Map specification detection method and system, medium and electronic equipment

Abstract

The invention provides a map specification detection method and system, a medium and electronic equipment. The method comprises the following steps: acquiring an input image; image judgment is carried out based on the input image to output a judgment result, the judgment result comprises a non-map, a map standard and a map non-standard, and map information identification is carried out on the input image based on a preset first classification model to judge and obtain the non-map; and performing map information identification on the input image based on a preset detection model to judge the non-map, the map standard and the map non-standard. According to the map specification detection method and system, the medium and the electronic equipment, whether the input image is the target map or not can be rapidly recognized, and rapidness and high efficiency are achieved; secondly, different image processing models are adopted to carry out targeted detection on the image information, so that the standard detection accuracy is improved; and the detection intelligence degree is high, practicability is high, and application and popularization are convenient.

Description

Technical Field

[0001] The present invention belongs to the technical field of image processing, and particularly relates to a method, a system, a medium, and an electronic device for map specification detection. Background Art

[0002] A map is a graphic or image that selectively represents several phenomena of the Earth (or other planets) in two-dimensional or multi-dimensional forms and means on a plane or a spherical surface according to certain rules. It has a strict mathematical basis, a symbol system, and text annotations, and can scientifically reflect the distribution characteristics and their interrelationships of natural and socio-economic phenomena using the map generalization principle.

[0003] In actual use, a national map represents the national territorial scope. In the actual production and living process, the existing Chinese maps have the following deficiencies:

[0004] (1) There are non-standard behaviors such as map information omission and missing;

[0005] (2) There are non-standard behaviors where the map information standards are incorrect. Summary of the Invention

[0006] In view of the above-mentioned deficiencies of the prior art, the purpose of the present invention is to provide a method, a system, a medium, and an electronic device for map specification detection to solve the problem of map specification detection.

[0007] In a first aspect, the present invention provides a method for map specification detection, and the method includes the following steps:

[0008] Obtain an input image;

[0009] Perform image judgment based on the input image to output a judgment result, where the judgment result includes non-map, map specification, and map non-specification. Among them,

[0010] Perform map information recognition on the input image based on a preset first classification model to determine the non-map;

[0011] Perform map information recognition on the input image based on a preset detection model to determine the non-map, the map specification, and the map non-specification.

[0012] In a possible implementation manner of the present application, the obtaining of the input image specifically includes:

[0013] Obtain the input data of the client;

[0014] Perform file format differentiation based on the input data, and among them, extract the data of the image file format to obtain the input image.

[0015] In a possible implementation manner of the present application, identifying map information for the input image based on a preset first classification model specifically includes:

[0016] The first classification model includes a mobile-net_v3 classification model, where

[0017] Classifying whether the current input image contains map information based on the mobile-net_v3 classification model, where

[0018] If the input image contains map information, output a judgment result to enter the next process;

[0019] If the input image does not contain map information, output a judgment result of non-map.

[0020] In a possible implementation manner of the present application, identifying map information for the input image based on a preset detection model specifically includes:

[0021] The detection model includes a pp-yoloe object detection model, where

[0022] Detecting feature information for the input image based on the pp-yoloe object detection model to output a judgment result, where

[0023] If the feature information is not detected in the input image, output a judgment result of non-map;

[0024] If not all of the feature information is detected in the input image, output a judgment result of map non-standard, where the feature information includes a first feature, a second feature, and a third feature;

[0025] If all of the feature information is detected in the input image, output a judgment result to enter the next process.

[0026] In a possible implementation manner of the present application, when the first feature is detected based on the input image, specifically includes:

[0027] The detection model further includes a pp-yolov2 object detection model, and detecting the number of archipelagos in the first feature based on the pp-yolov2 object detection model, where

[0028] If the detection result is different from a preset first correct value, output a judgment result of map non-standard;

[0029] If the detection result is the same as the preset first correct value, output a judgment result of map first feature standard.

[0030] In a possible implementation of the present application, when the second feature is detected based on the input image, it specifically includes:

[0031] The detection model further includes a pp-yolov2 object detection model, and the number of islands in the second feature is detected based on the pp-yolov2 object detection model, where

[0032] If the detection result is different from a preset second correct value, the output judgment result is that the map is not standard;

[0033] If the detection result is the same as the preset second correct value, the output judgment result is that the second feature of the map is standard.

[0034] In a possible implementation of the present application, when the first feature is detected based on the input image, the method further includes:

[0035] Classify the boundary lines in the first feature based on a preset second classification model, and the second classification model includes a VIT model, where

[0036] If the classified boundary lines are distorted, the output judgment result is that the map is not standard;

[0037] Otherwise, the output judgment result is that the boundary lines of the map are standard.

[0038] In a second aspect, the present invention provides a map standard detection system, and the system includes:

[0039] An acquisition module, configured to acquire an input image;

[0040] A judgment module, configured to perform image judgment based on the input image to output a judgment result, and the judgment result includes non-map, map standard, and map non-standard, where

[0041] A first recognition module, configured to perform map information recognition on the input image based on a preset first classification model to judge and obtain the non-map;

[0042] A second recognition module, configured to perform map information recognition on the input image based on a preset detection model to judge and obtain the non-map, the map standard, and the map non-standard.

[0043] In a third aspect, the present invention provides an electronic device, and the electronic device includes: a processor and a memory;

[0044] The memory is used to store a computer program;

[0045] The processor is configured to execute the computer program stored in the memory, so that the electronic device executes the above-mentioned map standard detection method.

[0046] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by an electronic device, the above-mentioned map specification detection method is implemented.

[0047] As described above, the map specification detection method, system, medium and electronic device of the present invention have the following beneficial effects:

[0048] (1) It can quickly identify whether the input image is a target map, such as a map of China, quickly and efficiently;

[0049] (2) Different image processing models are used to perform targeted detection on image information, improving the accuracy of specification detection;

[0050] (3) It has a high degree of intelligence and is very practical. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It shows a schematic diagram of a scene of the electronic device of the present invention in an embodiment;

[0052] Figure 2 It shows a flowchart of the map specification detection method of the present invention in an embodiment;

[0053] Figure 3 It shows a schematic diagram of steps of the map specification detection method of the present invention in an embodiment;

[0054] Figure 4 It shows a schematic structural diagram of the map specification detection system of the present invention in an embodiment;

[0055] Figure 5 It shows a schematic structural diagram of the electronic device of the present invention in an embodiment.

[0056] DESCRIPTION OF REFERENCE NUMERALS

[0057] Steps S302 to S308 40 Map specification detection system

[0058] 41 Acquisition module

[0059] 42 Judgment module

[0060] 43 First recognition module

[0061] 44 Second recognition module DETAILED DESCRIPTION OF THE INVENTION

[0062] The following specific examples illustrate the embodiments of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0063] It should be noted that the illustrations provided in the following embodiments only schematically illustrate the basic concept of the present invention. Therefore, only the components related to the present invention are shown in the drawings, rather than being drawn according to the number, shape, and size of the components in actual implementation. The type, quantity, and proportion of each component in actual implementation can be arbitrarily changed, and the component layout type may also be more complex.

[0064] The following embodiments of the present invention provide a method for detecting map specifications, which can be applied to an electronic device as shown in Figure 1 The electronic device described in the present invention may include a mobile phone 11 with a wireless charging function, a tablet computer 12, a laptop computer 13, a wearable device, a vehicle-mounted device, an augmented reality (AR) / virtual reality (VR) device, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), etc. The specific type of the electronic device in the embodiments of the present invention is not limited in any way.

[0065] For example, the electronic device may be a station (STAION, ST) in a WLAN with wireless charging function, a cellular phone with wireless charging function, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device with wireless charging function, a computing device or other processing device, a computer, a laptop computer, a handheld communication device, a handheld computing device, and / or other devices for communicating on a wireless system, as well as next-generation communication systems, such as mobile terminals in a 5G network, mobile terminals in a future evolved Public Land Mobile Network (PLMN), or mobile terminals in a future evolved Non-terrestrial Network (NTN).

[0066] For example, the electronic device may communicate with the network and other devices through wireless communication. The above wireless communication may use any communication standard or protocol, including but not limited to Global System of Mobile communication (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), email, Short Messaging Service (SMS), BT, GNSS, WLAN, NFC, FM, and / or IR technology, etc. The GNSS may include Global Positioning System (GPS), Global Navigation Satellite System (GLONASS), BeiDou navigation Satellite System (BDS), Quasi-Zenith Satellite System (QZSS), and / or Satellite Based Augmentation Systems (SBAS).

[0067] In order to quickly and accurately analyze whether a map meets the established specification standards, this application describes a method for map specification detection, and uses object detection and image classification technologies to detect map compliance. Among them, refer to Figure 2 , which is a schematic diagram of the map specification detection process described in this application. Among them, taking the scenario application of detecting whether the input image is a map of China as an example, for the input image, first, the mobile-net_v3 classification model is used for the first step of detection to distinguish non-map images and map images. Then, the pp-yoloe detection model is used to intercept different images based on the output coordinate information for feature information recognition, so as to distinguish non-map graphics and the detection results of non-compliant maps. Among them, the feature information includes the first feature, the second feature, and the third feature. Corresponding to the specific embodiments of this application, the first feature is the Chinese mainland, the second feature is Taiwan, and the third feature is the South China Sea Islands. Further, for the map that has detected all the feature information, it is necessary to further use the pp-yolov2 detection model and the VIT model for subsequent detection to obtain the corresponding detection results. Among them, the VIT model, that is, Vision Transformer, its main structure is based on the Encoder part of the Transformer model, and is mainly composed of two sub-layers: a multi-head attention mechanism layer and a multi-layer perceptron layer. Each sub-layer has a residual connection, and is used in this application to detect whether the boundary of the Chinese mainland is distorted. The pp-yoloe model is a single-stage Anchor-free model based on the pp-yolov2 model, and is used in this application to detect the feature information of the input image. And the pp-yolov2 model is also a version of the algorithm released based on the Baidu self-developed Paddle-Paddle deep learning framework, and is used in this application to detect the number of island groups in the image according to the coordinate information.

[0068] Next, the technical solutions in the embodiments of the present invention will be described in detail with reference to the accompanying drawings in the embodiments of the present invention.

[0069] Specifically, please refer to Figure 3 , in an embodiment of the invention, the map specification detection method of the present invention includes the following steps:

[0070] Step S302, obtain the input image;

[0071] Step S304, perform image judgment based on the input image to output a judgment result, and the judgment result includes non-map, map specification, and map non-compliance;

[0072] Step S306, perform map information recognition on the input image based on a preset first classification model to determine the non-map;

[0073] Step S308, perform map information recognition on the input image based on a preset detection model to determine the non-map, the map specification, and the non-compliant map.

[0074] It should be noted that in this embodiment, first, a target map needs to be determined, and then image data analysis is performed on the input image to determine whether the input image conforms to the specification of the current target map. Specifically, taking the map of China as an example, it contains various characteristic information such as the Chinese mainland, Taiwan region, and South China Sea region. First, the input image needs to be obtained, specifically including: obtaining the input data of the client, and then differentiating the file format based on the input data. Among them, the data of the image file format is extracted to obtain the input image.

[0075] Furthermore, image judgment is performed based on the input image to output a judgment result. The judgment result includes non-map, map specification, and non-compliant map. Among them, different classification or detection models are used to process the input image to obtain the corresponding judgment result.

[0076] Furthermore, in an embodiment of the invention, map information recognition is performed on the input image based on a preset first classification model. Specifically, the first classification model includes the mobile-net_v3 classification model. Among them, based on the mobile-net_v3 classification model, it is classified whether the current input image contains map information. If the input image contains map information, the judgment result is output to enter the next process; if the input image does not contain map information, the judgment result is output as non-map.

[0077] It should be noted that in this embodiment, for the input image, in the first step, the first classification model (i.e., the mobile-net_v3 classification model) is used to screen the map information. If the input image contains map information, the judgment result is output to enter the next process and wait for subsequent processing; if the input image does not contain map information, the judgment result is output as non-map, and the current map specification detection process is ended.

[0078] Furthermore, in an embodiment of the invention, the map information recognition of the input image based on the preset detection model specifically includes:

[0079] The detection model includes the pp-yoloe object detection model, where

[0080] Feature information detection is performed on the input image based on the pp-yoloe object detection model to output a judgment result, where

[0081] If the feature information is not detected in the input image, the output judgment result is non-map;

[0082] If all the feature information is not detected in the input image, the output judgment result is that the map is not standard, where the feature information includes the first feature, the second feature, and the third feature;

[0083] If all the feature information is detected in the input image, the output judgment result is to enter the next process.

[0084] It should be noted that in this embodiment, since the target map is the map of China, the corresponding map feature information includes the continental shelf and its affiliated islands, Taiwan region, South China Sea region, etc. Correspondingly, the continental shelf and its affiliated islands correspond to the first feature, the South China Sea region corresponds to the second feature, and the Taiwan region corresponds to the third feature. Among them, in practical applications, different feature information can be distinguished by color differentiation and other visualization means. Specifically, the pp-yoloe detection model is used to detect the feature information of the input image. Among them, if the feature information is not detected in the input image, the output judgment result is non-map, that is, it corresponds to not detecting any feature information in the map of China, indicating that the currently input image is not the map of China; further, if all the feature information is not detected in the input image, the output judgment result is that the map is not standard, where the feature information includes the first feature, the second feature, and the third feature, that is, when one or two of the three feature information are detected, it indicates that the currently detected input image is the map of China, but the map is not standard and needs to be adjusted, and the user will be reminded according to the missing feature information for supplementation; further, if all the feature information is detected in the input image, the output judgment result is to enter the next process. In this scenario, it indicates that the currently input image includes the three feature information of the map of China, meeting the basic requirements of the map of China, and further subdivision is required to determine whether it is a standardized map of China.

[0085] Further, in an embodiment of the invention, when the first feature is detected based on the input image, it specifically includes:

[0086] The detection model further includes the pp-yolov2 object detection model, and the number of archipelagos in the first feature is detected based on the pp-yolov2 object detection model, where

[0087] If the detection result is different from the preset first correct value, the output judgment result is that the map is not standard;

[0088] If the detection result is the same as the preset first correct value, the output judgment result is that the first feature of the map is standard.

[0089] It should be noted that in this embodiment, since the target map to be detected is a map of China, correspondingly, the first feature is the continental shelf and its affiliated islands. Therefore, the pp-yolov2 object detection model can be used to detect whether the number of continental islands is correct. The preset first correct value is "3". If the detection result is different from the preset first correct value, the judgment result is that the map is not standard, that is, when the detected number of continental islands is not "3", the judgment result output is that the map is not standard; if the detection result is the same as the preset first correct value, the judgment result is that the first feature of the map is standard, that is, when the detected number of continental islands is equal to "3", it indicates that the detection corresponding to the current first feature is correct, and the judgment result that the detection result of the first feature is that the map is standard can be output. For the entire map, the map standard can be finally output only when all feature information is ensured to be standard.

[0090] Further, in an embodiment of the invention, when the second feature is detected based on the input image, it specifically includes:

[0091] The detection model further includes the pp-yolov2 object detection model, which is used to detect the number of islands in the second feature based on the pp-yolov2 object detection model, where

[0092] If the detection result is different from the preset second correct value, the judgment result is that the map is not standard;

[0093] If the detection result is the same as the preset second correct value, the judgment result is that the second feature of the map is standard.

[0094] It should be noted that in this embodiment, since the target map to be detected is a map of China, correspondingly, the second feature is the South China Sea region. Therefore, the image of the South China Sea Islands can be intercepted through the coordinate information output by the pp-yoloe model and input into the pp-yolov2 detection model to detect whether the number of the South China Sea Islands is correct. The preset second correct value is "7". If the detection result is different from the preset second correct value, the judgment result is that the map is not standard, that is, when the detected number of the South China Sea Islands is not "7", the judgment result output is that the map is not standard; if the detection result is the same as the preset second correct value, the judgment result is that the second feature of the map is standard, that is, when the detected number of the South China Sea Islands is equal to "7", it indicates that the detection corresponding to the current second feature is correct, and the judgment result that the detection result of the second feature is that the map is standard can be output. For the entire map, the map standard can be finally output only when all feature information is ensured to be standard.

[0095] In addition, it should be noted that for the Taiwan region corresponding to the third feature, detection is also required. The specific detection steps are the same as those in the above embodiment and will not be elaborated here.

[0096] Further, in an embodiment of the invention, when the first feature is detected based on the input image, the method further includes:

[0097] Classify the boundary lines in the first feature based on a preset second classification model, where the second classification model includes a VIT model. Among them,

[0098] If the classified boundary lines are distorted, output a judgment result that the map is not standard;

[0099] Otherwise, output a judgment result that the map boundary lines are standard.

[0100] It should be noted that in this embodiment, for the first feature, in addition to detecting the number of its archipelagos, it is also necessary to detect the boundary line features of it. Specifically, the VIT model is used to classify the boundary lines in the first feature. Among them, if the classified boundary lines are distorted, output a judgment result that the map is not standard; otherwise, output a judgment result that the map boundary lines are standard. Among them, the VIT model, that is, the Vision Transformer model, is a conventional model known to those skilled in the art. The specific detection process will not be elaborated here. In this embodiment, it is only used as an application and does not involve the adjustment of the model itself.

[0101] In summary, after all feature information detections meet the specifications, the map information corresponding to the current input image can be judged to meet the map specifications before subsequent applications can be carried out.

[0102] The embodiment of the present application also provides a map specification detection system. The map specification detection system can implement the map specification detection method described in the present application. However, the implementation device of the map specification detection method described in the present application includes but is not limited to the structure of the map specification detection system listed in this embodiment. Any structural deformation and replacement of the prior art made according to the principle of the present application are included in the protection scope of the present application.

[0103] Please refer to Figure 4 , in an embodiment, a map specification detection system 40 provided in this embodiment, the system includes:

[0104] An acquisition module 41, configured to acquire an input image;

[0105] A judgment module 42, configured to perform image judgment based on the input image to output a judgment result, where the judgment result includes non-map, map specification, and map non-specification. Among them,

[0106] A first recognition module 43, configured to perform map information recognition on the input image based on a preset first classification model to judge and obtain the non-map;

[0107] A second recognition module 44, configured to perform map information recognition on the input image based on a preset detection model to determine the non-map, the map specification, and the map non-specification.

[0108] Since the specific implementation manner of this embodiment corresponds to the foregoing method embodiment, the same details will not be repeated here. Those skilled in the art should also understand that Figure 4 The division of each module in the embodiment is only a division of logical functions. In actual implementation, it can be fully or partially integrated into one or more physical entities, and these modules can all be implemented in the form of software called by processing elements, or all in the form of hardware, or some modules can be implemented in the form of software called by processing elements, and some modules can be implemented in the form of hardware.

[0109] In several embodiments provided by the present invention, it should be understood that the disclosed system, device, or method can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of modules / units is only a division of logical functions. In actual implementation, there may be other division methods. For example, multiple modules or units can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces, indirect coupling or communication connection of devices or modules or units, which can be electrical, mechanical or other forms.

[0110] The modules / units described as separate components may or may not be physically separated. The components shown as modules / units may or may not be physical modules, that is, they can be located in one place, or distributed to multiple network units. Part or all of the modules / units can be selected according to actual needs to achieve the purpose of the embodiments of the present invention. For example, in each embodiment of the present invention, the various functional modules / units can be integrated in a processing module, or each module / unit can exist physically alone, or two or more modules / units can be integrated in one module / unit.

[0111] Those of ordinary skill in the art should further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0112] Embodiments of the present invention also provide a computer-readable storage medium. Those of ordinary skill in the art can understand that all or part of the steps in the method for implementing the above embodiments can be completed by a program instructing a processor. The program can be stored in a computer-readable storage medium, and the storage medium is a non-transitory medium, such as random access memory, read-only memory, flash memory, hard disk, solid-state drive, magnetic tape, floppy disk, optical disc, and any combination thereof. The above storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., digital video disc (DVD)), or a semiconductor medium (e.g., solid-state disk (SSD)), etc.

[0113] Embodiments of the present application can also provide a computer program product, which includes one or more computer instructions. When the computer instructions are loaded and executed on a computing device, the processes or functions described in the embodiments of the present application are fully or partially generated. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, computer, or data center to another website, computer, or data center in a wired manner (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or a wireless manner (e.g., infrared, wireless, microwave, etc.).

[0114] When the computer program product is executed by a computer, the computer executes the method described in the foregoing method embodiments. The computer program product can be a software installation package. In the case where the foregoing method is required, the computer program product can be downloaded and executed on the computer.

[0115] The descriptions of the processes or structures corresponding to the above-mentioned various drawings each have their own focuses. For the parts not detailed in a certain process or structure, reference can be made to the relevant descriptions of other processes or structures.

[0116] The embodiment of the present invention also provides an electronic device. The electronic device includes a processor and a memory.

[0117] The memory is used to store a computer program.

[0118] The memory includes various media that can store program codes, such as ROM, RAM, magnetic disks, USB flash drives, memory cards, or optical discs.

[0119] The processor is connected to the memory and is used to execute the computer program stored in the memory, so that the electronic device executes the above-mentioned map specification detection method.

[0120] Preferably, the processor may be a general-purpose processor, including a central processing unit (abbreviated as CPU), a network processor (abbreviated as NP), etc.; it may also be a digital signal processor (abbreviated as DSP), an application specific integrated circuit (abbreviated as ASIC), a field programmable gate array (abbreviated as FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0121] As Figure 5 shown, the electronic device of the present invention is presented in the form of a general computing device. The components of the electronic device may include, but are not limited to: one or more processors or processing units 51, a memory 52, and a bus 53 connecting different system components (including the memory 52 and the processing unit 51).

[0122] The bus 53 represents one or more of several types of bus structures, including a memory bus or a memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any bus structure in a variety of bus structures. For example, these architectures include, but are not limited to, an industry standard architecture (ISA) bus, a microchannel architecture (MAC) bus, an enhanced ISA bus, a video electronics standards association (VESA) local bus, and a peripheral component interconnect (PCI) bus.

[0123] An electronic device typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device, including volatile and non-volatile media, removable and non-removable media.

[0124] Memory 52 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 521 and / or cache memory 522. The electronic device can further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 523 can be used for reading and writing on non-removable, non-volatile magnetic media ( Figure 5 not shown, commonly referred to as a "hard disk drive"). Although Figure 5 not shown in the figure, a disk drive for reading and writing on a removable non-volatile disk (such as a "floppy disk") and an optical disk drive for reading and writing on a removable non-volatile optical disk (such as a CD-ROM, DVD-ROM or other optical media) can be provided. In these cases, each drive can be connected to bus 53 through one or more data media interfaces. Memory 52 can include at least one program product having a set (such as at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0125] A program / utility 524 having a set (at least one) of program modules 5241 can be stored in, for example, memory 52. Such program modules 5241 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 5241 generally perform the functions and / or methods in the embodiments described in the present invention.

[0126] The electronic device can also communicate with one or more external devices (such as a keyboard, a pointing device, a display, etc.), and can also communicate with one or more devices that enable a user to interact with the electronic device, and / or communicate with any device that enables the electronic device to communicate with one or more other computing devices (such as a network card, a modem, etc.). Such communication can be carried out through an input / output (I / O) interface 54. And, the electronic device can also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN) and / or a public network, such as the Internet) through a network adapter 55. As Figure 5 shown, network adapter 55 communicates with other modules of the electronic device through bus 53. It should be understood that although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0127] The above embodiments are only illustrative of the principles and effects of the present invention and are not intended to limit the present invention. Any person familiar with this technology can modify or change the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or changes made by those with ordinary knowledge in the technical field without departing from the spirit and technical ideas disclosed by the present invention should still be covered by the claims of the present invention.

Claims

1. A method for detecting map specifications, characterized in that, Including: Obtain an input image; Perform image judgment based on the input image to output a judgment result, where the judgment result includes non-map, map specification, and map non-specification. Among them, Perform map information recognition on the input image based on a preset first classification model to determine the non-map; Perform map information recognition on the input image based on a preset detection model to determine the non-map, the map specification, and the map non-specification.

2. The map specification detection method according to claim 1, wherein The obtaining of the input image specifically includes: Obtain the input data of the client; Perform file format differentiation based on the input data. Among them, extract the data in the image file format to obtain the input image.

3. The map specification detection method according to claim 2, characterized in that Performing map information recognition on the input image based on a preset first classification model specifically includes: The first classification model includes a mobile-net_v3 classification model. Among them, Classify whether the current input image contains map information based on the mobile-net_v3 classification model. Among them, If the input image contains map information, output a judgment result to enter the next process; If the input image does not contain map information, output a judgment result of non-map.

4. The map specification detection method according to claim 3, wherein The performing of map information recognition on the input image based on a preset detection model specifically includes: The detection model includes a pp-yoloe object detection model. Among them, Perform feature information detection on the input image based on the pp-yoloe object detection model to output a judgment result. Among them, If the feature information is not detected in the input image, output a judgment result of non-map; If not all of the feature information is detected in the input image, output a judgment result of map non-specification, where the feature information includes a first feature, a second feature, and a third feature; If all of the feature information is detected in the input image, output a judgment result to enter the next process.

5. The map specification detection method according to claim 4, wherein When the first feature is detected based on the input image, specifically includes: The detection model further includes a pp-yolov2 object detection model. Detect the number of archipelagos in the first feature based on the pp-yolov2 object detection model. Among them, If the detection result is different from a preset first correct value, output a judgment result of map non-specification; If the detection result is the same as the preset first correct value, output a judgment result of map first feature specification.

6. The map specification detection method according to claim 4, characterized in that When the second feature is detected based on the input image, specifically includes: The detection model further includes a pp-yolov2 object detection model. Detect the number of archipelagos in the second feature based on the pp-yolov2 object detection model. Among them, If the detection result is different from a preset second correct value, output a judgment result of map non-specification; If the detection result is the same as the preset second correct value, output a judgment result of map second feature specification.

7. The map specification detection method according to claim 4, wherein When the first feature is detected based on the input image, the method further includes: Classify the boundary line in the first feature based on a preset second classification model. The second classification model includes a VIT model. Among them, If the classified boundary line is distorted, the output judgment result is that the map is not standard; Otherwise, the output judgment result is that the map boundary line is standard.

8. A map specification detection system, characterized in that, Including: An acquisition module for acquiring an input image; A judgment module for performing image judgment based on the input image to output a judgment result, the judgment result including non-map, map standard, and map non-standard, where A first recognition module for recognizing map information from the input image based on a preset first classification model to judge the non-map; A second recognition module for recognizing map information from the input image based on a preset detection model to judge the non-map, the map standard, and the map non-standard.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the map standard detection method described in any one of claims 1 to 7.

10. An electronic device, characterized in that, The electronic device includes: a processor and a memory; wherein, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory so that the electronic device executes the map standard detection method described in any one of claims 1 to 7.

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