CN117667951B

CN117667951B - Data processing method and device for characteristic data of camera

Info

Publication number: CN117667951B
Application number: CN202410141285.4A
Authority: CN
Inventors: 蔡赵烽
Original assignee: Hangzhou Hikvision Digital Technology Co Ltd
Current assignee: Hangzhou Hikvision Digital Technology Co Ltd
Priority date: 2024-01-31
Filing date: 2024-01-31
Publication date: 2024-05-03
Anticipated expiration: 2044-01-31
Also published as: CN117667951A

Abstract

The embodiment of the application provides a data processing method and device for feature data of a camera, and relates to the technical field of data processing. The specific implementation scheme is as follows: responding to the completion of powering up of the camera, and obtaining a target model of the camera; determining a target table name corresponding to a target model from a preset model index table; determining a function table with a target table name and a function table with a dependency relationship with the function table with the target table name; based on the determined dependency relationship among the function tables, carrying out data combination on the function tables to obtain a data combination result; and responding to an access instruction of any program module of the camera for the feature data, and performing feature data access on the data merging result based on the feature field to be accessed indicated by the access instruction to obtain a feature data access result of the feature field to be accessed. Therefore, the scheme can reduce the data quantity of the feature data management and the effective access requirement for the feature data.

Description

Data processing method and device for characteristic data of camera

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a method and an apparatus for processing feature data of a camera.

Background

The intrinsic attribute data of hardware and software in the camera is called feature data, and for example, the feature data of the camera may include: whether wifi (mobile hotspot) is supported, the storage capacity size, the dominant frequency of the CPU (Central Processing Unit ), etc. These feature data typically need to be referenced by software code in the camera to control and influence the running behavior of the software. The devices of the same device type can have multiple types.

In the related art, in order to realize access to feature data of cameras of respective models, feature data of each model is individually managed so that software codes of the cameras refer to the individually managed feature data to realize data access. However, when the model number is large, the management of the feature data becomes very difficult, that is, the amount of data to be managed is extremely large.

Therefore, how to reduce the data amount of the feature data management and the effective access requirement for the feature data is a problem to be solved.

Disclosure of Invention

The embodiment of the application aims to provide a data processing method and device for feature data of a camera, so as to reduce the data volume of feature data management and the effective access requirement for the feature data. The specific technical scheme is as follows:

the embodiment of the application provides a data processing method for feature data of a camera, which is applied to the camera, wherein the camera belongs to a target equipment type, each model under the target equipment type shares a base table belonging to a function table, and each preset feature field of the target equipment type and corresponding field content for representing the feature data are recorded in the base table; and, for any model, the characteristic data of each characteristic field of the equipment of the model is stored and managed according to a preset storage management mode by taking the base table as a function table of an initial level;

The storage management mode comprises the following steps: if the characteristic data of the equipment of the model is the same as the merging data corresponding to any one of the function table combinations, taking the function table of the highest level in the function table combination as an entry table corresponding to the model; otherwise, creating a function table with the level higher than the target function table and depending on the target function table, and taking the created function table as an entry table corresponding to the model; each function table is combined into at least one level of function table with continuous levels from a base table, corresponding merging data is obtained by merging the data of the at least one level of function table, the target function table is the function table with the highest level existing at present, and the function table is used for recording: the feature fields with differences and the corresponding field contents used for representing the feature data are compared with the merged data obtained by merging the data of the current existing function table; the method comprises the following steps:

responding to the completion of powering up of the camera, and acquiring a target model of the camera;

Determining a table name corresponding to the target model from a preset model index table, and taking the table name as a target table name; the model index table stores table names of an entry table corresponding to each model;

determining a function table with the target table name and a function table with a dependency relationship with the function table with the target table name;

based on the determined dependency relationship among the function tables, carrying out data combination on the determined function tables to obtain a data combination result;

And responding to an access instruction of any program module of the camera for the feature data, and based on the feature field to be accessed indicated by the access instruction, performing feature data access on the data merging result to obtain a feature data access result of the feature field to be accessed.

The embodiment of the application has the beneficial effects that:

According to the scheme provided by the embodiment of the application, the characteristic data of the characteristic field of any type of equipment is stored according to a preset storage management mode, and the storage management mode comprises the following steps: if the characteristic data of the equipment of the model is the same as the merging data corresponding to any one of the function table combinations, taking the function table of the highest level in the function table combination as an entry table corresponding to the model; otherwise, a function table with the level higher than the target function table and depending on the target function table is created, and the created function table is used as an entry table corresponding to the model. In this way, after determining the target table name of the entry table of the equipment of the model from the preset model index table according to the model of the camera, the function table with the target table name and the function table with the dependency relationship of the function table with the target table name can be determined. Therefore, the determined function tables can be combined based on the determined dependency relationship among the function tables, and a data combination result is obtained. And, the data combination result may be used to determine the characteristic data for the target model, so that the characteristic data access may be performed to the data combination result in response to an access instruction for the characteristic data by any program module of the camera. Therefore, the characteristic data is stored and managed according to the preset storage management mode, and a large amount of redundant data is not required to be stored, so that the data amount of the characteristic data which is required to be stored and managed is reduced, and after the camera is powered on, the characteristic data can be read based on the data combination result by combining the function tables to obtain the data combination result. Therefore, the scheme can reduce the data volume of the feature data management and the effective access requirement for the feature data.

Of course, it is not necessary for any one product or method of practicing the application to achieve all of the advantages set forth above at the same time.

Drawings

In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the application, and other embodiments may be obtained according to these drawings to those skilled in the art.

Fig. 1 is a flowchart of a data processing method for feature data of a camera according to an embodiment of the present application;

FIG. 2 is a flow chart of one way of determining a function table to rely on in accordance with an embodiment of the present application;

FIG. 3 is a flowchart of a method for reading feature data according to an embodiment of the present application;

Fig. 4 is a schematic diagram of a feature data management manner of a camera according to an embodiment of the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. Based on the embodiments of the present application, all other embodiments obtained by the person skilled in the art based on the present application are included in the scope of protection of the present application.

The following first describes terms of art according to embodiments of the present application.

Characteristic data: the intrinsic attribute data of hardware and software in the device comprises intrinsic characteristics of the device, default information of parameters and the like. These data are read-only and are determined at the completion of the production of the device. Such as whether a camera supports wifi, the size of the storage capacity, the main frequency of the CPU, etc. These feature data typically need to be referenced by the software code to control, affect, the software operation behavior.

Feature table: the table for describing the feature data of the camera includes a parameter definition table, a model index table, and a function table. The parameter definition table is used for defining the name, the data type and the value range of the characteristic data; the model index table is a table for managing all models and the characteristic table used as an access entry, and the table names of the initial addressing tables corresponding to different models are recorded in the model index table; the function table is used for recording the software and hardware characteristic data of the camera.

Base table: namely a basic feature table, which is a feature table depending on other feature tables, and is a representation form of cluster management in a feature data management mode. The design developer of the feature table can write the general feature data of various different types with the same equipment function on one feature table, and the feature table is a base table.

Extension table: and a table for expanding the feature data based on the base table. Such as: and continuing to describe the characteristic data of a certain subdivision device in the equipment on a characteristic table A describing the general characteristic data of the equipment to obtain a characteristic table B, wherein the characteristic table A is a base table of the characteristic table B, and the characteristic table B is an extension table of the characteristic table A.

Sub-and parent tables: in the tree structure management mode, the branches are sub-tables, the stems are mother tables, and the mother tables refer to the sub-tables.

Access path: the searching mode of the feature data is used for describing the position of certain feature data in the tree structure.

Access parameters: additional parameter information required when accessing certain item of feature data. For example, the feature data x managed in the feature table has a value of 10 in the mode a and a value of 20 in the mode B, and "mode a" and "mode B" are access parameters of the feature data x.

At present, the characteristic data of the camera is directly written into the software code of the camera in a hard coding mode. Because cameras have multiple models, cameras of different models usually have different characteristic data, and a hard coding mode is adopted to enable software codes developed for cameras of any model to be unsuitable for cameras of other models, so that flexibility and reusability of the software codes are limited. Especially, aiming at the scenes that the functions of the equipment are identical but a plurality of subdivision models exist, the defects are more obvious. In order to realize multiplexing of the feature data, in the related art, the feature data is listed in a unit of model into data in a certain format and written in a database or a configuration file. That is, the feature data of each model is individually managed so that the software code of the camera refers to the individually managed feature data at runtime to achieve data access. While this approach can ensure flexibility and reusability of software code, when the number of models is large, management of feature data becomes very difficult, that is, the amount of data to be managed is extremely large.

Based on the above, in order to reduce the data amount of feature data management and the effective access requirement for the feature data, the embodiment of the application provides a data processing method and device for the feature data of a camera.

Next, a description will be first given of a data processing method for feature data of a camera according to an embodiment of the present application.

The data processing method for the feature data of the camera provided by the embodiment of the application can be applied to the camera of the target equipment type, wherein the target equipment type can be any camera type, is named as the target equipment type and has no limiting meaning. In a specific application, the target equipment type can be any equipment type such as a gun camera, a ball camera, an intelligent gun-ball integrated device and the like. The target device type can have multiple types, and the multiple types of devices under the target device type have the same device function. For example, if the target device type is a bolt face type, the bolt face type may include a model representing multiple sub-division types of bolt faces of type 1, type 2, etc., each sub-division type of bolt face having the same device function.

It will be appreciated that since the plurality of types of devices under the target device type have the same device function, the plurality of types of devices have a large amount of the same feature data, and if the feature data of the plurality of types of devices are managed individually in units of the types, there is a large amount of redundancy in the data to be managed. To solve this problem, in the present embodiment, each model under the target device type shares a base table belonging to a function table in which each predetermined feature field of the target device type and corresponding field contents for characterizing feature data are recorded. For example, in practical application, a related technician managing feature data may empirically determine feature fields common to feature data of different models, that is, feature fields with the same corresponding feature data, as predetermined feature fields, and write each determined predetermined feature field and feature data corresponding to each field into a base table, so as to use the base table as a base on which other function tables depend.

For example, if the target device type is a bolt face type, there are three sub-division types of devices, model 1, model 2, and model 3, under the target device type. The characteristic data in the model 1 device are shown in table 1 below:

TABLE 1

The characteristic data in the model 2 device are shown in table 2 below:

TABLE 2

The characteristic data in the model 3 device are shown in table 3 below:

TABLE 3 Table 3

The fields "work_mode" and "audio_chan_num" may be determined as predetermined feature fields. At this time, the base table recorded with each predetermined feature field of the target device type and the corresponding field contents for characterizing the feature data is shown in the following table 4:

TABLE 4 Table 4

For any model, the feature data of each feature field of the equipment of the model is stored and managed according to a preset storage management mode by taking the base table as a function table of an initial level. The storage management mode comprises the following steps: (1) If the characteristic data of the equipment of the model is the same as the merging data corresponding to any one of the function table combinations, taking the function table of the highest level in the function table combination as an entry table corresponding to the model; (2) Otherwise, a function table with the level higher than the target function table and depending on the target function table is created, and the created function table is used as an entry table corresponding to the model. Each function table is combined into at least one level of function tables with continuous levels from the base table, and corresponding combined data are obtained by combining the data of the at least one level of function tables. In addition, the target function table is the function table with the highest level existing at present, a function table with the level higher than the target function table and depending on the target function table is created, and the function table with the level higher than the target function table is created. The created function table is used for recording: and the feature fields with differences and the corresponding field contents for characterizing the feature data are compared with the merged data obtained by merging the data of the current existing function table.

For example, for the feature data of each model of the device to be subjected to storage management, after the base table shared by each model under the target device type is constructed, the feature data of each model of the device may be traversed one by one. And comparing the characteristic data of the equipment with the model obtained by traversing firstly with the characteristic data recorded in the base table, if the characteristic data are the same, taking the base table as an entry table of the model, otherwise, creating an expansion table 1 depending on the base table, and taking the expansion table 1 as an entry table corresponding to the model. The level of the extension table 1 is higher than that of the base table, and the extension table 1 is used for recording the characteristic fields with differences relative to the characteristic data recorded in the base table and the corresponding field contents used for characterizing the characteristic data. Then, the feature data of the next model of equipment is traversed, and the feature data of the equipment of the current traversed model is compared with the feature data corresponding to any one of the function table combinations. At this time, since there are two-stage function tables including the base table and the extension table 1, the function table combination includes two kinds of function table combinations of { base table }, { base table, extension table 1 }. If the characteristic data of the equipment of the model is the same as the characteristic data corresponding to the function table combination of { base table }, taking the highest-level function table in the function table combination, namely the base table as an entry table of the model; if the feature data of the device of the model is the same as the feature data corresponding to the function table combination { base table, extension table 1}, the function table of the highest level in the function table combination, that is, extension table 1 is used as the entry table of the model. If the feature data of the equipment of the model is different from the feature data corresponding to each function table combination, a function table with the higher level than the currently existing function table with the highest level and depending on the function table with the highest level is created, namely an expansion table 2 is created, and the level of the expansion table 2 is higher than that of the expansion table 1 and depends on the expansion table 1. Then, the characteristic data of the next model of equipment is continuously traversed, and the like until the characteristic data storage of all models of equipment is completed.

It should be noted that, it is reasonable to store the created function table in the database local to the camera or in the database in the cloud. And, when the function table is created, the feature data in the function table can be checked by the name, the data type and the value range of the feature data defined in the parameter definition table to check whether the feature data in the function table has errors. The table is used as a description carrier of software and hardware characteristic data of the device, and can comprise various data file forms such as CSV (Comma-SEPARATED VALUES, character separation value), excel (electronic table) and the like. In addition, it can be understood that the data processing method for the feature data of the camera provided by the embodiment of the application can be implemented by software, hardware or a combination of software and hardware.

The data processing method for the feature data of the camera provided by the embodiment of the application can comprise the following steps:

The following describes a data processing method for feature data of a camera according to an embodiment of the present application with reference to the accompanying drawings.

As shown in fig. 1, the data processing method for feature data of a camera according to the embodiment of the present application may include steps S101 to S105:

S101, responding to completion of powering up of the camera, and acquiring a target model of the camera;

It can be understood that the camera is powered on after the power supply is started, and the main control program in the camera runs after the camera is powered on, so that the model of the camera, namely the target model, can be obtained. By way of example, the model of the camera may include: and the model of a camera of subdivision type under any target equipment type such as a gun camera, a spherical camera or an intelligent gun-ball integrated camera is characterized.

S102, determining a table name corresponding to the target model from a preset model index table as a target table name; the model index table stores the table name of the entry table corresponding to each model;

In practical application, for example, the feature data of each model is stored and managed according to a predetermined storage management mode, and a related technician may construct a model index table in advance according to the feature data stored and managed according to the predetermined storage management mode, where the model index table is used to store each model and a corresponding table name of the entry table corresponding to the model. The determining manner of the entry table corresponding to each model is described in the above description storage management manner, and is not described herein.

It can be understood that, because the table name of the entry table corresponding to each model is stored in the model index table, after the target model is obtained, the table name corresponding to the target model can be searched by traversing the model index table, and the searched table name is the table name of the entry table of the device of the target model.

By way of example, the model index table may be as shown in Table 5 below:

TABLE 5

Where the record under the "root" field is the table name of the entry table. From this table it can be seen that: the device with the model number of 0x28620 is characterized in that the table name of the corresponding entry table is root_base_E11_IPCE_D; the table name of the entry table corresponding to the device with the model number of 0xb20539 is "root_base_h9_ipde_ths".

S103, determining a function table with the target table name and a function table with a dependency relationship with the function table with the target table name;

In this embodiment, each table name and the access address of the function table with the table name have a preset mapping relationship, after the target table name corresponding to the target model is found through the model index table, the access address of the function table with the target table name can be obtained according to the target table name and the preset mapping relationship, so as to determine the function table with the target table name.

For example, in practical applications, it is reasonable that each function table may specify a function table on which the function table depends in a table by a predetermined syntax, or may represent a function table on which the function table depends in a predetermined format in a table name. Thus, after the function table with the target table name is determined, the function table with the dependency relationship with the function table with the target table name can be determined.

It should be noted that, for the sake of clarity of layout of the solution, in the following embodiments, an implementation manner of determining a function table having a dependency relationship with the target table name is described, which is not described herein.

S104, based on the determined dependency relationship among the function tables, carrying out data combination on the determined function tables to obtain a data combination result;

In this embodiment, after determining the function table with the target table name and each function table having a dependency relationship with the function table with the target table name in step S103, the determined function tables may be combined according to the determined dependency relationship between each function table, to obtain a data combination result.

Optionally, in an implementation manner, based on the determined dependency relationship between the function tables, data merging is performed on the determined function tables to obtain a data merging result, which may include steps A1-A2:

a1, forming a traversing sequence of each function table according to the determined dependency relationship among each function table; wherein the traversing order is from low to high according to the level;

A2, traversing to a function table of each function table every time, if the function table is the lowest level, taking the characteristic fields existing in the function table and the corresponding field contents used for representing the characteristic data as the current data merging result, otherwise, merging the contents existing in the function table to the current data merging result according to the preset merging processing operation until each function table is traversed;

wherein the merging processing operation includes: for the first type of characteristic fields in the function table, which are already existing in the current data merging result, replacing the field contents of the first type of characteristic fields in the current data merging result with the field contents of the first type of characteristic fields in the function table; and adding the second type characteristic field in the function table and the corresponding field content to the current data merging result aiming at the second type characteristic field in the function table which does not exist in the current data merging result.

For example, if the dependency relationship between the function tables is: the extension table 2 depends on the extension table 1, and the extension table 1 depends on the base table, so that the level of the extension table 2 is highest and the level of the base table is lowest in the respective function tables. According to the dependency relationship among the function tables, the formed traversal order is the traversal order from the base table to the extension table 1 to the extension table 2. And traversing each determined function table in turn according to the traversing sequence, and in the traversing process, if the traversed function table is the function table with the lowest level, taking the characteristic fields in the function table and the corresponding field contents used for representing the characteristic data as the current data merging result. Otherwise, a predetermined merging processing operation may be performed for different function tables, that is, for each function table except for the first function table in the traversal order, for the first type of feature field in the function table that already exists in the current data merging result, the field content of the first type of feature field in the function table is substituted for the field content of the first type of feature field in the current data merging result; and adding the second type characteristic field in the function table and the corresponding field content to the current data merging result aiming at the second type characteristic field in the function table which does not exist in the current data merging result.

It will be appreciated that, starting from the base table of the initial level, the feature data recorded in the function table of the subsequent level are: feature data having a difference from feature data corresponding to a function table combination when the previous function table is the highest-level function table among the function table combinations. That is, when the device is stored and managed, feature data different from the feature data recorded in the base table is stored in an expansion table obtained by expanding the base table. Therefore, when the data is read from the base table, if the first type characteristic field which is the same as that in the current data merging result exists in the function table of the next level, replacing the field content of the first type characteristic field in the current data merging result with the field content of the first type characteristic field in the function table of the next level. After traversing the characteristic data from the base table to the entry table as the camera, and processing the characteristic data according to a preset merging operation, the data merging result corresponding to the camera can be obtained.

S105, responding to an access instruction of any program module of the camera for the feature data, and based on the feature field to be accessed indicated by the access instruction, performing feature data access on the data merging result to obtain a feature data access result of the feature field to be accessed.

In this embodiment, when a program module in a camera executes, feature data of the camera is called, and at this time, in response to an access instruction for the feature data, a feature field to be accessed indicated by the access instruction may be accessed from the data merging result, so as to obtain a feature data access result of the feature field to be accessed.

It should be noted that, for the sake of clear layout of the solution, the access manner of the feature data of the feature field to be accessed is described hereinafter, which is not described herein.

Alternatively, in another embodiment of the present application, the table name of any function table other than the base table is: table names capable of characterizing the function table relied upon;

In this embodiment, when creating the function table, the table name of the function table on which the function table depends can be represented from the table names of any function table other than the base table. Therefore, after the entry table serving as a certain model is searched, the function table on which the function table depends can be determined according to the table name of the function table, and all the characteristic data of the equipment of the model are determined based on each function table.

Accordingly, in the present embodiment, the step S103 of determining the function table having the target table name and the function table having the dependency relationship with the function table having the target table name may include steps S1031 to S1032:

S1031, determining a function table with the target table name;

S1032, taking the target table name as the current table name to be analyzed, determining the function table on which the function table with the current table name to be analyzed depends based on the current table name to be analyzed, taking the determined table name of the function table as the current table name to be analyzed, and returning to the step of determining the function table on which the function table with the current table name to be analyzed depends based on the current table name to be analyzed.

It can be understood that, since the table name of the function table on which the function table depends can be represented in the table names of any function table other than the base table, the function table on which the function table depends can be determined according to the current table name to be analyzed by taking the target table name as the current table name to be analyzed. And, by continuing the table name of the determined function table as the current table name to be analyzed, returning to the step of determining the function table on which the function table with the current table name to be analyzed depends based on the current table name to be analyzed, the function table with each level of dependency relationship with the function table with the target table name can be determined.

Optionally, in one implementation, the table name of any function table except the base table includes: a first type of content and a second type of content which are associated through a preset association symbol, wherein the first type of content is table name content which is uniquely set for the function table, and the second type of content is table name content of the function table on which the function table depends;

when the function table on which the function table depends is the base table, the table name content of the function table on which the function table depends comprises the table name of the base table; when the function table on which the function table depends is not the base table, the table name contents of the function table on which the function table depends include: the first category of content in the table name of the function table relied upon.

For example, the predetermined association may be a special character of "%", "&" or the like. For example, if the predetermined association is "%", the table name of the function table may be a% B, where a is the first type of content and B is the second type of content. In this case, a is the table name content uniquely set for the function table, B is the table name content of the function table on which the function table depends, that is, if the function table on which the function table depends is a base table, B is the table name of the base table, and if the function table on which the function table depends is not a base table, B is the first type of content in the table names of the function table on which the function table depends, that is, the table name content uniquely set for the function table on which the function table depends.

Accordingly, in the present implementation manner, as shown in fig. 2, the determining, in the step S1032, the function table on which the function table having the current table name to be analyzed depends based on the current table name to be analyzed may include steps S201 to S202:

s201, determining second-class content in the current table name to be analyzed;

s202, the function table with the second class content is used as the function table on which the function table with the current table name to be analyzed depends, except the current table name to be analyzed.

It can be understood that, because the second class content is the table name content of the function table on which the function table depends, the second class content in the current table name to be analyzed can be determined, and according to the second class content, the function table containing the second class content in the table name except the current table name to be analyzed is searched and used as the function table on which the function table of the current table name to be analyzed depends.

For example, if the database stores 3 function tables with table names "C% B", "B% a" and "a", respectively, the function table with table name "a" is a base table. If the target table name is "C% B", the target table name is taken as the current table name to be analyzed, and the second type content "B" in the current table name to be analyzed, that is, the table name content of the function table on which the function table of the target table name depends includes "B", and at this time, the function table including "B" in the table names can be searched from the function tables stored in the database, and the function table including "B" in the table names except "C% B", that is, the function table having the table name of "B% a", is taken as the function table on which the function table having the table name of "C% B" depends. Then, taking the 'B% A' as the name of the current table to be analyzed, the second type content 'A' of the name of the current table to be analyzed can be determined, at this time, the function table of the 'A' can be searched from the function tables stored in the database, the function tables of the 'A' are included in the table names except the 'B% A', namely, the function table of the 'A' is taken as the function table on which the function table of the 'B% A' is depended. Thus, by the function table whose target table name is "C% B", the function table whose table name is "B% a" and the function table whose table name is "a" can be found, that is, the function table of each level having a dependency relationship with the function table of the target table name can be found.

The table name format of the table name of any function table other than the base table in the embodiment of the present application is not limited, and any table name format capable of characterizing the table name of the function table on which the function table depends may be used for naming the table name of any function table other than the base table in the present application.

Therefore, through the scheme, the function table with the dependency relationship with the function table of the target table name can be rapidly determined.

Optionally, in another embodiment of the present application, the field content of each feature field in any function table is: the unique feature data of the feature field, or at least one logic function set for the feature field, or a table name of a function table set for the feature field; the logic function is used for mapping different feature data of the feature field according to different condition contents of conditions depending on the feature field;

In this embodiment, the field content of a feature field in any function table may be unique feature data of the feature field, for example, if a certain type of device needs to be allocated to a starting memory of a certain software module 10MB, the field content of the feature field of the starting memory of the certain software module may be 10MB, where 10MB is the unique feature data of the feature field.

In addition, the field content of the feature field may also be at least one logic function set for the feature field, for example, if a device of a certain model supports wifi, it needs to allocate 50MB of starting memory to a certain software module, and if wifi is not supported, it needs to allocate 20MB of starting memory to a certain software module. At this time, the field content of the feature field characterizing the starting memory of the software module depends on the field content of the feature field "wifi_enable", that is, depends on the field content of other fields, and may be described by a logic function, where the logic function may be: "”。

Illustratively, at least one logical function may be a function named、/>、/>And/>One or more functions of (a) and (b). In addition, the field content of the feature field may also be a table name of a function table, where feature data characterizing the feature field is stored in other function tables, and feature data in other function tables, that is, sub-tables of the function table in which the feature field is located, are referenced. It will be appreciated that one mother table may refer to another table (sub-table) in the table, and that the reference format may be "sub-table name (parameter list)". Illustratively, the parameter list may be empty, characterizing feature data referencing all of the fields in the sub-table; or the parameter list is a certain feature field, and it is reasonable to characterize feature data referencing the feature field in the sub-table.

Accordingly, in this embodiment, as shown in fig. 3, in the step S105, based on the feature field to be accessed indicated by the access instruction, the feature data access is performed on the data merging result, so as to obtain a feature data access result of the feature field to be accessed, which may include steps S301 to S304:

S301, reading field contents of a feature field to be accessed indicated by the access instruction from a data merging result;

S302, responding to the read field content as the unique characteristic data of the characteristic field to be accessed, and determining the read field content as the characteristic data access result of the characteristic field to be accessed;

It can be understood that if the field content of the feature field to be accessed is the unique feature data of the feature field to be accessed, the read field content can be directly determined as the feature data of the feature field to be accessed.

S303, responding to the read field content as a logic function set for the feature field to be accessed, acquiring the condition content of the condition on which the feature field to be accessed depends, carried in the access instruction, and inputting the acquired condition content into the logic function set for the feature field to be accessed to obtain the feature data access result of the feature field to be accessed;

if the field content of the feature field to be accessed is a logic function set for the feature field to be accessed, the condition content of the condition on which the feature field to be accessed depends can be obtained from the access instruction, the obtained condition content is input into the logic function set for the feature field to be read, and the operation result of the logic function is used as the feature data of the feature field to be accessed. For example, if the field content of the field to be accessed is: " According to the logic function, the condition content of the dependent condition can be analyzed to be the field content of the characteristic field wifi_enable, and the field content of the wifi_enable can be input into the logic function. If the field content of the wifi_enable is Y, the operation result of the logic function is 50, and the feature data of the feature field to be read is 50; if the field content of wifi_enable is N, the operation result of the logic function is 20, and the feature data of the feature field to be read is 20.

It can be understood that by describing the dependency relationship between each feature data by using a logic function in the function table, for feature data with different values of different condition contents, different tables do not need to be set for data management, so that feature data with different values can be stored in the same table, and the data amount of feature data needing to be stored and managed is further reduced. In addition, it should be noted that the access instruction may not carry the condition content of the condition depending on the feature field to be accessed, and at this time, it is reasonable to analyze the condition content depending on the feature field to be accessed by reading the logic function set for the feature field to be accessed, and then obtain the condition content depending on the feature field by reading each function table.

S304, responding to the read field content as a table name, and reading to obtain a feature data access result of the feature field to be accessed based on the table name and a preset access path of the corresponding feature field to be accessed.

It can be understood that, in the data merging result obtained by merging the data of each function table, each feature field corresponds to a preset access path. If the read field content is a table name, reading a function table with the table name under the access path according to the table name and the access path of the corresponding feature field to be accessed, and taking the feature data in the read function table as a feature data access result of the feature field to be accessed. For example, if the function table a is referenced in the "media_map" field of the base table, each feature field in the function table a and the corresponding field content for characterizing feature data may be read as feature data of the feature field to be read.

It will be appreciated that if the read field is in content of a table name, then the table with that table name is a sub-table of the currently read table. It should be noted that, when the feature field of the sub-table is read, the field contents of the feature field of the sub-table may be the three cases, namely: the feature field has unique feature data, or at least one logical function set for the feature field, or a table name. At this time, reading of the field content is continued according to the above-described manner until the final feature data is obtained by reading. It is to be understood that, in the case of setting the sub-table, the configuration of the "base table+extension table" may be referred to. At this time, the feature data of each model is stored and managed in a tree structure in which a trunk is a mother table and a branch is a child table, each branch of the tree structure may have a plurality of levels of function tables, and the structure of the tables may be seen in fig. 4.

Therefore, through the scheme, the dependency relationship among the feature data is described by utilizing the logic function in the function table, so that the quantity of the feature data to be managed can be further reduced, and the data quantity of the feature data management and the effective access requirement on the feature data are reduced.

Optionally, in another embodiment of the present application, any of the function tables includes field contents corresponding to each feature field for characterizing feature data in at least one access dimension;

accordingly, in this embodiment, the feature field to be accessed indicated by the above access instruction is a feature field in the target access dimension;

In the step S105, based on the feature field to be accessed indicated by the access instruction, the feature data access is performed on the data merging result to obtain a feature data access result of the feature field to be accessed, which may include:

and accessing field contents of the feature field to be accessed in the data merging result under the target access dimension to obtain a feature data access result.

In this embodiment, the function table may include field contents corresponding to each feature field in at least one access dimension and used for characterizing feature data, that is, the field contents corresponding to each feature field in the at least one access dimension and used for characterizing feature data are stored and managed in the same table. For example, if a model of camera supports 3 paths of video, the function table includes access dimensions of 3 channels, and each feature field has a corresponding field content for characterizing feature data in each access dimension. By way of example, the function table may be as shown in Table 6 below:

TABLE 6

If the feature field to be accessed in the next target access dimension is expressed as: "dft_resolution [1]", when the field content of the "dft_resolution" field under channel 1 in the data merging result is accessed, the obtained characteristic data access result is 704×576.

It can be seen that, by storing the feature data in a plurality of access dimensions in one table, the number of tables to be managed can be reduced.

Optionally, in another embodiment of the present application, the model index table further stores custom feature data corresponding to at least one model and set for a specified feature field;

The above-described merging processing operation may further include:

If the model index table stores the custom characteristic data corresponding to the target model and set for the appointed characteristic field, when the appointed characteristic field is contained in the data merging result, the custom characteristic data corresponding to the target model and set for the appointed characteristic field is utilized to replace the characteristic data of the appointed characteristic field contained in the data merging result.

In this embodiment, the model index table may further store custom feature data set for the specified feature field corresponding to at least one model. It will be appreciated that if the feature data of a certain model is only slightly different from the feature data in the function table stored in the database, the number of tables is large if the table is to be re-created for management. Therefore, in this embodiment, the mode of storing the custom feature data set for the specified feature field in the model index table is adopted to store and manage the feature data, and when the specified feature field is included in the data merging result at this time, the custom feature data set for the specified feature field is used to replace the feature data of the specified feature field included in the data merging result. That is, the custom feature data stored in the model index table is taken as the final feature data of the specified feature field.

For example, the custom feature data set for the specified feature field may be stored in the model index table in the form of an access parameter, that is, as a parameter content carried after the table name. By way of example, the model index table may be as shown in Table 7:

TABLE 7

The feature data in the base table named "root_base_e11_ipce_d" are shown in table 8:

TABLE 8

In table 7, the content in the bracket after the table name "root_base_e11_ipce_d" is the custom feature data set for the designated feature field "chan_num". According to the model number "0x28620", a function table with the target table name "root_base_e11_ipce_d" can be determined, and from the function table, it can be seen that the field content including the "chan_num" field is 1. At this time, the feature data of the specified feature field is replaced by the custom feature data corresponding to the model "0x28620" and set for the "chan_num" field, so as to obtain the final access result as follows: the feature data of the feature field "chan_num" is 2.

Therefore, by the scheme, the data volume of the feature data required to be stored and managed can be further reduced, so that the data volume of the feature data management and the effective access requirement for the feature data are reduced.

For a better understanding of the embodiments of the present application, reference is made to the following description taken in conjunction with a specific example.

The present example employs a table as a description carrier of software and hardware feature data of a device (corresponding to the camera above), and the table includes various data file forms such as CSV, excel, database format, and the like. The tables include a parameter definition table, a model index table, and a function table. The parameter definition table is used for defining the name, the data type and the value range of the characteristic data. The model index table is used for recording the name and parameters of a start addressing table of a certain model. After the equipment is powered on, the main control program obtains the model of the equipment, and a root characteristic table (corresponding to the entry table corresponding to the model) corresponding to the model is searched in the model index table.

The function table as shown in table 6 above, it is possible to describe the value information of each feature field under different channels (corresponding to the access dimensions in the above). The format and value of these data follow the constraints of the names, data types and value ranges defined in the parameter definition table. That is, when performing feature data storage management, the relevant technician can check the feature data in the designed table by using the contents defined in the parameter definition table to construct a table conforming to the contents defined in the parameter definition table.

The dependency relationships between the various types of data are described in the function table in syntax (corresponding to the logical functions above). For example, if a certain model of device supports wifi, it needs to allocate 50MB of starting memory to a certain software module, and if wifi is not supported, it needs to allocate 20MB of starting memory to a certain software module. At this time, the field content of the feature field characterizing the starting memory of the software module depends on the field content of the feature field "wifi_enable (wifi is supported)", and can be described as: "”。

One function table may describe feature data on the basis of another function table, the table name of which follows the form of "extended table name% base table name". If abc% base, the description table abc is based on the table base description characteristic data. The rules for extending table references include: (1) The expansion table modifies the existing characteristic fields or the corresponding characteristic data in the base table; (2) If the feature data to be described does not exist in the base table, the feature data is newly added in the extension table. One table can be extended based on a certain Zhang Jibiao, and can be used as a base table of other extended tables. When the multi-stage expansion is performed, the expansion rule is always obtained by starting from the lowest-stage base table and expanding from bottom to top layer by layer.

One table (parent table) may refer to another table (sub-table) in the form of "sub-table name (parameter list)". In this way, all feature data becomes a tree structure. At this time, each feature data has a specific access path. It is assumed that the 0 th channel of the "media_map" field of the base table refers to the function table a, the 1 st channel of the "stream_map" field of the function table a refers to the function table b, and a feature parameter called resolution exists in the function table b. Its access path is then: media_map [0 ]/stream_map [1]/resolution.

If the value of a certain item of characteristic data depends on the values of other items of characteristic data, namely the item of characteristic data is a logic function, and the logic function is mapped to obtain different characteristic data according to different condition contents of the dependent conditions. The device adds conditional content to the access path for obtaining the item of characteristic data to obtain the item of characteristic data. Formats such as: wifi_enable=y, wherein "wifi_enable=y" is a conditional content, characterizing enabling wifi.

If the tree structure of the feature data of the camera a for storage management is shown in fig. 4, after the camera a is powered on, an entry table of the model can be found from a preset model index table according to the model of the camera a, that is, a function table with a table name of "extension table A3% extension table A2". The table name "extension table A3% extension table A2" is the target table name. By taking the target table name as the current table name to be analyzed, the function table on which the function table depends is determined to be an expansion table A2% expansion table A1, then the expansion table A2% expansion table A1 is taken as the current table name to be analyzed, the function table on which the function table with the table name of the expansion table A2% expansion table A1 depends is determined to be an expansion table A1% base table A, and the dependence relationship among all the function tables and all the function tables is searched by pushing the same. Then, the data merging is performed on the respective function tables based on the dependency relationship between the respective function tables, that is, the traversing order of forming the respective function tables is "base table a- > extension table A1% base table a- > extension table A2% extension table A1- > extension table A3% extension table A2" based on the determined dependency relationship. Traversing according to the traversing sequence, each time traversing to a function table of each function table, if the function table is the lowest level, taking the characteristic fields existing in the function table and the corresponding field contents used for representing the characteristic data as the current data merging result, otherwise, covering the characteristic data of the same field in the function table traversed later with the characteristic data of the characteristic field in the function table read before.

After the data merging result is obtained, when feature data of any program module of the camera is called, the feature data access is carried out on the data merging result, and a feature data access result of a feature field to be accessed is obtained.

When traversing to the function table named as the expansion table A1% base table A, the characteristic data in the function table refers to the characteristic data in the sub-table 1 and the sub-table 2 through the tree structure shown in fig. 4, wherein the sub-table 1 is the expansion table B3% expansion table B2, and the sub-table 2 is the expansion table C2% expansion table C1. At this time, traversing the sub-table 1 from the base table B with the lowest level, and carrying out data merging according to the traversing sequence of the base table B- > the expansion table B1% base table B- > the expansion table B2% expansion table B1- > the expansion table B3% expansion table B2", wherein the obtained data merging result is used as the characteristic data of the sub-table 1; traversing the sub-table 2 from the base table C with the lowest level, and merging data according to the traversing sequence of the base table C- > the expansion table C1% base table C- > the expansion table C2% expansion table C1, wherein the obtained data merging result is used as the quoted characteristic data. Similarly, when traversing to the function table named as "expansion table B2% expansion table B1", the function table refers to "expansion table D1% expansion table D", and at this time, data combination is performed in accordance with the traversing order of "base table D- > expansion table D1% base table D", and the obtained data combination result is used as the referenced feature data. Traversing to a function table named as an expansion table C1% base table C, wherein the function table refers to an expansion table E2% expansion table E1, and carrying out data merging according to the traversing sequence of the base table E- > the expansion table E1% base table E- > the expansion table E2% expansion table E1, wherein the obtained data merging result is used as the referenced characteristic data.

According to the scheme, the logic relation among the characteristic data of the equipment is described in the table by using the logic function, and for the characteristic data with different values of different condition contents, different tables are not required to be set for data management, so that the characteristic data with different values can be stored in the same table, and the data volume of the characteristic data required to be stored and managed can be reduced. The mode that the final characteristic data is obtained after the characteristic data are overlapped step by adopting the respective description characteristic data of the base table and the extension table does not need to store a large amount of redundant data, so that the data amount of the characteristic data needing to be stored and managed is reduced. Therefore, the scheme can reduce the data volume of the feature data management and the effective access requirement for the feature data.

Correspondingly, the embodiment of the application also provides a data processing device for the characteristic data of the camera, which is applied to the camera, wherein the camera belongs to a target equipment type, each model under the target equipment type shares a base table belonging to a function table, and each preset characteristic field of the target equipment type and corresponding field content for representing the characteristic data are recorded in the base table; and, for any model, the characteristic data of each characteristic field of the equipment of the model is stored and managed according to a preset storage management mode by taking the base table as a function table of an initial level;

The storage management mode comprises the following steps: if the characteristic data of the equipment of the model is the same as the merging data corresponding to any one of the function table combinations, taking the function table of the highest level in the function table combination as an entry table corresponding to the model; otherwise, creating a function table with the level higher than the target function table and depending on the target function table, and taking the created function table as an entry table corresponding to the model; each function table is combined into at least one level of function table with continuous levels from a base table, corresponding merging data is obtained by merging the data of the at least one level of function table, the target function table is the function table with the highest level existing at present, and the function table is used for recording: the feature fields with differences and the corresponding field contents used for representing the feature data are compared with the merged data obtained by merging the data of the current existing function table;

The device comprises:

The acquisition module is used for responding to the completion of the powering-on of the camera and acquiring the target model of the camera;

The first determining module is used for determining a table name corresponding to the target model from a preset model index table as a target table name; the model index table stores table names of an entry table corresponding to each model;

The second determining module is used for determining a function table with the target table name and a function table with a dependency relationship with the function table with the target table name;

The merging module is used for merging the data of each determined function table based on the determined dependency relationship among each function table to obtain a data merging result;

And the access module is used for responding to the access instruction of any program module of the camera for the characteristic data, and performing characteristic data access on the data merging result based on the characteristic field to be accessed indicated by the access instruction to obtain the characteristic data access result of the characteristic field to be accessed.

In the technical scheme of the application, related operations such as acquisition, storage, use, processing, transmission, provision, disclosure and the like of the personal information of the user are performed under the condition that the authorization of the user is obtained.

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, optical fiber, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, tape), an optical medium (e.g., DVD), or a Solid state disk (Solid STATE DISK, SSD), etc.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. 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 apparatus that comprises the element.

In this specification, each embodiment is described in a related manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments in part.

The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application are included in the protection scope of the present application.

Claims

1. The data processing method for the feature data of the camera is characterized by being applied to the camera, wherein the camera belongs to a target equipment type, each model under the target equipment type shares a base table belonging to a function table, and each preset feature field of the target equipment type and corresponding field content for representing the feature data are recorded in the base table; and, for any model, the characteristic data of each characteristic field of the equipment of the model is stored and managed according to a preset storage management mode by taking the base table as a function table of an initial level;

2. The method according to claim 1, wherein a table name of any function table other than the base table is: table names capable of characterizing the function table relied upon;

The determining the function table with the target table name and the function table with the dependency relationship with the function table with the target table name comprises the following steps:

Determining a function table with the target table name;

and determining a function table on which the function table with the current table name to be analyzed depends based on the current table name to be analyzed by taking the target table name as the current table name to be analyzed, and returning to the step of determining the function table on which the function table with the current table name to be analyzed depends based on the current table name to be analyzed by taking the determined table name of the function table as the current table name to be analyzed.

3. The method according to claim 2, wherein the table names of any function table other than the base table include: the method comprises the steps of carrying out association on first-class contents and second-class contents through preset association symbols, wherein the first-class contents are table name contents uniquely set for a function table, and the second-class contents are table name contents of the function table on which the function table depends;

4. A method according to claim 3, wherein said determining, based on the current table name to be analyzed, a function table on which the function table having the current table name to be analyzed depends, comprises:

Determining second-class content in the current table name to be analyzed;

and taking the function table with the second class content in the table names except the current table name to be analyzed as a function table on which the function table with the current table name to be analyzed depends.

5. The method according to any one of claims 1 to 4, wherein the performing data merging on the determined function tables based on the determined dependency relationship between the function tables to obtain a data merging result includes:

forming the traversing sequence of each function table according to the determined dependency relationship among each function table; wherein the traversing order is from low to high according to the level;

Every time traversing to a function table of each function table, if the function table is the lowest level, taking the characteristic field existing in the function table and the corresponding field content used for representing the characteristic data as the current data merging result, otherwise, merging the content existing in the function table into the current data merging result according to the preset merging processing operation until each function table is traversed;

6. The method of any one of claims 1-4, wherein the field content of each feature field in any one of the function tables is: the unique feature data of the feature field, or at least one logic function set for the feature field, or a table name of a function table set for the feature field; the logic function is used for mapping different feature data of the feature field according to different condition contents of conditions depending on the feature field;

And performing feature data access on the data merging result based on the feature field to be accessed indicated by the access instruction to obtain a feature data access result of the feature field to be accessed, wherein the feature data access result comprises:

reading the field content of the feature field to be accessed indicated by the access instruction from the data merging result;

responding to the read field content as the unique characteristic data of the characteristic field to be accessed, and determining the read field content as the characteristic data access result of the characteristic field to be accessed;

Responding to the read field content as a logic function set for a feature field to be accessed, acquiring condition content of conditions on which the feature field to be accessed depends, which is carried in the access instruction, and inputting the acquired condition content into the logic function set for the feature field to be accessed to obtain a feature data access result of the feature field to be accessed;

And responding to the read field content as a table name, and reading to obtain a feature data access result of the feature field to be accessed based on the table name and a preset access path of the corresponding feature field to be accessed.

7. The method according to any one of claims 1-4, wherein any function table contains field contents for characterizing feature data corresponding to respective feature fields in at least one access dimension;

the feature field to be accessed indicated by the access instruction is a feature field under the target access dimension;

8. The method of claim 5, wherein the model index table further stores custom feature data corresponding to at least one model and set for a specified feature field;

The merging processing operation further includes:

If the model index table stores the custom characteristic data which corresponds to the target model and is set for the appointed characteristic field, under the condition that the data merging result contains the appointed characteristic field, the custom characteristic data which corresponds to the target model and is set for the appointed characteristic field is utilized to replace the characteristic data of the appointed characteristic field contained in the data merging result.

9. The method of claim 8, wherein the custom characteristic data set for a specified characteristic field is stored in the model index table in the form of access parameters; wherein the access parameters are in the form of carrying parameters after the stored table names.

10. A data processing device for feature data of a camera, characterized in that the device is applied to the camera, the camera belongs to a target equipment type, each model under the target equipment type shares a base table belonging to a function table, and each preset feature field of the target equipment type and corresponding field content for representing the feature data are recorded in the base table; and, for any model, the characteristic data of each characteristic field of the equipment of the model is stored and managed according to a preset storage management mode by taking the base table as a function table of an initial level;

The device comprises: