A data processing system for determining the actual state analysis table of a target road

Abstract

The present application relates to the technical field of building data analysis, and in particular to a data processing system for determining an actual status analysis table of a target road, the system comprising: a target road image set, a processor, and a memory storing a computer program, and when the computer program is executed by the processor, the following steps are implemented: according to the target road image set, a target building area information set is determined, according to the target building area information set and a preset material list, a list of materials to be consumed corresponding to the target road is obtained, and according to the list of materials to be consumed, an actual status analysis table of the target road is determined. It can be seen that the present invention can determine the actual area corresponding to the target road based on the target road image taken by the drone, and record the material quantity of each area accordingly, so that the staff can grasp the material consumption and remaining situation in a timely manner.

Description

Technical Field

[0001] The invention relates to the technical field of building data analysis, and in particular to a data processing system for determining an actual state analysis table of a target road. Background Art

[0002] At present, in the process of road construction, due to factors such as long construction lines, multiple construction sites, and complex terrain conditions, it is difficult to obtain accurate construction progress statistics for the entire line, and the authenticity of the statistics is difficult to guarantee, making it difficult to formulate a reasonable progress plan. In addition, due to the large investment amount and the complex construction environment, when accurate road information cannot be obtained, it is also impossible to timely analyze the amount of materials required for each construction node, which may affect the distribution of materials and the authenticity of the statistical data. Summary of the invention

[0003] In view of the above technical problems, the technical solution adopted by the present invention is:

[0004] A data processing system for determining an actual state analysis table of a target road, the system comprising: a target road image set A = {A1, A2, ..., A i , ..., A m}, a processor and a memory storing a computer program, wherein A i It refers to the target road image list in the i-th preset time period, i=1, 2, ..., m, m is the number of target road image lists, and when the computer program is executed by the processor, the following steps are implemented:

[0005] S100, based on A, determine the target building area information set C of the target road corresponding to A = {C1, C2, ..., C i , ..., C m}, where C i A i The corresponding target building area information list.

[0006] In step S100, C is obtained by the following steps: i :

[0007] S101, Get A from A i ={A i1 , A i2 , ..., A ij , ..., A in(i)}, where A ij It refers to the jth target road image in the i-th preset time period, j=1, 2, ..., n(i), and n(i) refers to the number of target road images in the i-th preset time period.

[0008] S102, for Aij Process and obtain A ij Corresponding target building area information C ij ={C ij1 , C ij2 , C ij3 , C ij4}, where C ij1 is the length of the target building area, C ij2 is the width of the target building area, C ij3 is the longitude of the center point of the target building area, C ij4 is the latitude of the center point of the target building area.

[0009] S103, A i The n(i) target road images in C correspond to ij Combination C i .

[0010] S200, according to C and a preset bill of materials list, obtaining a list of materials to be consumed corresponding to the target road.

[0011] S300: Determine an actual status analysis table of the target road according to the list of materials to be consumed.

[0012] Compared with the prior art, the present invention has obvious beneficial effects. By means of the above technical solution, the data processing system for determining the actual state analysis table of the target road provided by the present invention can achieve considerable technical advancement and practicality, and has wide industrial utilization value, and has at least the following beneficial effects:

[0013] The present invention provides a data processing system for determining an actual state analysis table of a target road, the system comprising: a target road image set, a processor and a memory storing a computer program, and when the computer program is executed by the processor, the following steps are implemented: according to the target road image set, a target building area information set of the target road is determined; according to the target building area information set and a preset material list, a list of bills of materials to be consumed corresponding to the target road is obtained; according to the list of bills of materials to be consumed, an actual state analysis table of the target road is determined. The present invention provides a new data processing system for determining an actual status analysis table of a target road. On the one hand, a plurality of target road images taken are obtained according to the shooting duration and flight speed of a drone. At the same time, based on the setting of a diagonal field of view, each target road image can be connected end to end to obtain a more accurate target road image. On the other hand, by processing the boundary of an initial construction area, an intermediate construction area with a smooth boundary and a regular shape can be obtained, and then the actual construction area of ​​the target road can be accurately obtained, and the construction progress can be known, so that the actual area corresponding to each target road image and the amount of material to be consumed can be recorded in correspondence, so that the staff can timely grasp the remaining material situation and analyze the material situation in each area to ensure the normal progress of the construction progress. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0015] Figure 1 A flowchart of a data processing system executing a computer program for determining an actual state analysis table of a target road provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0017] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0018] A data processing system for determining an actual state analysis table of a target road, the system comprising: a target road image set A = {A1, A2, ..., A i , ..., A m}, a processor and a memory storing a computer program, wherein A i It refers to the target road image list in the i-th preset time period, i=1, 2, ..., m, m is the number of target road image lists, when the computer program is executed by the processor, the following steps are implemented, such as Figure 1 As shown:

[0019] S100, based on A, determine the target building area information set C of the target road corresponding to A = {C1, C2, ..., C i , ..., C m}, where C i A i The corresponding target building area information list.

[0020] Specifically, the unit of the preset time period is day, which can be understood as: the drone collects the target road image list for the target road once a day.

[0021] In a specific embodiment, in step S100, C is obtained by the following steps: i :

[0022] S101, Get A from A i ={A i1 , A i2 , ..., A ij , ..., A in(i)}, where A ij It refers to the jth target road image in the i-th preset time period, j=1, 2, ..., n(i), and n(i) refers to the number of target road images in the i-th preset time period.

[0023] Furthermore, the system also includes drone information B = {B1, B2, ..., B i , ..., B m}, where B i = {B i1 , B i2 , ..., B ij , ..., B in(i)}, B ij = {V, θ, B ij1}, V is the flight speed of the drone, θ is the diagonal field of view of the drone, B ij1 A ij The corresponding flight altitude of the drone can be understood as: B ij1 is the flight altitude when the j-th target road image is captured in the i-th preset time period.

[0024] Specifically, n(i) meets the following conditions:

[0025] n(i)=[L i / V]+1, where L i It is the duration that the UAV takes photos of the target road under construction in the i-th preset time period.

[0026] Specifically, θ is an angle preset according to the initial flight altitude of the UAV, so that when the UAV is shooting, the end of the first target road image is connected to the beginning of the second target road image.

[0027] As mentioned above, the flight speed and diagonal field of view of the drone during the shooting process are preset parameters, which are fixed values. The flight altitude will change slightly with factors such as wind force, which is a variable. By collecting the background information of the drone and obtaining the values ​​of the above parameters of the drone, it is beneficial to the data analysis of the target road image.

[0028] In a specific embodiment, in step S101, A is obtained by the following steps: i(j+1) :

[0029] S1011, according to A ij Each first pixel point corresponding to the first key boundary of A ij The second pixel points corresponding to each first pixel point are respectively obtained from the second key boundary of the next initial road image.

[0030] Specifically, the first critical boundary and the second critical boundary refer to A ij and A ij The two boundaries of the next initial road image connected can be understood as: the line segment connecting the first pixel point and the second pixel point is parallel to the target road.

[0031] S1012, obtaining the total grayscale value of the grayscale value of each first pixel and the grayscale value of the corresponding second pixel. It can be understood that the total grayscale value is the sum of the grayscale value of the first pixel and the grayscale value of the second pixel.

[0032] S1013, when the total grayscale values ​​are all within the preset threshold range, obtain A ij The next initial road image is A i(j+1) , wherein the preset threshold range is a range set by those skilled in the art according to actual needs and will not be repeated here.

[0033] S1014, when any total grayscale value is outside the preset threshold range, the second pixel point corresponding to the total grayscale value is processed to obtain A i(j+1) , in order to reduce the difference in grayscale values ​​of the first pixel and the second pixel corresponding to the total grayscale value, it can be understood as: adjusting the grayscale value of the second pixel according to the average value of the grayscale value of the first pixel and the grayscale value of the second pixel, so that the grayscale value of the second pixel is close to the grayscale value of the first pixel.

[0034] As mentioned above, due to the obstruction of objects and different weather conditions during the shooting process of the drone, the grayscale values ​​at the junction of two adjacent target road images will have deviations. Through the above processing, the grayscale values ​​of adjacent target road images with large deviations are processed, so that the colors of the two target road images are basically consistent, which is convenient for distinguishing the initial building area from other areas, so as to obtain accurate target building area information.

[0035] S102, for A ij Process and obtain A ij Corresponding target building area information C ij ={C ij1 , C ij2 , C ij3 , C ij4}, where C ij1 is the length of the target building area, C ij2 is the width of the target building area, C ij3 is the longitude of the center point of the target building area, C ij4 is the latitude of the center point of the target building area.

[0036] In a specific embodiment, step S102 also includes the following steps:

[0037] S1021, from A ijThe initial building pixel point coordinate set E={E1, E2, E3, E4} corresponding to the initial building area is obtained, wherein E1 is the first building boundary pixel point coordinate set corresponding to the first boundary of the initial building area, E2 is the second building boundary pixel point coordinate set corresponding to the second boundary of the initial building area, E3 is the third building boundary pixel point coordinate set corresponding to the third boundary of the initial building area, and E4 is the fourth building boundary pixel point coordinate set corresponding to the fourth boundary of the initial building area.

[0038] Specifically, the initial building area refers to the area from A to B according to the RGB color table. ij After comparing the colors of the initial building area with other areas, ij The building area with a zigzag boundary obtained from A can be understood as follows: the actual road area corresponding to the initial building area is a rectangle. ij The four sides of the initial building area obtained in the zigzag shape are all in the shape of a sawtooth. The first boundary and the third boundary are the two sides corresponding to the length of the rectangle, and the second boundary and the fourth boundary are the two sides corresponding to the width of the rectangle.

[0039] S1022, from A ij The image pixel point coordinate set F corresponding to E is obtained from F = {F1, F2, F3, F4}, where F1 is the first image boundary pixel point coordinate set corresponding to E1, F2 is the second image boundary pixel point coordinate set corresponding to E2, F3 is the third image boundary pixel point coordinate set corresponding to E3, and F4 is the fourth image boundary pixel point coordinate set corresponding to E4. It can be understood that: the first building boundary pixel point in E1 corresponds to the first image boundary pixel point in F1 one-to-one, and the straight line formed by the corresponding two pixel points is perpendicular to the first image boundary. The same is true for E2 and F2, E3 and F3, and E4 and F4.

[0040] S1023, based on E and F, obtain the target pixel point coordinate set G = {G1, G2, G3, G4} corresponding to the initial building area, wherein G1 is the target pixel point coordinate corresponding to E1 and F1, G2 is the target pixel point coordinate corresponding to E2 and F2, G3 is the target pixel point coordinate corresponding to E3 and F3, and G4 is the target pixel point coordinate corresponding to E4 and F4.

[0041] In a specific embodiment, in step S1023, G1 is obtained by the following steps:

[0042] S1, according to E1 = {E11, E12, ..., E1 p , ..., E1 q} and F1={F11,F12,……,F1 p , ..., F1 q},

[0043] Get the first target distance Z 0 1, among which, E1 p =(E1 p1 , E1 p2 ), F1 p =(F1 p1 , F1 p2 ), E1 p1 is the horizontal coordinate of the pth first building boundary pixel point, E1 p2 is the ordinate of the pth first building boundary pixel point, F1 p1 is the horizontal coordinate of the pth first image boundary pixel point, F1 p2 is the ordinate of the pth first image boundary pixel point.

[0044] Specifically, Z 0 1Meet the following conditions:

[0045] Z 0 1=(∑ q p＝1 ((E1 p1 -F1 p1 ) 2 +(E1 p2 -F1 p2 ) 2 ) 1 / 2 ) / q.

[0046] S2, according to Z 0 1 and A ij The corresponding first image boundary is obtained G1.

[0047] Specifically, G1 is parallel to the first image boundary and the distance between it and the first image boundary is Z 0 Any point on the straight line of 1.

[0048] Specifically, G2 is based on Z 0 2 and A ij The corresponding second image boundary is obtained in the same way as G1, where Z 0 2 is the second target distance obtained based on E2 and F2, and its acquisition method is the same as Z 0 1 is obtained in the same way.

[0049] Specifically, G3 is based on Z 0 3 and A ij The corresponding third image boundary is obtained in the same way as G1, where Z 0 3 is the third target distance obtained based on E3 and F3, and its acquisition method is the same as Z 0 1 is obtained in the same way.

[0050] Specifically, G4 is based on Z 0 4 and A ij The corresponding fourth image boundary is obtained in the same manner as G1, where Z 0 4 is the fourth target distance obtained based on E4 and F4, and its acquisition method is the same as Z 0 1 is obtained in the same way.

[0051] As described above, by comparing several pixel points at the edge of the initial building area with several pixel points in the target road image corresponding to the edge of the initial building area, it is possible to obtain the target pixel point corresponding to each irregular boundary of the initial building area. Through the above processing, the jagged boundary of the initial building area can be converted into a smooth boundary passing through the target pixel point, so as to obtain a regular intermediate building area.

[0052] S1024: According to G, obtain the intermediate building area corresponding to the initial building area.

[0053] Specifically, in step S1024, the intermediate building area is obtained through the following steps:

[0054] S01, based on G1, G2, G3, G4 and A ij , respectively obtain the first intermediate building boundary, the second intermediate building boundary, the third intermediate building boundary and the fourth intermediate building boundary.

[0055] Specifically, the first intermediate building boundary refers to the boundary passing through G1 and adjacent to A ij The border of the first image is parallel to the border.

[0056] Specifically, the second intermediate building boundary refers to the boundary passing through G2 and adjacent to A ij The border of the second image is parallel to the border.

[0057] Specifically, the third intermediate building boundary refers to the boundary passing through G3 and adjacent to A ij The border of the third image border is parallel to the border.

[0058] Specifically, the fourth intermediate building boundary refers to the boundary passing through G4 and adjacent to A ij The fourth image boundary is parallel to the boundary.

[0059] S02, acquiring the intermediate building area according to the first intermediate building boundary, the second intermediate building boundary, the third intermediate building boundary and the fourth intermediate building boundary, which can be understood as: the intermediate building area is a rectangular area formed by the first intermediate building boundary, the second intermediate building boundary, the third intermediate building boundary and the fourth intermediate building boundary.

[0060] As mentioned above, since A ijThe initial building area obtained in the method is an irregular area. The average distance between the four sides of the initial building area and the four sides of the target road image is calculated through several pixel points at the edge of the initial building area and several pixel points in the target road image corresponding to the edge of the initial building area. The coordinates of the target pixel point are calculated based on the average distance to obtain the middle building area corresponding to the initial building area, thereby improving the regularity of the rectangular building area and making it easy to obtain various parameters of the target building area.

[0061] S1025, according to B ij1 , θ and A ij , get C 0 ij ={C 0 ij1 , C 0 ij2}, where C 0 ij1 A ij The length of the corresponding actual area, C 0 ij2 A ij The width of the corresponding actual area.

[0062] Specifically, C. 0 ij1 Meet the following conditions:

[0063] C 0 ij1 =2B ij1 ×tan(θ / 2)×α ij / (α ij 2 +β ij 2 ) 1 / 2 , where α ij A ij The corresponding image length, β ij A ij The corresponding image width.

[0064] Specifically, C. 0 ij2 Meet the following conditions:

[0065] C 0 ij2 =2B ij1 ×tan(θ / 2)×β ij / (α ij 2 +β ij 2 ) 1 / 2 .

[0066] S1026, according to C0 ij and the intermediate building area, obtain C ij ={C ij1 , C ij2 , C ij3 , C ij4}; can be understood as: C ij1 is the length of the actual area corresponding to the middle building area, C ij2 is the width of the actual area corresponding to the middle building area, C ij3 is the longitude of the actual area corresponding to the middle building area, C ij4 is the latitude of the actual area corresponding to the middle building area.

[0067] Specifically, C. ij1 Meet the following conditions:

[0068] C ij1 =(α 0 ij / α ij )×C 0 ij1 , where α 0 ij is the image length corresponding to the middle building area.

[0069] Specifically, C. ij2 Meet the following conditions:

[0070] C ij2 =(β 0 ij / β ij )×C 0 ij1 , where β 0 ij is the image width corresponding to the middle building area.

[0071] Specifically, C. ij3 and C ij4 It is the longitude and latitude obtained according to the coordinates of the drone or the parameter information of the drone. The acquisition method is the existing technology in this field and will not be repeated here.

[0072] S103, A i The n(i) target road images in C correspond to ij Combination C i .

[0073] As mentioned above, by calculating the target construction area according to the length and width of the middle construction area and the parameters of the drone, that is, the actual construction area corresponding to the middle construction area, it is convenient for the staff to count the various data information of the target road and grasp the construction progress, so as to take corresponding construction measures in time according to the construction situation, and synchronize the material quantity corresponding to each construction stage with the construction progress, so that the statistical results are clearer.

[0074] S200, according to C and the preset material list W, obtain a list of materials to be consumed corresponding to the target road.

[0075] In a specific embodiment, in step S200, the list of materials to be consumed of the target road is obtained through the following steps:

[0076] S201, obtain the material consumption list D corresponding to C = {D1, D2, ..., D i , ..., D m}, D i ={D i1 , D i2 , ..., D ij , ..., D in(i)}, D ij ={D ij1 , D ij2 , ..., D ijx , ..., D ijk}, where D ijx C ij The consumption of the xth material in the corresponding material consumption list, in kg.

[0077] Specifically, the material refers to any material used in constructing the target road, such as asphalt, concrete, etc.

[0078] S202, compare D with the preset material list W = {W1, W2, ..., W i , ..., W m},W i = {W i1 , W i2 , ..., W ij , ..., W in(i)},W ij = {W ij1 , W ij2 , ..., W ijx , ..., W ijk} to obtain the list of materials to be consumed corresponding to the target road. 0 ={D 0 1, D 0 2, ..., D 0i , ..., D 0 m}, D 0 i ={D 0 i1 , D 0 i2 , ..., D 0 ij , ..., D 0 in(i)}, D 0 ij ={D 0 ij1 , D 0 ij2 , ..., D 0 ijx , ..., D 0 ijk}, where W ijx Refers to the preset bill of materials list and C ij The total amount of materials that matches the xth material in the corresponding material consumption list, D 0 ijx C ij The quantity to be consumed of the xth material in the corresponding material quantity to be consumed list.

[0079] Specifically, D 0 ijx Meet the following conditions:

[0080] D 0 ijx =W ijx -D ijx ,in.

[0081] As mentioned above, by counting the material consumption corresponding to the target building area information set and comparing it with the material consumption list corresponding to the target building area information set, the amount of each material to be consumed can be obtained, that is, the remaining amount of each material at the time of statistics, so that the staff can grasp the remaining material situation in time, and through the remaining material situation, they can replenish the materials in time before they are scarce, so as to ensure the normal progress of the construction project.

[0082] S300: Determine an actual status analysis table of the target road according to the list of materials to be consumed.

[0083] In a specific embodiment, in S300, the actual status analysis table is obtained by further performing the following steps:

[0084] S301, obtaining an initial state analysis table according to a number of target building area identifiers and a number of material names, which can be understood as: the horizontal headings of the initial state analysis table are a number of target building area identifiers, and the vertical headings of the initial state analysis table are a number of material names.

[0085] Specifically, the target building area identifier refers to a unique identifier of the target building area. For example, each target building area is distinguished by a number, and any two numbers are different.

[0086] S302, according to any C ij The corresponding target building area identification is divided into D 0 ij The corresponding data is added to the initial state analysis table to obtain the actual state analysis table; it can be understood that the actual state analysis table is an analysis table that is statistically analyzed based on the captured target road image.

[0087] As described above, by counting the amount of materials to be consumed corresponding to the target road, the actual situation of each construction stage of the target road can be grasped in real time, so that the staff can timely grasp the material consumption and material surplus situation, so that the staff can obtain the material usage through the material consumption situation, and prevent the material from being lost or used for other purposes by other personnel taking advantage of their position. Through the material surplus situation, the staff can grasp the remaining material amount in each construction stage, and the actual status analysis table obtained is convenient for other staff to query the data and guide the data of subsequent construction.

[0088] The present invention provides a data processing system for determining an actual state analysis table of a target road, the system comprising: a target road image set, a processor and a memory storing a computer program, and when the computer program is executed by the processor, the following steps are implemented: according to the target road image set, a target building area information set of the target road is determined; according to the target building area information set and a preset material list, a list of bills of materials to be consumed corresponding to the target road is obtained; according to the list of bills of materials to be consumed, an actual state analysis table of the target road is determined. The present invention provides a new data processing system for determining an actual status analysis table of a target road. On the one hand, a plurality of target road images taken are obtained according to the shooting duration and flight speed of a drone. At the same time, based on the setting of a diagonal field of view, each target road image can be connected end to end to obtain a more accurate target road image. On the other hand, by processing the boundary of an initial construction area, an intermediate construction area with a smooth boundary and a regular shape can be obtained, and then the actual construction area of ​​the target road can be accurately obtained, and the construction progress can be known, so that the actual area corresponding to each target road image and the amount of material to be consumed can be recorded in correspondence, so that the staff can timely grasp the remaining material situation and analyze the material situation in each area to ensure the normal progress of the construction progress.

[0089] Although some specific embodiments of the present invention have been described in detail by way of example, it will be appreciated by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It will also be appreciated by those skilled in the art that various modifications may be made to the embodiments without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.

Claims

1. A data processing system for determining an actual state analysis table of a target road, characterized in that: The system comprises: a target road image set A={A1, A2, ..., A i , ..., A m }, a processor and a memory storing a computer program, wherein A i It refers to the target road image list in the i-th preset time period, i=1, 2, ..., m, m is the number of target road image lists, and when the computer program is executed by the processor, the following steps are implemented: S100, based on A, determine the target building area information set C of the target road corresponding to A = {C1, C2, ..., C i , ..., C m }, where C i A i Corresponding target building area information list; In step S100, C is obtained by the following steps: i : S101, Get A from A i ={A i1 , A i2 , ..., A ij , ..., A in(i) }, where A ij refers to the jth target road image in the i-th preset time period, j=1, 2, ..., n(i), and n(i) refers to the number of target road images in the i-th preset time period; S102, for A ij Process and obtain A ij Corresponding target building area information C ij ={C ij1 , C ij2 , C ij3 , C ij4 }, where C ij1 is the length of the target building area, C ij2 is the width of the target building area, C ij3 is the longitude of the center point of the target building area, C ij4 is the latitude of the center point of the target building area; S103, A i The n(i) target road images in C correspond to ij Combination C i ; S200, obtaining a list of materials to be consumed corresponding to the target road according to C and a preset list of materials; S300, determining an actual status analysis table of the target road according to the list of materials to be consumed; Wherein, step S102 also includes the following steps: S1021, from A ij Obtain the initial building pixel point coordinate set E={E1, E2, E3, E4} corresponding to the initial building area, where E1 is the first building boundary pixel point coordinate set corresponding to the first boundary of the initial building area, E2 is the second building boundary pixel point coordinate set corresponding to the second boundary of the initial building area, E3 is the third building boundary pixel point coordinate set corresponding to the third boundary of the initial building area, and E4 is the fourth building boundary pixel point coordinate set corresponding to the fourth boundary of the initial building area; S1022, from A ij Obtain the image pixel point coordinate set F={F1, F2, F3, F4} corresponding to E, where F1 is the first image boundary pixel point coordinate set corresponding to E1, F2 is the second image boundary pixel point coordinate set corresponding to E2, F3 is the third image boundary pixel point coordinate set corresponding to E3, and F4 is the fourth image boundary pixel point coordinate set corresponding to E4; S1023, according to E and F, obtain the target pixel point coordinate set G={G1, G2, G3, G4} corresponding to the initial building area, wherein G1 is the target pixel point coordinate corresponding to E1 and F1, G2 is the target pixel point coordinate corresponding to E2 and F2, G3 is the target pixel point coordinate corresponding to E3 and F3, and G4 is the target pixel point coordinate corresponding to E4 and F4; obtain G1 by the following steps: according to E1={E11, E12, ..., E1 p , ..., E1 q } and F1={F11, F12, …, F1 p , ..., F1 q }, get the first target distance Z 0 1, among which, E1 p =(E1 p1 , E1 p2 ), F1 p =(F1 p1 , F1 p2 ), E1 p1 is the horizontal coordinate of the pth first building boundary pixel point, E1 p2 is the ordinate of the pth first building boundary pixel point, F1 p1 is the horizontal coordinate of the pth pixel point on the first image boundary, F1 p2 is the ordinate of the pth first image boundary pixel point; where Z 0 1=(∑ q p=1 ((E1 p1 -F1 p1 ) 2 +(E1 p2 -F1 p2 ) 2 ) 1 / 2 ) / q; according to Z 0 1 and A ij The corresponding first image boundary, obtain G1; S1024, according to G, obtaining an intermediate building area corresponding to the initial building area; S1025, according to B ij1 , θ and A ij , get C 0 ij ={C 0 ij1 , C 0 ij2 }, where C 0 ij1 A ij The length of the corresponding actual area, C 0 ij2 A ij The width of the corresponding actual area, B ij1 A ij The corresponding UAV’s flight altitude, θ is the diagonal field of view of the UAV; S1026, according to C 0 ij and the intermediate building area, obtain C ij ={C ij1 , C ij2 , C ij3 , C ij4 }.

2. The data processing system for determining the actual state analysis table of the target road according to claim 1, characterized in that: In step S101, A is obtained by the following steps: i（j+1） : S1011, according to A ij Each first pixel point corresponding to the first key boundary of A ij respectively obtaining a second pixel point corresponding to each first pixel point from a second key boundary of the next initial road image; S1012, obtaining a total grayscale value of the grayscale value of each first pixel and the grayscale value of the corresponding second pixel; S1013, when the total grayscale values ​​are all within the preset threshold range, obtain A ij The next initial road image is A i（j+1） ; S1014, when any total grayscale value is outside the preset threshold range, the second pixel point corresponding to the total grayscale value is processed to obtain A i（j+1） .

3. The data processing system for determining the actual state analysis table of the target road according to claim 1, characterized in that: In step S1024, the intermediate building area is obtained by the following steps: S01, based on G1, G2, G3, G4 and A ij , respectively obtaining a first intermediate building boundary, a second intermediate building boundary, a third intermediate building boundary and a fourth intermediate building boundary; S02: Acquire the intermediate building area according to the first intermediate building boundary, the second intermediate building boundary, the third intermediate building boundary and the fourth intermediate building boundary.

4. The data processing system for determining the actual state analysis table of the target road according to claim 1, characterized in that: C 0 ij1 Meet the following conditions: C 0 ij1 =2B ij1 ×tan(θ / 2)×α ij / (α ij 2 +β ij 2 ) 1 / 2 , where α ij A ij The corresponding image length, β ij A ij The corresponding image width; C 0 ij2 Meet the following conditions: C 0 ij2 =2B ij1 ×tan (θ / 2) × β ij / (a ij 2 +b ij 2 ) 1 / 2 。 5. The data processing system for determining the actual state analysis table of the target road according to claim 1, characterized in that: In step S200, the list of materials to be consumed for the target road is obtained through the following steps: S201, obtain the material consumption list D corresponding to C = {D1, D2, ..., D i , ..., D m }, D i ={D i1 , D i2 , ..., D ij , ..., D in(i) }, D ij ={D ij1 , D ij2 , ..., D ijx , ..., D ijk }, where D ijx C ij The consumption of the xth material in the corresponding material consumption list, in kg; S202, compare D with the preset bill of materials list W={W1, W2, ..., W i , ..., W m },W i ={W i1 , W i2 , ..., W ij , ..., W in(i) },W ij ={W ij1 , W ij2 , ..., W ijx , ..., W ijk } to obtain the list of materials to be consumed corresponding to the target road. 0 ={D 0 1, D 0 2, ..., D 0 i , ..., D 0 m }, D 0 i ={D 0 i1 , D 0 i2 , ..., D 0 ij , ..., D 0 in(i) }, D 0 ij ={D 0 ij1 , D 0 ij2 , ..., D 0 ijx , ..., D 0 ijk }, where W ijx Refers to the preset bill of materials list and C ij The total amount of materials that matches the xth material in the corresponding material consumption list, D 0 ijx C ij The quantity to be consumed of the xth material in the corresponding material quantity to be consumed list; Among them, D 0 ijx Meet the following conditions: D 0 ijx =W ijx -D ijx , where W ijx Refers to the preset bill of materials list and C ij The total amount of material that matches the xth material in the corresponding material consumption list.

6. The data processing system for determining the actual state analysis table of the target road according to claim 1, characterized in that: In S300, the actual status analysis table is obtained through the following steps: S301, obtaining an initial state analysis table according to a plurality of target building area identifiers and a plurality of material names; S302, according to any C ij The corresponding target building area identification is divided into D 0 ij The corresponding data is added to the initial state analysis table to obtain the actual state analysis table.

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