Container damage quantification method, system and equipment based on geometric calibration and medium

Abstract

The invention provides a geometric calibration-based container damage quantification method, a geometric calibration-based container damage quantification system, a geometric calibration-based container damage quantification device and a medium, and is applied to the technical field of wharf container damage detection. Determining relative positions and spatial layouts of each component (such as a container door, a container front, side surfaces, a top surface and the like) of the container, and further deducing specific working conditions of the container, so as to establish a quantization vector scale of each component of the container in the image under the working conditions; and finally, quantitative results such as the damaged position of the container and the actual size of the damaged frame are obtained by utilizing the established geometric model and the quantitative vector scale, and quantitative processing of the damaged container is realized.

Description

Technical Field

[0001] The present application relates to the technical field of container damage detection at a terminal, and in particular to a method, system, device and medium for quantifying container damage based on geometric calibration. Background Art

[0002] During long-distance transportation and frequent loading and unloading of containers, containers often suffer varying degrees of damage due to external impact, improper loading and unloading, or vibration during long-distance transportation. These damages not only affect the service life of the container, but may also threaten the safety of the goods. Therefore, accurately quantifying the size of these damages is crucial for the maintenance and safe use of containers.

[0003] Some existing solutions directly predict the category and location information of container damage from images, such as CN112819793A, CN115187535A, CN115222697A, etc. Although they can realize the recognition and classification of container damage, the damage recognition based on images is limited to predicting the category and approximate location of damage, and does not consider the quantification of damage size, which affects the reliability of repair and maintenance decisions. Other existing technologies detect container damage based on images and point cloud data, such as CN110992337A and CN115965885A, etc., which achieve more accurate recognition and quantification of damage by obtaining three-dimensional structural information of containers through laser radar scanning, but rely on the use of laser radar scanning to obtain point cloud data, which increases the hardware and computing cost, maintenance difficulty and system complexity of container damage detection and quantification systems. In some logistics and port environments, it is not feasible to deploy and use laser radar. Summary of the invention

[0004] In view of this, the present invention provides a container damage quantification method, system, device and medium based on geometric calibration, which establishes a geometric model according to a two-dimensional image, and facilitates the establishment of a new quantitative vector scale based on the known standard size of the actual container, so as to calculate quantitative data such as the damage position and the size of the marking box using the quantitative scale.

[0005] The present invention provides the following technical solutions: The present invention provides a container damage quantification method based on geometric calibration, comprising: Based on the segmentation result of the container image, a geometric model of each component of the container in the container image is constructed, wherein each component includes one or more of the following parts: container door, container front, side, top, corner surface; Determine the relative position and spatial layout of each of the components according to the position of the corner piece and the segmentation result, and infer the specific working condition of the container according to the relative position and spatial layout; Combined with the standard dimensions of different box types and corner pieces, quantitative vector scales are established for each of the components; The actual position of the container damage is determined based on the geometric model and the quantized vector scale established in the image; and the actual size of the damage frame is calculated based on the quantized vector scale established on the surface where the container damage is located.

[0006] Compared with the prior art, the beneficial effects that can be achieved by at least one of the above technical solutions adopted by the present invention include at least: 1. The present invention establishes a geometric model of each part of the container in the image, realizes the inference of the specific working condition of the container based on the two-dimensional image, and establishes a quantitative vector scale of the door, front, side and top surface of the container, realizing the geometric calibration of the two-dimensional image; 2. The present invention determines the location of the damage by combining the standard size of the container with the segmentation result, and calculates the actual size of the damage frame based on the established quantitative vector scale; 3. The present invention achieves the size quantification of container damage only through two-dimensional images and image segmentation technology, avoiding expensive lidar equipment and complex data processing procedures, simplifying the implementation of the damage quantification system, and reducing the hardware cost, maintenance difficulty and overall complexity of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0008] Figure 1 It is an overall schematic diagram of container damage quantification processing based on geometric calibration in this application; Figure 2 is a flow chart of the container damage quantification method in the present application; Figure 3 It is a schematic diagram of calculating the actual size of the damaged frame based on the vector ruler in this application; Figure 4 is a flow chart of a container damage quantification method in this application; Figure 5 It is a schematic diagram of the structure of the container damage quantification system based on geometric calibration in this application; Figure 6 It is a schematic diagram of the structure of the electronic device in this application. DETAILED DESCRIPTION

[0009] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0010] The following describes the implementation methods of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The present application can also be implemented or applied through other different specific implementation methods, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that, in the absence of conflict, the following embodiments and the features in the embodiments can be combined with each other. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work belong to the scope of protection of the present application.

[0011] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present application, it should be understood by those skilled in the art that an aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number and aspect described herein can be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this device and / or practice this method.

[0012] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present application. The drawings only show components related to the present application rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0013] Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the examples can be practiced without these specific details.

[0014] The existing container damage detection quantification technology, on the one hand, only predicts the category and location information of container damage based on images, which cannot provide the basic conditions required for quantification, resulting in the inability to quantify the damage size. On the other hand, the solution based on images and point cloud data increases the hardware and computing costs, maintenance difficulty and system complexity of the container damage detection system, and has poor practical feasibility in terminal application scenarios.

[0015] In view of this, the present invention proposes a container damage quantification method based on geometric calibration: Figure 1As described above, a geometric model of each part of the container is constructed based on the image segmentation result, and the actual specific working conditions of the container (such as the relative positions and spatial layouts of the door, front, side and top surfaces) are introduced to establish a standardized quantitative vector scale. Therefore, the position and size of the damaged container can be quantified in combination with the geometric model and the quantitative vector scale. For example, in the size quantification, the size of the damage frame is calculated using the basis vector scale of the surface on which it is located, and finally the quantification of the container damage can be achieved.

[0016] The technical solutions provided by various embodiments of the present application are described below in conjunction with the accompanying drawings.

[0017] like Figure 2 As shown, the present invention provides a container damage quantification method, which may include: Step S202: constructing geometric models of various components of the container in the container image based on the segmentation result of the container image, wherein each component includes one or more of the following parts: container door, container front, side, top, and corner surface.

[0018] It should be noted that the camera equipment used to collect images of containers is usually subject to some restrictions such as the site and shooting requirements, and can only be fixedly deployed in certain places and shoot at specific angles, etc. This is also the reason why the solution of using radar to form point cloud data does not have the actual deployment capability in actual applications. Therefore, if some calibration measures cannot be effectively adopted in the processing, the processing conditions are not met when quantifying the damage based on the two-dimensional image, which is also the reason why the aforementioned existing technology fails to provide quantification capabilities.

[0019] Therefore, the present invention aims at the relevant positions where damage may appear on the container and combines the quantification needs. It first segments the various components that may be related to quantification from the collected container image data, such as the container door, front, side, top, corner surface, etc., and constructs geometric models of these components. By converting the two-dimensional container image into a geometric model, it is convenient to perform geometric calibration transformation on the actually collected two-dimensional image based on the geometric model.

[0020] Step S204: determine the relative position and spatial layout of each component according to the corner fitting position and the segmentation result, and infer the specific working condition of the container according to the relative position and spatial layout.

[0021] After establishing the geometric model of each component, the positional relationship, spatial layout, etc. of each part can be determined according to the corner fittings, and then the specific working condition of the container can be inferred based on some prior knowledge, that is, the specific working condition of the actual placement of the container in the two-dimensional image.

[0022] During implementation, since the corner fittings of the container are located at the connection between the top surface and the side surface, the present invention uses the corner fittings as prior knowledge to determine the relative position and spatial layout between these surfaces, and then infer the actual specific working condition (i.e., placement posture) of the container in the two-dimensional image.

[0023] Step S206: Combine the standard sizes of different box types and corner pieces to establish quantitative vector scales for each component in the image.

[0024] Since the captured two-dimensional images have different proportions on each side of the box due to the limitation of the acquisition angle, we can combine the standard box, that is, use the standard sizes of different box types and corner fittings to establish a scale for the container in the graphic, so as to facilitate the use of the scale for quantification in subsequent processing.

[0025] It should be noted that establishing a quantization vector scale can be said to be predicting a new scale (ie, a new scale) of the two-dimensional image.

[0026] Step S208: determine the actual location of the container damage based on the geometric model and the quantized vector scale established in the image, and calculate the actual size of the damage frame based on the quantized vector scale established on the surface where the container damage is located.

[0027] Based on the geometric model and ruler, the actual location and size of the damaged container can be quantified.

[0028] In some embodiments, when building a geometric model for each surface, reference may be made to the preferred examples provided below, that is, further considering the actual conditions of these surfaces in the two-dimensional image, so that the constructed geometric model is more consistent with the actual container conditions in the two-dimensional image, which helps to improve the quantification accuracy.

[0029] For example, in establishing the geometric model of the box door and the box front, corner point detection is used to find the coordinates of the four vertices of the box door and the box front that appear in the image, or the coordinates of the five vertices of the incomplete box door and the box front that are missing a corner, and their coordinates are sorted counterclockwise starting from the upper left corner, and the geometric model of the box door and the box front is constructed based on the sorting results.

[0030] For example, in constructing the geometric model of the top surface, when the top surface is an incomplete box top that only contains one end of the container in the image, corner point detection is used to find the four vertex coordinates of the partial box top that only contains one end in the image, and their coordinates are sorted counterclockwise starting from the upper left corner, and the geometric model of the top surface is constructed according to the sorting results.

[0031] For example, when constructing a geometric model of the side, when the side is a complete side or an incomplete container side that only contains one end of the container in the image, corner point detection is used to find the four vertex coordinates of the partial container top that only contains one end or the four vertex coordinates of the complete container side in the image, and their coordinates are sorted counterclockwise starting from the upper left corner, and the geometric model of the side is constructed according to the sorting results.

[0032] For example, when constructing the geometric model of the corner piece surface, when the top and side corner piece surfaces are the corner piece top surfaces or corner piece side surfaces that exist on the top or side of the box in the image, image processing is used to find their minimum circumscribed rectangle to construct the geometric model of the corner piece surface.

[0033] In some embodiments, when determining the working condition, the relative positions and spatial layout of the components may be made more consistent with the actual situation of the container in the two-dimensional image based on the examples provided below.

[0034] Therefore, when determining the relative position and spatial layout of each component, if the container image contains only a single box, the door, front, side, top and corner fittings detected in the image are classified as the same box; if the container image contains multiple boxes, the door, front, side, top and corner fittings belonging to the same box are classified as the same box using the center distance of each component.

[0035] In some implementations, since the quantization vector scale is a new scale for subsequently quantizing damage appearing in a two-dimensional image, preferred examples of establishing the scale may refer to the following embodiments.

[0036] For example, in establishing a quantitative vector scale for a container door or front, if the door or front is complete, a pair of basis vectors are formed with the edges of the door or front in the height and width directions, and the vector modulus of the basis vectors is established according to the standard width and height of the actual container to obtain a mapping relationship between pixel values; if the door or front is incomplete with a missing corner, the two edges of the missing corner are extended and intersected to obtain vertices that are obscured or not captured in the image, and then a pair of basis vectors are formed with the edges of the door or front in the height and width directions, and the vector modulus of the basis vector is established according to the standard width and height of the actual container to obtain a mapping relationship between pixel values.

[0037] By using the standard width and height of the actual standard box, a mapping relationship between the vector modulus in the height and width directions, i.e., pixel values, in the image is established, so that the new ruler is more consistent with the actual two-dimensional image reality.

[0038] For example, in establishing a quantitative vector scale for the side of a container, if the side of the container is complete, a pair of basis vectors are formed with the edges of the side of the container in the length and height directions, and the vector modulus of the basis vectors is established according to the standard length and height of the standard container, and the mapping relationship between pixel values ​​is obtained; if the side of the container only includes one end of the container, a pair of basis vectors are formed with the edges of the side of the container in the length and height directions, and then the actual length of the side of the container in the length direction is estimated using the standard length of the corner piece and the projection length of its vector in the length direction, and the height is set to the height of the actual container, and the vector modulus of the basis vector is established to obtain the mapping relationship between pixel values; The vector modulus is set according to the actual situation of different box sides. For example, for a complete box side, the vector modulus and mapping relationship is established according to the standard box. If the box side is incomplete, projection in the length direction and the actual box height in the height direction are used to make the vector modulus more consistent with the actual situation of the box.

[0039] For example, in establishing a quantitative vector scale for the top surface of a container, a pair of basis vectors are formed with the edges in the height and width directions of the top of the box, and then the actual length of the top of the box in the height direction is estimated using the standard length of the corner piece and the projection length of its vector in the height direction. The width is set to the actual box width, and the vector modulus of the basis vector is established to obtain the mapping relationship between pixel values.

[0040] Similarly, setting the vector modulus for the top of the box can also better fit the actual situation of the box.

[0041] In some embodiments, when determining the damage location, an improved algorithm provided in the following example may be used. That is, based on the vertex coordinates of each part of the container and the center coordinates of the damage frame, a point-in-polygon algorithm is used to determine whether the damage is located on a certain container surface.

[0042] In some embodiments, in the quantization calculation, the calculation of the actual size of the damage frame includes: expressing the length and width of the damage frame with the basis vectors of the surface on which they are located to obtain the modulus of the length and width, and then calculating the actual size of the damage frame based on the vector modulus, that is, the mapping relationship between the pixel value and the actual size length of the basis vector.

[0043] refer to Figure 3 Schematically, the calculation formula can be expressed as:

[0044]

[0045] in, is the damaged frame edge vector, is the basis vector, , is the preset coefficient, , is the actual length of the basis vector, is the angle between the basis vectors, The actual length of the calculated damaged frame edge.

[0046] In some embodiments, in establishing a geometric model using the segmentation result, the segmentation result may be a segmentation of the acquired two-dimensional image using an existing segmentation model, or may be a segmentation model provided by the following example: During implementation, the container image is segmented based on a preset segmentation model to form the segmentation result, and the pre-trained segmentation model is a model trained through the following steps: labeling the components of the container in the container image to obtain a data set required for instance segmentation, and training the preset segmentation model based on the data set.

[0047] It should be noted that the segmented components may be parts that can reflect the posture, position, etc. of the container, for example, container doors, front, top, side, corner fitting top, corner fitting side, sling, etc.

[0048] It should be noted that the two-dimensional container image used in the present invention may be an image captured by a camera device of a dock crane.

[0049] Another example is given below, which is a schematic illustration formed by combining the above-mentioned examples.

[0050] refer to Figure 4 In summary, the present invention proposes a container damage quantification method based on geometric calibration, which may include the following steps: Step 1: Based on the image segmentation results, construct the geometric models of the container door, front, side, top, and top and side corner surfaces in the image; Step 2: According to the position of the corner fittings and the segmentation results, determine the relative position and spatial layout of the door, front, side, top, and top and side corner fittings, and infer the specific working conditions of the container; Step 3: Combine the standard dimensions of different box types and corner pieces to establish quantitative vector scales for the door, front, side and top of the box; Step 4: Determine the location of the damaged container based on the geometric model and scale established in the image; Step 5: Calculate the actual size of the damage frame based on the quantitative vector scale established on the surface where the container is damaged.

[0051] Furthermore, the method for constructing the geometric model of the container door and the front of the container in step 1 is to use corner point detection to find the four vertex coordinates of the door and the front of the container appearing in the image or the five vertex coordinates of the incomplete door and the front of the container that is missing a corner, and sort their coordinates counterclockwise starting from the upper left corner.

[0052] Furthermore, the top surface of the container in step 1 is an incomplete container top that only includes one end of the container in the image, and its geometric model construction method is to use corner point detection to find the four vertex coordinates of the partial container top that only includes one end in the image, and sort its coordinates counterclockwise starting from the upper left corner.

[0053] Furthermore, in the step 1, the side of the container is a complete side or an incomplete container side that only includes one end of the container in the image, and the method for constructing the geometric model is to use corner point detection to find the four vertex coordinates of the partial container top that only includes one end in the image or the four vertex coordinates of the complete container side, and sort their coordinates counterclockwise starting from the upper left corner.

[0054] Furthermore, the corner fitting surfaces of the top and side surfaces of the container in step 1 are the corner fitting top surfaces or corner fitting side surfaces where the corner fittings exist on the top or side of the container in the image, and the method for constructing the geometric model is to use image processing to find its minimum circumscribed rectangle.

[0055] Furthermore, the method for inferring the specific working condition of the container in step 2 is that in the case of a single container, the container door, container front, side, top surface and corner fittings detected in the image are classified as one container body, and the relative positions of each part are known. In the case of two containers, the container door, container front, side, top surface and corner fittings belonging to the same container body are classified as one container body using the detection results and the center distance of each part, and the relative positions and spatial layouts of each part are determined.

[0056] Furthermore, the method for establishing the quantitative vector scale of the container door and the front of the box in the step 3 is to form a pair of basis vectors with the edges in the height and width directions of the door or the front of the box when the door and the front of the box are complete, and at the same time, establish a mapping relationship between the vector modulus in the height and width directions, that is, the pixel value, according to the standard width and height of the actual box. In the case that the door or the front of the box is missing a corner in the image, the two edges of the missing corner are extended and intersected to obtain the vertices that are obscured or not photographed in the image, and then form a pair of basis vectors with the edges in the height and width directions of the door or the front of the box, and at the same time, establish a mapping relationship between the vector modulus in the height and width directions, that is, the pixel value, according to the standard width and height of the actual box.

[0057] Furthermore, the method for establishing the quantitative vector scale of the container side in step 3 is to form a pair of basis vectors with the edges in the length and height directions of the box side when the box side is complete, and at the same time establish a mapping relationship between the vector modulus, i.e., pixel value, in the length and width directions according to the standard length and height of the actual box body. When the box side only includes one end of the container in the image, a pair of basis vectors are formed with the edges in the length and height directions of the box side, and then the actual length of the box side in the length direction is estimated using the standard length of the corner piece and the projection length of its vector in the length direction. The height is still the actual box height, and a mapping relationship between the vector modulus, i.e., pixel value, in the length and width directions is established.

[0058] Furthermore, the method for establishing the quantitative vector scale of the container top surface in step 3 is to form a pair of basis vectors with the edges in the height and width directions of the box top, and then use the standard length of the corner piece and the projection length of the vector in the height direction to estimate the actual length of the box top in the height direction. The width is still the actual box width, and a mapping relationship between the vector modulus in the height and width directions, that is, the pixel value, is established.

[0059] Furthermore, the method for determining the damaged location of the container in step 4 is based on the vertex coordinates of each part of the container, combined with the center coordinates of the damage frame, and uses the point-in-polygon algorithm to determine whether the damage is located on a certain container surface.

[0060] Furthermore, the calculation method of the actual size of the damaged frame in step 5 is to express the length and width of the damaged frame with the basis vector of the surface where the damaged frame is located to obtain the modulus of the length and width, and then calculate the actual size of the damaged frame based on the mapping relationship between the vector modulus, i.e., the pixel value and the actual size length of the basis vector. The calculation formula can refer to the above example and will not be expanded.

[0061] Based on the same inventive concept, the present invention also provides a container damage quantification system based on geometric calibration.

[0062] refer to Figure 5 Schematically, a container damage quantification system 100 based on geometric calibration may include: The geometric model subsystem 101 constructs a geometric model of each component of the container in the container image based on the segmentation result of the container image, wherein each component includes one or more of the following parts: container door, container front, side, top, corner surface; Inference subsystem 103: determining the relative position and spatial layout of each of the components according to the corner piece position and the segmentation result, and inferring the specific working condition of the container according to the relative position and spatial layout; Vector scale subsystem 105: establishing quantitative vector scales of each component in combination with standard sizes of different box types and corner pieces; The calculation subsystem 107 determines the location of the damaged container based on the geometric model and scale established in the image; and calculates the actual size of the damaged frame based on the quantitative vector scale established on the surface where the damaged container is located.

[0063] It should be noted that the settings of the unit module functions and the number of modules in the container damage quantification system can be set accordingly according to the aforementioned method embodiments, and will not be further described here.

[0064] Based on the same inventive concept, the present invention also provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute: a container damage quantification method based on geometric calibration as described in any embodiment of the present application.

[0065] like Figure 6 As shown, the present application also provides a schematic diagram of the structure of an electronic device, which shows the structure of the electronic device 500. The electronic device 500 is merely an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0066] The electronic device 500 may include: at least one processor 510; and a memory 520 communicatively connected to the at least one processor; wherein the memory 520 stores instructions executable by the at least one processor 510, and the instructions are executed by the at least one processor 510 so that the at least one processor 510 can execute: the container damage quantification method based on geometric calibration described in any embodiment of the present application.

[0067] It should be noted that the electronic device 500 may be in the form of a general-purpose computing device, for example, it may be a server device.

[0068] In implementation, the components of the electronic device 500 may include but are not limited to: the above-mentioned at least one processor 510, the above-mentioned at least one memory 520, and a bus 530 connecting different system components (including the memory 520 and the processor 510), wherein the bus 530 may include a data bus, an address bus, and a control bus.

[0069] In implementation, the memory 520 may include a volatile memory, such as a random access memory (RAM) 5201 and / or a cache memory 5202 , and may further include a read-only memory (ROM) 5203 .

[0070] The memory 520 may also include a program tool 5205 having a set (at least one) of program modules 5204, such program modules 5204 including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include the implementation of a network environment.

[0071] The processor 510 executes various functional applications and data processing by running computer programs stored in the memory 520 .

[0072] The electronic device 500 may also communicate with one or more external devices 540 (e.g., keyboards, pointing devices, etc.). Such communication may be performed via an input / output (I / O) interface 550. Furthermore, the electronic device 500 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 560, which communicates with other modules in the electronic device 500 via a bus 530. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 500, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.

[0073] In this specification, the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the embodiments described later, the description is relatively simple, and the relevant parts can be referred to the partial description of the previous embodiments.

[0074] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A container damage quantification method based on geometric calibration, characterized in that: include: Based on the segmentation result of the container image, a geometric model of each component of the container in the container image is constructed, each of the components including one or more of the following parts: container door, container front, side, top surface, corner surface; Determine the relative position and spatial layout of each of the components according to the position of the corner piece and the segmentation result, and infer the specific working condition of the container according to the relative position and spatial layout; Combined with the standard dimensions of different box types and corner pieces, quantitative vector scales are established for each of the components; The actual location of the container damage is determined based on the geometric model and quantized vector scale established in the image, and the actual size of the damage frame is calculated based on the quantized vector scale established on the surface where the container damage is located.

2. The container damage quantification method based on geometric calibration according to claim 1 is characterized in that: In building the geometric model, include: Corner point detection is used to find the coordinates of the four vertices of the box door and the box front that appear in the image, or the coordinates of the five vertices of the incomplete box door and the box front that lack a corner, and their coordinates are sorted counterclockwise from the upper left corner to construct the geometric model of the box door and the box front; And / or, when the top surface is an incomplete container top that only includes one end of the container in the image, corner point detection is used to find the coordinates of the four vertices of the partial container top that only includes one end in the image, and the coordinates are sorted counterclockwise from the upper left corner to construct a geometric model of the top surface; And / or, when the side surface is a complete side surface or an incomplete container side surface including only one end of the container in the image, corner point detection is used to find the coordinates of the four vertices of the partial container top including only one end or the coordinates of the four vertices of the complete container side surface in the image, and the coordinates are sorted counterclockwise from the upper left corner to construct a geometric model of the side surface; And / or, when the corner piece surfaces of the top and side surfaces are the corner piece top surfaces or corner piece side surfaces where the corner piece exists on the top or side of the box in the image, image processing is used to find its minimum circumscribed rectangle to construct a geometric model of the corner piece surface.

3. The container damage quantification method based on geometric calibration according to claim 1 is characterized in that: Determining the relative positions and spatial layouts of each of the components includes: if the container image contains only a single box, classifying the door, front, side, top and corner fittings detected in the image as the same box body; if the container image contains multiple boxes, classifying the door, front, side, top and corner fittings belonging to the same box body as the same box body using the center distance of each of the components.

4. The container damage quantification method based on geometric calibration according to claim 1 is characterized in that: Establishing a quantitative vector scale for the door and front of a container includes: if the door and front of a container are complete, a pair of basis vectors are formed with the edges of the door or front of a container in the height and width directions, and the vector modulus of the basis vectors is established according to the standard width and height of the actual container, so as to obtain a mapping relationship between pixel values; if the door or front of a container is incomplete with a corner missing, the two edges of the missing corner are extended and intersected to obtain the vertices that are blocked or not photographed in the image, and then a pair of basis vectors are formed with the edges of the door or front of a container in the height and width directions, and the vector modulus of the basis vector is established according to the standard width and height of the actual container, so as to obtain a mapping relationship between pixel values; And / or, establishing a quantitative vector scale of the side of the container includes: if the side of the container is complete, forming a pair of basis vectors with the sides of the side of the container in the length and height directions, and establishing the vector modulus of the basis vectors according to the standard length and height of the standard container, and obtaining a mapping relationship between pixel values; if the side of the container only includes one end of the container, forming a pair of basis vectors with the sides of the side of the container in the length and height directions, and then estimating the actual length of the side of the container in the length direction by using the standard length of the corner piece and the projection length of its vector in the length direction, and setting the height to the height of the actual container, establishing the vector modulus of the basis vectors, and obtaining a mapping relationship between pixel values; And / or, establishing a quantitative vector scale for the top surface of the container includes: forming a pair of basis vectors with the edges in the height and width directions of the box top, and then using the standard length of the corner piece and the projection length of its vector in the height direction to estimate the actual length of the box top in the height direction, setting the width to the actual box width, establishing the vector modulus of the basis vector, and obtaining a mapping relationship between pixel values.

5. The container damage quantification method based on geometric calibration according to claim 1, characterized in that: Determining the damaged position of the container includes: based on the vertex coordinates of each part of the container, combined with the center coordinates of the damage frame, using a point-in-polygon algorithm to determine whether the damage is located on a certain container surface.

6. The container damage quantification method based on geometric calibration according to claim 1, characterized in that: The calculation of the actual size of the damaged frame includes: expressing the length and width of the damaged frame with the basis vector of the surface where the damaged frame is located to obtain the modulus of the length and width, and then calculating the actual size of the damaged frame based on the mapping relationship between the vector modulus, i.e., the pixel value and the actual size length of the basis vector; The calculation formula can be expressed as: in, is the damaged frame edge vector, is the basis vector, , is the preset coefficient, , is the actual length of the basis vector, is the angle between the basis vectors, The actual length of the calculated damaged frame edge.

7. The container damage quantification method based on geometric calibration according to any one of claims 1 to 6, characterized in that: The container image is segmented based on a preset segmentation model to form the segmentation result; wherein the pre-trained segmentation model is trained by the following steps: the component parts of the container in the container image are marked to obtain a data set required for instance segmentation, and the preset segmentation model is trained based on the data set.

8. A container damage quantification system based on geometric calibration, characterized in that: include: Geometric model subsystem: based on the segmentation result of the container image, construct the geometric model of each component of the container in the container image, each of which includes one or more of the following parts: container door, container front, side, top, corner surface; Inference subsystem: determines the relative position and spatial layout of each component according to the position of the corner piece and the segmentation result, and infers the specific working condition of the container according to the relative position and spatial layout; Vector scale subsystem: combining the standard sizes of different box types and corner pieces to establish the quantitative vector scales of each component; Computing subsystem: determines the location of container damage based on the geometric model and scale established in the image; And, based on the quantitative vector scale established on the surface where the container is damaged, the actual size of the damage frame is calculated.

9. An electronic device, characterized in that: include: at least one processor; And, a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute: the container damage quantification method based on geometric calibration as described in any one of claims 1-7.

10. A computer storage medium, characterized in that: The computer storage medium stores computer executable instructions, and when the computer executable instructions are executed by the processor, they perform: the container damage quantification method based on geometric calibration as described in any one of claims 1-7.

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