WO2024088251A1 - 包裹尺寸测量方法、装置、计算机设备及存储介质 - Google Patents

包裹尺寸测量方法、装置、计算机设备及存储介质 Download PDF

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Publication number
WO2024088251A1
WO2024088251A1 PCT/CN2023/126186 CN2023126186W WO2024088251A1 WO 2024088251 A1 WO2024088251 A1 WO 2024088251A1 CN 2023126186 W CN2023126186 W CN 2023126186W WO 2024088251 A1 WO2024088251 A1 WO 2024088251A1
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point cloud
package
cloud set
target
point
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PCT/CN2023/126186
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English (en)
French (fr)
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樊海风
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顺丰科技有限公司
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Publication of WO2024088251A1 publication Critical patent/WO2024088251A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes

Definitions

  • the present application relates to the field of logistics, and specifically to a package size measurement method, device, computer equipment and storage medium.
  • the embodiment of the present application provides a package size measurement method, aiming to improve the problem of large size error existing in the package size measurement method in the prior art.
  • the present application provides a package size measurement method, the package size measurement method comprising:
  • a first point cloud set corresponding to a target package is obtained, the first point cloud set being point cloud data of the target package collected in a preset package area, and the target package is a package whose size is to be measured; an initial background point cloud set of the preset package area is obtained, the initial background point cloud set being a point cloud data set obtained by collecting data from the preset package area when there is no target package in the preset package area; the initial background point cloud set is filtered out from the first point cloud set to obtain a second point cloud set corresponding to the target package; and the size of the target package is determined based on the second point cloud set.
  • filtering out the initial background point cloud set in the first point cloud set to obtain a second point cloud set corresponding to the target package includes: establishing a background model corresponding to the preset package area, wherein the background model represents a reference coordinate system; based on the background model, filtering out the initial background point cloud set in the first point cloud set to obtain the second point cloud set.
  • establishing the background model corresponding to the preset package area includes: projecting multiple point clouds in the initial background point cloud set to the first direction, the second direction and the third direction respectively to determine the first direction vector, the second direction vector and the third direction vector with the smallest projection error, the first direction and the second direction are perpendicular to each other, the second direction and the third direction are perpendicular to each other, and the third direction and the first direction are perpendicular to each other; calculating the center of gravity position of the initial background point cloud set to obtain the background center of gravity point cloud coordinates; determining the background model corresponding to the preset package area according to the first direction vector, the second direction vector, the third direction vector and the background center of gravity point cloud coordinates.
  • the multiple point clouds in the initial background point cloud set are projected to the first direction, the second direction and the third direction respectively to determine the first direction vector, the second direction vector and the third direction vector with the smallest projection error, including: projecting the multiple point clouds in the initial background point cloud set to the initial first direction, the initial second direction and the initial third direction respectively; calculating the lengths of perpendicular lines from the feature vectors corresponding to the multiple point clouds to the initial first direction, the initial second direction and the initial third direction respectively; adjusting the initial first direction, the initial second direction and the initial third direction so that the value of the perpendicular line length is minimized, and the first direction, the second direction and the third direction are obtained, and during the adjustment process, the initial first direction, the initial second direction and the initial third direction remain perpendicular to each other; projecting the multiple point clouds in the initial background point cloud set to the first direction, the second direction and the third direction respectively to obtain the first direction vector, the second direction vector and the third direction vector.
  • filtering out the initial background point cloud set in the first point cloud set to obtain the second point cloud set includes: based on the background model, filtering out the initial background point cloud set Performing coordinate transformation on multiple point clouds in the cloud set to obtain a first background point cloud set; based on the background model, performing coordinate transformation on multiple point clouds in the first point cloud set to obtain a third point cloud set, wherein the third point cloud set includes multiple third point clouds, and the multiple third point clouds are all three-dimensional point clouds, and the three-dimensional point clouds include x values, y values, and z values; determining the z value z max of the first target point cloud with the largest z value in the first background point cloud set; in the third point cloud set, eliminating the third point cloud with a z value less than z max to obtain the second point cloud set.
  • the second point cloud set includes multiple second point clouds
  • determining the size of the target package based on the second point cloud set includes: determining the package point cloud set corresponding to the target package based on multiple package point cloud distances between each second point cloud and other second point clouds in the multiple second point clouds, wherein each package point cloud distance in the multiple package point cloud distances is the distance between the second point cloud and any other second point cloud; and determining the size of the target package based on the package point cloud set.
  • determining the package point cloud set corresponding to the target package based on the multiple package point cloud distances between each second point cloud in the multiple second point clouds and other second point clouds includes: taking each second point cloud in the second point cloud set as a seed point cloud; sorting the multiple package point cloud distances corresponding to the seed point cloud to obtain a candidate package point cloud set corresponding to the seed point cloud; and screening out the target package point cloud set with the largest number of point clouds from the candidate package point cloud sets corresponding to the multiple second point clouds, and using the target package point cloud set as the final package point cloud set of the target package.
  • the distance sorting of the multiple package point cloud distances corresponding to the seed point cloud to obtain the candidate package point cloud set corresponding to the seed point cloud includes: adding the seed point cloud to a preset initial candidate package point cloud set; sorting the multiple package point cloud distances corresponding to the seed point cloud in order from small to large, and determining a fourth point cloud set consisting of multiple second point clouds corresponding to a preset number of package point cloud distances starting from a starting position from the sorted multiple package point cloud distances; determining a second target point cloud in the fourth point cloud set whose package point cloud distance with the seed point cloud is less than a preset point cloud distance threshold; adding the second target point cloud to the initial candidate package point cloud set, and taking the second target point cloud newly added to the initial candidate package point cloud set each time as the seed point cloud, cyclically executing the operation of determining the package point cloud distance, determining a new second target point cloud corresponding to a new seed point cloud according to the package point cloud distance, and adding the new
  • determining the size of the target package based on the package point cloud set includes: determining the maximum z value as the height of the target package for all point cloud data in the package point cloud set; extracting x values and y values corresponding to all point cloud data in the package point cloud set to form multiple two-dimensional point clouds; in a two-dimensional plane, connecting the multiple two-dimensional point clouds in sequence to obtain a two-dimensional image; in the two-dimensional plane, determining the vertices and length and width of the minimum circumscribed rectangle corresponding to the two-dimensional image to obtain the length and width of the target package.
  • the present application provides a package size measurement device, which includes: a package point cloud acquisition module, used to acquire a first point cloud set corresponding to a target package, the first point cloud set being the point cloud data of the target package collected in a preset package area, and the target package is a package whose size is to be measured; a background point cloud acquisition module, used to acquire an initial background point cloud set of the preset package area, the initial background point cloud set being a point cloud data set obtained by collecting the preset package area when there is no target package in the preset package area; a package point cloud determination module, used to filter out the initial background point cloud set in the first point cloud set to obtain a second point cloud set corresponding to the target package; and a size determination module, used to determine the size of the target package based on the second point cloud set.
  • a package point cloud acquisition module used to acquire a first point cloud set corresponding to a target package, the first point cloud set being the point cloud data of the target package collected in a preset package area, and the target package is
  • the package point cloud determination module is specifically used to: establish a background model corresponding to the preset package area, wherein the background model represents a reference coordinate system; based on the background model, filter out the initial background point cloud set in the first point cloud set to obtain the second point cloud set.
  • the package point cloud determination module is used to: project multiple point clouds in the initial background point cloud set to the first direction, the second direction and the third direction respectively to determine the first direction vector, the second direction vector and the third direction vector with the smallest projection error, the first direction and the second direction are perpendicular to each other, the second direction and the third direction are perpendicular to each other, and the third direction and the first direction are perpendicular to each other; calculate the initial background point cloud
  • the center of gravity position of the set is used to obtain the background center of gravity point cloud coordinates; and the background model corresponding to the preset package area is determined according to the first direction vector, the second direction vector, the third direction vector and the background center of gravity point cloud coordinates.
  • the second point cloud set includes multiple second point clouds
  • the size determination module is specifically used to: determine the package point cloud set corresponding to the target package based on multiple package point cloud distances between each second point cloud and other second point clouds in the multiple second point clouds, wherein each package point cloud distance in the multiple package point cloud distances is the distance between the second point cloud and any other second point cloud; determine the size of the target package based on the package point cloud set.
  • the present application also provides a computer device, comprising: one or more processors; a memory; and one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the package size measurement method described in any one of the first aspects.
  • the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is loaded by a processor to execute the steps in the package size measurement method described in any one of the first aspects.
  • the present application provides a package size measurement method, device, computer equipment and storage medium, including: obtaining a first point cloud set corresponding to a target package to be measured, the first point cloud set being the collected point cloud data of the target package in a preset package area; obtaining an initial background point cloud set corresponding to the preset package area; filtering the initial background point cloud set from the first point cloud set to obtain a second point cloud set corresponding to the target package; and determining the size of the target package based on the second point cloud set.
  • background point cloud data that may affect the package size measurement is eliminated to improve the accuracy of the package size measurement.
  • FIG1 is a schematic diagram of a scenario of a package size measurement system provided in an embodiment of the present application.
  • FIG. 2 is a flow chart of an embodiment of a method for measuring package size provided in an embodiment of the present application.
  • FIG. 3 is a schematic diagram of a flow chart of an embodiment of determining a second point cloud set provided in an embodiment of the present application.
  • FIG. 4 is a schematic diagram of a flow chart of an embodiment of determining a second point cloud set provided in an embodiment of the present application.
  • FIG. 5 is a schematic diagram of a flow chart of an embodiment of determining a package contour provided in an embodiment of the present application.
  • FIG6 is a schematic diagram of a flow chart of an embodiment of determining a candidate package point cloud set provided in an embodiment of the present application.
  • FIG. 7 is a schematic structural diagram of an embodiment of a package size measuring device provided in an embodiment of the present application.
  • FIG8 is a schematic diagram of the structure of an embodiment of a computer device provided in an embodiment of the present application.
  • first and second are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the terms “first” and “second” are limited to The features of a may include one or more of the features explicitly or implicitly. In the description of this application, the meaning of “plurality” is two or more, unless otherwise clearly and specifically defined.
  • the embodiments of the present application provide a package size measurement method, apparatus, computer equipment, and storage medium, which are described in detail below.
  • the package size measurement system may include a computer device 100, and a package size measurement device is integrated in the computer device 100, such as the computer device in Figure 1.
  • the computer device 100 is mainly used to obtain a first point cloud set corresponding to a target package of a size to be measured, and the first point cloud set is point cloud data of the target package collected in a preset package area; that is, a target package is placed in the preset package area, and the first point cloud set is a point cloud set collected from the preset package area when the target package exists in the preset package area, and the first point cloud set includes the point cloud set of the target package.
  • the target package is a package of a size to be measured.
  • An initial background point cloud set corresponding to the preset package area is obtained, and the initial background point cloud set is a point cloud data set obtained by collecting the preset package area when the target package does not exist in the preset package area; the initial background point cloud set is filtered out from the first point cloud set to obtain a second point cloud set corresponding to the target package; based on the second point cloud set, the size of the target package is determined.
  • the computer device 100 may be an independent server, or a server network or server cluster composed of servers.
  • the computer device 100 described in the embodiment of the present application includes but is not limited to a computer, a network host, a single network server, a plurality of network server sets or a cloud server composed of a plurality of servers.
  • the cloud server is composed of a large number of computers or network servers based on cloud computing.
  • the computer device 100 used in the embodiments of the present application may be a device including receiving and transmitting hardware, that is, a device having receiving and transmitting hardware capable of performing two-way communication on a two-way communication link.
  • a device may include: a cellular or other communication device having a single-line display or a multi-line display or a cellular or other communication device without a multi-line display.
  • the specific computer device 100 may be a desktop terminal or a mobile terminal, and the computer device 100 may also be one of a mobile phone, a tablet computer, a laptop computer, etc.
  • FIG. 1 is merely one application scenario of the present application and does not constitute a limitation on the application scenario of the present application.
  • Other application environments may also include more or fewer computer devices than those shown in FIG. 1 .
  • only one computer device is shown in FIG. 1 .
  • the package size measurement system may also include one or more other servers, which are not specifically limited here.
  • the package size measurement system may further include a storage module 200 for storing data, such as storing point cloud data.
  • scenario diagram of the parcel size measurement system shown in Figure 1 is only an example.
  • the parcel size measurement system and scenario described in the embodiment of the present application are intended to more clearly illustrate the technical solution of the embodiment of the present application, and do not constitute a limitation on the technical solution provided in the embodiment of the present application.
  • Ordinary technicians in this field can know that with the evolution of the parcel size measurement system and the emergence of new business scenarios, the technical solution provided in the embodiment of the present application is also applicable to similar technical problems.
  • a package size measurement method is provided in an embodiment of the present application.
  • the execution subject of the package size measurement method is a package size measurement device, and the package size measurement device is applied to a computer device.
  • the package size measurement method includes: obtaining a first point cloud set.
  • the first point cloud set is the point cloud data of the target package collected in a preset package area, and the target package is the package whose size is to be measured; obtaining an initial background point cloud set corresponding to the preset package area, and the initial background point cloud set is a point cloud data set obtained by collecting the preset package area when there is no target package in the preset package area; filtering out the initial background point cloud set in the first point cloud set to obtain a second point cloud set corresponding to the target package; and determining the size of the target package based on the second point cloud set.
  • FIG. 2 it is a schematic diagram of a flow chart of a method for measuring the size of a package in an embodiment of the present application.
  • the method for measuring the size of a package includes:
  • initial background point cloud set i.e., initial background point cloud data
  • the package size measurement method provided in the embodiment of the present application is applicable to the field of logistics, especially packages on a conveying device such as a conveyor belt.
  • the shooting angle of the RGBD (RGB-Depth) camera that usually obtains the package point cloud data is directly above, and the point cloud data of the bottom of the package cannot be obtained, resulting in inaccurate recognition of the package size, especially inaccurate recognition of irregular package size.
  • first point cloud set containing the target package whose size is to be measured; wherein the first point cloud set is the point cloud data of the target package collected in a preset package area (usually an area on a conveyor belt). It is also necessary to obtain initial background point cloud data (i.e., initial background point cloud set) corresponding to the preset package area, and the initial background point cloud data does not include any package, but only the background (when the preset package area is a conveyor belt, the background is the conveyor belt).
  • initial background point cloud data i.e., initial background point cloud set
  • the area outside the target package is considered to be the background area.
  • the point cloud data in the first point cloud set includes both the point cloud data of the target package and the point cloud data of the background area except the target package; therefore, it is necessary to remove the initial background point cloud set in the first point cloud set to avoid the point cloud data of the background area affecting the determination of the target package size.
  • the first point cloud data (i.e., the first point cloud set) in this application is usually the point cloud data of a target package; and the initial background point cloud data does not include any package, and is the point cloud data obtained by collecting the preset package area when there is no target package in the preset package area, for example, only the point cloud data corresponding to the conveyor belt.
  • the present application needs to filter out the initial background point cloud in the first point cloud set to obtain the second point cloud set corresponding to the target package; and then determine the size of the target package based on the second point cloud set.
  • the first point cloud set and the initial background point cloud set are obtained by using an RGBD camera or other device; and the first point cloud set includes multiple point cloud coordinates, and the initial background point cloud also includes multiple point cloud coordinates.
  • the point clouds in the first point cloud set and the initial background point cloud set are all three-dimensional coordinates of (x, y, z).
  • the package size measurement method provided in the embodiment of the present application includes: obtaining a first point cloud set including a target package to be measured, the first point cloud set being point cloud data collected for a preset package area where the target package is placed, the target package is located in the preset package area, so the first point cloud set is a point cloud set including the target package; obtaining an initial background point cloud set of the preset package area; filtering out the initial background point cloud set in the first point cloud set to obtain a second point cloud set corresponding to the target package; and determining the size of the target package based on the second point cloud set.
  • background point cloud data that may affect the package size measurement is eliminated to improve the accuracy of the package size measurement.
  • a schematic diagram of a flow chart of an embodiment of determining a second point cloud set provided in an embodiment of the present application may include:
  • the entire preset package area can be regarded as the background area.
  • the background area needs to be modeled to obtain a standard reference coordinate system.
  • the corresponding initial background point cloud set determines the coordinate system corresponding to the background.
  • the preset package area is a conveyor belt, so the plane where the conveyor belt is located can be set as the xy plane in the coordinate system corresponding to the background, and the origin in the standard reference coordinate system is also located on the plane where the conveyor belt is located; and the z-axis in the standard reference coordinate system is perpendicular to the plane where the conveyor belt is located.
  • the initial background point cloud set P can be subjected to principal component analysis, and the initial background point cloud set P can be regarded as a set of eigenvectors, and the point clouds in the initial background point cloud set P can be projected into an orthogonal coordinate system consisting of a first direction, a second direction, and a third direction that are perpendicular to each other.
  • the specific directions of the first direction, the second direction, and the third direction can be continuously adjusted (the first direction, the second direction, and the third direction must still be perpendicular to each other during the adjustment process) so that the projection error of the point cloud data corresponding to a certain first direction, second direction, and third direction is minimized.
  • the eigenvector of the point cloud data can be determined, and the length of the perpendicular line from the eigenvector to the first direction, the second direction, and the third direction is calculated.
  • the projection error is the smallest; at this time, the specific directions of the first direction, the second direction, and the third direction can be determined.
  • the first direction vector of the point cloud data projected to the first direction can be calculated; similarly, the second direction vector of the point cloud data projected to the second direction can also be calculated, and the third direction vector of the point cloud data projected to the third direction can also be calculated; thereby determining the first direction vector, the second direction vector, and the third direction vector. It can be written as:
  • u can be a first direction vector
  • v can be a second direction vector
  • w can be a third direction vector.
  • the vectors of the three directions are all three-dimensional vectors, so the first direction vector, the second direction vector and the third direction vector are shown in the above formula, and all include data in the three directions of x, y, and z.
  • the process of determining a first direction vector, a second direction vector, and a third direction vector may include: projecting multiple point clouds in an initial background point cloud set to an initial first direction, an initial second direction, and an initial third direction, respectively; calculating the lengths of perpendicular lines from feature vectors corresponding to multiple point clouds to the initial first direction, the initial second direction, and the initial third direction, respectively; adjusting the initial first direction, the initial second direction, and the initial third direction so that the value of the perpendicular line length is minimized, and obtaining the first direction, the second direction, and the third direction.
  • the initial first direction, the initial second direction, and the initial third direction remain perpendicular to each other; projecting multiple point clouds in an initial background point cloud set to a first direction, a second direction, and a third direction, respectively, to obtain a first direction vector, a second direction vector, and a third direction vector.
  • the background centroid point cloud is also a three-dimensional point cloud data; and the centroid in the three-dimensional coordinate system can be obtained by determining the point cloud data corresponding to the initial background with n known coordinates; specifically, it can be obtained by calculating the average value of the point cloud coordinates of n known coordinates, as shown in the above formula.
  • N is the point cloud data in the initial background point cloud with n known coordinates.
  • the initial background point cloud in the first point cloud set is filtered out to obtain a second point cloud set of the target package.
  • the background model corresponding to the preset package area can be determined; and the second point cloud set corresponding to the target package can be obtained according to the background model.
  • FIG. 4 it is a schematic diagram of a flow chart of an embodiment of determining a second point cloud set provided in an embodiment of the present application.
  • the determination process may specifically include the following contents.
  • the coordinate system parameter T corresponding to the standard reference coordinate system can be further determined.
  • the coordinate system parameter T is as follows:
  • modeling the preset package area i.e., establishing the background model
  • the present application only converts the initial background point cloud data and the packaged point cloud data into the same standard reference coordinate system; to ensure that the point cloud data is in the same standard.
  • the coordinate system parameter T is the bridge of conversion, so the coordinate system parameter T corresponding to the standard coordinate system can be determined. If the point cloud in the first point cloud set is converted to the background model, the first point cloud set and the coordinate system parameter T can be used directly.
  • the coordinate system parameter T can be used to transform different coordinate systems into the standard coordinate system corresponding to the coordinate system parameter T; that is, the point cloud data in the first point cloud set is converted to the standard coordinate system corresponding to the coordinate system parameter T.
  • the acquisition equipment may have certain fluctuations when acquiring point cloud data corresponding to the preset package area, resulting in inaccurate point cloud data; therefore, in the present application, it is also necessary to perform coordinate conversion on the initial background point cloud data, and convert the originally inaccurate initial background point cloud data into a more accurate standard coordinate system to obtain a first background point cloud set.
  • the first background point cloud set and the third point cloud set are actually obtained by using the coordinate system parameter T.
  • it can be: according to the coordinate system parameter T and the initial background point cloud data P, coordinate transformation is performed to obtain a new point cloud, namely, the first background point cloud set Pt; wherein, That is, any point cloud Pi in the initial background point cloud data can be converted into new point cloud data using the coordinate system parameter T.
  • the coordinate system parameter T in this application is a certain matrix, and the coordinates of any point cloud data in the initial background point cloud set can also be determined; therefore, the new point cloud data after transformation can be obtained by directly calculating the product of the two.
  • the coordinate system parameter T can also be used to determine the new point cloud coordinates after the coordinate system is transformed. Specifically, as in the method for determining the first background point cloud set described above, the product between any point cloud data in the first point cloud set and the coordinate system parameter T can be calculated, which will not be repeated here.
  • the third point cloud with a z value less than z max is eliminated to obtain the second point cloud set.
  • the data in the initial background point cloud set and the first point cloud set are respectively converted into the coordinate system under the same standard to obtain the first background point cloud set and the third point cloud set, and the point cloud data corresponding to the background area in the third point cloud set needs to be further filtered out to avoid the point cloud data in the background area affecting the accuracy of the package size calculation.
  • the first background point cloud set in the third point cloud set can be removed by a straight-through filter to obtain the second point cloud set corresponding to the target package.
  • the straight-through filter can filter out the points that are not in the value range of a specified dimension, and remove the points within or outside the specified range. Therefore, in the present application, the data in the first direction, the second direction and the third direction can be filtered out separately.
  • the point cloud sets in this application all include multiple three-dimensional point clouds; that is, the first point cloud set includes multiple first point clouds, the second point cloud set includes multiple second point clouds, the third point cloud set includes multiple third point clouds, and the first background point cloud set includes multiple first background point clouds; and the multiple first point clouds, multiple second point clouds, multiple third point clouds and multiple first background point clouds are
  • the clouds are all three-dimensional point clouds of (x, y, z). Therefore, the first target point cloud with the largest z value (z max ) in the first background point cloud set can be determined; and in the third point cloud set containing the target package, the third point cloud with a z value less than z max is eliminated to obtain the second point cloud set. And the z value of each second point cloud in the second point cloud set is greater than the z value in the first target point cloud, that is, greater than z max .
  • the z value in the background point cloud data is generally 0 for the background part, while the z value of the package placed on the conveyor belt is generally greater than 0. Therefore, this application needs to determine the z max with the largest z value in the first background point cloud set to remove the abnormal values in the third point cloud set, so as to avoid the abnormal point cloud data affecting the subsequent calculation of the package size.
  • each package point cloud distance is the distance between a certain point cloud and any other point cloud.
  • a schematic diagram of a process for determining a package outline may include:
  • the seed point cloud calculate the distances of multiple package point clouds and sort the distances to obtain the candidate package point cloud set corresponding to the seed point cloud.
  • each second point cloud in the second point cloud set is obtained, and each second point cloud in the second point cloud set corresponds to a candidate package point cloud set.
  • Target package point cloud set selects the set with the largest number of point clouds (target package point cloud set) from among multiple candidate package point cloud sets as the final target package point cloud set.
  • the second point cloud set includes multiple second point clouds, and each second point cloud is a three-dimensional point cloud of (x, y, z).
  • a second point cloud in the second point cloud set as a seed point cloud, and find the adjacent points of the seed point cloud; that is, determine the point cloud that is close to the seed point cloud and may constitute the target package, so as to determine the complete candidate package point set that the target package may correspond to.
  • the specific determination method will be described in detail later.
  • each candidate package point cloud set finally obtained includes multiple second point clouds.
  • each second point cloud in the second point cloud set can be used as a seed point cloud
  • multiple candidate package point cloud sets can be obtained after each second point cloud is used as a seed point cloud.
  • each second point cloud data in the second point cloud set corresponds to a candidate package point cloud set.
  • the set with the largest number of second point clouds among multiple candidate package point sets can be selected as the package point cloud set corresponding to the target package.
  • FIG6 it is a schematic diagram of a flow chart of an embodiment of determining a candidate package point cloud set provided in an embodiment of the present application. Determining a candidate package point cloud set in the present application may include:
  • the second point cloud set includes multiple second point clouds, and in the present application, point clouds within a preset distance range around each second point cloud in the second point cloud set are respectively determined to determine the point clouds that may constitute the package, and then determine the corresponding point cloud of the target package. Therefore, in the present application, a second point cloud is first selected from the second point cloud set as a seed point cloud, and other point clouds that may form a package around the seed point cloud are determined.
  • the multiple package point cloud distances are sorted in a certain order, usually from small to large; and multiple second point clouds corresponding to a preset number of package point cloud distances located at the starting point are determined from the sorted multiple package point cloud distances.
  • the multiple second point clouds corresponding to the preset number of package point cloud distances selected form the fourth point cloud set.
  • Some of the second point clouds and seed point clouds that are closer to the seed point cloud may be the point cloud data that constitutes the target package.
  • the multiple package point cloud distances are sorted in ascending order, it is possible to determine a preset number of partial package point cloud distances starting from the starting position (which can be regarded as the first-ranked package point cloud distance).
  • the multiple second point clouds corresponding to these partial package point cloud distances are also the partial second point clouds closest to the seed point cloud. Specifically, it can be: among the sorted multiple package point cloud distances, the 20 (or other number) package point cloud distances starting from the first one (including the first one) (that is, the preset number of "package point cloud distances" starting from the starting position of the sorting of the multiple package point cloud distances).
  • the second point clouds that are closer to the seed point cloud are first screened out according to the distance, and then it is determined whether the package point cloud distance corresponding to these second point clouds is less than the preset point cloud distance threshold.
  • the package point cloud distance is less than the preset point cloud distance threshold, it can be determined that, for example, 30 second point clouds with different coordinates meet the conditions. If the second point cloud that is closer to the seed point cloud is first screened out according to the distance, for example, only the first 20 second point clouds in the sorting are screened; then it is determined whether the package point cloud distances corresponding to each of these 20 point clouds meet the threshold conditions. If all conditions are met, there are 20 second point clouds screened out, while there are 30 second point clouds selected in the aforementioned embodiment. The number of point clouds obtained by these two screening methods is completely different. Therefore, in the embodiment of the present application, it is necessary to first determine the package point cloud distances located at the starting point and a preset number among the multiple package point cloud distances after sorting; then determine whether the screened package point cloud distances meet the threshold conditions.
  • an initial candidate package point cloud set is first set, and the initial candidate package point cloud set is an empty set, that is, it does not include point cloud data.
  • the selected seed point cloud is added to the initial candidate package point cloud set, and other point clouds that are close to the seed point cloud and meet the preset conditions are added to continuously fill the initial candidate package point cloud set.
  • any selected seed point cloud is first used as a subset of the initial candidate package point cloud set corresponding to the target package; and after determining a second target point cloud that meets the conditions, the second target point cloud can be added to the initial candidate package point cloud set; at this time, the second target point cloud and the seed point cloud are both point clouds that constitute the target package.
  • any point cloud in the newly added second target point cloud as a new seed point cloud, and repeat the aforementioned steps of calculating the package point cloud distance, sorting according to the package point cloud distance, and judging whether the package point cloud distance is less than the preset point cloud distance threshold.
  • the aforementioned embodiment only judged the second target point cloud that is close to the current seed point cloud, and it is also necessary to judge the part of the second point cloud that is close to the second target point cloud; through continuous looping operations, until other second target point clouds that meet the conditions around each newly added second point cloud are determined, a complete point cloud set corresponding to the target package can be obtained.
  • any point cloud in the newly added second target point cloud can be used as a new seed point cloud, and then the parcel point cloud distances between the other second point clouds in the second point cloud set except the new seed point cloud and the new seed point cloud are calculated to obtain multiple new parcel point cloud distances.
  • the multiple new parcel point cloud distances are sorted in ascending order, and a fifth point cloud set consisting of a portion of the second point clouds corresponding to a preset number of parcel point cloud distances located at the starting point is determined from the sorted multiple new parcel point cloud distances.
  • Determining the fifth point cloud set located at the starting position here actually determines the distance of a certain number of new package point clouds located at the starting position; it is necessary to determine the distances of these new package point clouds to the corresponding second point clouds.
  • the number of point clouds in the fifth point cloud set determined here can be the same as the number of point clouds in the aforementioned fourth point cloud set. That is, in this application, each time the partial point cloud closest to the seed point cloud is determined, the number of point clouds determined can be the same.
  • the fifth point cloud set After the fifth point cloud set is determined, it is also necessary to determine whether the distances of multiple new package point clouds corresponding to the multiple point clouds in the fifth point cloud set are less than the preset point cloud distance threshold.
  • only new target point clouds whose new package point cloud distances are less than the preset point cloud distance threshold are obtained.
  • the newly confirmed target point cloud is added to the initial candidate package point cloud set to update the initial candidate package point cloud set.
  • the candidate package point cloud set includes the seed point cloud selected for the first time, the second target point cloud, and any point cloud in the second target point cloud corresponding to the seed point cloud selected for the first time is used as a new seed point cloud, and then the new target point cloud corresponding to the newly selected seed point cloud is determined.
  • the second target point clouds corresponding to different seed point clouds may be repeated; or when selecting different seed point clouds and determining the second target point clouds that meet the conditions corresponding to the seed point clouds, a point cloud may be both the second target point cloud corresponding to the seed point cloud selected for the first time and the second target point cloud corresponding to the seed point cloud selected for the second time. If this happens, only one of the multiple repeated point clouds can be retained and saved in the initial candidate package point cloud set.
  • multiple candidate package point cloud sets that may constitute the target package are determined in the second point cloud set, and the candidate package point cloud set with the most point cloud data is selected from the multiple candidate package point cloud sets as the package point cloud set corresponding to the final target package; the size of the package can be further determined based on the package point cloud set.
  • the maximum z value can be determined as the height of the target package among all the third target point clouds in the package point cloud set. Since each third target point cloud includes data in the three directions of x, y, and z, after determining the height of the target package, there is no need to consider the z value in the original third target point cloud. Therefore, all x values and y values in the package point cloud set can be extracted to form a new two-dimensional point cloud; and the two-dimensional point cloud includes multiple (x, y) two-dimensional point clouds.
  • these two-dimensional point clouds can be projected into a two-dimensional plane to determine a two-dimensional image composed of multiple two-dimensional point clouds in the two-dimensional point cloud.
  • the four vertices and length and width of the minimum circumscribed rectangle corresponding to the two-dimensional image are further determined to determine the length and width of the target package.
  • the maximum z value in all third target point clouds is determined as the height corresponding to the target package; at the same time, the x values and y values in all third target point clouds are selected to form a two-dimensional point cloud, and a two-dimensional image composed of the x values and y values in the two-dimensional point cloud is determined.
  • multiple points determined at positions can be determined in the xy plane, and any two adjacent points can be connected to determine the two-dimensional image composed of the two-dimensional point cloud.
  • the minimum bounding rectangle method is used to determine the minimum bounding rectangle corresponding to the two-dimensional image, so as to determine the length and width of the minimum bounding rectangle as the length and width of the target package.
  • the present application also provides a package size measuring device, as shown in FIG7 , which is a schematic diagram of the structure of an embodiment of a package size measuring device provided in an embodiment of the present application, and may include:
  • the package point cloud acquisition module 701 is used to acquire a first point cloud set corresponding to a target package, where the first point cloud set is point cloud data of the target package collected in a preset package area, and the target package is a package whose size is to be measured.
  • the background point cloud acquisition module 702 is used to acquire an initial background point cloud set of a preset package area.
  • the initial background point cloud set is a point cloud data set obtained by collecting data from the preset package area when there is no target package in the preset package area.
  • the package point cloud determination module 703 is used to filter out the initial background point cloud set from the first point cloud set to obtain a second point cloud set corresponding to the target package.
  • the size determination module 704 is used to determine the size of the target package based on the second point cloud set.
  • the package size measurement device obtaineds a first point cloud set corresponding to the target package to be measured, the first point cloud set being the point cloud data of the target package collected in the preset package area; obtains an initial background point cloud set corresponding to the preset package area; filters out the initial background point cloud set from the first point cloud set to obtain a second point cloud set corresponding to the target package; and determines the size of the target package based on the second point cloud set.
  • background point cloud data that may affect the package size measurement is eliminated to improve the accuracy of the package size measurement.
  • the package point cloud determination module 703 is specifically used to: establish a background model corresponding to a preset package area, wherein the background model represents a reference coordinate system; based on the background model, filter out the initial background point cloud set in the first point cloud set to obtain a second point cloud set.
  • the package point cloud determination module 703 can be used to: project multiple point clouds in the initial background point cloud set to the first direction, the second direction and the third direction respectively to determine the first direction vector, the second direction vector and the third direction vector with the smallest projection error, the first direction and the second direction are perpendicular to each other, the second direction and the third direction are perpendicular to each other, and the third direction and the first direction are perpendicular to each other; calculate the center of gravity position of the initial background point cloud set to obtain the background center of gravity point cloud coordinates; determine the background model corresponding to the preset package area according to the first direction vector, the second direction vector, the third direction vector and the background center of gravity point cloud coordinates.
  • the package point cloud determination module 703 can be used to: project multiple point clouds in the initial background point cloud set to the initial first direction, the initial second direction, and the initial third direction respectively; calculate the length of the perpendicular lines from the feature vectors corresponding to the multiple point clouds to the initial first direction, the initial second direction, and the initial third direction respectively; adjust the initial first direction, the initial second direction, and the initial third direction so that the value of the perpendicular line length is minimized, and the first direction, the second direction, and the third direction are obtained.
  • the initial first direction, the initial second direction, and the initial third direction remain perpendicular to each other; project multiple point clouds in the initial background point cloud set to the first direction, the second direction, and the third direction respectively to obtain a first direction vector, a second direction vector, and a third direction vector.
  • the package point cloud determination module 703 can be used to: based on the background model, perform coordinate transformation on multiple point clouds in the initial background point cloud set to obtain a first background point cloud set; based on the background model, perform coordinate transformation on multiple point clouds in the first point cloud set to obtain a third point cloud set, the third point cloud set includes multiple third point clouds, and the multiple third point clouds are all three-dimensional point clouds, and the three-dimensional point clouds include x value, y value and z value; determine the z value z max of the first target point cloud with the largest z value in the first background point cloud set; in the third point cloud set, eliminate the third point cloud with a z value less than z max to obtain a second point cloud set.
  • the second point cloud set includes multiple second point clouds
  • the size determination module 704 can be specifically used to: determine the package point cloud set corresponding to the target package based on multiple package point cloud distances between each second point cloud and other second point clouds in the multiple second point clouds, wherein each package point cloud distance in the multiple package point cloud distances is the distance between the second point cloud and any other second point cloud; determine the size of the target package based on the package point cloud set.
  • the size determination module 704 can be used to: use each second point cloud in the second point cloud set as a seed point cloud; sort the distances of multiple package point clouds corresponding to the seed point cloud to obtain a candidate package point cloud set corresponding to the seed point cloud; and screen out a target package point cloud set with the largest number of point clouds from the candidate package point cloud sets corresponding to the multiple second point clouds, and use the target package point cloud set as the final target package point cloud set.
  • the size determination module 704 can be used to: add the seed point cloud to a preset initial candidate package point cloud set; sort the multiple package point cloud distances corresponding to the seed point cloud in ascending order, and determine a fourth point cloud set consisting of multiple second point clouds corresponding to a preset number of package point cloud distances starting from the starting position from the sorted multiple package point cloud distances; determine a second target point cloud in the fourth point cloud set whose package point cloud distance with the seed point cloud is less than a preset point cloud distance threshold; add the second target point cloud to the initial candidate package point cloud set, and use the second target point cloud newly added to the initial candidate package point cloud set each time as the seed point cloud, cyclically execute the determination of the package point cloud distance, and based on the The new second target point cloud corresponding to the new seed point cloud is determined according to the package point cloud distance, and the new second target point cloud corresponding to the new seed point cloud is added to the initial candidate package set until no new point cloud is added to the initial candidate package point cloud set,
  • the size determination module 704 can be specifically used to: determine the maximum z value as the height of the target package for all point cloud data in the package point cloud set; extract the x values and y values corresponding to all point cloud data in the package point cloud set to form multiple two-dimensional point clouds; in a two-dimensional plane, connect the multiple two-dimensional point clouds in sequence to obtain a two-dimensional image; in the two-dimensional plane, determine the vertices and length and width of the minimum circumscribed rectangle corresponding to the two-dimensional image to obtain the length and width of the target package.
  • the embodiment of the present application further provides a computer device, which integrates any package size measuring device provided in the embodiment of the present application, and the computer device includes:
  • processors one or more processors
  • One or more applications wherein the one or more applications are stored in the memory and are configured to cause the processor to execute the steps of the package size measurement method described in any of the above package size measurement method embodiments.
  • the present application also provides a computer device that integrates any package size measuring device provided in the present application. As shown in FIG8 , it shows a schematic diagram of the structure of the computer device involved in the present application. Specifically:
  • the computer device may include components such as a processor 801 with one or more processing cores, a memory 802 with one or more computer-readable storage media, a power supply 803, and an input unit 804.
  • a processor 801 with one or more processing cores
  • a memory 802 with one or more computer-readable storage media
  • a power supply 803 with one or more computer-readable storage media
  • FIG8 does not constitute a limitation on the computer device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. Among them:
  • the processor 801 is the control center of the computer device. It uses various interfaces and lines to connect various parts of the entire computer device. By running or executing software programs and/or modules stored in the memory 802 and calling data stored in the memory 802, it executes various functions of the computer device and processes data, thereby monitoring the computer device as a whole.
  • the processor 801 may include one or more processing cores; preferably, the processor 801 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 801.
  • the memory 802 can be used to store software programs and modules.
  • the processor 801 executes various functional applications and data processing by running the software programs and modules stored in the memory 802.
  • the memory 802 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc.
  • the memory 802 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 802 may also include a memory controller to provide the processor 801 with access to the memory 802.
  • the computer device also includes a power supply 803 for supplying power to each component.
  • the power supply 803 can be logically connected to the processor 801 through a power management system, so as to manage charging, discharging, and power consumption through the power management system.
  • the power supply 803 can also include any components such as one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, and power status indicators.
  • the computer device may further include an input unit 804, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.
  • an input unit 804 which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.
  • the computer device may further include a display unit, etc., which will not be described in detail herein.
  • the processor 801 in the computer device will load the executable files corresponding to the processes of one or more application programs into the memory 802 according to the following instructions, and the processor 801 will run the application programs stored in the memory 802, thereby realizing various functions, as follows:
  • the background point cloud set is a point cloud data set obtained by collecting the preset package area when there is no target package in the preset package area; the initial background point cloud set is filtered out in the first point cloud set to obtain the second point cloud set of the target package; based on the second point cloud set, the size of the target package is determined.
  • the embodiment of the present application provides a computer-readable storage medium, which may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.
  • ROM read-only memory
  • RAM random access memory
  • a computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in any of the package size measurement methods provided in the embodiment of the present application.
  • the computer program can be loaded by the processor to execute the following steps:
  • a first point cloud set corresponding to a target package is obtained, where the first point cloud set is point cloud data of the target package collected in a preset package area, and the target package is a package whose size is to be measured; an initial background point cloud set of the preset package area is obtained, where the initial background point cloud set is a point cloud data set obtained by collecting the preset package area when there is no target package in the preset package area; the initial background point cloud set is filtered out from the first point cloud set to obtain a second point cloud set of the target package; and the size of the target package is determined based on the second point cloud set.
  • the above units or structures can be implemented as independent entities, or can be arbitrarily combined to be implemented as the same or several entities.
  • the specific implementation of the above units or structures can refer to the previous method embodiments, which will not be repeated here.

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Abstract

本申请提供一种包裹尺寸测量方法、装置、计算机设备及存储介质，包括：获取待测量尺寸的目标包裹对应的第一点云集合，第一点云集合为采集到的目标包裹在预设包裹区域的点云数据；获取预设包裹区域对应的初始背景点云集合；在第一点云集合中滤除初始背景点云集合，得到目标包裹对应的第二点云集合；基于第二点云集合，确定目标包裹的尺寸。本申请中剔除了可能影响包裹尺寸测量的背景点云数据，以提高包裹尺寸测量的精度。

Description

包裹尺寸测量方法、装置、计算机设备及存储介质 技术领域
本申请涉及物流领域，具体涉及一种包裹尺寸测量方法、装置、计算机设备及存储介质。
发明背景
在物流领域中，包裹的形状复杂多样，如何快速可靠的计算出不规则包裹的尺寸是非常有价值的。在实际应用中，由于包裹形状复杂以及点云质量的原因，常常使得计算出的长宽高方向与实际方向偏差过大，导致尺寸计算错误。
发明内容
本申请实施例提供一种包裹尺寸测量方法，旨在提高现有技术中的包裹尺寸测量方法所存在的尺寸误差较大的问题。
第一方面，本申请提供一种包裹尺寸测量方法，所述包裹尺寸测量方法包括：
在本申请一些实施方案中，获取目标包裹对应的第一点云集合，所述第一点云集合为采集到的所述目标包裹在预设包裹区域的点云数据，所述目标包裹为待测量尺寸的包裹；获取所述预设包裹区域的初始背景点云集合，所述初始背景点云集合是所述预设包裹区域不存在目标包裹时，对所述预设包裹区域进行采集得到的点云数据集；在所述第一点云集合中滤除所述初始背景点云集合，得到所述目标包裹对应的第二点云集合；基于所述第二点云集合，确定所述目标包裹的尺寸。
在本申请一些实施方案中，所述在所述第一点云集合中滤除所述初始背景点云集合，得到所述目标包裹对应的第二点云集合，包括：建立所述预设包裹区域对应的背景模型，其中，所述背景模型表征一个参考坐标系；基于所述背景模型，将所述第一点云集合中的所述初始背景点云集合滤除，得到所述第二点云集合。
在本申请一些实施方案中，所述建立所述预设包裹区域对应的背景模型，包括：将所述初始背景点云集合中的多个点云分别投射到第一方向、第二方向和第三方向上，以确定投射误差最小的第一方向向量、第二方向向量和第三方向向量，所述第一方向和所述第二方向互相垂直，所述第二方向和所述第三方向互相垂直，所述第三方向和所述第一方向互相垂直；计算所述初始背景点云集合的重心位置，得到背景重心点云坐标；根据所述第一方向向量、所述第二方向向量、所述第三方向向量和所述背景重心点云坐标，确定所述预设包裹区域对应的背景模型。
在本申请一些实施方案中，所述将所述初始背景点云集合中的多个点云分别投射到第一方向、第二方向和第三方向上，以确定投射误差最小的第一方向向量、第二方向向量和第三方向向量，包括：将所述初始背景点云集合中的所述多个点云分别投射到初始第一方向、初始第二方向和初始第三方向上；计算所述多个点云对应的特征向量分别到所述初始第一方向、所述初始第二方向和所述初始第三方向的垂线长度；对所述初始第一方向、所述初始第二方向和所述初始第三方向进行调整，使得所述垂线长度的值最小，并得到所述第一方向、所述第二方向和所述第三方向，在调整过程中，所述初始第一方向、所述初始第二方向和所述初始第三方向保持两两互相垂直；将所述初始背景点云集合中的所述多个点云分别投射到所述第一方向、所述第二方向和所述第三方向上，得到所述第一方向向量，所述第二方向向量和所述第三方向向量。
在本申请一些实施方案中，所述基于所述背景模型，将所述第一点云集合中的所述初始背景点云集合滤除，得到所述第二点云集合，包括：基于所述背景模型，对所述初始背景点 云集合中的多个点云进行坐标变换，得到第一背景点云集合；基于所述背景模型，对所述第一点云集合中的多个点云进行坐标变换，得到第三点云集合，所述第三点云集合中包括多个第三点云，所述多个第三点云均为三维点云，所述三维点云包括x值、y值和z值；确定所述第一背景点云集合中，z值最大的第一目标点云的z值zmax；在所述第三点云集合中，剔除z值小于zmax的第三点云，得到所述第二点云集合。
在本申请一些实施方案中，所述第二点云集合中包括多个第二点云，所述基于所述第二点云集合，确定所述目标包裹的尺寸，包括：根据所述多个第二点云中每个第二点云与其他第二点云之间的多个包裹点云距离，确定所述目标包裹对应的包裹点云集合，其中，所述多个包裹点云距离中每个包裹点云距离为所述第二点云与其他任一第二点云的距离；根据所述包裹点云集合，确定所述目标包裹的尺寸。
在本申请一些实施方案中，所述根据所述多个第二点云中每个第二点云与其他第二点云之间的多个包裹点云距离，确定所述目标包裹对应的包裹点云集合，包括：将所述第二点云集合中的每个第二点云作为种子点云；对所述种子点云对应的多个包裹点云距离进行距离排序，获得所述种子点云对应的候选包裹点云集合；在所述多个第二点云分别对应的候选包裹点云集合中，筛选出点云数量最多的目标包裹点云集合，并将所述目标包裹点云集合作为最终的所述目标包裹的包裹点云集合。
在本申请一些实施方案中，所述对所述种子点云对应的多个包裹点云距离进行距离排序，获得所述种子点云对应的候选包裹点云集合，包括：将所述种子点云添加到预设的初始候选包裹点云集合；按照从小到大的顺序，对所述种子点云对应的多个包裹点云距离进行排序，并在排序后的多个包裹点云距离中确定从起始位置开始的预设数量的包裹点云距离对应的多个第二点云组成的第四点云集合；确定所述第四点云集合中，与所述种子点云之间的包裹点云距离小于预设点云距离阈值的第二目标点云；将所述第二目标点云加入所述初始候选包裹点云集合中，并以每次新加入所述初始候选包裹点云集合的第二目标点云为种子点云，循环执行确定包裹点云距离，并根据包裹点云距离确定新的种子点云对应的新的第二目标点云，并将新的种子点云对应的新的第二目标点云加入所述初始候选包裹集合的操作，直至所述初始候选包裹点云集合中没有新的点云加入，得到所述候选包裹点云集合。
在本申请一些实施方案中，所述根据所述包裹点云集合，确定所述目标包裹的尺寸，包括：针对所述包裹点云集合的所有点云数据，确定最大的z值作为所述目标包裹的高度；抽取所述包裹点云集合中所有点云数据分别对应的x值和y值，组成多个二维点云；在二维平面中，将所述多个二维点云依次相连，得到二维图像；在二维平面中，确定所述二维图像对应的最小外接矩形的顶点和长宽，以得到所述目标包裹的长宽。
第二方面，本申请提供一种包裹尺寸测量装置，所述包裹尺寸测量装置包括：包裹点云获取模块，用于获取目标包裹对应的第一点云集合，所述第一点云集合为采集到的所述目标包裹在预设包裹区域的点云数据，所述目标包裹为待测量尺寸的包裹；背景点云获取模块，用于获取所述预设包裹区域的初始背景点云集合，所述初始背景点云集合是所述预设包裹区域不存在目标包裹时，对所述预设包裹区域进行采集得到的点云数据集；包裹点云确定模块，用于在所述第一点云集合中滤除所述初始背景点云集合，得到所述目标包裹对应的第二点云集合；尺寸确定模块，用于基于所述第二点云集合，确定所述目标包裹的尺寸。
在本申请一些实施方案中，所述包裹点云确定模块具体用于：建立所述预设包裹区域对应的背景模型，其中，所述背景模型表征一个参考坐标系；基于所述背景模型，将所述第一点云集合中的所述初始背景点云集合滤除，得到所述第二点云集合。
在本申请一些实施方案中，所述包裹点云确定模块用于：将所述初始背景点云集合中的多个点云分别投射到第一方向、第二方向和第三方向上，以确定投射误差最小的第一方向向量、第二方向向量和第三方向向量，所述第一方向和所述第二方向互相垂直，所述第二方向和所述第三方向互相垂直，所述第三方向和所述第一方向互相垂直；计算所述初始背景点云 集合的重心位置，得到背景重心点云坐标；根据所述第一方向向量、所述第二方向向量、所述第三方向向量和所述背景重心点云坐标，确定所述预设包裹区域对应的背景模型。
在本申请一些实施方案中，所述第二点云集合中包括多个第二点云，所述尺寸确定模块具体用于：根据所述多个第二点云中每个第二点云与其他第二点云之间的多个包裹点云距离，确定所述目标包裹对应的包裹点云集合，其中，所述多个包裹点云距离中每个包裹点云距离为所述第二点云与其他任一第二点云的距离；根据所述包裹点云集合，确定所述目标包裹的尺寸。
第三方面，本申请还提供一种计算机设备，所述计算机设备包括：一个或多个处理器；存储器；以及一个或多个应用程序，其中所述一个或多个应用程序被存储于所述存储器中，并配置为由所述处理器执行以实现第一方面中任一项所述的包裹尺寸测量方法。
第四方面，本申请还提供一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器进行加载，以执行第一方面任一项所述的包裹尺寸测量方法中的步骤。
本申请提供一种包裹尺寸测量方法、装置、计算机设备及存储介质，包括：获取待测量尺寸的目标包裹对应的第一点云集合，第一点云集合为采集到的所述目标包裹在预设包裹区域的点云数据；获取预设包裹区域对应的初始背景点云集合；在第一点云集合中滤除初始背景点云集合，得到目标包裹对应的第二点云集合；基于第二点云集合，确定所述目标包裹的尺寸。本申请中剔除了可能影响包裹尺寸测量的背景点云数据，以提高包裹尺寸测量的精度。
附图简要说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本申请实施例提供的包裹尺寸测量系统的场景示意图。
图2是本申请实施例中提供的包裹尺寸测量方法的一个实施例流程示意图。
图3为本申请实施例提供的确定第二点云集合的一实施例流程示意图。
图4为本申请实施例提供的确定第二点云集合的一实施例流程示意图。
图5为本申请实施例提供的确定包裹轮廓一实施例流程示意图。
图6为本申请实施例提供的确定候选包裹点云集合一实施例流程示意图。
图7是本申请实施例中提供的包裹尺寸测量装置的一个实施例结构示意图。
图8是本申请实施例中提供的计算机设备的一个实施例结构示意图。
实施本发明的方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
在本申请的描述中，需要理解的是，术语“中心”、“纵向”、“横向”、“长度”、“宽度”、“厚度”、“上”、“下”、“前”、“后”、“左”、“右”、“竖直”、“水平”、“顶”、“底”、“内”、“外”等指示的方位或位置关系为基于附图所示的方位或位置关系，仅是为了便于描述本申请和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本申请的限制。此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二” 的特征可以明示或者隐含地包括一个或者更多个所述特征。在本申请的描述中，“多个”的含义是两个或两个以上，除非另有明确具体的限定。
在本申请中，“示例性”一词用来表示“用作例子、例证或说明”。本申请中被描述为“示例性”的任何实施例不一定被解释为比其它实施例更优选或更具优势。为了使本领域任何技术人员能够实现和使用本申请，给出了以下描述。在以下描述中，为了解释的目的而列出了细节。应当明白的是，本领域普通技术人员可以认识到，在不使用这些特定细节的情况下也可以实现本申请。在其它实例中，不会对公知的结构和过程进行详细阐述，以避免不必要的细节使本申请的描述变得晦涩。因此，本申请并非旨在限于所示的实施例，而是与符合本申请所公开的原理和特征的最广范围相一致。
需要说明的是，本申请实施例方法由于是在电子设备中执行，各电子设备的处理对象均以数据或信息的形式存在，例如时间，实质为时间信息，可以理解的是，后续实施例中若提及尺寸、数量、位置等，均为对应的数据存在，以便电子设备进行处理，具体此处不作赘述。
本申请实施例提供一种包裹尺寸测量方法、装置、计算机设备及存储介质，以下分别进行详细说明。
请参阅图1，图1为本申请实施例所提供的包裹尺寸测量系统的场景示意图，该包裹尺寸测量系统可以包括计算机设备100，计算机设备100中集成有包裹尺寸测量装置，如图1中的计算机设备。
本申请实施例中计算机设备100主要用于获取待测量尺寸的目标包裹对应的第一点云集合，第一点云集合为采集到的目标包裹在预设包裹区域的点云数据；即在预设包裹区域，放置有目标包裹，第一点云集合为预设包裹区域存在目标包裹时，对预设包裹区域采集的点云集合，第一点云集合包括了目标包裹的点云集合。目标包裹为待测量尺寸的包裹。获取预设包裹区域对应的初始背景点云集合，初始背景点云集合是预设包裹区域不存在目标包裹时，对预设包裹区域进行采集得到的点云数据集；在第一点云集合中滤除初始背景点云集合，得到目标包裹对应的第二点云集合；基于第二点云集合，确定目标包裹的尺寸。
本申请实施例中，该计算机设备100可以是独立的服务器，也可以是服务器组成的服务器网络或服务器集群，例如，本申请实施例中所描述的计算机设备100，其包括但不限于计算机、网络主机、单个网络服务器、多个网络服务器集或多个服务器构成的云服务器。其中，云服务器由基于云计算(Cloud Computing)的大量计算机或网络服务器构成。
可以理解的是，本申请实施例中所使用的计算机设备100可以是包括接收和发射硬件的设备，即具有能够在双向通信链路上，执行双向通信的接收和发射硬件的设备。这种设备可以包括：蜂窝或其他通信设备，其具有单线路显示器或多线路显示器或没有多线路显示器的蜂窝或其他通信设备。具体的计算机设备100具体可以是台式终端或移动终端，计算机设备100具体还可以是手机、平板电脑、笔记本电脑等中的一种。
本领域技术人员可以理解，图1中示出的应用环境，仅仅是本申请方案一种应用场景，并不构成对本申请方案应用场景的限定，其他的应用环境还可以包括比图1中所示更多或更少的计算机设备，例如图1中仅示出1个计算机设备，可以理解的，该包裹尺寸测量系统还可以包括一个或多个其他服务器，具体此处不作限定。
另外，如图1所示，该包裹尺寸测量系统还可以包括存储模块200，用于存储数据，如存储点云数据。
需要说明的是，图1所示的包裹尺寸测量系统的场景示意图仅仅是一个示例，本申请实施例描述的包裹尺寸测量系统以及场景是为了更加清楚的说明本申请实施例的技术方案，并不构成对于本申请实施例提供的技术方案的限定，本领域普通技术人员可知，随着包裹尺寸测量系统的演变和新业务场景的出现，本申请实施例提供的技术方案对于类似的技术问题，同样适用。
首先，本申请实施例中提供一种包裹尺寸测量方法，该包裹尺寸测量方法的执行主体为包裹尺寸测量装置，该包裹尺寸测量装置应用于计算机设备，该包裹尺寸测量方法包括：获取第一点云集合，如上所述，第一点云集合为采集到的目标包裹在预设包裹区域的点云数据，目标包裹为待测量尺寸的包裹；获取预设包裹区域对应的初始背景点云集合，初始背景点云集合是预设包裹区域不存在目标包裹时，对预设包裹区域进行采集得到的点云数据集；在第一点云集合中滤除初始背景点云集合，得到目标包裹对应的第二点云集合；基于第二点云集合，确定目标包裹的尺寸。
如图2所示，为本申请实施例中包裹尺寸测量方法的一个实施例流程示意图，该包裹尺寸测量方法包括：
21、获取目标包裹的第一点云集合，第一点云集合为采集到的目标包裹在预设包裹区域的点云数据。
22、获取预设包裹区域对应的初始背景点云集合(即初始背景点云数据)。
本申请实施例提供的包裹尺寸测量方法适用于物流领域，尤其是位于传送装置如传送带上的包裹。对于这一类包裹来说，通常获取包裹点云数据的RGBD(RGB-Depth)相机的拍摄角度为正上方，无法获取包裹底部的点云数据，从而导致包裹的尺寸识别不准，尤其是对不规则的包裹尺寸识别不准。
本申请中需要获取包含待测量尺寸的目标包裹的第一点云集合；其中，第一点云集合为采集到的目标包裹在预设包裹区域(通常为传送带上的某个区域)的点云数据。还需要获取预设包裹区域对应的初始背景点云数据(即初始背景点云集合)，而初始背景点云数据中不包括任何包裹，仅包括背景(当预设包裹区域为传送带时则背景是传送带)。
需要说明的是，在预设包裹区域中，当存在目标包裹时，目标包裹之外的区域被认为是背景区域。第一点云集合中的点云数据同时包括目标包裹的点云数据以及除目标包裹外的背景区域的点云数据；因此才需要去除第一点云集合中的初始背景点云集合，避免背景区域的点云数据影响目标包裹尺寸的确定。且本申请中的第一点云数据(即第一点云集合)通常为一个目标包裹的点云数据；而初始背景点云数据不包括任何包裹，是预设包裹区域不存在目标包裹时，对所述预设包裹区域进行采集获得的点云数据，例如仅为传送带对应的点云数据。
23、在第一点云集合中滤除初始背景点云集合，得到目标包裹对应的第二点云集合。
24、基于第二点云集合，确定目标包裹的尺寸。
由于获取到的第一点云集合中也包括背景对应的部分点云数据，因此本申请中需要在第一点云集合中滤除初始背景点云，以得到目标包裹对应的第二点云集合；进而根据第二点云集合，确定目标包裹的尺寸大小。
需要说明的是，在本申请的实施例中，是利用RGBD相机或其他装置获取到第一点云集合和初始背景点云集合；且第一点云集合中包括多个点云坐标，初始背景点云中也包括多个点云坐标。第一点云集合和初始背景点云集合中的点云均为(x，y，z)的三维坐标。
本申请实施例提供的包裹尺寸测量方法，包括：获取包含待测量尺寸的目标包裹的第一点云集合，第一点云集合为针对放置有目标包裹的预设包裹区域采集到的点云数据，所述目标包裹位于所述预设包裹区域中，所以第一点云集合是包括目标包裹的点云集合的；获取预设包裹区域的初始背景点云集合；在第一点云集合中滤除初始背景点云集合，得到目标包裹对应的第二点云集合；基于第二点云集合，确定目标包裹的尺寸。本申请中剔除了可能影响包裹尺寸测量的背景点云数据，以提高包裹尺寸测量的精度。
如图3所示，为本申请实施例提供的确定第二点云集合的一实施例流程示意图，可以包括：
31、将初始背景点云集合中的点云分别投射到两两互相垂直的第一方向、第二方向和第三方向上，以确定投射误差最小的第一方向向量、第二方向向量和第三方向向量。
在本申请中，若是预设包裹区域不存在目标包裹，则整个预设包裹区域可以看作是背景区域，首先需要对背景区域进行建模，得到一个标准的参考坐标系。具体可以利用背景区域 对应的初始背景点云集合确定背景对应的坐标系。且在本申请的实施例中，预设包裹区域为传送带，因此可以将传送带所在的平面设定为背景对应的坐标系中的xy平面，标准的参考坐标系中的原点也位于传送带所在的平面上；而标准的参考坐标系中的z轴垂直于传送带所在的平面。
首先确定初始背景点云集合P＝{p1,p2,…,pn}，其中初始背景点云中的每一个坐标均为：
可以对初始背景点云集合P进行主成分分析，将初始背景点云集合P视为一组特征向量，将初始背景点云集合P中的点云投射到一个两两垂直的第一方向、第二方向和第三方向组成的正交坐标系下。在上述投射的过程中，可以不断调整第一方向、第二方向和第三方向的具体方向(调整过程中仍要保证第一方向、第二方向和第三方向两两互相垂直)，使得点云数据在某个确定的第一方向、第二方向和第三方向下对应的投射误差最小。其中，可以确定点云数据的特征向量，并计算特征向量分别到第一方向、第二方向和第三方向做垂线的垂线长度。当垂线长度最小时，即投射误差最小；此时第一方向、第二方向和第三方向的具体方向可以确定。且点云数据投射到第一方向上的第一方向向量可以计算得到；同理点云数据投射到第二方向上的第二方向向量也可以计算得到，点云数据投射到第三方向上的第三方向向量也可以计算得到；从而确定第一方向向量、第二方向向量和第三方向向量。可以记作：
其中，u可以为第一方向向量、v可以为第二方向向量，w可以为第三方向向量。且本申请中三个方向的向量均为三维的向量，因此第一方向向量、第二方向向量和第三方向向量如上公式所示，均包括x、y、z三个方向的数据。
在一示例中，确定第一方向向量、第二方向向量和第三方向向量的过程可包括：将初始背景点云集合中的多个点云分别投射到初始第一方向、初始第二方向和初始第三方向上；计算多个点云对应的特征向量分别到初始第一方向、初始第二方向和初始第三方向的垂线长度；对初始第一方向、初始第二方向和初始第三方向进行调整，使得垂线长度的值最小，并得到第一方向、第二方向和第三方向，在调整过程中，初始第一方向、初始第二方向和初始第三方向保持两两互相垂直；将初始背景点云集合中的多个点云分别投射到第一方向、第二方向和第三方向上，得到第一方向向量，第二方向向量和第三方向向量。
32、计算初始背景点云集合的重心位置，得到背景重心点云坐标。
本申请中还需要计算初始背景点云集合的重心位置，得到背景重心点云坐标(xc、yc，zc)。具体可以为：
其中，背景重心点云也是一个三维的点云数据；而三维坐标系中的重心可以通过确定初始背景对应的点云数据中n个坐标已知的点云计算得到；具体可以计算n个坐标已知的点云坐标的均值得到，如上公式所示。N即为n个坐标已知的初始背景点云中的点云数据，通过求和并计算均值可以得到背景重心对应x、y、z的具体值。
33、根据第一方向向量、第二方向向量、第三方向向量和背景重心点云坐标，确定坐标系参数，根据坐标系参数确定预设包裹区域对应的背景模型。
34、基于背景模型，将第一点云集合中的初始背景点云滤除，得到目标包裹的第二点云集合。
在确定了第一方向向量、第二方向向量、第三方向向量和背景重心点云坐标后，就可以确定预设包裹区域对应的背景模型；以根据背景模型得到目标包裹对应的第二点云集合。
如图4所示，为本申请实施例提供的确定第二点云集合一实施例流程示意图，确定过程(步骤34)具体可以包括如下内容。
41、基于背景模型，对初始背景点云集合中的所有点云进行坐标变换，得到第一背景点云集合。
42、基于背景模型，对所述第一点云集合中的所有点云进行坐标变换，得到第三点云集合。
在确定第一方向向量、第二方向向量、第三方向向量以及背景重心点云坐标后，就可以进一步确定标准的参考坐标系对应的坐标系参数T。在一个具体实施例中，坐标系参数T如下：
在上述实施例中，对预设包裹区域进行建模(即背景模型的建立)实际上就是根据预设包裹区域确定一个标准的参考坐标系；本申请只是将初始背景点云数据和包裹的点云数据转换到同一个标准的参考坐标系中；以保证点云数据处于同一标准。而坐标系参数T则是转换的桥梁，因此可以确定标准坐标系对应的坐标系参数T。若是将第一点云集合中的点云转换到背景模型中，直接利用第一点云集合和坐标系参数T即可。利用坐标系参数T可以将不同坐标系变换到坐标系参数T对应的标准坐标系下；即将第一点云集合中的点云数据转换到坐标系参数T对应的标准坐标系下。
同时，在本申请的实施例中，由于在采集预设包裹区域对应的点云数据时，采集设备会存在一定的波动导致点云数据不够准确；因此本申请中还需要将初始背景点云数据也进行坐标转换，将原本不够精确的初始背景点云数据转换到更加准确的标准坐标系中，得到第一背景点云集合。
在上述实施例中，实际上是利用坐标系参数T得到第一背景点云集合和第三点云集合。具体可以为：根据坐标系参数T和初始背景点云数据P，进行坐标变换得到新的点云，即第一背景点云集合Pt；其中，即初始背景点云数据中的任意点云Pi都可以利用坐标系参数T得到转换后的新的点云数据。
其中，代表初始背景点云集合中的任意点云经过坐标系参数T变换得到的新的点云数据；而计算得到的方法即为：计算坐标系参数T和初始背景点云集合中任意点云数据Pi之间的乘积。本申请中的坐标系参数T为一个确定的矩阵，而初始背景点云集合中的任意点云数据的坐标也是可以确定的；因此直接计算两者的乘积即可到达变换后的新的点云数据。
同理，对于目标包裹对应的第一点云集合P0＝(P1、P2…Pm)来说，也可以利用坐标系参数T确定变换坐标系后的新的点云坐标。具体如前述确定第一背景点云集合中的方法，计算第一点云集合中任意点云数据与坐标系参数T之间的乘积即可，此处不再赘述。
43、确定第一背景点云集合中，z值最大的第一目标点云的z值zmax。
44、在第三点云集合中，剔除z值小于zmax的第三点云，得到第二点云集合。
上述实施例中分别将初始背景点云集合和第一点云集合中的数据，转换同一标准下的坐标系中，分别获得第一背景点云集合和第三点云集合，还需要进一步滤除第三点云集合中的背景区域对应的点云数据，以避免背景区域的点云数据影响包裹尺寸计算的准确性。具体地，可以利用直通滤波器去除第三点云集合中的第一背景点云集合，得到目标包裹对应的第二点云集合。其中，直通滤波器可以针对指定的某一维度，将这个维度上不在取值范围的点过滤掉，去掉指定范围内或范围外的点。因此本申请中可以第一方向、第二方向和第三方向上的数据分别滤除。
本申请中的点云集合中均包括多个三维点云；即第一点云集合中包括多个第一点云、第二点云集合中包括多个第二点云、第三点云集合中包括多个第三点云、第一背景点云集合中包括多个第一背景点云；且多个第一点云、多个第二点云、多个第三点云和多个第一背景点 云均为(x，y，z)的三维点云。因此可以确定第一背景点云集合中，z值最大(zmax)的第一目标点云；并在包含目标包裹的第三点云集合中，剔除z值小于zmax的第三点云，得到第二点云集合。且第二点云集合中的每个第二点云的z值，均大于前述第一目标点云中的z值，即大于zmax。
由于本申请中以传送带所在平面为坐标系中的xy平面，因此对于背景部分来说，背景的点云数据中的z值一般为0；而放置在传送带上的包裹的z值一般大于0。因此本申请需要在第一背景点云集合中确定z值最大的zmax以将第三点云集合中的异常值剔除，避免异常的点云数据影响后续对包裹尺寸的计算。
在上述实施例中，虽然在第一点云集合中去除背景部分的点云数据得到了第二点云集合，但由于获取点云数据时的精度问题，以及在去除背景部分的点云数据和滤波过程中的不完全性；因此还需要对第二点云集合中的数据进行二次筛选，确定最终目标包裹对应的包裹点云集合。本申请中可以计算第二点云集合中各点云与其他点云之间的多个包裹点云距离，以在第二点云集合中确定目标包裹对应的包裹点云集合，以根据包裹点云集合确定目标包裹的轮廓，进而确定目标包裹的尺寸大小。其中，各包裹点云距离为某一点云与其他任一点云之间的距离。
如图5所示，为本申请实施例提供的确定包裹轮廓一实施例流程示意图，可以包括：
51、在第二点云集合中任意选取一个第二点云作为种子点云。
52、根据种子点云，计算多个包裹点云距离并进行距离排序，获得种子点云对应的候选包裹点云集合。
53、在第二点云集合中的各第二点云均作为种子点云完成上述步骤后，得到多个候选包裹点云集合，第二点云集合中每个第二点云均对应一个候选包裹点云集合。
54、选取多个候选包裹点云集合中，点云数量最多的集合(目标包裹点云集合)作为最终的目标包裹的包裹点云集合。
本申请中第二点云集合中包括多个第二点云，且每个第二点云均为(x，y，z)的三维点云。首先可以在第二点云集合中任意选取一个第二点云作为种子点云，并寻找种子点云的临近点；即确定与种子点云相距较近的，可能组成目标包裹的点云，以此确定目标包裹可能对应的完整的候选包裹点集，具体确定方式后续会具体阐述。其中，最终获得的各候选包裹点云集合中均包括多个第二点云。
由于第二点云集合中的每一个第二点云均可以作为种子点云，因此当每个第二点云均作为种子点云后，可以得到多个候选包裹点云集合。且第二点云集合中的每个第二点云数据均对应一个候选包裹点云集合。本申请中可以选取多个候选包裹点集中，第二点云数量最大的集合作为目标包裹对应的包裹点云集合。
如图6所示，为本申请实施例提供的确定候选包裹点云集合一实施例流程示意图。本申请中确定候选包裹点云集合可以包括：
61、将种子点云添加到目标包裹对应的预设的初始候选包裹点云集合，该初始候选包裹点云集合的初始状态是空集。
62、分别计算第二点云集合中除种子点云外的其他点云，与种子点云之间的距离，得到多个包裹点云距离。
63、按照从小到大的顺序对多个包裹点云距离进行排序，并在排序后的多个包裹点云距离中确定从起始位置开始处的，预设数量的包裹点云距离对应的多个第二点云组成的第四点云集合。
64、确定第四点云集合中，与种子点云之间的包裹点云距离小于预设点云距离阈值的第二目标点云。
第二点云集合中包括多个第二点云，而本申请中通过分别确定第二点云集合中的每个第二点云周围预设距离范围内的点云，以确定可能组成包裹的点云，进而确定目标包裹对应的 包裹点云集合。因此本申请中首先在第二点云集合中选取一个第二点云作为种子点云，并确定种子点云周围可能组成包裹的其他点云。
具体地，需要分别计算第二点云集合中除种子点云外的其他点云，与种子点云之间的距离，得到多个包裹点云距离。并按照一定的顺序对多个包裹点云距离进行排序，通常为从小到大的顺序进行排序；并在排序后的多个包裹点云距离中确定位于起始处的，预设数量的多个包裹点云距离对应的多个第二点云。而筛选出的预设数量的多个包裹点云距离对应的多个第二点云组成第四点云集合。
之所以需要计算包裹点云距离并进行排序筛选，是为了筛选出距离种子点云较近的第二点云，距离种子点云较近的部分第二点云和种子点云可能为组成目标包裹的点云数据。
由于按照从小到大的顺序对多个包裹点云距离进行了排序，因此可以确定从起始位置开始的(可以看作是排序第一的包裹点云距离)，预设数量的部分包裹点云距离，这部分包裹点云距离对应的多个第二点云也是最靠近种子点云的部分第二点云。具体可以为：在排序后的多个包裹点云距离中，从第一个开始(包括第一个)往后20个(或其他数量)的包裹点云距离(即从多个包裹点云距离排序的起始位置开始的预设数量个“包裹点云距离”)。接着还需要进一步判断筛选出的部分包裹点云距离，是否小于预设点云距离阈值；只有小于预设点云距离阈值的第二点云，才能确认为组成目标包裹的点云，即为第二目标点云。
需要说明的是，本申请中并不直接判断多个包裹点云距离是否小于预设点云距离阈值；而是先按照距离筛选出距离种子点云较近的部分第二点云，再判断这些第二点云对应的包裹点云距离是否小于预设点云距离阈值。
在一个具体实施例中，若是直接判断包裹点云距离是否小于预设点云距离阈值，则可以确定例如30个不同坐标的第二点云满足条件。而若是先按照距离筛选出距离种子点云较近的部分第二点云，则例如仅筛选排序前20的第二点云；再判断这20个点云各自对应的包裹点云距离是否满足阈值条件。若是都满足条件，则筛选出的第二点云有20个，而前述实施例中选取的第二点云有30个。这两种筛选方法得到的点云的数量是完全不同的。因此在本申请的实施例中，需要先在排序后的多个包裹点云距离中，确定位于起始处且预设数量的包裹点云距离；再确定筛选出的这些包裹点云距离是否满足阈值条件。
本申请中首先设定一个初始候选包裹点云集合，而初始候选包裹点云集合中为空集，即并不包括点云数据。此时将选取的种子点云加入初始候选包裹点云集合中，并加入与种子点云相距较近且满足预设条件的其他点云，以不断填充初始候选包裹点云集合。
65、将第二目标点云加入初始候选包裹点云集合中，并在第二点云集合中，以任一第二目标点云(之前位于第二点云集合中的位置为依据)为新的种子点云，按照上述步骤循环执行确定各个第二目标点云的包裹点云距离排序，并根据包裹点云距离确定新的种子点云对应的新的第二目标点云，并将新的种子点云对应的新的第二目标点云加入所述初始候选包裹点云集合的操作，直至初始候选包裹点云集合中没有新的点云加入(即所有的第二目标点云作为种子点云进行上述步骤的循环结束)，得到候选包裹点云集合。
在本申请的实施例中，首先将选取的任一种子点云作为目标包裹对应的初始候选包裹点云集合的子集；而在确定了满足条件的第二目标点云后，可以将第二目标点云加入初始候选包裹点云集合中；此时第二目标点云和种子点云均是组成目标包裹的点云。
同时，在本申请的实施例中，还需要再以新加入的第二目标点云中的任意点云为新的种子点云，并重复前述计算包裹点云距离、根据包裹点云距离排序以及判断包裹点云距离是否小于预设点云距离阈值的步骤。这是因为前述实施例中仅判断了与当前种子点云相距较近的第二目标点云，还需要判断与第二目标点云相距较近的部分第二点云；通过不断的循环操作，直至确定每一个新加入的第二点云周围满足条件的其他第二目标点云，才能得到目标包裹对应的完整的点云集合。
具体地，可以将新加入的第二目标点云中的任意点云作为新的种子点云，此时再分别计算第二点云集合中除新的种子点云外的其他第二点云，与新的种子点云之间的包裹点云距离，得到多个新的包裹点云距离。同样地按照从小到大的顺序对多个新的包裹点云距离进行排序，并在排序后的多个新的包裹点云距离中确定位于起始处的，预设数量的包裹点云距离对应的部分第二点云组成的第五点云集合。
此处确定位于起始位置处(即起始处)的第五点云集合，实际上是确定位于起始位置处的一定数量的新的包裹点云距离；需要确定这些新的包裹点云距离各自对应的第二点云。此处确定的第五点云集合中的点云的数量，可以与前述第四点云集合中点云的数量相同。即本申请中在每次确定距离种子点云最近的部分点云时，确定的点云的数量可以相同。
在确定了第五点云集合后，还需要判断第五点云集合中的多个点云对应的多个新的包裹点云距离，是否小于预设点云距离阈值。此处也仅获取新的包裹点云距离小于预设点云距离阈值的新的目标点云。并将新确认的目标点云加入到初始候选包裹点云集合中，以更新初始候选包裹点云集合。此时的候选包裹点云集合中包括第一次选取的种子点云、第二目标点云和将第一次选取的种子点云对应的第二目标点云中的任意点云作为新的种子点云后，确定新选取的种子点云对应的新的目标点云。
在上述更新初始候选包裹点云集合的过程中，不同的种子点云对应的第二目标点云之间可能存在重复；或者说选取不同的种子点云并确定种子点云对应的满足条件的第二目标点云时，某个点云可能既是第一次选取的种子点云对应的第二目标点云；也是第二次选取的种子点云对应的第二目标点云。若出现这种情况，则将多个重复的点云仅保留一个保存在初始候选包裹点云集合中即可。
本申请中需要在初始候选包裹点云集合中加入新的点云的同时，再以新加入的点云作为种子点云，并计算新的种子点云与第二点云集合中的其他点云之间的点云距离。根据新的点云距离确定与新的种子点云相距较近，且点云距离小于预设点云距离阈值的点云。并将新的点云加入初始候选包裹点云集合中，直至初始候选包裹点云集合中不再加入新的点云，初始候选包裹点云集合不再更新。此时不再更新的初始候选包裹点云，即为种子点云对应的候选包裹点云。
上述实施例中，在第二点云集合中确定了可能组成目标包裹的多个候选包裹点云集合，并在多个候选包裹点云集合中选取了点云数据最多的候选包裹点云集合作为最终的目标包裹对应的包裹点云集合；可以进一步根据包裹点云集合确定包裹的尺寸大小。具体地，可以在包裹点云集合的所有第三目标点云中，确定最大的z值作为目标包裹的高度。又由于每个第三目标点云均包括x、y、z三个方向的数据，在确定了目标包裹的高度后，无需考虑原本第三目标点云中的z值。因此可以将包裹点云集合中所有的x值和y值抽取出来，组成新的二维点云；而二维点云中包括多个(x，y)的二维点云。
在确定了多个二维点云后，可以将这些二维点云投射到二维平面中，确定二维点云中的多个二维点云组成的二维图像。并进一步确定二维图像对应的最小外接矩形的四个顶点和长宽，以确定目标包裹的长宽尺寸。
上述实施例中，确定所有第三目标点云中的最大z值作为目标包裹对应的高；同时选取所有第三目标点云中的x值和y值组成二维点云，并确定二维点云中的x值和y值组成的二维图像。其中，根据所有的二维点云可以在xy平面确定多个位置确定的点，而将任意相邻的两个点连接起来即可确定二维点云组成的二维图像。利用最小外接矩形法，确定二维图像对应的最小外接矩形，以确定最小外接矩形的长宽，作为目标包裹的长宽。
本申请还提供一种包裹尺寸测量装置，如图7所示，为本申请实施例提供的包裹尺寸测量装备一实施例结构示意图，可以包括：
包裹点云获取模块701，用于获取目标包裹对应的第一点云集合，第一点云集合为采集到的目标包裹在预设包裹区域的点云数据，所述目标包裹为待测量尺寸的包裹。
背景点云获取模块702，用于获取预设包裹区域的初始背景点云集合，初始背景点云集合是预设包裹区域不存在目标包裹时，对预设包裹区域进行采集得到的点云数据集。
包裹点云确定模块703，用于在第一点云集合中滤除初始背景点云集合，得到目标包裹对应的第二点云集合。
尺寸确定模块704，用于基于第二点云集合，确定目标包裹的尺寸。
本申请实施例提供的包裹尺寸测量装置，获取待测量尺寸的目标包裹对应的第一点云集合，第一点云集合为采集到的目标包裹在预设包裹区域的点云数据；获取预设包裹区域对应的初始背景点云集合；在第一点云集合中滤除初始背景点云集合，得到目标包裹对应的第二点云集合；基于第二点云集合，确定目标包裹的尺寸。本申请中剔除了可能影响包裹尺寸测量的背景点云数据，以提高包裹尺寸测量的精度。
在一些实施例中，包裹点云确定模块703具体用于：建立预设包裹区域对应的背景模型，其中，背景模型表征一个参考坐标系；基于背景模型，将第一点云集合中的初始背景点云集合滤除，得到第二点云集合。
在一些实施例中，包裹点云确定模块703可以用于：将初始背景点云集合中的多个点云分别投射到第一方向、第二方向和第三方向上，以确定投射误差最小的第一方向向量、第二方向向量和第三方向向量，所述第一方向和所述第二方向互相垂直，所述第二方向和所述第三方向互相垂直，所述第三方向和所述第一方向互相垂直；计算初始背景点云集合的重心位置，得到背景重心点云坐标；根据第一方向向量、第二方向向量、第三方向向量和背景重心点云坐标，确定预设包裹区域对应的背景模型。
在一些实施例中，包裹点云确定模块703可以用于：将初始背景点云集合中的多个点云分别投射到初始第一方向、初始第二方向和初始第三方向上；计算多个点云对应的特征向量分别到初始第一方向、初始第二方向和初始第三方向的垂线长度；对初始第一方向、初始第二方向和初始第三方向进行调整，使得垂线长度的值最小，并得到第一方向、第二方向和第三方向，在调整过程中，初始第一方向、初始第二方向和初始第三方向保持两两互相垂直；将初始背景点云集合中的多个点云分别投射到第一方向、第二方向和第三方向上，得到第一方向向量，第二方向向量和第三方向向量。
在一些实施例中，包裹点云确定模块703可以用于：基于背景模型，对初始背景点云集合中的多个点云进行坐标变换，得到第一背景点云集合；基于背景模型，对第一点云集合中的多个点云进行坐标变换，得到第三点云集合，第三点云集合中包括多个第三点云，多个第三点云均为三维点云，三维点云包括x值、y值和z值；确定第一背景点云集合中，z值最大的第一目标点云的z值zmax；在第三点云集合中，剔除z值小于zmax的第三点云，得到第二点云集合。
在一些实施例中，第二点云集合中包括多个第二点云，尺寸确定模块704具体可以用于：根据多个第二点云中每个第二点云与其他第二点云之间的多个包裹点云距离，确定目标包裹对应的包裹点云集合，其中，多个包裹点云距离中每个包裹点云距离为第二点云与其他任一第二点云的距离；根据包裹点云集合，确定目标包裹的尺寸。
在一些实施例中，尺寸确定模块704可以用于：将第二点云集合中的每个第二点云作为种子点云；对种子点云对应的多个包裹点云距离进行距离排序，获得种子点云对应的候选包裹点云集合；在多个第二点云分别对应的候选包裹点云集合中，筛选出点云数量最多的目标包裹点云集合，并将目标包裹点云集合作为最终的目标包裹的包裹点云集合。
在一些实施例中，尺寸确定模块704可以用于：将所述种子点云添加到预设的初始候选包裹点云集合；按照从小到大的顺序，对种子点云对应的多个包裹点云距离进行排序，并在排序后的多个包裹点云距离中确定从起始位置开始的预设数量的包裹点云距离对应的多个第二点云组成的第四点云集合；确定第四点云集合中，与种子点云之间的包裹点云距离小于预设点云距离阈值的第二目标点云；将第二目标点云加入初始候选包裹点云集合中，并以每次新加入初始候选包裹点云集合的第二目标点云为种子点云，循环执行确定包裹点云距离，并根 据包裹点云距离确定新的种子点云对应的新的第二目标点云，并将新的种子点云对应的新的第二目标点云加入初始候选包裹集合的操作，直至初始候选包裹点云集合中没有新的点云加入，得到候选包裹点云集合。
在一些实施例中，尺寸确定模块704具体可以用于：针对包裹点云集合的所有点云数据，确定最大的z值作为目标包裹的高度；抽取包裹点云集合中所有点云数据分别对应的x值和y值，组成多个二维点云；在二维平面中，将多个二维点云依次相连，得到二维图像；在二维平面中，确定二维图像对应的最小外接矩形的顶点和长宽，以得到目标包裹的长宽。
本申请实施例还提供一种计算机设备，其集成了本申请实施例所提供的任一种包裹尺寸测量装置，所述计算机设备包括：
一个或多个处理器；
存储器；以及
一个或多个应用程序，其中所述一个或多个应用程序被存储于所述存储器中，并配置为由所述处理器执行上述包裹尺寸测量方法实施例中任一实施例中所述的包裹尺寸测量方法中的步骤。
本申请实施例还提供一种计算机设备，其集成了本申请实施例所提供的任一种包裹尺寸测量装置。如图8所示，其示出了本申请实施例所涉及的计算机设备的结构示意图，具体来讲：
该计算机设备可以包括一个或者一个以上处理核心的处理器801、一个或一个以上计算机可读存储介质的存储器802、电源803和输入单元804等部件。本领域技术人员可以理解，图8中示出的计算机设备结构并不构成对计算机设备的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。其中：
处理器801是该计算机设备的控制中心，利用各种接口和线路连接整个计算机设备的各个部分，通过运行或执行存储在存储器802内的软件程序和/或模块，以及调用存储在存储器802内的数据，执行计算机设备的各种功能和处理数据，从而对计算机设备进行整体监控。可选的，处理器801可包括一个或多个处理核心；优选的，处理器801可集成应用处理器和调制解调处理器，其中，应用处理器主要处理操作系统、用户界面和应用程序等，调制解调处理器主要处理无线通信。可以理解的是，上述调制解调处理器也可以不集成到处理器801中。
存储器802可用于存储软件程序以及模块，处理器801通过运行存储在存储器802的软件程序以及模块，从而执行各种功能应用以及数据处理。存储器802可主要包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的应用程序(比如声音播放功能、图像播放功能等)等；存储数据区可存储根据计算机设备的使用所创建的数据等。此外，存储器802可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他易失性固态存储器件。相应地，存储器802还可以包括存储器控制器，以提供处理器801对存储器802的访问。
计算机设备还包括给各个部件供电的电源803，优选的，电源803可以通过电源管理系统与处理器801逻辑相连，从而通过电源管理系统实现管理充电、放电、以及功耗管理等功能。电源803还可以包括一个或一个以上的直流或交流电源、再充电系统、电源故障检测电路、电源转换器或者逆变器、电源状态指示器等任意组件。
该计算机设备还可包括输入单元804，该输入单元804可用于接收输入的数字或字符信息，以及产生与用户设置以及功能控制有关的键盘、鼠标、操作杆、光学或者轨迹球信号输入。
尽管未示出，计算机设备还可以包括显示单元等，在此不再赘述。具体在本实施例中，计算机设备中的处理器801会按照如下的指令，将一个或一个以上的应用程序的进程对应的可执行文件加载到存储器802中，并由处理器801来运行存储在存储器802中的应用程序，从而实现各种功能，如下：
获取目标包裹对应的第一点云集合，第一点云集合为采集到的目标包裹在预设包裹区域的点云数据，目标包裹为待测量尺寸的包裹；获取预设包裹区域的初始背景点云集合，初始 背景点云集合是预设包裹区域不存在目标包裹时，对预设包裹区域进行采集得到的点云数据集；在第一点云集合中滤除初始背景点云集合，得到目标包裹的第二点云集合；基于第二点云集合，确定目标包裹的尺寸。
本领域普通技术人员可以理解，上述实施例的各种方法中的全部或部分步骤可以通过指令来完成，或通过指令控制相关的硬件来完成，该指令可以存储于一计算机可读存储介质中，并由处理器进行加载和执行。
为此，本申请实施例提供一种计算机可读存储介质，该存储介质可以包括：只读存储器(ROM，Read Only Memory)、随机存取记忆体(RAM，Random Access Memory)、磁盘或光盘等。其上存储有计算机程序，所述计算机程序被处理器进行加载，以执行本申请实施例所提供的任一种包裹尺寸测量方法中的步骤。例如，所述计算机程序被处理器进行加载可以执行如下步骤：
获取目标包裹对应的第一点云集合，第一点云集合为采集到的目标包裹在预设包裹区域的点云数据，目标包裹为待测量尺寸的包裹；获取预设包裹区域的初始背景点云集合，初始背景点云集合是预设包裹区域不存在目标包裹时，对预设包裹区域进行采集得到的点云数据集；在第一点云集合中滤除初始背景点云集合，得到目标包裹的第二点云集合；基于第二点云集合，确定目标包裹的尺寸。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述的部分，可以参见上文针对其他实施例的详细描述，此处不再赘述。
具体实施时，以上各个单元或结构可以作为独立的实体来实现，也可以进行任意组合，作为同一或若干个实体来实现，以上各个单元或结构的具体实施可参见前面的方法实施例，在此不再赘述。
以上各个操作的具体实施可参见前面的实施例，在此不再赘述。
以上对本申请实施例所提供的一种包裹尺寸测量方法、装置、计算机设备及存储介质进行了详细介绍，本文中应用了具体个例对本申请的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本申请的方法及其核心思想；同时，对于本领域的技术人员，依据本申请的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本申请的限制。

Claims (15)

  1. 一种包裹尺寸测量方法，其特征在于，所述包裹尺寸测量方法包括：
    获取目标包裹对应的第一点云集合，所述第一点云集合为采集到的所述目标包裹在预设包裹区域的点云数据，所述目标包裹为待测量尺寸的包裹；
    获取所述预设包裹区域的初始背景点云集合，所述初始背景点云集合是所述预设包裹区域不存在目标包裹时，对所述预设包裹区域进行采集得到的点云数据集；
    在所述第一点云集合中滤除所述初始背景点云集合，得到所述目标包裹对应的第二点云集合；
    基于所述第二点云集合，确定所述目标包裹的尺寸。
  2. 根据权利要求1所述的包裹尺寸测量方法，其特征在于，所述在所述第一点云集合中滤除所述初始背景点云集合，得到所述目标包裹对应的第二点云集合，包括：
    建立所述预设包裹区域对应的背景模型，其中，所述背景模型表征一个参考坐标系；
    基于所述背景模型，将所述第一点云集合中的所述初始背景点云集合滤除，得到所述第二点云集合。
  3. 根据权利要求2所述的包裹尺寸测量方法，其特征在于，所述建立所述预设包裹区域对应的背景模型，包括：
    将所述初始背景点云集合中的多个点云分别投射到第一方向、第二方向和第三方向上，以确定投射误差最小的第一方向向量、第二方向向量和第三方向向量，所述第一方向和所述第二方向互相垂直，所述第二方向和所述第三方向互相垂直，所述第三方向和所述第一方向互相垂直；
    计算所述初始背景点云集合的重心位置，得到背景重心点云坐标；
    根据所述第一方向向量、所述第二方向向量、所述第三方向向量和所述背景重心点云坐标，确定所述预设包裹区域对应的背景模型。
  4. 根据权利要求3所述的包裹尺寸测量方法，其特征在于，所述将所述初始背景点云集合中的多个点云分别投射到第一方向、第二方向和第三方向上，以确定投射误差最小的第一方向向量、第二方向向量和第三方向向量，包括：
    将所述初始背景点云集合中的所述多个点云分别投射到初始第一方向、初始第二方向和初始第三方向上；
    计算所述多个点云对应的特征向量分别到所述初始第一方向、所述初始第二方向和所述初始第三方向的垂线长度；
    对所述初始第一方向、所述初始第二方向和所述初始第三方向进行调整，使得所述垂线长度的值最小，并得到所述第一方向、所述第二方向和所述第三方向，在调整过程中，所述初始第一方向、所述初始第二方向和所述初始第三方向保持两两互相垂直；
    将所述初始背景点云集合中的所述多个点云分别投射到所述第一方向、所述第二方向和所述第三方向上，得到所述第一方向向量，所述第二方向向量和所述第三方向向量。
  5. 根据权利要求2～4中任一项所述的包裹尺寸测量方法，其特征在于，所述基于所述背景模型，将所述第一点云集合中的所述初始背景点云集合滤除，得到所述第二点云集合，包括：
    基于所述背景模型，对所述初始背景点云集合中的多个点云进行坐标变换，得到第一背景点云集合；
    基于所述背景模型，对所述第一点云集合中的多个点云进行坐标变换，得到第三点云集合，所述第三点云集合中包括多个第三点云，所述多个第三点云均为三维点云，所述三维点云包括x值、y值和z值；
    确定所述第一背景点云集合中，z值最大的第一目标点云的z值zmax；
    在所述第三点云集合中，剔除z值小于zmax的第三点云，得到所述第二点云集合。
  6. 根据权利要求1～5中的任一项所述的包裹尺寸测量方法，其特征在于，所述第二点云集合中包括多个第二点云，所述基于所述第二点云集合，确定所述目标包裹的尺寸，包括：
    根据所述多个第二点云中每个第二点云与其他第二点云之间的多个包裹点云距离，确定所述目标包裹对应的包裹点云集合，其中，所述多个包裹点云距离中每个包裹点云距离为所述第二点云与其他任一第二点云的距离；
    根据所述包裹点云集合，确定所述目标包裹的尺寸。
  7. 根据权利要求6所述的包裹尺寸测量方法，其特征在于，所述根据所述多个第二点云中每个第二点云与其他第二点云之间的多个包裹点云距离，确定所述目标包裹对应的包裹点云集合，包括：
    将所述第二点云集合中的每个第二点云作为种子点云；
    对所述种子点云对应的多个包裹点云距离进行距离排序，获得所述种子点云对应的候选包裹点云集合；
    在所述多个第二点云分别对应的候选包裹点云集合中，筛选出点云数量最多的目标包裹点云集合，并将所述目标包裹点云集合作为最终的所述目标包裹的包裹点云集合。
  8. 根据权利要求7所述的包裹尺寸测量方法，其特征在于，所述对所述种子点云对应的多个包裹点云距离进行距离排序，获得所述种子点云对应的候选包裹点云集合，包括：
    将所述种子点云添加到预设的初始候选包裹点云集合；
    按照从小到大的顺序，对所述种子点云对应的多个包裹点云距离进行排序，并在排序后的多个包裹点云距离中确定从起始位置开始的预设数量的包裹点云距离对应的多个第二点云组成的第四点云集合；
    确定所述第四点云集合中，与所述种子点云之间的包裹点云距离小于预设点云距离阈值的第二目标点云；
    将所述第二目标点云加入所述初始候选包裹点云集合中，并以每次新加入所述初始候选包裹点云集合的第二目标点云为种子点云，循环执行确定包裹点云距离，并根据包裹点云距离确定新的种子点云对应的新的第二目标点云，并将新的种子点云对应的新的第二目标点云加入所述初始候选包裹集合的操作，直至所述初始候选包裹点云集合中没有新的点云加入，得到所述候选包裹点云集合。
  9. 根据权利要求6～8中任一项所述的包裹尺寸测量方法，其特征在于，所述根据所述包裹点云集合，确定所述目标包裹的尺寸，包括：
    针对所述包裹点云集合的所有点云数据，确定最大的z值作为所述目标包裹的高度；
    抽取所述包裹点云集合中所有点云数据分别对应的x值和y值，组成多个二维点云；
    在二维平面中，将所述多个二维点云依次相连，得到二维图像；
    在二维平面中，确定所述二维图像对应的最小外接矩形的顶点和长宽，以得到所述目标包裹的长宽。
  10. 一种包裹尺寸测量装置，其特征在于，所述包裹尺寸测量装置包括：
    包裹点云获取模块，用于获取目标包裹对应的第一点云集合，所述第一点云集合为采集到的所述目标包裹在预设包裹区域的点云数据，所述目标包裹为待测量尺寸的包裹；
    背景点云获取模块，用于获取所述预设包裹区域的初始背景点云集合，所述初始背景点云集合是所述预设包裹区域不存在目标包裹时，对所述预设包裹区域进行采集得到的点云数据集；
    包裹点云确定模块，用于在所述第一点云集合中滤除所述初始背景点云集合，得到所述目标包裹对应的第二点云集合；
    尺寸确定模块，用于基于所述第二点云集合，确定所述目标包裹的尺寸。
  11. 根据权利要求10所述的包裹尺寸测量装置，其特征在于，所述包裹点云确定模块具体用于：
    建立所述预设包裹区域对应的背景模型，其中，所述背景模型表征一个参考坐标系；
    基于所述背景模型，将所述第一点云集合中的所述初始背景点云集合滤除，得到所述第二点云集合。
  12. 根据权利要求11所述的包裹尺寸测量装置，其特征在于，所述包裹点云确定模块用于：
    将所述初始背景点云集合中的多个点云分别投射到第一方向、第二方向和第三方向上，以确定投射误差最小的第一方向向量、第二方向向量和第三方向向量，所述第一方向和所述第二方向互相垂直，所述第二方向和所述第三方向互相垂直，所述第三方向和所述第一方向互相垂直；
    计算所述初始背景点云集合的重心位置，得到背景重心点云坐标；
    根据所述第一方向向量、所述第二方向向量、所述第三方向向量和所述背景重心点云坐标，确定所述预设包裹区域对应的背景模型。
  13. 根据权利要求10～12中任一项所述的包裹尺寸测量装置，其特征在于，所述第二点云集合中包括多个第二点云，所述尺寸确定模块具体用于：
    根据所述多个第二点云中每个第二点云与其他第二点云之间的多个包裹点云距离，确定所述目标包裹对应的包裹点云集合，其中，所述多个包裹点云距离中每个包裹点云距离为所述第二点云与其他任一第二点云的距离；
    根据所述包裹点云集合，确定所述目标包裹的尺寸。
  14. 一种计算机设备，其特征在于，所述计算机设备包括：
    一个或多个处理器；
    存储器；以及
    一个或多个应用程序，其中所述一个或多个应用程序被存储于所述存储器中，并配置为由所述处理器执行以实现权利要求1至9中任一项所述的包裹尺寸测量方法。
  15. 一种计算机可读存储介质，其特征在于，其上存储有计算机程序，所述计算机程序被处理器进行加载，以执行权利要求1至9任一项所述的包裹尺寸测量方法中的步骤。
PCT/CN2023/126186 2022-10-24 2023-10-24 包裹尺寸测量方法、装置、计算机设备及存储介质 WO2024088251A1 (zh)

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