CN111178147B - Screen crushing and grading method, device, equipment and computer readable storage medium - Google Patents
Screen crushing and grading method, device, equipment and computer readable storage medium Download PDFInfo
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Abstract
The application provides a screen crushing and grading method, a device, equipment and a computer readable storage medium, wherein the method comprises the following steps: obtaining a broken screen claim photo, and carrying out authenticity verification on the broken screen claim photo; when the broken screen claim photo passes the authenticity verification, a screen breaking area in the broken screen claim photo is obtained through a preset broken screen detection model; and determining the screen crushing grade of the screen crushing claim photo according to a preset screen crushing degree grading model and the screen crushing area. The application relates to image detection, which can accurately and quickly check photos by checking the authenticity of the broken screen claim photos, automatically evaluate the broken degree of the screen and reduce the risk of cheating protection.
Description
Technical Field
The present application relates to the field of image detection technologies, and in particular, to a method, an apparatus, a device, and a computer readable storage medium for screen crushing and grading.
Background
With the popularization and application of electronic devices, such as smart phones, tablet computers, electronic learning machines and electronic readers, the problems of depreciation, screen breakage and the like of the electronic devices are also endless, particularly the problem of screen breakage, the screen of the electronic devices is generally expensive, a certain amount of money is required to be replaced after the screen is broken, and the loss is brought to users. At present, money loss after screen breaking can be reduced by applying screen breaking risk, when screen breaking occurs to electronic equipment applied by a user, claim settlement can be initiated to an insurance company, and the damage is verified by the insurance company.
The traditional check damage is that a check person manually compares a screen broken photo of a claim with a screen photo of an electronic device to be applied, whether the electronic device for checking the claim is the electronic device applied by a user or not, and after the check passes, the screen broken degree is estimated according to experience. Therefore, how to accurately and rapidly check photos and evaluate the screen breakage degree is a problem to be solved at present.
Disclosure of Invention
The application mainly aims to provide a screen crushing and grading method, device and equipment and a computer readable storage medium, and aims to accurately and rapidly check photos and evaluate the crushing degree of a screen.
In a first aspect, the present application provides a screen crushing and classifying method, comprising the steps of:
obtaining a broken screen claim photo, and carrying out authenticity verification on the broken screen claim photo;
when the broken screen claim photo passes the authenticity verification, a screen breaking area in the broken screen claim photo is obtained through a preset broken screen detection model;
And determining the screen crushing grade of the screen crushing claim photo according to a preset screen crushing degree grading model and the screen crushing area.
In a second aspect, the present application also provides a screen crushing and classifying apparatus, the screen crushing and classifying apparatus comprising:
the verification module is used for obtaining the broken screen claim photo and carrying out authenticity verification on the broken screen claim photo;
the broken screen detection module is used for acquiring a screen broken area in the broken screen claim photo through a preset broken screen detection model when the broken screen claim photo passes the authenticity verification;
and the crushing grade determining module is used for determining the screen crushing grade of the screen crushing claim photo according to a preset screen crushing degree grading model and the screen crushing area.
In a third aspect, the present application also provides a computer device comprising a processor, a memory, and a computer program stored on the memory and executable by the processor, wherein the computer program when executed by the processor implements the steps of a screen break classification method as described above.
In a fourth aspect, the present application also provides a computer readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of a screen break up classification method as described above.
The application provides a screen crushing and grading method, a device, equipment and a computer readable storage medium.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a screen crushing and grading method according to an embodiment of the present application;
fig. 2 is a schematic view of a scene for implementing the screen crushing and grading method according to the present embodiment;
FIG. 3 is a schematic flow chart of another screen crushing and classifying method according to an embodiment of the present application;
FIG. 4 is a flow chart of sub-steps of the screen crushing and classifying method of FIG. 3;
FIG. 5 is a schematic block diagram of a screen crushing and grading device according to an embodiment of the present application;
FIG. 6 is a schematic block diagram of another screen crushing and grading device provided by an embodiment of the present application;
fig. 7 is a schematic block diagram of a computer device according to an embodiment of the present application.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The flow diagrams depicted in the figures are merely illustrative and not necessarily all of the elements and operations/steps are included or performed in the order described. For example, some operations/steps may be further divided, combined, or partially combined, so that the order of actual execution may be changed according to actual situations.
The embodiment of the application provides a screen crushing and grading method, device and equipment and a computer readable storage medium. The screen crushing and grading method can be applied to a server, wherein the server can be a single server or a server cluster consisting of a plurality of servers.
Some embodiments of the present application are described in detail below with reference to the accompanying drawings. The following embodiments and features of the embodiments may be combined with each other without conflict.
Referring to fig. 1, fig. 1 is a flow chart of a screen crushing and classifying method according to an embodiment of the application.
As shown in fig. 1, the screen crushing and classifying method includes steps S101 to S103.
And step S101, obtaining a broken screen claim photo, and carrying out authenticity verification on the broken screen claim photo.
The terminal equipment receives the garrulous screen claim settlement photo uploaded based on the garrulous screen claim settlement page, generates the garrulous screen claim settlement request carrying the garrulous screen claim settlement photo, sends the garrulous screen claim settlement request to the server, receives the garrulous screen claim settlement request, acquires the garrulous screen claim settlement photo in the garrulous screen claim settlement request, can determine the screen crushing grade based on the garrulous screen claim settlement photo in real time, can also store the garrulous screen claim settlement photo first, and can acquire the garrulous screen crushing grade based on the acquired garrulous screen claim photo at a later time. It should be noted that the terminal device may be a broken screen terminal, or may be other terminal devices for capturing a broken screen terminal, which is not particularly limited in the present application.
In an embodiment, when the server receives the garrulous screen claim settlement request, validity check can be performed on the garrulous screen claim settlement photo in the garrulous screen claim settlement request, when the garrulous screen claim settlement photo passes the validity check, the screen breaking grade can be determined based on the garrulous screen claim settlement photo in real time or at fixed time, and when the garrulous screen claim settlement photo does not pass the validity check, reminding information is sent to the terminal device to remind a user to upload or shoot the garrulous screen claim settlement photo again. Through carrying out validity check to this garrulous screen claim photo, can obtain the garrulous screen claim photo that definition is higher, can improve the degree of accuracy of confirming screen breakage class based on garrulous screen claim photo.
It can be understood that, when the terminal device uploads or shoots the broken screen claim photo, the terminal device performs validity check on the broken screen claim photo, when the broken screen claim photo passes the validity check, a broken screen claim request carrying the broken screen claim photo is generated, the broken screen claim request is sent to the server, and when the broken screen claim photo does not pass the validity check, the user is reminded to upload or shoot the broken screen claim photo again.
The method for verifying the validity of the broken screen claim photo specifically comprises the following steps: the terminal equipment or the server runs a pre-stored definition detection program to determine the image definition of the broken screen claim photo, judges whether the image definition is larger than or equal to a preset threshold, determines that the broken screen claim photo passes the validity check if the image definition is larger than or equal to the preset threshold, and determines that the broken screen claim photo fails the validity check if the image definition is smaller than the preset threshold. Wherein the image sharpness is used to characterize the sharpness of the image.
It should be noted that the above-mentioned preset threshold may be set based on actual situations, and the sharpness detection procedure may be implemented based on a Brenner gradient function, a tenngrad gradient function, a Laplacian gradient function, an SMD (gray variance) function, an energy gradient function, and the like, which is not particularly limited in the present application.
The server acquires the broken screen claim photo in real time or at regular time and performs authenticity verification on the broken screen claim photo, wherein authenticity refers to whether the broken screen claim photo uploaded by a user is a true and error-free broken screen photo or not, the risk of cheating protection of the broken screen claim photo with higher authenticity is lower, and the risk of cheating protection of the broken screen claim photo with lower authenticity is higher.
Specifically, the way of verifying the authenticity is specifically: extracting character check codes from the broken screen claim photo, and determining whether the character check codes are the same as preset character check codes or not; if the character check code is the same as the preset character check code, determining that the broken screen claim photo passes the authenticity check; if the character check code is different from the preset character check code, determining that the broken screen claim photo fails to pass the authenticity check. It should be noted that the character check code may be set based on practical situations, which is not particularly limited in the present application.
In an embodiment, the character check code is an international mobile equipment identification code (International Mobile Equipment Identity, IMEI) of the terminal device, when the user uploads the broken screen claim photo through the terminal device, input reminding information of the IMEI of the broken screen terminal is displayed to remind the user to input the IMEI of the broken screen terminal, the user shoots a local information page of the broken screen terminal through the terminal device, the local information page displays the IMEI, the broken screen claim photo containing the IMEI can be obtained, the user selects the IMEI in the broken screen claim photo to obtain the broken screen claim photo with the IMEI area, when the broken screen claim photo is processed, the server firstly intercepts the IMEI area from the broken screen claim photo to obtain an IMEI area screenshot, character recognition is carried out on the IMEI area screenshot to obtain a character recognition result, then the IMEI is obtained from the character recognition result according to an expression regular pattern corresponding to the IMEI, whether the obtained IMEI is the same as the preset IMEI or not is determined, if the obtained IMEI is the same as the preset IMEI, the broken screen claim photo passes through the preset photo, and if the obtained IMEI is not verified truly, and if the obtained IMI is not verified.
In an embodiment, the manner of authenticity verification may be: and when the server receives the broken screen claim settlement request, acquiring the IMEI and the broken screen claim settlement photo from the broken screen claim settlement request, carrying out authenticity verification on the broken screen claim settlement photo according to the IMEI, namely acquiring a pre-stored IMEI corresponding to the broken screen claim settlement photo, determining whether the acquired IMEI is identical to a preset IMEI, if the acquired IMEI is identical to the preset IMEI, determining that the broken screen claim settlement photo passes the authenticity verification, and if the acquired IMEI is different from the preset IMEI, determining that the broken screen claim photo does not pass the authenticity verification.
And S102, when the broken screen claim photo passes the authenticity verification, acquiring a screen broken area in the broken screen claim photo through a preset broken screen detection model.
When the broken screen claim photo passes the authenticity verification, a screen breaking area in the broken screen claim photo is obtained through a preset broken screen detection model, namely, the breaking probability of each pixel point in the broken screen claim photo is determined through the broken screen detection model, the pixel points with the breaking probability larger than or equal to a set probability threshold value are obtained, and then the area formed by the obtained pixel points is used as the screen breaking area to be output, so that the screen breaking area in the broken screen claim photo is obtained. It should be noted that, when the broken screen detection model is trained, the probability threshold is determined, the breaking probability of the pixel point is the probability that the pixel point is a broken point, and the higher the breaking probability of the pixel point is, the higher the probability that the pixel point is a broken point, and the lower the breaking probability of the pixel point is, the lower the probability that the pixel point is a broken point.
In an embodiment, a neural network model and a sample data set are obtained, wherein the sample data set is a picture set marked with a screen broken area; and carrying out iterative training on the neural network model according to the sample data set until the neural network model converges, obtaining and storing a preset broken screen detection model. Wherein the neural network model is implemented based on a deep neural network including, but not limited to, convolutional neural networks and recurrent neural networks. Through the broken screen detection model that trains, the broken screen area in the broken screen claim photo of acquisition that can be quick accurate, the degree of accuracy of effectual improvement screen breakage class.
Optionally, the deep neural network is Mask R-CNN, screen broken pictures are collected, screen broken areas are marked, a large amount of marked sample data are obtained, and a sample data set is formed; inputting the sample data set into the Mask R-CNN for training until the Mask R-CNN converges, and obtaining a broken screen detection model; when the screen crushing area is predicted, inputting the screen crushing claim photo into the screen crushing detection model, and obtaining the screen crushing area.
In one embodiment, the server determines a screen area in the broken screen claim photo; and acquiring a screen crushing area from the screen area through a preset screen crushing detection model. The screen area is extracted from the broken screen claim photo, and then the broken screen area is obtained from the screen area through the broken screen detection model, so that the broken screen area can be quickly and accurately obtained, and the accuracy of the broken screen grade is effectively improved.
The determination mode of the screen area is specifically as follows: detecting the angles of the straight lines and each straight line in the broken screen claim photo through Hough transformation to obtain a first candidate straight line set, and detecting the angles of the straight lines and each straight line in the broken screen claim photo through Lato transformation to obtain a second candidate straight line set; and comparing the candidate straight lines in the first candidate straight line set and the second candidate straight line set, taking the candidate straight lines with the angle errors in a preset angle range and the pixel errors in a preset pixel range as target straight lines, thereby obtaining the outline of the screen frame in the broken screen claim photo, and cutting out the screen area from the broken screen claim photo based on the outline of the screen frame, thereby determining the screen area. It should be noted that the preset angle range and the preset pixel range may be set based on practical situations, which is not particularly limited in the present application.
And step S103, determining the screen crushing grade of the screen crushing claim photo according to a preset screen crushing degree grading model and the screen crushing area.
After determining the screen crushing area, the screen crushing grade of the screen crushing claim photo can be determined according to a preset screen crushing degree grading model and the screen crushing area, namely the screen crushing area is input into the screen crushing degree grading model, the screen crushing degree grading model outputs the screen crushing grade corresponding to the screen crushing area, and the output screen crushing grade is used as the screen crushing grade of the screen crushing claim photo.
In one embodiment, a neural network model is acquired, along with a sample dataset, wherein the sample dataset is a dataset comprising screen break areas and annotated screen break levels; and carrying out iterative training on the neural network model according to the sample data set until the neural network model converges, obtaining and storing a preset broken screen degree grading model. Wherein the neural network model is implemented based on a deep neural network. And carrying out iterative training on the neural network model through the marked sample data, so that a screen breakage degree grading model with higher accuracy can be obtained.
Optionally, training a screen breaking degree grading model by adopting a 50-layer depth residual error network (Residual Neural Network, resNet), collecting screen breaking areas, and marking corresponding screen breaking grades based on different service requirements to obtain marked sample data under different service scenes so as to form a sample data set; and inputting the sample data set into a 50-layer depth residual error network for model training until the 50-layer depth residual error network converges, and obtaining the broken screen degree grading model.
In an embodiment, the determination manner of the screen breaking level may specifically be: and determining crushing parameter information according to the screen crushing area, and determining the screen crushing grade according to the crushing parameter information, wherein the crushing parameter information comprises at least one of crushing area, the number of crushing marks and crushing positions.
Specifically, calculating the area of a screen crushing area, and marking the area as a crushing area; and/or counting the number of broken marks in the broken area of the screen, and recording the number as the number of broken marks; and/or determining the position of the screen crushing zone in the screen zone, noted as crushing position; the screen crush grade is determined according to the crush area, the number of the crushed marks and/or the crush position. Crushing locations include, but are not limited to, screen upper locations, screen lower locations, screen middle locations, and screen edge locations.
The determination mode of the crushing degree index of the screen crushing area specifically comprises the following steps: acquiring specific values of each crushing parameter from the crushing parameter information, and determining a crushing degree index corresponding to each crushing parameter based on the specific values of each crushing parameter; determining the crushing degree index of the screen crushing region according to the respective corresponding crushing degree index of each crushing parameter, namely acquiring the respective corresponding preset weight coefficient of each crushing parameter, calculating the sum of the respective corresponding crushing degree index of each crushing parameter and the corresponding preset weight coefficient to obtain the respective corresponding crushing degree weight index of each crushing parameter, and accumulating the respective corresponding crushing degree weight index of each crushing parameter to obtain the crushing degree index of the screen crushing region. It should be noted that the preset weight coefficient may be set based on practical situations, which is not particularly limited in the present application.
The determination mode of the crushing degree index corresponding to each crushing parameter is specifically as follows: obtaining a mapping relation table between a specific numerical value of a pre-stored crushing parameter and a crushing degree index; and inquiring the mapping relation table to obtain a crushing degree index corresponding to the specific numerical value of the crushing parameter. It should be noted that, the crushing degree index corresponding to each specific value of each crushing parameter may be stored in one mapping table, or the crushing degree index corresponding to each specific value of one crushing parameter may be stored in one mapping table, so as to obtain multiple mapping tables.
Referring to fig. 2, fig. 2 is a schematic diagram of a scenario in which the screen crushing and grading method provided in this embodiment is implemented, as shown in fig. 2, a user initiates a screen crushing and claim settlement request to a server through a terminal device, the server receives the screen crushing and claim settlement request, and determines a screen crushing grade based on a screen crushing and claim settlement photo in the screen crushing and claim settlement request.
According to the screen crushing and grading method provided by the embodiment, the authenticity verification is carried out on the broken screen claim photo, after the broken screen claim photo passes through the authenticity verification, the screen crushing area in the broken screen claim photo is quickly obtained according to the broken screen detection model, finally, the screen crushing grade of the screen crushing area can be quickly and accurately determined based on the broken screen degree grading model, manual processing is not needed in the whole process, the photo can be accurately and quickly verified and the screen crushing degree can be evaluated, and the cheating protection risk is reduced.
Referring to fig. 3, fig. 3 is a flow chart of another screen crushing and classifying method according to an embodiment of the application.
As shown in fig. 3, the screen crushing and classifying method includes steps S201 to 206.
And S201, acquiring a broken screen claim photo, and carrying out authenticity verification on the broken screen claim photo.
The terminal equipment receives the garrulous screen claim settlement photo uploaded based on the garrulous screen claim settlement page, generates the garrulous screen claim settlement request carrying the garrulous screen claim settlement photo, sends the garrulous screen claim settlement request to the server, receives the garrulous screen claim settlement request, acquires the garrulous screen claim settlement photo in the garrulous screen claim settlement request, can determine the screen crushing grade based on the garrulous screen claim settlement photo in real time, can also store the garrulous screen claim settlement photo first, and can acquire the garrulous screen crushing grade based on the acquired garrulous screen claim photo at a later time.
And S202, when the broken screen claim photo passes the authenticity verification, acquiring a screen broken area in the broken screen claim photo through a preset broken screen detection model.
When the broken screen claim photo passes the authenticity verification, a screen breaking area in the broken screen claim photo is obtained through a preset broken screen detection model, namely, the breaking probability of each pixel point in the broken screen claim photo is determined through the broken screen detection model, the pixel points with the breaking probability larger than or equal to a set probability threshold value are obtained, and then the area formed by the obtained pixel points is used as the screen breaking area to be output, so that the screen breaking area in the broken screen claim photo is obtained.
And step 203, determining the screen crushing grade of the screen crushing claim photo according to a preset screen crushing degree grading model and the screen crushing area.
After determining the screen crushing area, the screen crushing grade of the screen crushing claim photo can be determined according to a preset screen crushing degree grading model and the screen crushing area, namely the screen crushing area is input into the screen crushing degree grading model, the screen crushing degree grading model outputs the screen crushing grade corresponding to the screen crushing area, and the output screen crushing grade is used as the screen crushing grade of the screen crushing claim photo.
And S204, determining crushing parameter information according to the screen crushing area, wherein the crushing parameter information comprises at least one of crushing area, the number of the crushing marks and crushing positions.
Specifically, crushing parameter information is determined according to the screen crushing area, wherein the crushing parameter information includes at least one of a crushing area, a number of cracks, and a crushing position. Specifically, calculating the area of a screen crushing area, and marking the area as a crushing area; and/or counting the number of broken marks in the broken area of the screen, and recording the number as the number of broken marks; and/or determining the position of the screen crushing zone in the screen zone, noted as crushing position. Crushing locations include, but are not limited to, screen upper locations, screen lower locations, screen middle locations, and screen edge locations.
And step 205, checking the screen crushing grade according to the crushing parameter information, and storing the screen crushing grade when the screen crushing grade passes the checking.
The server can check the screen crushing grade according to the crushing parameter information, store the screen crushing grade when the screen crushing grade passes the check, and can redetermine the screen crushing grade when the screen crushing grade does not pass the check. By checking the screen crushing level, the accuracy of the screen crushing level can be further improved.
In one embodiment, referring to fig. 4, step S205 includes: substep S2051 to substep S2053.
And step S2051, determining a first crushing degree index of the screen crushing area according to the crushing parameter information.
Specifically, the server determines a crushing degree index corresponding to at least one crushing parameter according to the value of at least one crushing parameter in the crushing parameter information, namely, a pre-stored mapping relation table between the value of at least one crushing parameter and the crushing degree index is obtained, and the mapping relation table is inquired to obtain the crushing degree index corresponding to the value of at least one crushing parameter; and determining a first crushing degree index of the screen crushing area according to the crushing degree index corresponding to at least one crushing parameter, namely determining the first crushing degree index of the screen crushing area according to the crushing degree index corresponding to the crushing area, the number of the crushing marks and/or the numerical value of the crushing position.
In an embodiment, a preset weight coefficient corresponding to at least one crushing parameter is obtained; determining a crushing degree weight index corresponding to at least one crushing parameter according to the crushing degree index corresponding to the at least one crushing parameter and the preset weight coefficient; and determining a first crushing degree index of the screen crushing area according to the crushing degree weight index corresponding to the at least one crushing parameter. It should be noted that, the sum of the preset weight coefficients corresponding to each crushing parameter in the at least one crushing parameter is 1, and the preset weight coefficient is greater than or equal to 0 and less than 1, and the preset weight coefficient corresponding to each crushing parameter may be set based on the actual situation, which is not particularly limited in the present application.
Taking crushing parameters as crushing areas, the number of crushing marks and crushing positions as examples, the determination of the first crushing degree index is explained. Specifically, preset weight coefficients corresponding to the crushing area, the number of the crushing marks and the crushing positions are obtained, the sum of the crushing degree indexes corresponding to the crushing area, the number of the crushing marks and the crushing positions and the corresponding preset weight coefficients is calculated, the crushing degree weight indexes corresponding to the crushing area, the number of the crushing marks and the crushing positions are obtained, and then the crushing degree weight indexes corresponding to the crushing area, the number of the crushing marks and the crushing positions are accumulated to obtain a first crushing degree index of the crushing area of the screen. It should be noted that the sum of the preset weight coefficients of the crushing area, the number of the crushing marks and the crushing position is 1.
And step S2052, obtaining a second crushing degree index corresponding to the screen crushing grade of the screen crushing claim photo according to a mapping relation table between the pre-stored crushing degree index and the screen crushing grade.
Specifically, the server obtains a second crushing degree index corresponding to the screen crushing grade of the screen crushing claim photo according to a pre-stored mapping relation table between the crushing degree index and the screen crushing grade, namely, inquires the mapping relation table, obtains the crushing degree index corresponding to the screen crushing grade, and takes the obtained crushing degree index as the second crushing degree index.
And step S2053, checking the screen crushing grade according to the first crushing degree index and the second crushing degree index.
Specifically, according to the first crushing degree index and the second crushing degree index, the screen crushing grade is checked, namely, the absolute value of the difference value between the first crushing degree index and the second crushing degree index is calculated, whether the absolute value of the difference value is smaller than or equal to a set value is determined, if the absolute value of the difference value is smaller than or equal to the set value, the screen crushing grade is determined to pass the check, and if the absolute value of the difference value is larger than the set value, the screen crushing grade is determined to not pass the check.
According to the screen crushing and grading method provided by the embodiment, the accuracy of the screen crushing grade can be further improved by checking the screen crushing grade.
Referring to fig. 5, fig. 5 is a schematic block diagram of a screen crushing and grading device according to an embodiment of the application.
As shown in fig. 5, the screen crushing and classifying apparatus 300 includes: a verification module 301, a broken screen detection module 302 and a broken level determination module 303.
And the verification module 301 is configured to obtain a broken screen claim photo, and perform authenticity verification on the broken screen claim photo.
And the broken screen detection module 302 is configured to obtain a screen broken area in the broken screen claim photo through a preset broken screen detection model when the broken screen claim photo passes the authenticity verification.
The crushing grade determining module 303 is configured to determine a screen crushing grade of the screen crushing claim photo according to a preset screen crushing degree classification model and the screen crushing area.
Further, the verification module 301 is further configured to extract a character verification code from the broken screen claim photo, and determine whether the character verification code is the same as a preset character verification code; if the character check code is the same as the preset character check code, determining that the broken screen claim photo passes the authenticity check; if the character check code is different from the preset character check code, determining that the broken screen claim photo fails to pass the authenticity check.
Further, the screen crushing and grading device further comprises:
the acquisition module is used for acquiring a neural network model and a sample data set, wherein the sample data set is a picture set marked with a screen crushing area;
and the training module is used for carrying out iterative training on the neural network model according to the sample data set until the neural network model converges, obtaining and storing the preset broken screen detection model.
Referring to fig. 6, fig. 6 is a schematic block diagram of another screen crushing and grading device according to an embodiment of the present application.
As shown in fig. 6, the screen crushing and classifying apparatus 400 includes: a first verification module 401, a broken screen detection module 402, a broken level determination module 403, a parameter information determination module 404 and a second verification module 405.
The first verification module 401 is configured to obtain a broken screen claim photo, and perform authenticity verification on the broken screen claim photo.
And the broken screen detection module 402 is configured to obtain a screen broken area in the broken screen claim photo through a preset broken screen detection model when the broken screen claim photo passes the authenticity verification.
The crushing grade determining module 403 is configured to determine a screen crushing grade of the screen crushing claim photo according to a preset screen crushing degree classification model and the screen crushing area.
And the parameter information determining module 404 is configured to determine crushing parameter information according to the screen crushing area, where the crushing parameter information includes at least one of a crushing area, a number of cracks and a crushing position.
And the second checking module 405 is configured to check the screen crushing level according to the crushing parameter information, and store the screen crushing level when the screen crushing level passes the check.
Further, the second checking module 405 is further configured to determine a first crushing degree index of the screen crushing area according to the crushing parameter information; obtaining a second crushing degree index corresponding to the screen crushing grade of the screen crushing claim photo according to a mapping relation table between the pre-stored crushing degree index and the screen crushing grade; and verifying the screen crushing grade according to the first crushing degree index and the second crushing degree index.
Further, the second checking module 405 is further configured to determine a crushing degree index corresponding to at least one crushing parameter according to a value of the at least one crushing parameter in the crushing parameter information; and determining a first crushing degree index of the screen crushing area according to the crushing degree index corresponding to at least one crushing parameter.
Further, the second checking module 405 is further configured to obtain a preset weight coefficient corresponding to at least one crushing parameter; determining a crushing degree weight index corresponding to at least one crushing parameter according to the crushing degree index corresponding to at least one crushing parameter and the preset weight coefficient; and determining a first crushing degree index of the screen crushing area according to the crushing degree weight index corresponding to at least one crushing parameter.
It should be noted that, for convenience and brevity of description, specific working processes of the above-described apparatus and modules and units may refer to corresponding processes in the foregoing embodiments of the screen crushing and classifying method, and will not be described herein again.
The apparatus provided by the above embodiments may be implemented in the form of a computer program which may be run on a computer device as shown in fig. 7.
Referring to fig. 7, fig. 7 is a schematic block diagram of a computer device according to an embodiment of the present application. The computer device may be a server.
As shown in fig. 7, the computer device includes a processor, a memory, and a network interface connected by a system bus, wherein the memory may include a non-volatile storage medium and an internal memory.
The non-volatile storage medium may store an operating system and a computer program. The computer program comprises program instructions that, when executed, cause the processor to perform any of a number of screen fragmentation classification methods.
The processor is used to provide computing and control capabilities to support the operation of the entire computer device.
The internal memory provides an environment for the execution of a computer program in a non-volatile storage medium that, when executed by a processor, causes the processor to perform any of a number of screen fragmentation classification methods.
The network interface is used for network communication such as transmitting assigned tasks and the like. It will be appreciated by those skilled in the art that the structure shown in FIG. 7 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
It should be appreciated that the processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field-programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Wherein in one embodiment the processor is configured to run a computer program stored in the memory to implement the steps of:
Obtaining a broken screen claim photo, and carrying out authenticity verification on the broken screen claim photo;
when the broken screen claim photo passes the authenticity verification, a screen breaking area in the broken screen claim photo is obtained through a preset broken screen detection model;
and determining the screen crushing grade of the screen crushing claim photo according to a preset screen crushing degree grading model and the screen crushing area.
In one embodiment, before implementing obtaining the broken-screen claim photo and performing the authenticity check on the broken-screen claim photo, the processor is further configured to implement:
acquiring a neural network model and a sample data set, wherein the sample data set is a picture set marked with a screen crushing area;
and carrying out iterative training on the neural network model according to the sample data set until the neural network model converges, obtaining and storing the preset broken screen detection model.
In one embodiment, the processor, when implementing the authenticity verification of the broken screen claim photograph, is configured to implement:
extracting a character check code from the broken screen claim photo, and determining whether the character check code is identical to a preset character check code;
If the character check code is the same as the preset character check code, determining that the broken screen claim photo passes the authenticity check;
if the character check code is different from the preset character check code, determining that the broken screen claim photo fails to pass the authenticity check.
Wherein in another embodiment the processor is configured to run a computer program stored in the memory to implement the steps of:
obtaining a broken screen claim photo, and carrying out authenticity verification on the broken screen claim photo;
when the broken screen claim photo passes the authenticity verification, a screen breaking area in the broken screen claim photo is obtained through a preset broken screen detection model;
determining the screen crushing grade of the screen crushing claim photo according to a preset screen crushing degree grading model and the screen crushing area;
determining crushing parameter information according to the screen crushing area, wherein the crushing parameter information comprises at least one of crushing area, the number of crushing marks and crushing positions;
and checking the screen crushing grade according to the crushing parameter information, and storing the screen crushing grade when the screen crushing grade passes the checking.
In one embodiment, the processor is configured to, when implementing verification of the screen crushing level according to the crushing parameter information, implement:
determining a first crushing degree index of the screen crushing area according to the crushing parameter information;
obtaining a second crushing degree index corresponding to the screen crushing grade of the screen crushing claim photo according to a mapping relation table between the pre-stored crushing degree index and the screen crushing grade;
and verifying the screen crushing grade according to the first crushing degree index and the second crushing degree index.
In one embodiment, the processor, when implementing determining the first crushing degree index of the screen crushing area according to the crushing parameter information, is configured to implement:
determining a crushing degree index corresponding to at least one crushing parameter according to the value of the at least one crushing parameter in the crushing parameter information;
and determining a first crushing degree index of the screen crushing area according to the crushing degree index corresponding to at least one crushing parameter.
In one embodiment, the processor is configured to, when implementing determining the first crushing degree index of the screen crushing area according to the crushing degree index corresponding to at least one of the crushing parameters, implement:
Acquiring at least one preset weight coefficient corresponding to the crushing parameter;
determining a crushing degree weight index corresponding to at least one crushing parameter according to the crushing degree index corresponding to at least one crushing parameter and the preset weight coefficient;
and determining a first crushing degree index of the screen crushing area according to the crushing degree weight index corresponding to at least one crushing parameter.
Embodiments of the present application also provide a computer readable storage medium having a computer program stored thereon, the computer program including program instructions that, when executed, implement a method that may refer to various embodiments of the screen crushing and classification method of the present application.
The computer readable storage medium may be an internal storage unit of the computer device according to the foregoing embodiment, for example, a hard disk or a memory of the computer device. The computer readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, which are provided on the computer device.
It is to be understood that the terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should also be understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments. While the application has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the application. Therefore, the protection scope of the application is subject to the protection scope of the claims.
Claims (8)
1. A screen crushing and grading method, comprising:
obtaining a broken screen claim photo, and carrying out authenticity verification on the broken screen claim photo;
when the broken screen claim photo passes the authenticity verification, a screen broken area in the broken screen claim photo is obtained through a preset broken screen detection model, wherein the preset broken screen detection model is obtained by performing iterative training on a neural network model according to a picture set marked with the screen broken area;
determining the screen crushing grade of the screen breakage claim photo according to a preset screen breakage degree grading model and the screen crushing area, wherein determining the screen crushing grade of the screen breakage claim photo according to the preset screen breakage degree grading model and the screen crushing area comprises: inputting the screen crushing area into a preset screen crushing degree grading model, outputting a screen crushing grade corresponding to the screen crushing area as the screen crushing grade of the screen crushing claim photo by the preset screen crushing degree grading model, and performing iterative training on a neural network model according to a data set comprising the screen crushing area and the marked screen crushing grade;
Determining crushing parameter information according to the screen crushing area, wherein the crushing parameter information comprises at least one of crushing area, the number of crushing marks and crushing positions;
determining a first crushing degree index of the screen crushing area according to the crushing parameter information;
obtaining a second crushing degree index corresponding to the screen crushing grade of the screen crushing claim photo according to a mapping relation table between the pre-stored crushing degree index and the screen crushing grade;
and checking the screen crushing grade according to the first crushing degree index and the second crushing degree index, and storing the screen crushing grade when the screen crushing grade passes the checking.
2. The screen fragmentation classification method of claim 1, wherein before the capturing the fragment-screen claim photo and performing the authenticity verification on the fragment-screen claim photo, further comprises:
acquiring a neural network model and a sample data set, wherein the sample data set is a picture set marked with a screen crushing area;
and carrying out iterative training on the neural network model according to the sample data set until the neural network model converges, obtaining and storing the preset broken screen detection model.
3. The screen crushing and grading method according to claim 1, wherein the determining the first crushing degree index of the screen crushing area according to the crushing parameter information includes:
determining a crushing degree index corresponding to at least one crushing parameter according to the value of the at least one crushing parameter in the crushing parameter information;
and determining a first crushing degree index of the screen crushing area according to the crushing degree index corresponding to at least one crushing parameter.
4. A screen crush grading method according to claim 3, wherein the determining a first crush degree index of the screen crush zone according to the crush degree index corresponding to at least one of the crush parameters includes:
acquiring at least one preset weight coefficient corresponding to the crushing parameter;
determining a crushing degree weight index corresponding to at least one crushing parameter according to the crushing degree index corresponding to at least one crushing parameter and the preset weight coefficient;
and determining a first crushing degree index of the screen crushing area according to the crushing degree weight index corresponding to at least one crushing parameter.
5. The screen fragmentation classification method of claim 1 or 2, wherein the performing an authenticity check on the fragment-screen claim photo comprises:
extracting a character check code from the broken screen claim photo, and determining whether the character check code is identical to a preset character check code;
if the character check code is the same as the preset character check code, determining that the broken screen claim photo passes the authenticity check;
if the character check code is different from the preset character check code, determining that the broken screen claim photo fails to pass the authenticity check.
6. A screen crushing and grading device, characterized in that the screen crushing and grading device comprises:
the first verification module is used for obtaining the broken screen claim photo and carrying out authenticity verification on the broken screen claim photo;
the broken screen detection module is used for obtaining a screen broken area in the broken screen claim photo through a preset broken screen detection model when the broken screen claim photo passes the authenticity verification, wherein the preset broken screen detection model is obtained by performing iterative training on a neural network model according to a picture set marked with the screen broken area;
the crushing grade determining module is configured to determine a screen crushing grade of the screen breakage claim photo according to a preset screen breakage degree classification model and the screen crushing region, wherein determining the screen crushing grade of the screen breakage claim photo according to the preset screen breakage degree classification model and the screen crushing region includes: inputting the screen crushing area into a preset screen crushing degree grading model, outputting a screen crushing grade corresponding to the screen crushing area as the screen crushing grade of the screen crushing claim photo by the preset screen crushing degree grading model, and performing iterative training on a neural network model according to a data set comprising the screen crushing area and the marked screen crushing grade;
The parameter information determining module is used for determining crushing parameter information according to the screen crushing area, wherein the crushing parameter information comprises at least one of crushing area, the number of the crushing marks and crushing positions;
the second checking module is used for determining a first crushing degree index of the screen crushing area according to the crushing parameter information; obtaining a second crushing degree index corresponding to the screen crushing grade of the screen crushing claim photo according to a mapping relation table between the pre-stored crushing degree index and the screen crushing grade; and checking the screen crushing grade according to the first crushing degree index and the second crushing degree index, and storing the screen crushing grade when the screen crushing grade passes the checking.
7. A computer device comprising a processor, a memory, and a computer program stored on the memory and executable by the processor, wherein the computer program when executed by the processor implements the steps of the screen break classification method of any of claims 1 to 5.
8. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program, wherein the computer program, when executed by a processor, implements the steps of the screen break up classification method according to any of claims 1 to 5.
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| CN112268912A (en) * | 2020-10-09 | 2021-01-26 | 支付宝(杭州)信息技术有限公司 | Screen damage verification method and device based on mirror shooting |
| CN113537218B (en) * | 2021-07-27 | 2024-02-06 | 京东科技信息技术有限公司 | Image recognition method and device |
| CN114663418A (en) * | 2022-04-06 | 2022-06-24 | 京东安联财产保险有限公司 | Image processing method and device, storage medium and electronic equipment |
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