. According to the invention, suspected obstacle point clusters are extracted based on a reflection intensity threshold and a spatial proximity relation in an enhanced point cloud, a theoretical parallax model of a real static obstacle is constructed under the constraint of a robot motion trajectory, and Doppler velocity distribution of each frame is combined with a static obstacle Doppler physical law for comparison. And classifying the point clusters which do not meet the multi-view geometric consistency or Doppler physical law, and distinguishing multipath false point clusters from dynamic point clusters.

The invention relates to the technical field of three-dimensional imaging, in particular to a four-eye structured light stereoscopic vision imaging method, which comprises the following steps of: arranging four cameras and synchronously acquiring multi-view image data with structured light stripes; carrying out image preprocessing and stripe code identification on the obtained four-view-angle structured light image data, and extracting structured light stripe center line positions and corresponding space projection information under each view angle; generating three-dimensional point cloud data of the high-precision target sample by using parallax calculation and a three-dimensional reconstruction algorithm, and completing spatial registration and filtering optimization of point cloud; fusing the point cloud and the light intensity data by combining the reflection intensity information of the multi-view structured light stripes to generate a composite data set containing space and spectral information; and constructing a dense parallax field and executing three-dimensional consistency verification, and generating a high-fidelity three-dimensional reconstruction model with a complete topological relation and sparse shielding compensation capability. According to the invention, the problems of insufficient view angle coverage, shielding area information loss, difficult edge structure matching and the like of traditional stereoscopic vision imaging can be solved.

The invention relates to the field of image processing, and discloses a lightweight container correction method and system based on machine vision, and the method comprises the steps: building a detection model through enhancing the feature response of a corner fitting region, detecting a corner fitting, calculating a disparity map of a multispectral image, reconstructing the three-dimensional coordinates of the corner fitting, and carrying out the pose conversion; identifying time-varying parameters on line to construct a state transition matrix, calculating predicted vibration displacement, projecting the vibration displacement to a world coordinate system, and calculating innovative sequence variance to dynamically adjust noise parameters; an inner and outer ring control framework is constructed, and an outer ring visual controller generates target force by calculating pose errors in a world coordinate system; an inner loop force control compensator combines predicted vibration offset and force sensor feedback to correct a mechanical arm control instruction, control gain is scheduled through a task stage, and vibration frequency self-adaptive adjustment parameters are analyzed; and performing force control compensation based on the target force, and discretizing the continuous impedance model to obtain a recursive control law to resist external disturbance.

The invention discloses a naked-eye 3D display optimization method based on real-time eyeball tracking, and particularly relates to the technical field of naked-eye 3D display, and the method comprises the steps: capturing eyeball movement data in real time through a visual angle tracking sensor, and collecting illumination information in combination with an ambient light sensor; depth perception parameters are calculated based on pupil diameter variation and frequency, and a time sequence prediction type dynamic compensation coefficient is generated in combination with eyeball movement acceleration; acquiring an initial fixation point coordinate by using an improved spherical projection mapping model, and performing compensation coefficient correction to obtain a real-time coordinate; and finally, according to the real-time coordinates, dynamically adjusting the refractive index distribution of the nanostructure layer, the rotation angle of the polarizer, the focal length of the optical lens and other optical modulation parameters. The real-time distance is calculated through the binocular parallax algorithm, the depth mapping value is generated by combining the focal length of the camera and the baseline distance, the method can adapt to the illumination change and the user view angle, and the 3D display effect is optimized.

The invention relates to the technical field of goods shelf detection, in particular to a self-detection method and device for goods shelf settlement, and provides the following scheme: obtaining a top view image through an image sensor arranged right above the top of a goods shelf, dividing the image into a plurality of grid units, and positioning a rectangular geometric shape by utilizing Hough transform; and screening a plurality of to-be-detected areas in combination with the edge features. For an area to be measured, homographic registration and ortho-rectification are carried out based on a reference image, a displacement field is obtained by adopting sub-pixel-level dense registration, and a geometric parallax component field corresponding to imaging parameters is obtained through robust estimation. And under the hypothesis of small deformation, inverting the parallax into a pixel normal distance, and carrying out weighted aggregation on the local region to obtain a local distance measurement result. And by iteratively combining adjacent grids, determining a settlement area boundary, and finally outputting a settlement detection result. Millimeter-level settlement quantification can be realized under a single-frame image, hardware transformation is avoided, and the method is suitable for automatic detection and long-term monitoring of multi-specification goods shelves.

The embodiment of the invention provides a bolt and bolt group monitoring method and device, and a bolt looseness detection system is constructed by combining an engineering mechanical model and a multi-source image analysis technology. According to the method, detection units are divided, a stress distribution model is established, median filtering and a bolt segmentation model are used for processing two-dimensional image data, depth image data are analyzed in combination with a binocular depth estimation algorithm based on parallax consistency check, and accurate recognition of the position and state of the bolt is achieved. The system judges transverse and longitudinal loosening states through comparative analysis of measured average angles and distances, and evaluates the influence of loosening propagation. According to the method, the defects of the traditional technology in the aspects of detection efficiency and precision are effectively overcome, and reliable technical support is provided for safety monitoring of the bolt connection structure.

The invention belongs to the technical field of stereoscopic vision, and discloses a depth estimation method based on adaptive structured light. The method comprises the following steps: acquiring a camera visual angle RGB image in a scene that a projector is turned off, acquiring a camera visual angle coarse disparity map through a semi-global matching algorithm, generating a projector visual angle RGB image and a projector visual angle coarse disparity map through projection transformation, and inputting the images into an adaptive structured light generation module to generate an adaptive structured light projection pattern; the adaptive structured light projection pattern generates a camera visual angle structured light image through a physical perception differentiable imaging module; the parallax attention depth estimation module receives the camera visual angle RGB image and the camera visual angle structured light image and outputs a depth estimation result; and taking the depth error as a loss function, jointly training and optimizing the adaptive structured light generation module and the parallax attention depth estimation module, and performing depth estimation after optimization. The optimal structured light mode is dynamically generated according to the real-time information of the scene, and the problem that traditional fixed-mode structured light cannot adapt to scene changes is solved.

The invention provides a three-dimensional modeling method and device based on visual fusion, a terminal and a storage medium, and relates to the technical field of computer vision and three-dimensional modeling. The method comprises the steps that multi-angle shooting is carried out on a target object through a multi-binocular-camera system after internal and external parameter calibration, a disparity map, shot by each binocular camera, of the target object is obtained, the multi-binocular-camera system comprises multiple binocular cameras, and each binocular camera comprises a left camera and a right camera; fusing each disparity map by using a spatial transformation fusion algorithm to obtain a complete disparity map of the target object; and calculating point cloud data by using the complete disparity map of the target object, and constructing a visual three-dimensional model of the target object based on the point cloud data. According to the method, not only can the integrity and accuracy of the visual three-dimensional model in a complex scene and an object structure be greatly improved, but also the modeling efficiency can be improved.

The invention relates to the field of remote sensing image processing and computer vision, and discloses a satellite image cascade matching method and system based on double-branch context awareness, and the method comprises the following steps: constructing a heterogeneous double-branch feature extraction network, extracting multi-scale detail features through a main feature network, and capturing global semantic information through a context coding network; fusing multi-scale main features and context features to construct a group-related cost body, and adaptively enhancing key region matching response in combination with a channel incentive mechanism; optimizing the cost body by adopting a cross-scale information transfer and multi-dimensional attention fusion strategy, and generating a multi-scale initial disparity map; image edge geometric features and semantic contexts are fused, and high-resolution parallax details are recovered through a multi-stage residual decoder. According to the method, the problem of matching fuzziness of a traditional method in weak texture, repeated structure and parallax abrupt change areas of a satellite image is solved, and the three-dimensional reconstruction precision and the edge detail integrity in a complex scene are remarkably improved.

The invention provides an SLAM positioning method and system based on multi-sensor fusion, and the method comprises the steps: firstly receiving data of a plurality of sensors, and obtaining initial data including visual feature data, I MU pre-integration data and UWB distance data through anomaly detection and processing; initializing by using visual feature data and I MU pre-integration data, estimating an initial pose, and predicting a UWB anchor point position as a fixed constraint in combination with UWB distance data; inputting the initial data into a sliding window, outputting drifting-free odometer data, judging the motion state of the SLAM system according to the data, and if the motion state is static, executing zero-speed updating to obtain target pose data; and finally, determining a new key frame based on the parallax or visual feature data quantity of the current frame and the previous key frame. According to the invention, the problems of relatively weak robustness and relatively low positioning accuracy of the system facing extreme scenes are solved; by means of motion state judgment and zero-speed updating, the robustness of the system in long-term operation is improved.

The invention discloses a naked eye 3D transparent display imaging system, and relates to the technical field of 3D transparent imaging. The method comprises the steps that a multi-scale parallax layer construction module is used for decomposing a multi-scale parallax layer and dividing regional images; the dynamic viewpoint prediction module is used for generating two-eye three-dimensional space coordinates through human eye parameters; the parallax scheduling mapping module is used for performing space mapping according to the binocular three-dimensional space coordinates to generate a target visual angle image; the background compensation module is used for carrying out brightness correction on the target view angle image to obtain a compensated view angle image; the directional light field regulation and control module is used for processing the compensation view angle image and generating directional light field information; and the full-layer fusion module is used for processing directional light field information, eliminating interface artifacts between layers and generating a naked-eye 3D transparent display image. Through multi-scale parallax construction, dynamic viewpoint tracking and multi-layer light field fusion, the visual angle adaptability and image fusion quality of naked eye 3D display are improved, and a transparent three-dimensional imaging effect with high immersion, high consistency and high definition is realized.

The technology introduces 3D Moments, a new computational photography effect. As input a pair of near-duplicate photos is taken (FIG. 1A), i.e., photos of moving subjects from similar viewpoints, which may be very common in people's photo collections. As output, the system produces a video that smoothly interpolates the scene motion from the first photo to the second, while also producing camera motion with parallax that gives a heightened sense of 3D (FIG. 1B). To achieve this effect, the scene is represented as a pair of feature-based layered depth images augmented with scene flow (306). This representation enables motion interpolation along with independent control of the camera viewpoint. The system produces photorealistic space-time videos with motion parallax and scene dynamics (322), while plausibly recovering regions occluded in the original views. Experimentation demonstrating superior performance over baselines on public benchmarks and in-the-wild photos.

The invention discloses a space-time speckle projection three-dimensional imaging method based on multi-frame optical flow alignment. Firstly, a projector based on DLP is used for projecting a space-time speckle pattern to a measured scene, and a binocular camera synchronously collects a three-dimensional space-time speckle image. The calibration parameters of the binocular camera are used to carry out stereo correction on an acquired original speckle image, and a parallax image is generated frame by frame in combination with a coarse-to-fine single-frame speckle matching strategy. And estimating a two-dimensional inter-frame displacement field between continuous disparity maps by using an optical flow method by taking an intermediate frame disparity map as a reference, compensating motion artifacts in a space-time speckle image, and ensuring strict space-time registration of a dynamic target. And based on the speckle image after motion correction, a speckle matching strategy is expanded to a time-space domain, and high-precision multi-frame three-dimensional measurement of a complex dynamic scene is realized. The method is suitable for performing rapid and high-precision three-dimensional modeling on a moving target in an unstructured environment, and can perform accurate three-dimensional measurement on a high-speed dynamic target undergoing any translation or rotation motion.

The invention relates to the technical field of image data processing, in particular to an urban building three-dimensional reconstruction method and device, and the method comprises the steps: obtaining a multi-view satellite orthoimage from the same scene, satellite-borne laser height measurement data of a target region, a digital terrain model and two-dimensional building vector data; performing accurate geometric registration on the multi-view satellite orthoimage, and executing dense matching to generate an initial parallax point cloud; and combining azimuth angle information of the multi-view orthoimage to construct a disparity map with accurate plane positioning. And calculating an elevation value above the earth surface by using satellite-borne laser altimetry data and a digital terrain model. And jointly estimating a parallax elevation proportionality coefficient by using the elevation value and the parallax value so as to convert the parallax map into a height map. And generating three-dimensional building vector data of the target area in combination with the two-dimensional building vector data. Therefore, the problems that cost based on surveying and mapping level remote sensing data is high, data collection is limited, and the requirement for global city three-dimensional reconstruction cannot be met in the prior art are solved.

The invention relates to the technical field of artificial intelligence, in particular to an image depth estimation method and device, electronic equipment and a storage medium. The method comprises the following steps: extracting a frame of binocular image from video data acquired by a binocular camera, and preprocessing a left eye image and a right eye image in the frame of binocular image; performing feature extraction on the preprocessed left eye image and right eye image to obtain corresponding left image features and right image features, and performing pixel-level similarity calculation on the left image features and the right image features to obtain corresponding feature similarity information; determining target parallax information of the frame of binocular image based on the feature similarity information and the image features in combination with reference parallax information of a previous frame of binocular image of the frame of binocular image; and obtaining target depth information based on the target parallax information of the frame of binocular image in combination with camera parameters of the binocular camera. The effect of the generated depth map is improved, so that the requirements of various application scenes of the depth map are met.

Electronic equipment includes a processor, and a memory storing a program which, when executed by the processor, causes the electronic equipment to acquire a third image in which a first image captured via a first optical system and a second image captured via a second optical system and having parallax with respect to the first image are arranged side by side, apply predetermined processing to a target range included in the third image, and, wherein each of the first image and the second image is a circular region, set a rectangular region circumscribed around a circular region of the first image or a circular region of the second image as a movable region in which the target range included in the third image is movable.

The invention discloses a micro-sensing trapezoidal method, device and equipment based on Aruco recognition and a medium, and relates to the field of computer vision. The method comprises the following steps: S1, projecting an Aruco grid and collecting an image, and extracting marked angular points to construct a position set; s2, calculating a trapezoid tension factor based on the trapezoid area and the opposite side distance, and quantifying local deformation; s3, fusing multi-labeled spatial parallax and tension information, constructing a continuous tension equilibrium domain, and generating a final mapping position through gradient correction basic inverse projection mapping and boundary disturbance compensation; and S4, outputting an inverse perspective matrix based on a fusion result, and estimating a microscopic pose offset parameter for fine adjustment of the projector. And through tension factor and spatial parallax modeling, adaptive correction of a distortion region is realized, the edge consistency and overall symmetry of the image are improved, and the stability and precision of the projected image are enhanced.

A method in XR technology to determine whether an actual touch of a function region during virtual typing or touch control performed on the palm or on a real object is achieved, by marking preset points on the palm; assigning a function region to each preset point; setting two trigger determination points WL and WR; acquiring N number of video streams with parallax; tracking and determining whether a trigger fingertip P is located between the two trigger determination points in all corresponding N number of images bearing a same time from the N number of video streams; in each of the N number of images, calculate a ratio being a difference in X-axis value between P and WR to a difference in X-axis value between WL and P; only when all ratios in all images are the same, the trigger fingertip P is determined to have touched the function region.

A vehicle external environment recognition apparatus includes at least one processor, and at least one memory coupled to the at least one processor. The at least one processor is configured to operate in cooperation with at least one program stored in the at least one memory to execute processing. The processing includes generating a distance image from luminance images, specifying, by using semantic segmentation, a floating matter class in the luminance images, and invalidating parallax associated with floating pixels that are included in the distance image and belong to the floating matter class.

Embodiments of the present disclosure relate to surface estimation using stereo imaging and surface disparities. For example, a surface disparity field representing a surface in the environment (e.g., the ground) may be estimated from stereo image data and used for various downstream tasks. For example, the difference between a stereo disparity field and a ground disparity field may be used to detect objects, a representation of a navigable space may be generated by radially casting 2D rays in the ground disparity field, the ground disparity field may be used to compensate ego-motion for high dynamic attitude changes, and / or the ground disparity field may be lifted to 3D and used to fit a surface profile to points sampled from the lifted point cloud.

The invention relates to the technical field of image processing, in particular to an anomaly detection method for a ballast bed cover plate of a railway track. Comprising the following steps: synchronously acquiring track area images from different angles by using at least two cameras, calculating a depth value of the ballast bed cover plate according to parallax of the same target track area in imaging of different cameras, and constructing a three-dimensional model of the ballast bed cover plate; in the high-speed running process of the train, real-time compensation processing is carried out on the image; a periodic action sequence including different illumination intensities, focal length adjustment and shooting frame rate changes is set, the duration of each action is set according to the train running speed and the camera shooting frequency, and multiple sets of track images are collected during the duration of each action. According to the railway track ballast bed cover plate anomaly detection method, the depth value of the ballast bed cover plate is obtained, the tilting anomaly of the cover plate is recognized, real-time compensation processing is carried out on the image, and the detection precision and efficiency are improved.

The invention relates to a naked eye 3D binocular image acquisition and real-time processing system based on hardware synchronous triggering, and belongs to the technical field of image processing and three-dimensional display. According to the system, a hardware synchronous triggering mechanism is adopted, a time sequence synchronous control unit is used for sending a synchronous pulse signal to a binocular image sensor, and strict synchronization of left and right viewpoint image acquisition is ensured. The image signal processing unit processes collected original data, the stereo parallax correction module performs epipolar correction, and the sub-pixel interleaving module generates a composite view frame according to grating parameters of the display terminal. The system realizes high-speed data transmission through a double-buffer direct memory access DMA mechanism. The problems of visual tearing and weak stereoscopic impression caused by asynchronous binocular image acquisition in the prior art are solved, nanosecond-level synchronization precision is realized, optical crosstalk is reduced, and smoothness and comfort of stereoscopic display are ensured.