CN113792168A - Method, system, electronic device and storage medium for self-maintenance of human face bottom library - Google Patents
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Abstract
The application relates to a method, a system, an electronic device and a storage medium for self-maintenance of a human face bottom library, wherein the method comprises the following steps: acquiring character warehousing data, performing repeated detection according to character information, and renaming the image of the character according to a result obtained by the detection; then, carrying out face detection and face alignment on the renamed figure image, outputting to obtain an aligned face, manually confirming whether the aligned face is put in storage, and under the condition of confirming that the face is put in storage, extracting the features of the aligned face and adding the features into a temporary storage; and finally, combining the aligned features of the face with the features of the base library, carrying out recognition test on the features in the base library through a test set to obtain a test result, judging whether the test result reaches the standard through a test index, and entering the aligned features of the face into a base library to take effect under the condition of judging that the test result reaches the standard. The human face warehousing process is effectively simplified, the labor cost is saved, and the instantaneity is improved.
Description
Technical Field
The present application relates to the field of face recognition technologies, and in particular, to a method, a system, an electronic device, and a storage medium for self-maintenance of a face base.
Background
Face recognition is a biometric technique for identifying an identity based on facial feature information of a person. The 1: N mode in the face recognition technology is that after face detection and face alignment are carried out on an input picture, characteristics are extracted and compared with characteristics stored in a face base library, person information corresponding to Top1 similarity in the base library is taken, and the name of a person is judged under a certain threshold value.
In the related art, under the normal condition, the human face features in the bottom library need to be modified by specific algorithm personnel, the flow of modifying the features is fixed, and the repetitive work can occupy more time of the algorithm personnel and is time-consuming and labor-consuming; after the characteristics are modified, testing is needed to verify whether the overall indexes are affected; after the test is carried out without problems, the model needs to be manually released to be on line, and the release of the model is constrained by the stability and the availability of a company and cannot be immediately modified and immediately effective, so that the emergency cannot be responded in real time; in addition, the whole bottom library modification process is very complicated, and the task needs to be finished by appointed personnel, so that the labor cost is high. Therefore, how to implement the automatic maintenance of the human face bottom library is a topic worthy of research.
At present, no effective solution is provided for the problems of complex flow, high labor cost and poor real-time performance existing in the related art when a human face base library is modified and maintained.
Disclosure of Invention
The embodiment of the application provides a method, a system, an electronic device and a storage medium for self-maintenance of a human face base library, so as to at least solve the problems of complex flow, high labor cost and poor real-time performance when the human face base library is modified and maintained in the related technology.
In a first aspect, an embodiment of the present application provides a method for self-maintenance of a face base library, where the method includes:
acquiring character warehousing data, performing repeated detection according to the character information, and renaming the image of the character according to the result obtained by the detection;
carrying out face detection and face alignment on the renamed figure image, outputting to obtain an aligned face, manually confirming whether the aligned face is put in storage, and extracting the characteristics of the aligned face and adding the characteristics into a temporary storage under the condition of confirming the storage;
combining the characteristics with the characteristics of the base library, carrying out identification test on the characteristics in the base library through a test set to obtain a test result, judging whether the test result reaches the standard or not through a test index, and entering the base library by the characteristics under the condition of judging that the test result reaches the standard, wherein the base library takes effect.
In some embodiments, performing the repeatability detection based on the information of the person comprises:
searching in the base according to the information of the figure stored in the base, and detecting whether the situation of figure information repetition exists or not, wherein the figure information comprises Chinese names and pinyin;
and outputting the aligned human face and the human information of the repeated human in the base library under the condition that the duplication of the human information is detected.
In some embodiments, renaming the image of the person according to the detection result includes:
under the condition that the person is judged to be a non-repetitive person, assigning a new ID of the person, and renaming the image of the person;
in a case where it is determined that the person is a duplicated person, an ID of the duplicated person is assigned to the person, and an image of the person is renamed.
In some embodiments, the manually confirming whether the aligned face is put in storage further includes:
and under the condition that the person is confirmed not to be put in storage, the unqualified face in the aligned faces can be deleted, other faces are continuously put in storage, or all the faces in the aligned faces are directly abandoned, and new storage data of the person is obtained again.
In some of these embodiments, prior to performing the identification test on the features in the underlying library through the test set, the method includes:
determining the person to be deleted through the person ID, and deleting the person data in the bottom library through a bottom library deleting module;
and determining the person needing to be modified through the person ID, and modifying the person information through the bottom library modification module.
In some embodiments, performing an identification test on the features in the base library through the test set to obtain a test result includes:
and comparing and identifying the test set subjected to face detection, face alignment and feature extraction with features in the base library, obtaining final similarity through a figure risk prevention and control layering system, and taking figure information corresponding to the first similarity.
In some of these embodiments, after the base library is validated, the method includes:
and determining the person to be inquired through the person ID, inquiring through the bottom library inquiring module, and outputting to obtain corresponding person information.
In a second aspect, an embodiment of the present application provides a system for self-maintenance of a human face base library, where the system includes:
the acquisition module is used for acquiring character warehousing data, performing repeated detection according to the character information and renaming the image of the character according to the result obtained by the detection;
the storage module is used for carrying out face detection and face alignment on the renamed figure image, outputting the aligned face, manually confirming whether the aligned face is stored in a storage or not, and extracting the characteristics of the aligned face and adding the characteristics into a temporary storage under the condition of confirming the storage;
and the test module is used for combining the features and the features of the base library, carrying out recognition test on the features in the base library through the test set to obtain a test result, judging whether the test result reaches the standard through the test indexes, and entering the features into the base library to take effect under the condition of judging that the test result reaches the standard.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor, when executing the computer program, implements the method for self-maintenance of the human face base library according to the first aspect.
In a fourth aspect, the present application provides a storage medium, on which a computer program is stored, where the program, when executed by a processor, implements the method for self-maintenance of a human face base library as described in the first aspect above.
Compared with the related technology, the method for self-maintaining the human face base, provided by the embodiment of the application, comprises the steps of obtaining character database data, carrying out repeated detection according to character information, and renaming the image of the character according to the result obtained by the detection; then, carrying out face detection and face alignment on the renamed figure image, outputting to obtain an aligned face, manually confirming whether the aligned face is put in storage, and under the condition of confirming that the face is put in storage, extracting the features of the aligned face and adding the features into a temporary storage; and finally, combining the aligned features of the face with the features of the base library, carrying out recognition test on the features in the base library through a test set to obtain a test result, judging whether the test result reaches the standard through a test index, and entering the aligned features of the face into a base library to take effect under the condition of judging that the test result reaches the standard.
Aiming at the problems that the maintenance process of the human face base is complicated, the labor cost is high, and the model release is restricted by the stability and the availability of a company, so that the emergency can not be responded in real time, the human face base maintenance system is optimized, is put into storage and tested in a platform and automation mode, and is integrated, the integration from character data collection, real-time storage and effective operation to a human face testing and identifying module is realized, the human face storage process is effectively simplified, and the labor cost is saved. In addition, the method and the device can also modify and take effect on the character information, so that the emergency can be responded in real time, and the efficiency is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a schematic diagram of an application environment of a method for self-maintenance of a human face base library according to an embodiment of the present application;
FIG. 2 is a flow chart of a method of self-maintenance of a face base according to an embodiment of the present application;
FIG. 3 is a schematic flow chart of self-maintenance of a face base according to an embodiment of the present application;
FIG. 4 is a block diagram of a system for self-maintenance of a face base according to an embodiment of the present application;
fig. 5 is an internal structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments provided in the present application without any inventive step are within the scope of protection of the present application. Moreover, it should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the specification. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of ordinary skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments without conflict.
Unless defined otherwise, technical or scientific terms referred to herein shall have the ordinary meaning as understood by those of ordinary skill in the art to which this application belongs. Reference to "a," "an," "the," and similar words throughout this application are not to be construed as limiting in number, and may refer to the singular or the plural. The present application is directed to the use of the terms "including," "comprising," "having," and any variations thereof, which are intended to cover non-exclusive inclusions; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to the listed steps or elements, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. Reference to "connected," "coupled," and the like in this application is not intended to be limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. Reference herein to "a plurality" means greater than or equal to two. "and/or" describes an association relationship of associated objects, meaning that three relationships may exist, for example, "A and/or B" may mean: a exists alone, A and B exist simultaneously, and B exists alone. Reference herein to the terms "first," "second," "third," and the like, are merely to distinguish similar objects and do not denote a particular ordering for the objects.
The method for self-maintaining the face bottom library can be applied to an application environment shown in fig. 1, and fig. 1 is an application environment schematic diagram of the method for self-maintaining the face bottom library according to the embodiment of the application, as shown in fig. 1. The terminal 11 and the server 10 communicate with each other via a network. The server 10 acquires character warehousing data, performs repeated detection according to character information, and renames the image of the character according to the detection result; then, carrying out face detection and face alignment on the renamed figure image, outputting to obtain an aligned face, manually confirming whether the aligned face is put in storage through equipment 11, and under the condition of confirming that the face is put in storage, extracting the features of the aligned face and adding the features into a temporary storage; and finally, combining the aligned features of the face with the features of the base library, carrying out recognition test on the features in the base library through a test set to obtain a test result, judging whether the test result reaches the standard through a test index, and entering the aligned features of the face into a base library to take effect under the condition of judging that the test result reaches the standard. The terminal 11 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 10 may be implemented by an independent server or a server cluster formed by a plurality of servers.
The embodiment provides a method for self-maintaining a human face base library, and fig. 2 is a flowchart of the method for self-maintaining the human face base library according to the embodiment of the present application, and as shown in fig. 2, the flowchart includes the following steps:
step S201, acquiring character warehousing data, performing repeated detection according to character information, and renaming an image of a character according to a result obtained by the detection;
optionally, person storage data is obtained, specifically, each person storage data includes 5 face images, which are a front face, a left face, a right side point, a head-up face, and a head-down face, and attribute categories of the persons are determined.
Preferably, in this embodiment, according to the information of the people put in the base, searching is performed in the base, and whether the situation of repeated information of the people exists is detected, wherein the information of the people includes a Chinese name and pinyin; and under the condition that the duplication of the figure information is detected, outputting the aligned human face and the figure information of the duplicated figure in the base library so that the user judges whether the two are the same person or not.
Further, under the condition that the person is judged to be a non-repetitive person, a new ID of the person is allocated, the image of the person is renamed, and specifically, the new ID and the image are input into a renaming module for renaming; under the condition that the person is judged to be the repeated person, the ID of the repeated person is assigned to the person, and the image of the person is renamed, specifically, the ID and the image are input into a renaming module for renaming;
step S202, carrying out face detection and face alignment on the renamed figure image, outputting the aligned face, manually confirming whether the aligned face is put in storage, and extracting the features of the aligned face and adding the features into a temporary library under the condition of confirming the storage;
preferably, after the renamed character image is obtained in step S201, the renamed image is input into a face detection algorithm, and if a plurality of faces are detected in one image, the largest face is selected for output; then, inputting the face output by the face detection algorithm into a face alignment algorithm, and outputting to obtain an aligned face;
further, manually confirming whether the aligned human faces are put in storage or not, and extracting the characteristics of the aligned human faces and adding the characteristics into a temporary library under the condition of confirming the storage; under the condition of confirming that the person is not put in storage, the unqualified face in the aligned faces can be deleted, other faces are put in storage continuously, or all the faces in the aligned faces are directly abandoned, new storage data of the person is obtained again, and a new round of information detection, face detection and face alignment are carried out;
step S203, combining the characteristics with the characteristics of the base library, performing identification test on the characteristics in the base library through the test set to obtain a test result, judging whether the test result reaches the standard through the test index, and entering the base library by the characteristics under the condition that the test result reaches the standard, wherein the base library takes effect.
Preferably, after combining the features of the aligned face obtained in step S202 with the existing features of the base library, performing an identification test on all the features in the base library through the test set to obtain a test result, and determining whether the test result meets the standard through the test index, where the features enter the base library and the base library takes effect when the test result meets the standard. Optionally, the test set subjected to face detection, face alignment and feature extraction is compared with features in the base library for identification, a final similarity is obtained through a person risk prevention and control layering system, person information corresponding to the first similarity is obtained, and the person features are added into the base library, so that the base library takes effect in real time.
Specifically, in this embodiment, the person risk prevention and control hierarchical system assigns different thresholds to different attributes according to the prevention and control requirements of the different attributes, so that the person attributes can be determined through the different thresholds. The calculation formula of the person risk prevention and control hierarchy is shown as the following formula 1:
wherein A is an nxd dimension base library characteristic; b is the characteristic of the test sample with dimension of d multiplied by m; n is the total sample size of the bottom library; m is the number of the human faces of the test sample; d is a characteristic dimension; the thrDiff is an n multiplied by m dimension exclusive threshold difference value, is a difference value between different threshold values and fixed threshold values which are distributed to different attributes by a person risk prevention and control layered system according to prevention and control requirements, and the n base samples have corresponding threshold difference values according to corresponding attribute categories; argmax indicates the maximum value index.
In some embodiments, before the characteristics in the bottom library are subjected to identification test through the test set, the person needing to be deleted can be determined through the person ID, and the person data in the bottom library is deleted through the bottom library deletion module; or determining the person needing to be modified through the person ID, and modifying the person information through the bottom library modification module, wherein the modified information comprises but is not limited to the name and the attribute of the person.
In some embodiments, after the base library takes effect, the person needing to be queried can be determined through the person ID, and the query is performed through the base library query module, and the corresponding person information is output.
Fig. 3 is a schematic view of a process of self-maintenance of a human face base according to an embodiment of the present application, and as shown in fig. 3, through the steps S201 to S203, the embodiment of the present application optimizes a human face base maintenance system composed of a base task module addition module, a testing module, and a base task module deletion and modification module in fig. 3, and integrates warehousing and testing, thereby realizing integration from character data collection, real-time warehousing and validation to a human face testing and recognition module, effectively simplifying a human face warehousing process, and saving labor cost. In addition, the embodiment of the application is not limited by stability and availability of companies, and can be effective when the character information is modified, so that the emergency is responded in real time, and the efficiency is improved. The problems of complex flow, high labor cost and poor real-time performance when the human face bottom library is modified and maintained are solved.
It should be noted that the steps illustrated in the above-described flow diagrams or in the flow diagrams 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 flow diagrams, in some cases, the steps illustrated or described may be performed in an order different than here.
The embodiment also provides a system for self-maintenance of a face base, which is used for implementing the above embodiments and preferred embodiments, and the description of the system that has been already made is omitted. As used hereinafter, the terms "module," "unit," "subunit," and the like may implement a combination of software and/or hardware for a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 4 is a block diagram of a system for self-maintenance of a human face base library according to an embodiment of the present application, and as shown in fig. 4, the system includes an acquisition module 41, a warehousing module 42, and a testing module 43:
the acquisition module 41 is used for acquiring character warehousing data, performing repeated detection according to character information, and renaming the image of the character according to the detection result; the warehousing module 42 is used for performing face detection and face alignment on the renamed figure image, outputting the aligned face, manually confirming whether the aligned face is warehoused, and extracting the features of the aligned face and adding the features into a temporary library under the condition of confirming the warehousing; the test module 43 is configured to combine the features with the features of the base library, perform an identification test on the features in the base library through the test set to obtain a test result, determine whether the test result meets the standard through the test index, and enter the base library and take effect when the determination meets the standard.
Through the system, in the embodiment of the application, the acquisition module 41 acquires character warehousing data and performs repeated detection and image renaming on the warehousing data, and the warehousing module 42 performs feature warehousing after performing face detection, alignment and manual confirmation on the renamed images; finally, the test module 43 tests the identification feature information, and adds the features up to the standard to the bottom library, so that the bottom library takes effect in real time. The whole system is platform-based and automatic, and integrates warehousing and testing, so that integration from character data collection, real-time warehousing and validation to the face test recognition module is realized, the face warehousing process is effectively simplified, and the labor cost is saved. In addition, the embodiment of the application is not limited by stability and availability of companies, and can be effective when the character information is modified, so that the emergency is responded in real time, and the efficiency is improved. The problems of complex flow, high labor cost and poor real-time performance when the human face bottom library is modified and maintained are solved.
It should be noted that, for specific examples in this embodiment, reference may be made to examples described in the foregoing embodiments and optional implementations, and details of this embodiment are not described herein again.
Note that each of the modules may be a functional module or a program module, and may be implemented by software or hardware. For a module implemented by hardware, the modules may be located in the same processor; or the modules can be respectively positioned in different processors in any combination.
The present embodiment also provides an electronic device comprising a memory having a computer program stored therein and a processor configured to execute the computer program to perform the steps of any of the above method embodiments.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
In addition, in combination with the method for self-maintenance of the face base in the foregoing embodiment, the embodiment of the present application may provide a storage medium to implement. The storage medium having stored thereon a computer program; the computer program, when executed by a processor, implements any one of the above-described embodiments of the method for self-maintenance of a human face base.
In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of face chassis self-maintenance. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
In one embodiment, fig. 5 is a schematic diagram of an internal structure of an electronic device according to an embodiment of the present application, and as shown in fig. 5, an electronic device is provided, where the electronic device may be a server, and the internal structure diagram may be as shown in fig. 5. The electronic device comprises a processor, a network interface, an internal memory and a non-volatile memory connected by an internal bus, wherein the non-volatile memory stores an operating system, a computer program and a database. The processor is used for providing calculation and control capability, the network interface is used for communicating with an external terminal through network connection, the internal memory is used for providing an environment for an operating system and the running of a computer program, the computer program is executed by the processor to realize a method for self-maintenance of the human face base, and the database is used for storing data.
Those skilled in the art will appreciate that the configuration shown in fig. 5 is a block diagram of only a portion of the configuration associated with the present application, and does not constitute a limitation on the electronic device to which the present application is applied, and a particular electronic device may include more or less components than those shown in the drawings, or may combine certain components, or have a different arrangement of components.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It should be understood by those skilled in the art that various features of the above-described embodiments can be combined in any combination, and for the sake of brevity, all possible combinations of features in the above-described embodiments are not described in detail, but rather, all combinations of features which are not inconsistent with each other should be construed as being within the scope of the present disclosure.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for self-maintenance of a face base, the method comprising:
acquiring character warehousing data, performing repeated detection according to the character information, and renaming the image of the character according to the result obtained by the detection;
carrying out face detection and face alignment on the renamed figure image, outputting to obtain an aligned face, manually confirming whether the aligned face is put in storage, and extracting the characteristics of the aligned face and adding the characteristics into a temporary storage under the condition of confirming the storage;
combining the characteristics with the characteristics of the base library, carrying out identification test on the characteristics in the base library through a test set to obtain a test result, judging whether the test result reaches the standard or not through a test index, and entering the base library by the characteristics under the condition of judging that the test result reaches the standard, wherein the base library takes effect.
2. The method of claim 1, wherein performing a repeatability test based on the information of the person comprises:
searching in the base according to the information of the figure stored in the base, and detecting whether the situation of figure information repetition exists or not, wherein the figure information comprises Chinese names and pinyin;
and outputting the aligned human face and the human information of the repeated human in the base library under the condition that the duplication of the human information is detected.
3. The method of claim 1, wherein renaming the image of the person based on the detection comprises:
under the condition that the person is judged to be a non-repetitive person, assigning a new ID of the person, and renaming the image of the person;
in a case where it is determined that the person is a duplicated person, an ID of the duplicated person is assigned to the person, and an image of the person is renamed.
4. The method of claim 1, wherein the step of manually confirming whether the aligned faces are put in storage further comprises:
and under the condition that the person is confirmed not to be put in storage, the unqualified face in the aligned faces can be deleted, other faces are continuously put in storage, or all the faces in the aligned faces are directly abandoned, and new storage data of the person is obtained again.
5. The method of any of claims 1-4, wherein prior to performing an identification test on features in an underlying library through a test set, the method comprises:
determining the person to be deleted through the person ID, and deleting the person data in the bottom library through a bottom library deleting module;
and determining the person needing to be modified through the person ID, and modifying the person information through the bottom library modification module.
6. The method of claim 1, wherein performing recognition testing on the features in the base library through the test set to obtain a test result comprises:
and comparing and identifying the test set subjected to face detection, face alignment and feature extraction with features in the base library, obtaining final similarity through a figure risk prevention and control layering system, and taking figure information corresponding to the first similarity.
7. The method of claim 1, wherein after the base library is validated, the method comprises:
and determining the person to be inquired through the person ID, inquiring through the bottom library inquiring module, and outputting to obtain corresponding person information.
8. A system for self-maintenance of a human face base, the system comprising:
the acquisition module is used for acquiring character warehousing data, performing repeated detection according to the character information and renaming the image of the character according to the detection result;
the storage module is used for carrying out face detection and face alignment on the renamed figure image, outputting the aligned face, manually confirming whether the aligned face is stored in a storage or not, and extracting the characteristics of the aligned face and adding the characteristics into a temporary storage under the condition of confirming the storage;
and the test module is used for combining the features and the features of the base library, carrying out recognition test on the features in the base library through the test set to obtain a test result, judging whether the test result reaches the standard through the test indexes, and entering the features into the base library to take effect under the condition of judging that the test result reaches the standard.
9. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and the processor is configured to execute the computer program to perform the method of self-maintenance of a human face chassis according to any one of claims 1 to 7.
10. A storage medium having stored thereon a computer program, wherein the computer program is arranged to perform the method of self-maintenance of a face chassis according to any one of claims 1 to 7 when executed.
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