CN112883882A - Face recognition fusion processing method and system - Google Patents
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Abstract
The application discloses a face recognition fusion processing method and a system, wherein the method comprises the following steps: acquiring a character string used as an input of a face recognition algorithm, wherein the character string is transmitted through a standardized general interface; acquiring a first face recognition algorithm engine used at this time from a plurality of face recognition algorithm engines stored in a database in advance; packaging the character string into parameter data according to a packaging protocol of the first face recognition algorithm engine; calling a face recognition function corresponding to the first face recognition algorithm engine by using the packaged input parameters, and acquiring a returned result; and packaging the result by using the normalized universal interface and then returning. The method and the device solve the problem that the face recognition algorithm is inconvenient to replace due to the fact that different face recognition algorithms use different protocols, and improve the applicability of the different face recognition algorithms.
Description
Technical Field
The application relates to the field of face recognition, in particular to a face recognition fusion processing method and system.
Background
At present, a plurality of suppliers provide face recognition algorithm services, but a standard communication protocol is not unified among all the suppliers. Due to some nonreactive factors, the user may need to replace the face recognition algorithms of different suppliers, or use the face recognition functions of multiple suppliers to ensure the reliability and accuracy of the face recognition algorithms. If a user needs to change a face recognition algorithm supplier in the scene, the different suppliers have different protocols, so that the method is invasive to the finished functions of the existing system, and the cost of replacing the suppliers is high.
Disclosure of Invention
The embodiment of the application provides a face recognition fusion processing method and a face recognition fusion processing system, which at least solve the problem that the face recognition algorithm is inconvenient to replace due to the fact that different face recognition algorithms use different protocols.
According to one aspect of the application, a face recognition fusion processing method is provided, which comprises the following steps: acquiring a character string used as an input of a face recognition algorithm, wherein the character string is transmitted through a standardized general interface; acquiring a first face recognition algorithm engine used at this time from a plurality of face recognition algorithm engines stored in a database in advance; packaging the character string into parameter data according to a packaging protocol of the first face recognition algorithm engine; calling a face recognition function corresponding to the first face recognition algorithm engine by using the packaged input parameters, and acquiring a returned result; and packaging the result by using the normalized universal interface and then returning.
Further, the specification of the generic interface includes at least one of: creating a face recognition database, deleting the face database, registering a user face, updating the user face, deleting the user face, searching the user face 1VN, and comparing the user picture 1V 1.
Further, after obtaining the first face recognition algorithm engine used this time, the method further comprises: and caching the operation of obtaining the first face recognition algorithm engine into a cache library.
Further, invoking a face recognition function corresponding to the first face recognition algorithm engine and obtaining a returned result includes: and remotely calling an HTTP interface through the Fegin to obtain a result returned by the face recognition function.
Further, before acquiring the character string as an input of the face recognition algorithm, the method further comprises: receiving a face recognition service request from a service through middleware; acquiring the character string corresponding to the face recognition service request through the middleware, wherein the middleware is used for executing asynchronous service operation; and returning a result packaged by using the normalized universal interface to the business service through the middleware.
According to another aspect of the present application, there is also provided a face recognition fusion processing system, including: the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a character string which is used as the input of a face recognition algorithm, and the character string is transmitted through a standardized general interface; the second acquisition module is used for acquiring the first face recognition algorithm engine used at the time from a plurality of face recognition algorithm engines which are pre-stored in a database; the packaging module is used for packaging the character string into the parameter data according to the packaging protocol of the first face recognition algorithm engine; the third acquisition module is used for calling a face recognition function corresponding to the first face recognition algorithm engine by using the encapsulated input parameters and acquiring a returned result; and the return module is used for packaging the result by using the normalized universal interface and then returning the result.
Further, the specification of the generic interface includes at least one of: creating a face recognition database, deleting the face database, registering a user face, updating the user face, deleting the user face, searching the user face 1VN, and comparing the user picture 1V 1.
Further, still include: and the cache module is used for caching the operation of obtaining the first face recognition algorithm engine into a cache library.
Further, the third obtaining module is further configured to obtain a result returned by the face recognition function by using a Fegin remote call HTTP interface.
Further, still include: the middleware is used for receiving a face recognition service request from a service and transmitting the character string corresponding to the face recognition service request to the first acquisition module, wherein the middleware is used for executing asynchronous service operation; the middleware is further configured to return the result, encapsulated by using the normalized universal interface, from the return module to the business service.
In the embodiment of the application, the method comprises the steps of acquiring a character string used as input of a face recognition algorithm, wherein the character string is transmitted through a standardized general interface; acquiring a first face recognition algorithm engine used at this time from a plurality of face recognition algorithm engines stored in a database in advance; packaging the character string into the parameter data according to a packaging protocol of a first face recognition algorithm engine; calling a face recognition function corresponding to the first face recognition algorithm engine by using the packaged input parameters, and acquiring a returned result; and packaging the result by using a standardized universal interface and then returning. The method and the device solve the problem that the face recognition algorithm is inconvenient to replace due to the fact that different face recognition algorithms use different protocols, and improve the applicability of the different face recognition algorithms.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application. In the drawings:
FIG. 1 is a flow chart of a face recognition fusion processing method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a generic interface specification according to an embodiment of the present application;
FIG. 3 is a schematic diagram of an algorithm engine operation according to an embodiment of the present application;
FIG. 4 is a diagram of middleware processing according to an embodiment of the application.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In this embodiment, an electronic device is provided, comprising a memory in which a computer program is stored and a processor arranged to run the computer program to perform the method in the following embodiments.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that 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 an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
The embodiment of the application provides a storage medium, on which a program or software is stored, and the program realizes the method when being executed by a processor. The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.
In this embodiment, a face recognition fusion processing method is provided, and fig. 1 is a flowchart of a face recognition fusion processing method according to an embodiment of the present application, as shown in fig. 1, the method includes the following steps:
step S102, obtaining a character string used as the input of a face recognition algorithm, wherein the character string is transmitted through a normalized general interface.
The specification of the generic interface may be formulated as desired, for example, the specification of the generic interface may include at least one of: creating a face recognition database, deleting the face database, registering a user face, updating the user face, deleting the user face, searching the user face 1VN, and comparing the user picture 1V 1.
And step S104, acquiring a first face recognition algorithm engine used at this time from a plurality of face recognition algorithm engines stored in a database in advance.
In an alternative embodiment, the operation of obtaining the first face recognition algorithm engine may be cached in a cache library in order to improve the efficiency of the next query.
And step S106, packaging the character string into the parameter data according to the packaging protocol of the first face recognition algorithm engine.
And step S108, calling a face recognition function corresponding to the first face recognition algorithm engine by using the packaged input parameters, and acquiring a returned result.
Various modes for calling the face recognition function are available, and the selection can be flexibly performed during implementation, for example, the result returned by the face recognition function can be obtained by remotely calling an HTTP interface through Fegin. It should be noted that this is only an alternative way and is not limited to this.
And step S110, packaging the result by using the normalized universal interface and then returning.
The normalized input and the normalized output are used through the steps, and the plurality of face recognition algorithm engines are stored in the database and called to transmit the parameters when in use. Therefore, the problem that the face recognition algorithm is inconvenient to replace due to the fact that different face recognition algorithms use different protocols is solved through the steps, and the applicability of the face recognition algorithms is improved.
In order to prevent the pressure caused by high concurrent requests, in an alternative embodiment, middleware can be added for processing, and in the embodiment, a face recognition service request from a service is received through the middleware; acquiring a character string corresponding to a face recognition service request through a middleware, wherein the middleware is used for executing asynchronous service operation; and returning a result packaged by using the normalized universal interface to the business service through the middleware.
As an optional and additional embodiment, in the case that the service does not specify the face recognition algorithm engine used by the service, the middleware sends the service request to a plurality of face recognition algorithm engines, and records the time required from sending to each face recognition algorithm engine to receiving the returned result, the middleware binds the corresponding relationship between the service and the face recognition algorithm engine with the shortest time consumption in a predetermined time period, and sends the requests from the service to the bound face recognition algorithm engines in the predetermined time period. And when the business service request carries the specified face recognition algorithm engine, the business service is sent to the specified face recognition algorithm engine.
As another optional embodiment that can be added, before sending the service request to the multiple face recognition algorithm engines, the middleware determines whether the load exceeds a threshold, and if the load exceeds the threshold, sends the service request to the face recognition algorithm engine that is randomly selected. If the load does not exceed the threshold, the service request is sent to a plurality of face recognition algorithm engines.
As another optional embodiment that can be added, the middleware is configured with a weight of each face recognition algorithm engine, and requests of middleware service are allocated to the corresponding face recognition algorithm engine according to the size of the weight, wherein the larger the weight, the more the requests are received.
In this embodiment, a face recognition fusion processing system is further provided, where modules in the system correspond to the above method, the models are used to implement the above method steps, names of the modules are only used to identify the modules, and do not constitute a limitation on specific contents of the modules. The face recognition fusion processing system can also be called a face recognition fusion platform system.
The face recognition fusion processing system comprises: the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a character string which is used as the input of a face recognition algorithm, and the character string is transmitted through a standardized general interface; the second acquisition module is used for acquiring the first face recognition algorithm engine used at the time from a plurality of face recognition algorithm engines which are pre-stored in a database; the packaging module is used for packaging the character string into the parameter data according to the packaging protocol of the first face recognition algorithm engine; the third acquisition module is used for calling a face recognition function corresponding to the first face recognition algorithm engine by using the encapsulated input parameters and acquiring a returned result; and the return module is used for packaging the result by using the standardized general interface and then returning the result.
As a preferred embodiment, the specification of the generic interface comprises at least one of: creating a face recognition database, deleting the face database, registering a user face, updating the user face, deleting the user face, searching the user face 1VN, and comparing the user picture 1V 1.
As a preferred embodiment, the method further comprises the following steps: and the cache module is used for caching the operation of obtaining the first face recognition algorithm engine into a cache library.
As a preferred embodiment, the third obtaining module is further configured to obtain a result returned by the face recognition function through a Fegin remote call HTTP interface.
As a preferred embodiment, the method further comprises the following steps: the middleware is used for receiving a face recognition service request from a service and transmitting a character string corresponding to the face recognition service request to the first acquisition module, wherein the middleware is used for executing asynchronous service operation; the middleware is also used for returning the encapsulated result from the return module by using the normalized universal interface to the business service.
In the preferred embodiment, a face recognition fusion platform system is provided, which may also be referred to as a software or a service, and the platform of the system may include the following logic:
(1) a generic function interface specification is defined. Fig. 2 is a schematic diagram of a generic interface specification according to an embodiment of the present application, and as shown in fig. 2, the generic interface specification includes: creating a face database, deleting the face database, registering a user face, updating the user face, deleting the user face, searching the user face 1VN and comparing the user face 1V 1.
(2) And (4) interfacing face recognition algorithms of different suppliers. At present, the face recognition algorithms of a plurality of manufacturers can be docked, and as shown in fig. 4, the face recognition algorithms are three-party suppliers, such as Huashi, spacious sight, Tencent excel drawing, Eigent drawing and Baidu. In the future, if more face recognition manufacturers appear, the embodiment can also carry out docking.
(3) And the face recognition platform fusion algorithm selects a face recognition algorithm according to the engine configuration items. Fig. 3 is a schematic diagram of an algorithm engine operation according to an embodiment of the present application, and as shown in fig. 3, a database stores an available algorithm engine of a three-party vendor, matches the algorithm engine to a corresponding algorithm engine according to an incoming character string, and caches the operation of obtaining the algorithm engine to a cache library to improve the efficiency of next query. And after acquiring the corresponding algorithm engine, packaging the input parameter data according to different algorithm engine protocol rules, remotely calling an Http interface through Fegin to acquire a return result of the face recognition function, analyzing the contents of the return result of the three-party interface, and returning the contents of the uniform format interface after packaging.
Optionally, referring to fig. 3, the method sequentially includes the following steps: the configuration center is configured with an available algorithm engine, obtains the algorithm engine according to a specific character string, obtains the operation of the algorithm engine and caches the operation in a cache library, identifies the logic operation of the face, packages the interface parameter, calls a face identification algorithm API by a margin, analyzes the interface parameter and returns an operation result set. And acquiring an algorithm engine according to the specific character string, and performing face recognition logic operation under the condition of no cache hit.
(4) The message middleware decoupling system performs peak clipping and valley removal. Fig. 4 is a middleware processing diagram according to an embodiment of the application, and as shown in fig. 4, a data loss problem may be caused by a pressure of a high-concurrency request on a server due to a machine performance limit or a network bandwidth limit during face recognition, in order to ensure reliability of data and high availability of a service, a message middleware is added between a service application and a face recognition convergence platform system, and the face recognition convergence platform system operates as a consumer to an asynchronous consumption service application and completes a response within milliseconds.
Two specific algorithms are described below as examples.
Example one
The user purchases a Huacheng face recognition algorithm, and a face recognition fusion platform system is never deployed.
1) Enabling the Huawei algorithm configuration items in the configuration center, and configuring an algorithm server address;
2) configuring a message middleware address by a configuration center;
3) a user uses an agreed standard protocol to call a face recognition fusion platform system to provide an interface or realize that a message middleware producer calls a unified face recognition function;
4) the face recognition platform fusion algorithm acquires a face recognition algorithm service address through the configuration item and calls a corresponding face recognition algorithm function;
5) and returning the agreed standard protocol content, and analyzing the returned content by the user to finish the operation.
Example two
The user uses the Hua as a face recognition algorithm, and the field-of-view face recognition algorithm is used instead for special reasons.
1) Disabling Huawei algorithm configuration items in the configuration center;
2) and starting the configuration item of the clear-view algorithm in the configuration center, and configuring the address of the algorithm server to finish the operation.
In the preferred embodiment, a uniform face recognition function interface is standardized, and service application is decoupled through message middleware, so that the scheme of the face recognition algorithm engine which is easy to expand is provided by the embodiment.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A face recognition fusion processing method is characterized by comprising the following steps:
acquiring a character string used as an input of a face recognition algorithm, wherein the character string is transmitted through a standardized general interface;
acquiring a first face recognition algorithm engine used at this time from a plurality of face recognition algorithm engines stored in a database in advance;
packaging the character string into parameter data according to a packaging protocol of the first face recognition algorithm engine;
calling a face recognition function corresponding to the first face recognition algorithm engine by using the packaged input parameters, and acquiring a returned result;
and packaging the result by using the normalized universal interface and then returning.
2. The method of claim 1, wherein the specification of the generic interface comprises at least one of:
creating a face recognition database, deleting the face database, registering a user face, updating the user face, deleting the user face, searching the user face 1VN, and comparing the user picture 1V 1.
3. The method of claim 1, wherein after obtaining the first facial recognition algorithm engine for this use, the method further comprises:
and caching the operation of obtaining the first face recognition algorithm engine into a cache library.
4. The method of claim 1, wherein invoking a face recognition function corresponding to the first face recognition algorithm engine and obtaining a returned result comprises:
and remotely calling an HTTP interface through the Fegin to obtain a result returned by the face recognition function.
5. The method according to any one of claims 1 to 4,
before acquiring the character string as an input of the face recognition algorithm, the method further comprises: receiving a face recognition service request from a service through middleware; acquiring the character string corresponding to the face recognition service request through the middleware, wherein the middleware is used for executing asynchronous service operation;
and returning a result packaged by using the normalized universal interface to the business service through the middleware.
6. A face recognition fusion processing system, comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a character string which is used as the input of a face recognition algorithm, and the character string is transmitted through a standardized general interface;
the second acquisition module is used for acquiring the first face recognition algorithm engine used at the time from a plurality of face recognition algorithm engines which are pre-stored in a database;
the packaging module is used for packaging the character string into the parameter data according to the packaging protocol of the first face recognition algorithm engine;
the third acquisition module is used for calling a face recognition function corresponding to the first face recognition algorithm engine by using the encapsulated input parameters and acquiring a returned result;
and the return module is used for packaging the result by using the normalized universal interface and then returning the result.
7. The system of claim 6, wherein the specification of the generic interface comprises at least one of:
creating a face recognition database, deleting the face database, registering a user face, updating the user face, deleting the user face, searching the user face 1VN, and comparing the user picture 1V 1.
8. The system of claim 6, further comprising:
and the cache module is used for caching the operation of obtaining the first face recognition algorithm engine into a cache library.
9. The system of claim 6,
and the third acquisition module is also used for acquiring a result returned by the face recognition function by remotely calling an HTTP interface through the Fegin.
10. The system of any one of claims 6 to 9, further comprising: the intermediate piece is used for the intermediate piece,
the middleware is used for receiving a face recognition service request from a service and transmitting the character string corresponding to the face recognition service request to the first acquisition module, wherein the middleware is used for executing asynchronous service operation;
the middleware is further configured to return the result, encapsulated by using the normalized universal interface, from the return module to the business service.
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| CN110659087A (en) * | 2019-09-11 | 2020-01-07 | 旭辉卓越健康信息科技有限公司 | Face recognition algorithm engineering system applied to intelligent medical treatment |
| CN111339345A (en) * | 2020-02-26 | 2020-06-26 | 北京国网信通埃森哲信息技术有限公司 | Method, system and storage medium for differential shielding of multi-platform face recognition service interface |
| CN111738446A (en) * | 2020-06-12 | 2020-10-02 | 北京百度网讯科技有限公司 | Scheduling method, device, equipment and medium of deep learning inference engine |
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| CN110659087A (en) * | 2019-09-11 | 2020-01-07 | 旭辉卓越健康信息科技有限公司 | Face recognition algorithm engineering system applied to intelligent medical treatment |
| CN111339345A (en) * | 2020-02-26 | 2020-06-26 | 北京国网信通埃森哲信息技术有限公司 | Method, system and storage medium for differential shielding of multi-platform face recognition service interface |
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Application publication date: 20210601 |