A method, device, equipment and storage medium for automatically identifying seats in a venue

Abstract

The present application discloses a method, device, equipment, and storage medium for automatic identification of seats in a stadium, the method comprising: obtaining an input file, the input file comprising a first part of data and a second part of data, the first part of data comprising stand area coordinate parameters, and the second part of data comprising seat parameters; determining the stand area area according to the first part of data; determining the seat distribution according to the stand area area and the second part of data; determining the optimal solution parameters according to the stand area and the number of people input; determining the seat coordinates corresponding to each intelligent agent according to the seat distribution and the optimal solution parameters; and generating an output file according to each seat distribution and the seat coordinates.

Description

Technical Field

[0001] The present application relates to the field of simulation technology, and in particular to a method, device, equipment, and storage medium for automatic identification of seats in a stadium. Background Art

[0002] In recent years, with the development of computer science and technology, large-scale crowd simulation has been widely used. As an analytical tool, crowd simulation can be used to simulate various public places and large-scale activities. For example, crowd assembly and evacuation simulation can be used in large places such as stadiums, cinemas, and squares to assist in judging whether the flow design of entrances and exits, corridors, etc. is reasonable and whether it causes congestion; or it can simulate crowd evacuation plans in emergency situations such as earthquakes and fires, so as to conduct various emergency pre-exercises at a lower cost in the computer, saving economic and human resource costs. On the other hand, simulation technology can be used as a visualization tool to more intuitively and realistically display the movement of the crowd through 2D or 3D models, so as to help decision makers make macro-control.

[0003] Simulation technology generally includes processes such as physical modeling, logic design, parameter optimization, and simulation calculation. Among them, physical modeling is the most basic step in the early process, which mainly presents the real building models such as roads, walls, obstacles, etc. in a specific simulation scene in proportion in the computer simulation system. Large-scale crowd gathering and evacuation simulation often has the problem of seat arrangement. In these actual scenes, there are fixed stands with fixed positions and numbers, such as in the gymnasium, and temporary stands with uncertain sizes and numbers. In the crowd gathering and evacuation simulation process with spectators going up and down the stands, the different arrangements of the stands will have a significant impact on the simulation results. In order to ensure the accuracy of the simulation results, the model construction of large-scale stands in the simulation system is very delicate and cumbersome, and the temporary stands may be adjusted many times due to actual conditions, simulation results and other factors. Before the optimal simulation plan is determined, the technicians may face hundreds of physical modeling of the stands in the venue, which undoubtedly adds a lot of repetitive work to the simulation process.

[0004] In summary, the crowd simulation process requires repeated modeling of stadium seats. Currently, there is no automatic dynamic seat recognition technology that can cope with uncertain sizes and numbers of stadium stands. Summary of the invention

[0005] The present application provides a method, device, equipment, and storage medium for automatic identification of seats in a stadium, which solves technical problems in existing simulation technologies such as difficulty in evenly distributing seats in stands and difficulty in obtaining seat location information.

[0006] A method for automatically identifying seats in a venue, comprising:

[0007] Acquire an input file, the input file comprising a first part of data and a second part of data, the first part of data comprising stand area coordinate parameters, the second part of data comprising seat parameters;

[0008] Determine the area of ​​the grandstand according to the first part of data;

[0009] Determine the seat distribution according to the area of ​​the stand area and the second part of data;

[0010] Determine the optimal solution parameters according to the area of ​​the stand area and the number of people input;

[0011] Determine the seat coordinates corresponding to each agent according to the seat distribution and the optimal solution parameters;

[0012] An output file is generated according to each seat distribution and the seat coordinates.

[0013] In an embodiment of the present application, determining the area of ​​the stand region according to the first part of data specifically includes:

[0014] The first part of data includes x-coordinates, y-coordinates, and z-coordinates of the outline nodes of the stand area;

[0015] Connecting the x-coordinates, y-coordinates, and z-coordinates of the outline nodes in sequence to form the shape of the stand area;

[0016] The area within the shape of the stand area is calculated based on the x-coordinate, y-coordinate, and z-coordinate of the contour node.

[0017] In one embodiment of the present application, determining the seat distribution according to the area of ​​the stand area and the second part of data specifically includes:

[0018] The second part of data includes the number of seats, the length of the seat interval, and the width of the seat interval in the grandstand area;

[0019] Determining the distribution of seats according to the number of seats in the grandstand area, the length of the seat interval, the width of the seat interval and the area of ​​the grandstand area;

[0020] The coordinates of each seat are determined according to the distribution of the seats and the first part of data.

[0021] In one embodiment of the present application, determining the optimal solution parameters according to the area of ​​the stand area and the number of people input specifically includes:

[0022] Determine the seating spacing parameters of the stand area that conforms to the uniform distribution condition according to the area of ​​the stand area and the input number of people;

[0023] It is determined whether the seat spacing parameter is an optimal solution parameter. If not, the seat spacing parameter is continuously iteratively optimized until the seat spacing parameter is an optimal solution parameter.

[0024] In one embodiment of the present application, generating an output file according to each seat distribution and the seat coordinates specifically includes:

[0025] Determine the x-coordinate, y-coordinate, row, column, and corresponding position label of each seat coordinate or seat label according to the seat distribution, wherein the corresponding position label includes left, middle, and right;

[0026] A table file is generated according to the x-coordinate, y-coordinate, row, column, and corresponding position label of each seat coordinate or seating arrangement label, and a visual view of the seat or seating arrangement is generated according to the table file.

[0027] A venue seat automatic identification device, comprising:

[0028] An input module, used for acquiring an input file, wherein the input file includes a first part of data and a second part of data, wherein the first part of data includes a stand area coordinate parameter, and the second part of data includes a seat parameter;

[0029] A calculation module, used to determine the area of ​​the stand area according to the first part of the data; determine the seat distribution according to the area of ​​the stand area and the second part of the data; determine the optimal solution parameters according to the area of ​​the stand area and the number of people input; determine the seat coordinates corresponding to each intelligent agent according to the seat distribution and the optimal solution parameters;

[0030] An output module is used to generate an output file according to each seat distribution and the seat coordinates.

[0031] In one embodiment of the present application, the first part of data includes x-coordinates, y-coordinates, and z-coordinates of outline nodes of the stand area;

[0032] The calculation module includes an area calculation unit for

[0033] Connecting the x-coordinates, y-coordinates, and z-coordinates of the outline nodes in sequence to form the shape of the stand area;

[0034] The area within the shape of the stand area is calculated based on the x-coordinate, y-coordinate, and z-coordinate of the contour node.

[0035] In one embodiment of the present application, the calculation module further includes an optimal solution parameter calculation unit for

[0036] Determine the seating spacing parameters of the stand area that conforms to the uniform distribution condition according to the area of ​​the stand area and the input number of people;

[0037] It is determined whether the seat spacing parameter is an optimal solution parameter. If not, the seat spacing parameter is continuously iteratively optimized until the seat spacing parameter is an optimal solution parameter.

[0038] A device for large-scale crowd motion simulation, comprising:

[0039] at least one processor; and,

[0040] a memory communicatively connected to the at least one processor; wherein,

[0041] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to cause the at least one processor to execute:

[0042] Acquire an input file, the input file comprising a first part of data and a second part of data, the first part of data comprising stand area coordinate parameters, the second part of data comprising seat parameters;

[0043] Determine the area of ​​the grandstand according to the first part of data;

[0044] Determine the seat distribution according to the area of ​​the stand area and the second part of data;

[0045] Determine the optimal solution parameters according to the area of ​​the stand area and the number of people input;

[0046] Determine the seat coordinates corresponding to each agent according to the seat distribution and the optimal solution parameters;

[0047] An output file is generated according to each seat distribution and the seat coordinates.

[0048] A non-volatile storage medium stores computer executable instructions, wherein the computer executable instructions are executed by a processor to implement the following steps:

[0049] Acquire an input file, the input file comprising a first part of data and a second part of data, the first part of data comprising stand area coordinate parameters, the second part of data comprising seat parameters;

[0050] Determine the area of ​​the grandstand according to the first part of data;

[0051] Determine the seat distribution according to the area of ​​the stand area and the second part of data;

[0052] Determine the optimal solution parameters according to the area of ​​the stand area and the number of people input;

[0053] Determine the seat coordinates corresponding to each agent according to the seat distribution and the optimal solution parameters;

[0054] An output file is generated according to each seat distribution and the seat coordinates.

[0055] The present application provides a method, device, equipment, and storage medium for automatic identification of seats in a stadium, which at least include the following beneficial effects: 1. It can automatically generate a seat point coordinate file and a schematic diagram according to the dynamic area shape, size, and number of people, satisfying the generation of stand seats in most scenarios; 2. It provides a recommendation algorithm, which can find the optimal seat spacing parameters according to the shape and number of people, and recommend them to the user. At the same time, the recommended parameters can also improve the calculation efficiency; 3. It is convenient for input and output, and the calculation can be completed by providing only the number of people and the stand coordinates. The stand coordinates can be generated in a unified format by the simulation personnel through the simulation system, and the calculated point coordinate file can be directly used by the simulation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0057] Figure 1 A schematic diagram of the steps of a method for automatically identifying seats in a stadium provided in an embodiment of the present application;

[0058] Figure 2 An architecture diagram of a venue seat automatic recognition system provided in an embodiment of the present application;

[0059] Figure 3 An example diagram of the shape of the stand area provided in the embodiment of the present application;

[0060] Figure 4 A flow chart of seat coordinate calculation provided in the embodiment of the present application;

[0061] Figure 5 A seat visualization view provided for an embodiment of the present application;

[0062] Figure 6 A structural diagram of a venue seat automatic recognition device provided in an embodiment of the present application;

[0063] Figure 7 A diagram showing the composition of an automatic venue seating recognition device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be described clearly and completely in conjunction with the specific embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0065] There are currently two main defects in the venue seating arrangement problem in the crowd simulation system:

[0066] 1. The seats in the stands cannot be evenly distributed. First of all, the design of the stands must ensure that the distance between adjacent seats is consistent, and at the same time, they should be evenly distributed in the stands. In the past, due to the irregular shape of the stands and the uncertainty of the number of people, the simulation software may have problems such as inconsistent distance between the front and back rows of seats and insufficient seats in the stands. The seats in the stands cannot be evenly distributed, which does not conform to the actual situation and will directly lead to calculation errors in the simulation.

[0067] Second, it is impossible to display the positional relationship of the stands. In the simulation system, it is necessary to obtain the point coordinates of each stand seat and the relative position of this seat in the stands (row, column), so as to help calculate the action trajectory of the intelligent agent. In the dynamic and uncertain stand model, it is difficult for general simulation systems to directly obtain the position information of the seats.

[0068] In order to solve the above problems, this application proposes a method, device, equipment, and storage medium for automatic identification of stadium seats. It can help simulation technicians to quickly calculate and generate seat coordinates and schematic diagrams that can meet uniform distribution for complex and irregular stand shapes and uncertain number of seats during simulation modeling. The following is a detailed description.

[0069] Figure 1 A schematic diagram of a method for automatically identifying seats in a venue provided in an embodiment of the present application may include the following steps:

[0070] S100: Acquire an input file, the input file includes a first part of data and a second part of data, the first part of data includes stand area coordinate parameters, and the second part of data includes seat parameters.

[0071] Specifically, the system architecture of this application is mainly divided into three layers: input layer, calculation layer and output layer. Figure 2 As shown in the figure, the input layer specifies the parameter format and data type of the algorithm input. The calculation layer uses the core algorithm to calculate the optimal parameters and seat points (seat coordinates). The algorithm flow mainly includes three parts: area calculation, parameter optimization, and coordinate generation. The output layer specifies the system output format and other related information.

[0072] The main input file of the input layer is the input.txt file, as shown in Table 1. The file includes two parts of data. The first line of the file contains the second part of the data. The 1713 in the first line represents the total number of seats planned to be generated in this stand area, and the length and width are both 50 pixels. The unit is constrained to pixels here to facilitate the interface with the simulation system. In the simulation system, the pixel unit can be converted into distance according to the actual situation.

[0073] The next n lines are the first part of the data, including the node coordinates necessary to describe the selected stand area. Similarly, the input format of x, y, z coordinates is used to facilitate the connection with the simulation system. In the simulation system, such coordinate text can be automatically exported according to the visualization interface.

[0074] The second part of the data is shown in Table 2, including the number of seats, the length of the seat interval, and the width of the seat interval. The first part of the data is shown in Table 3, including the necessary node coordinates to describe the selected stand area. It should be noted that Table 1 can be used as an input file alone, or Table 2 and Table 3 can be combined as an input file. The combination of Table 2 and Table 3 is Table 1.

[0075] Table 1

[0076] 1713 50 50 0 0 0 2 289 0 34 344 0 88 434 0 185 566 0 186 124 0 170 106 0 155 82 0 142 53 0 132 26 0 124 0 0

[0077] Table 2

[0078] Seating capacity long Width 1713 50 50

[0079] Table 3

[0080] X Y Z 0 0 0 2 289 0 34 344 0 88 434 0 185 566 0 186 124 0 170 106 0 155 82 0 142 53 0 132 26 0 124 0 0

[0081] S110: Determine the area of ​​the grandstand region according to the first part of data.

[0082] In one embodiment of the present application, the first part of data includes the x-coordinates, y-coordinates, and z-coordinates of the contour nodes of the stand area; the x-coordinates, y-coordinates, and z-coordinates of the contour nodes are connected in sequence to form the shape of the stand area; and the area within the shape of the stand area is calculated based on the x-coordinates, y-coordinates, and z-coordinates of the contour nodes.

[0083] Specifically, the coordinates contained in Table 3 represent the edge nodes of the stand area. Connecting the 11 edge nodes in sequence represents an irregular shape of the stand area, such as Figure 3 After the shape of the stand area is determined, the area of ​​the stand area shape is calculated by the x, y, and z coordinates, so that the actual area of ​​the stand area can be obtained by enlarging it according to a preset ratio.

[0084] S120: Determine the seat distribution according to the area of ​​the stand and the second part of data.

[0085] In one embodiment of the present application, the second part of data includes the number of seats, seat interval length, and seat interval width in the stand area; the seat distribution is determined based on the number of seats, seat interval length, seat interval width, and area of ​​the stand area; and the coordinates of each seat are determined based on the seat distribution and the first part of data.

[0086] Specifically, in order to simulate the seating arrangement in the scene, it is necessary to calculate the distribution of seats in the stand area based on the stand area simulation (generally taking the optimal distribution as the output result). In this application, the distribution of seats is calculated according to the input number of seats, the length of the interval between the left and right seats, the width of the interval between the front and rear seats, and the area of ​​the stand area (generally in accordance with uniform distribution) according to the set algorithm. Since the edge node coordinates of the stand area are known, the coordinates of each seat can be further calculated through the coordinates of the edge nodes, i.e., the first part of the data. Therefore, the staff can make further adjustments based on these data.

[0087] S130: Determine optimal solution parameters according to the area of ​​the stand and the number of people input.

[0088] In one embodiment of the present application, the seating spacing parameters of the stand area that meet the uniform distribution condition are determined based on the area of ​​the stand area and the number of people input; it is determined whether the seating spacing parameters are the optimal solution parameters, and if not, the seating spacing parameters are continuously iterated and optimized until the seating spacing parameters are the optimal solution parameters.

[0089] Specifically, in order to make the stand area look neat and orderly, the seats of the agents can be evenly arranged in the stand area. Therefore, the seat spacing parameters between each agent are calculated based on the input number of people and the area of ​​the stand area, that is, the number of seats between each agent. Each time a result is obtained in the calculation layer, it is determined whether the result has room for further optimization. If so, the calculation results are continuously iterated and optimized to make the seating position of each agent most consistent with the uniform distribution, so as to obtain the optimal solution parameters.

[0090] S140: Determine the seat coordinates corresponding to each intelligent agent according to the seat distribution and the optimal solution parameters.

[0091] Specifically, when the coordinates of each seat and the optimal solution parameters (that is, the seat spacing between each intelligent agent) are known, it is easy to know the seat coordinates corresponding to each intelligent agent. Since the seat coordinates represent the position of the seat, it is easy to know the row and column of each intelligent agent's seat in the stand area through the seat coordinates.

[0092] like Figure 4The figure shows the solution flow chart of the corresponding seat coordinates for each agent. The algorithm flow of the calculation layer mainly includes three parts: area calculation, parameter optimization, and coordinate generation. Among them, the calculation of the stand area is mainly solved by calculating the coordinates of each group (x, y, z) in the input layer; then iterative optimization is performed based on the area of ​​the stand area and the number of people input to obtain the optimal solution parameters; finally, based on the optimal solution parameters, the seat coordinates of each agent seat corresponding to the number are obtained. Finally, the results are output.

[0093] S150: Generate an output file according to each seat distribution and seat coordinate.

[0094] In one embodiment of the present application, the x-coordinate, y-coordinate, row, column, and corresponding position label of each seat coordinate or seat arrangement label are determined according to the seat distribution, and the corresponding position labels include left, center, and right; a table file is generated according to the x-coordinate, y-coordinate, row, column, and corresponding position label of each seat coordinate or seat arrangement label, and a visual view of the seat or seat arrangement is generated according to the table file.

[0095] Specifically, the output layer results include two parts: one is to obtain the x-coordinate, y-coordinate, z-coordinate and corresponding label of each seat that meets the conditions according to the parameters in the input file, and the result is displayed in the output.txt file; the other is to simply visualize the txt coordinate file, and the result is displayed in a .png picture.

[0096] As shown in Table 4, each line of the output file represents a seat, and each column represents the x-coordinate, y-coordinate, row, column and label. The labels are left, mid and right, which respectively indicate whether the seat is at the left, middle or right position in the current row.

[0097] Table 4

[0098] x y row colum label 7.5 11.4 1 1 Left 15.1 11.4 1 2 Mid 30.0 11.4 1 3 Mid 37.5 11.4 1 4 Mid 45.0 11.4 1 5 Right

[0099] like Figure 5 As shown, the output.png image file is generated in the output layer, which visually displays the calculation results.

[0100] This application designs an algorithm to calculate the area size of the stand area through the coordinates of the edge nodes of the irregular stand area; by calculating the optimal solution parameters, first find the optimal solution for the seat spacing in the stand area under the condition of uniform distribution, and use the optimal solution as a parameter for calculation to improve the efficiency of the algorithm; through point recording, generate a txt file to record the coordinates of each seat in the area, the row it belongs to, the column it belongs to, and a label of whether it is at the head of the row.

[0101] The above is a method for automatically identifying the seating arrangement in a stadium provided by the embodiment of the present application. Based on the same inventive idea, the embodiment of the present application also provides a corresponding device for automatically identifying the seating arrangement in a stadium, such as Figure 6 As shown, including:

[0102] An input module 601 is used to obtain an input file, the input file includes a first part of data and a second part of data, the first part of data includes stand area coordinate parameters, and the second part of data includes seat parameters;

[0103] The calculation module 602 is used to determine the area of ​​the stand area according to the first part of the data; determine the seat distribution according to the area of ​​the stand area and the second part of the data; determine the optimal solution parameters according to the area of ​​the stand area and the number of people input; determine the seat coordinates corresponding to each intelligent agent according to the seat distribution and the optimal solution parameters;

[0104] The output module 603 is used to generate an output file according to each seat distribution and seat coordinate.

[0105] The present application also provides a corresponding venue seat automatic recognition device, such as Figure 7 As shown, including:

[0106] at least one processor 701; and,

[0107] A memory 702 connected to at least one processor 701 via a bus 703; wherein,

[0108] The memory 702 stores instructions that can be executed by at least one processor 701. The instructions are executed by at least one processor 701 to enable the at least one processor 701 to:

[0109] Obtain an input file, the input file includes a first part of data and a second part of data, the first part of data includes stand area coordinate parameters, and the second part of data includes seat parameters;

[0110] Determine the area of ​​the grandstand based on the data in the first part;

[0111] Determine the seating distribution based on the area of ​​the stand and the second part of the data;

[0112] Determine the optimal solution parameters based on the area of ​​the stand and the number of people input;

[0113] Determine the seat coordinates corresponding to each agent based on the seat distribution and optimal solution parameters;

[0114] Generate output files based on each seat distribution and seat coordinates.

[0115] Based on the same idea, some embodiments of the present application also provide a medium corresponding to the above method.

[0116] Some embodiments of the present application provide a storage medium storing computer executable instructions, where the computer executable instructions are configured as follows:

[0117] Obtain an input file, the input file includes a first part of data and a second part of data, the first part of data includes stand area coordinate parameters, and the second part of data includes seat parameters;

[0118] Determine the area of ​​the grandstand based on the data in the first part;

[0119] Determine the seat distribution based on the area of ​​the stand and the second part of the data;

[0120] Determine the optimal solution parameters based on the area of ​​the stand and the number of people input;

[0121] Determine the seat coordinates corresponding to each agent based on the seat distribution and optimal solution parameters;

[0122] Generate output files based on each seat distribution and seat coordinates.

[0123] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the method and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0124] The methods and media provided in the embodiments of the present application correspond one-to-one to the method, and therefore, the methods and media also have similar beneficial technical effects as the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the methods and media will not be repeated here.

[0125] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or method including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or method. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or method including the elements.

[0126] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should all be included within the scope of the embodiments of the present application.

Claims

1. A method for automatically identifying seats in a venue, characterized in that: include: Acquire an input file, the input file comprising a first part of data and a second part of data, the first part of data comprising stand area coordinate parameters, the second part of data comprising seat parameters; Determine the area of ​​the grandstand according to the first part of data; Determine the seat distribution according to the area of ​​the stand area and the second part of data; Determine the seat spacing parameter between each agent in the stand area under the uniform distribution condition according to the area of ​​the stand area and the input number of people; determine whether the seat spacing parameter is an optimal solution parameter, and if not, continue to iteratively optimize the seat spacing parameter until the seat spacing parameter is an optimal solution parameter; Determine the seat coordinates corresponding to each agent according to the seat distribution and the optimal solution parameters; An output file is generated according to each seat distribution and the seat coordinates.

2. The method according to claim 1, characterized in that Determining the area of ​​the stand according to the first part of data specifically includes: The first part of data includes x-coordinates, y-coordinates, and z-coordinates of the outline nodes of the stand area; Connecting the x-coordinates, y-coordinates, and z-coordinates of the outline nodes in sequence to form the shape of the stand area; The area within the shape of the stand area is calculated based on the x-coordinate, y-coordinate, and z-coordinate of the contour node.

3. The method according to claim 1, characterized in that The determining of the seat distribution according to the area of ​​the stand area and the second part of data specifically includes: The second part of data includes the number of seats, the length of the seat interval, and the width of the seat interval in the grandstand area; Determining the distribution of seats according to the number of seats in the grandstand area, the length of the seat interval, the width of the seat interval and the area of ​​the grandstand area; The coordinates of each seat are determined according to the distribution of the seats and the first part of data.

4. The method according to claim 1, characterized in that The step of generating an output file according to each seat distribution and the seat coordinates specifically includes: Determine the x-coordinate, y-coordinate, row, column, and corresponding position label of each seat coordinate or seat label according to the seat distribution, wherein the corresponding position label includes left, middle, and right; A table file is generated according to the x-coordinate, y-coordinate, row, column, and corresponding position label of each seat coordinate or seating arrangement label, and a visual view of the seat or seating arrangement is generated according to the table file.

5. A venue seat automatic recognition device, characterized in that: include: An input module, used for acquiring an input file, wherein the input file includes a first part of data and a second part of data, wherein the first part of data includes a stand area coordinate parameter, and the second part of data includes a seat parameter; A calculation module is used to determine the area of ​​the stand area according to the first part of the data; determine the seat distribution according to the area of ​​the stand area and the second part of the data; determine the seat spacing parameter between each intelligent body in the stand area under the condition of uniform distribution according to the area of ​​the stand area and the input number of people; determine whether the seat spacing parameter is an optimal solution parameter, and if not, continue to iteratively optimize the seat spacing parameter until the seat spacing parameter is an optimal solution parameter; determine the seat coordinates corresponding to each intelligent body according to the seat distribution and the optimal solution parameter; An output module is used to generate an output file according to each seat distribution and the seat coordinates.

6. The device according to claim 5, characterized in that The first part of data includes x-coordinates, y-coordinates, and z-coordinates of the outline nodes of the stand area; The calculation module includes an area calculation unit for Connecting the x-coordinates, y-coordinates, and z-coordinates of the outline nodes in sequence to form the shape of the stand area; The area within the shape of the stand area is calculated based on the x-coordinate, y-coordinate, and z-coordinate of the contour node.

7. The device according to claim 5, characterized in that The calculation module also includes an optimal solution parameter calculation unit for Determine the seating spacing parameters of the stand area that conforms to the uniform distribution condition according to the area of ​​the stand area and the input number of people; It is determined whether the seat spacing parameter is an optimal solution parameter. If not, the seat spacing parameter is continuously iteratively optimized until the seat spacing parameter is an optimal solution parameter.

8. An automatic venue seat identification device, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to cause the at least one processor to execute: Acquire an input file, the input file comprising a first part of data and a second part of data, the first part of data comprising stand area coordinate parameters, the second part of data comprising seat parameters; Determine the area of ​​the grandstand according to the first part of data; Determine the seat distribution according to the area of ​​the stand area and the second part of data; Determine the seat spacing parameter between each agent in the stand area under the uniform distribution condition according to the area of ​​the stand area and the input number of people; determine whether the seat spacing parameter is an optimal solution parameter, and if not, continue to iteratively optimize the seat spacing parameter until the seat spacing parameter is an optimal solution parameter; Determine the seat coordinates corresponding to each agent according to the seat distribution and the optimal solution parameters; An output file is generated according to each seat distribution and the seat coordinates.

9. A non-volatile storage medium storing computer executable instructions, characterized in that: The computer executable instructions are executed by a processor to implement the following steps: Acquire an input file, the input file comprising a first part of data and a second part of data, the first part of data comprising stand area coordinate parameters, the second part of data comprising seat parameters; Determine the area of ​​the grandstand according to the first part of data; Determine the seat distribution according to the area of ​​the stand area and the second part of data; Determine the seat spacing parameter between each agent in the stand area under the uniform distribution condition according to the area of ​​the stand area and the input number of people; determine whether the seat spacing parameter is an optimal solution parameter, and if not, continue to iteratively optimize the seat spacing parameter until the seat spacing parameter is an optimal solution parameter; Determine the seat coordinates corresponding to each agent according to the seat distribution and the optimal solution parameters; An output file is generated according to each seat distribution and the seat coordinates.

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