CN114358710A - A face recognition sensorless attendance method, device and storage medium - Google Patents

Abstract

A face recognition sensorless attendance method, device and storage medium, the method comprises the steps of: acquiring a partition tree code of an office area; acquiring a face recognition database of the office area; acquiring an attendance partition set according to the partition tree code obtaining attendance source data of the office area; generating attendance credentials according to the attendance source data; generating attendance results according to the face recognition database and the attendance credentials. The present application provides a face recognition sensorless attendance method, device and storage medium, which does not have an attendance checkpoint, which can greatly speed up the time for attendance personnel to enter the office space and save time; attendance personnel do not need to queue for face capture, saving effort ; Save time attendance equipment and space, save money; Data access to the attendance system is reduced and safe; It can directly verify whether the attendance personnel are on duty and accurate.

Description

A face recognition sensorless attendance method, device and storage medium

technical field

The invention belongs to the technical field of employee attendance, and in particular relates to a face recognition sensorless attendance method, device and storage medium.

Background technique

In daily production and life, attendance actually needs to identify three things: identity, time and place. The existing attendance methods mainly include:

(1) For manual attendance, it is necessary to invest in attendance recording manpower, and those who participate in attendance go to the recording office to sign in;

(2) Location-based attendance, participants use their portable devices or actively send location information through a dedicated application program, or passively find and record them at the attendance site by the attendance machine;

(3) Feature-based attendance, personnel participating in attendance use their own unique characteristics, which can be their own characteristics that are different from other individuals, such as fingerprints, iris and face, or can be identification such as time cards, work cards, etc. ;

(4) Mixed attendance, a method of combining several attendance methods to submit composite information. For example, some attendance software requires uploading attendance location information and uploading self-portrait photos of attendance personnel at the workplace, which also has the characteristics of, And make the location information more credible; more commonly, it is supplemented by a human-supervised attendance system.

The above attendance methods have application scenarios in real life, and there is no absolute advanced or backward. For example, in a work group that often works outside, manual attendance is simple and convenient, and other attendance methods are thankless. In the attendance method of a specific office space (such as an office building), the advantage of feature-based attendance is obvious.

The existing attendance methods are often to allow the personnel involved in attendance to swipe their faces, swipe cards, and collect fingerprints one by one at a specific attendance location, which appears in almost every office space. In the feature-based attendance, the external identity identification ability is poor, and the phenomenon of surrogacy is repeated. Fingerprints have the same problem, while iris collection is expensive and difficult to collect.

Faces are easy to collect and feature rich. It is a compromise solution and has become the most mainstream attendance method. However, since the attendance period is fixed and the collection can only be carried out one by one, the existing feature-based attendance methods are time-consuming and labor-intensive: the attendance time is long, and the attendance queue is also long.

For this reason, in a scenario with many attendance personnel, it is often the method of arranging more feature collection equipment, which is expensive, but the attendance site cannot be expanded accordingly, and it is not economical, so the sudden change before the end of the attendance period The situation of traffic congestion caused by traffic still exists. What's even more unacceptable is that the frequent missed clock-in mistakes will increase the burden on employees before they start work. The use of human assistance can help improve these problems, but the exposure and modification of attendance data is tantamount to drinking poison to quench thirst. What's worse, the separation of the attendance site and the work site makes the attendance result not really representative of the attendance of the personnel involved in the attendance.

To sum up, the current attendance methods have the following problems:

(1) Time-consuming and long attendance time;

(2) It is laborious, queuing is hard, and the queuing is congested during emergency hours;

(3) It is not economical, whether it is to increase the attendance equipment or expand the attendance site, additional expenses are required;

(4) Torturing people, missing punch cards will result in wrong attendance, and heavy attendance tasks will add extra burden;

(5) The data is not safe, and the attendance data is exposed and can be modified;

(6) The attendance is inaccurate, and the attendance site is separated from the work site.

SUMMARY OF THE INVENTION

In view of the above problems, the present invention provides a face recognition sensorless attendance method, device and storage medium that overcome the above problems or at least partially solve the above problems.

In order to solve the above-mentioned technical problems, the present invention provides a non-sensing time attendance method for face recognition, the method includes the steps:

Get the partition tree code of the office area;

Obtain the face recognition database of the office area;

Obtain the attendance partition set according to the partition tree code;

Obtain the attendance source data of the office area;

generate attendance credentials according to the attendance source data;

An attendance result is generated according to the face recognition database and the attendance credential.

Preferably, the obtaining of the partition tree code of the office area includes the steps:

partitioning the office area and obtaining office partitions;

Obtain the number of workstations in each of the office partitions;

creating a partition tree of the office area;

Create a root node on the partition tree according to the number of the office areas;

Create branch nodes on the root node according to the number of office partitions;

Create a leaf node on the corresponding branch node according to the number of the workstations in each of the office partitions;

All the root nodes, the branch nodes and the leaf nodes are sequentially encoded to obtain the partition tree encoding.

Preferably, the acquiring the face recognition database of the office area includes the steps of:

Create an empty database;

Obtain all attendance personnel in the said office area;

Acquiring a face collection image of each of the attendance personnel;

performing facial feature extraction on each of the face collection images and obtaining facial feature recognition data;

establishing a mapping between the attendance personnel and the corresponding facial feature recognition data;

The mapping is stored in the database and the face recognition database is obtained.

Preferably, the obtaining the attendance partition set according to the partition tree code comprises the steps of:

Get the actual attendance personnel;

Obtain the office partition and workstation corresponding to each of the actual attendance personnel;

obtain the partition tree code;

Obtain all branch nodes and all corresponding leaf nodes in the partition tree encoding;

An attendance partition set of the actual attendance personnel is generated according to the office partition and the branch node, as well as the work station and the leaf node.

Preferably, the acquiring the attendance source data of the office area includes the steps of:

Set attendance data collection equipment in the office area according to the partition tree code;

Obtain attendance pictures in the corresponding office partition through the attendance data collection device;

Collect time processing for each of the attendance pictures;

Collect and partition each of the attendance pictures;

The attendance source data is generated according to the collection time processing and the collection partition processing.

Preferably, the generating an attendance credential according to the attendance source data includes the steps of:

Perform face detection and screening on the attendance source data to obtain a candidate face image;

Performing live detection and screening on the candidate face image to obtain a candidate face image;

generating a standard frontal face image according to the candidate face image;

obtaining the acquisition time and the acquisition zone corresponding to the standard frontal face image;

Carrying out acquisition time processing on each of the standard frontal face images;

Collecting and partitioning each of the standard frontal face images;

The attendance credential is generated according to the collection time processing and the collection partition processing.

Preferably, generating an attendance result according to the face recognition database and the attendance credential includes the steps of:

obtaining a standard frontal face image in the attendance credential;

performing facial feature extraction on the standard frontal face image and obtaining facial features;

comparing the facial features with the facial recognition database;

Obtain all remaining standard frontal face images that are successfully compared;

Obtain the attendance personnel, collection time and collection area corresponding to all the remaining standard frontal face images;

The attendance result is generated according to the attendance personnel, the collection time and the collection zone.

The application also provides a face recognition sensorless attendance device, the device includes:

The partition tree code acquisition module is used to obtain the partition tree code of the office area;

a face recognition database acquisition module for acquiring the face recognition database of the office area;

an attendance partition set acquisition module, used for acquiring the attendance partition set according to the partition tree code;

an attendance source data acquisition module, used to acquire the attendance source data of the office area;

an attendance credential generating module, used for generating an attendance credential according to the attendance source data;

An attendance result generating module, configured to generate an attendance result according to the face recognition database and the attendance credential.

The present application also provides an electronic device, the electronic device comprising:

at least one processor; and,

a memory communicatively coupled to the at least one processor; wherein,

The memory stores instructions executable by the at least one processor, the instructions are executed by the at least one processor, so that the at least one processor can perform any one of the aforementioned face recognition sensorless attendance method.

The present application also provides a non-transitory computer-readable storage medium, where the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause the computer to execute any of the aforementioned methods for non-sensing attendance by face recognition .

One or more technical solutions in the embodiments of the present invention have at least the following technical effects or advantages: a face recognition sensorless attendance method, device and storage medium provided by the present application do not set attendance checkpoints, which can greatly speed up attendance personnel The time to enter the office space is time-saving; the attendance personnel do not need to queue for face capture, which saves effort; the attendance equipment and the attendance space are saved, which saves money; the data access to the attendance system is reduced and safe; it can directly verify whether the attendance personnel are on duty or not. ,precise.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings used in the description of the embodiments. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without any creative effort.

1 is a schematic flowchart of a face recognition sensorless attendance method provided by an embodiment of the present invention;

2 is a schematic structural diagram of a face recognition sensorless attendance device provided by an embodiment of the present invention;

3 is a schematic structural diagram of an electronic device provided by the present invention;

FIG. 4 is a schematic structural diagram of a non-transitory computer-readable storage medium provided by the present invention.

Detailed ways

The present invention will be described in detail below with reference to specific embodiments and examples, and the advantages and various effects of the present invention will be more clearly presented therefrom. It should be understood by those skilled in the art that these specific embodiments and examples are used to illustrate the present invention, but not to limit the present invention.

Throughout the specification, unless specifically stated otherwise, terms used herein are to be understood as commonly used in the art. Therefore, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. In case of conflict, the present specification takes precedence.

Unless otherwise specified, various raw materials, reagents, instruments and equipment used in the present invention can be purchased from the market or can be prepared by existing methods.

As shown in FIG. 1, in the embodiment of the present application, the present invention provides a non-sensing time attendance method for face recognition, and the method includes the steps:

S1: Obtain the partition tree code of the office area;

In the embodiment of the present application, the obtaining of the partition tree code of the office area includes the steps:

partitioning the office area and obtaining office partitions;

Obtain the number of workstations in each of the office partitions;

creating a partition tree of the office area;

Create a root node on the partition tree according to the number of the office areas;

Create branch nodes on the root node according to the number of office partitions;

Create a leaf node on the corresponding branch node according to the number of the workstations in each of the office partitions;

All the root nodes, the branch nodes and the leaf nodes are sequentially encoded to obtain the partition tree encoding.

In the embodiment of the present application, the generation process of the partition tree code is described by way of example. Office area A is divided into 2 office areas, namely office area A1 and A2. The number of workstations in office area A1 and A2 is 1, which are represented by B1 and B2 respectively. At this time, the partition tree of the office area is created. The partition tree has 1 root node (denoted by A), this 1 root node has 2 branch nodes (denoted by A1 and A2 respectively), the A1 branch node has 1 leaf node (denoted by B1), and the A2 branch node has 1 leaf node (represented by B2), then encode all root nodes, branch nodes and leaf nodes in turn to obtain the partition tree encoding, that is, the partition tree encoding can be AA1B1 and AA2B2.

In this embodiment of the present application, after the partition tree is established, not only can attendance be performed on leaf nodes (branch nodes and leaf nodes), but all nodes (including the root node) on the partition tree can be used as attendance locations. In a general office, an employee can be required to be at the workstation, or an employee can be required to be in a certain office, or even to enter the entire site. In some scenarios, there may be no concept of workstations. In this case, employees only need to enter the workstation level (specific area), and do not necessarily need to fall on the workstations (such as branch nodes and leaf nodes).

S2: Obtain the face recognition database of the office area;

In the embodiment of the present application, the acquiring the face recognition database of the office area includes the steps:

Create an empty database;

Obtain all attendance personnel in the said office area;

Acquiring a face collection image of each of the attendance personnel;

performing facial feature extraction on each of the face collection images and obtaining facial feature recognition data;

establishing a mapping between the attendance personnel and the corresponding facial feature recognition data;

The mapping is stored in the database and the face recognition database is obtained.

In the embodiment of the present application, the face recognition database can be created through the following steps: collecting face collection images of all attendance personnel in the office area, and performing face feature extraction on each face collection image to obtain face feature recognition data, Then, the mapping between attendance personnel and the corresponding facial feature recognition data is established, and finally the mapping is stored in the database to obtain the facial recognition database.

S3: Obtain the attendance partition set according to the partition tree code;

In the embodiment of the present application, the obtaining the attendance partition set according to the partition tree code includes the steps:

Get the actual attendance personnel;

Obtain the office partition and workstation corresponding to each of the actual attendance personnel;

obtain the partition tree code;

Obtain all branch nodes and all corresponding leaf nodes in the partition tree encoding;

An attendance partition set of the actual attendance personnel is generated according to the office partition and the branch node, as well as the work station and the leaf node.

In the embodiment of the present application, when obtaining the attendance partition set according to the partition tree code, first obtain the actual attendance personnel (such as C) who need attendance, and the office partition of the actual attendance personnel C is A1, and the work position is B1, then The attendance partition set of the actual attendance staff C can be generated according to the partition tree codes AA1B1 and AA2B2. The attendance partition set is used to uniquely locate the office partition and workstation to which the actual attendance staff belongs. For example, the attendance partition set of the actual attendance staff C can represent is (A1, B1).

S4: Obtain the attendance source data of the office area;

In the embodiment of the present application, the acquiring the attendance source data of the office area includes the steps:

Set attendance data collection equipment in the office area according to the partition tree code;

Obtain attendance pictures in the corresponding office partition through the attendance data collection device;

Collect time processing for each of the attendance pictures;

Collect and partition each of the attendance pictures;

The attendance source data is generated according to the collection time processing and the collection partition processing.

In the embodiment of the present application, since there are two partition tree codes (AA1B1 and AA2B2), two attendance data collection devices can be prepared, which are respectively set in the office partitions A1 and A2, and obtain the corresponding data in the office partitions A1 and A2 respectively. The attendance picture (the pictures in the office partition can be taken regularly or irregularly), and the collection time processing (mark the shooting time) and the collection partition processing (mark the office partition number) for each attendance picture, so, each attendance picture Attendance pictures will have a shooting time and office partition number.

S5: generate attendance credentials according to the attendance source data;

In the embodiment of the present application, the generating of the attendance credential according to the attendance source data includes the steps:

Perform face detection and screening on the attendance source data to obtain a candidate face image;

Performing live detection and screening on the candidate face image to obtain a candidate face image;

generating a standard frontal face image according to the candidate face image;

obtaining the acquisition time and the acquisition zone corresponding to the standard frontal face image;

Carrying out acquisition time processing on each of the standard frontal face images;

Collecting and partitioning each of the standard frontal face images;

The attendance credential is generated according to the collection time processing and the collection partition processing.

In the embodiment of the present application, since the attendance picture may include other pictures (such as objects) in addition to the human face, it is necessary to perform face detection and screening on the attendance source data at this time, so as to filter out the faces containing the human face from all the attendance pictures. The picture is called the candidate face image; then the candidate face image is subjected to in vivo detection and screening to obtain candidate face images (such as detection of in vivo information, such as iris information, etc., to prevent the use of pictures taken in advance for attendance cheating, or false Use the face photo in the office area as the attendance picture), then generate the standard frontal face image according to the candidate face image (that is, generate the complete frontal face image from the incomplete face image), and then obtain the standard frontal face The collection time and collection division corresponding to the image (that is, the shooting time and office division number of the candidate face image corresponding to the standard frontal face image), and then the collection time processing (marking the shooting time) and collection of each attendance picture are performed. Partition processing (marked with the office partition number), so that attendance credentials can be generated.

S6: Generate an attendance result according to the face recognition database and the attendance credential.

In the embodiment of the present application, the generating an attendance result according to the face recognition database and the attendance credential includes the steps:

obtaining a standard frontal face image in the attendance credential;

performing facial feature extraction on the standard frontal face image and obtaining facial features;

comparing the facial features with the facial recognition database;

Obtain all remaining standard frontal face images that are successfully compared;

Obtain the attendance personnel, collection time and collection area corresponding to all the remaining standard frontal face images;

The attendance result is generated according to the attendance personnel, the collection time and the collection zone.

In the embodiment of the present application, the face features of the standard frontal face image are extracted to obtain the face features, and then the face features are compared with the face recognition database. When the comparison is successful, it is explained that the standard frontal face image has For the attendance personnel who have collected face images, that is, the staff in the office area, the attendance personnel (name of attendance personnel), collection time (shooting time) corresponding to the remaining standard frontal face images are obtained. ) and the collection partition (office partition number), and then the attendance result can be generated. For example, the attendance result of attendance staff C is: C (attendance staff name)—09:00 (shooting time)—A1 (office partition number).

As shown in FIG. 2, in the embodiment of the present application, the present application also provides a face recognition sensorless attendance device, the device includes:

A partition tree code acquisition module 10, for acquiring the partition tree code of the office area;

a face recognition database acquisition module 20 for acquiring the face recognition database of the office area;

an attendance partition set acquiring module 30, configured to acquire an attendance partition set according to the partition tree code;

an attendance source data acquisition module 40, configured to acquire the attendance source data of the office area;

An attendance credential generating module 50, configured to generate an attendance credential according to the attendance source data;

The attendance result generating module 60 is configured to generate an attendance result according to the face recognition database and the attendance credential.

A face recognition sensorless attendance device provided by the present application can execute the face recognition sensorless attendance method provided by the above steps.

Referring next to FIG. 3 , it shows a schematic structural diagram of an electronic device 100 suitable for implementing an embodiment of the present disclosure. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablets), PMPs (portable multimedia players), vehicle-mounted terminals (eg, mobile terminals such as in-vehicle navigation terminals), etc., and stationary terminals such as digital TVs, desktop computers, and the like. The electronic device shown in FIG. 3 is only an example, and should not impose any limitation on the function and scope of use of the embodiments of the present disclosure.

As shown in FIG. 3 , the electronic device 100 may include a processing device (eg, a central processing unit, a graphics processor, etc.) 101 that may be loaded into random access according to a program stored in a read only memory (ROM) 102 or from a storage device 108 Various appropriate actions and processes are executed by the programs in the memory (RAM) 103 . In the RAM 103, various programs and data necessary for the operation of the electronic device 100 are also stored. The processing device 101 , the ROM 102 , and the RAM 103 are connected to each other through a bus 104 . An input/output (I/O) interface 105 is also connected to the bus 104 .

Typically, the following devices can be connected to the I/O interface 105: input devices 106 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; including, for example, a liquid crystal display (LCD), speakers, An output device 107 of a vibrator or the like; a storage device 108 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 109 . Communication means 109 may allow electronic device 100 to communicate wirelessly or by wire with other devices to exchange data. While the figures show electronic device 100 having various means, it should be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.

In particular, according to embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the method illustrated in the flowchart. In such an embodiment, the computer program may be downloaded and installed from the network via the communication device 109 , or from the storage device 108 , or from the ROM 102 . When the computer program is executed by the processing apparatus 101, the above-mentioned functions defined in the methods of the embodiments of the present disclosure are executed.

4, which shows a schematic structural diagram of a computer-readable storage medium suitable for implementing the embodiments of the present disclosure, where the computer-readable storage medium stores a computer program, and the computer program can be executed by a processor. Implement the sensorless attendance method for face recognition as described in any one of the above.

It should be noted that the computer-readable medium mentioned above in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or a combination of any of the above. More specific examples of computer readable storage media may include, but are not limited to, electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable Programmable read only memory (EPROM or flash memory), fiber optics, portable compact disk read only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. In this disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present disclosure, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave with computer-readable program code embodied thereon. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device . Program code embodied on a computer readable medium may be transmitted using any suitable medium including, but not limited to, electrical wire, optical fiber cable, RF (radio frequency), etc., or any suitable combination of the foregoing.

The above-mentioned computer-readable medium may be included in the above-mentioned electronic device; or may exist alone without being assembled into the electronic device.

The above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by the electronic device, the electronic device: acquires at least two Internet Protocol addresses; A node evaluation request for an Internet Protocol address, wherein the node evaluation device selects an Internet Protocol address from the at least two Internet Protocol addresses and returns it; receives the Internet Protocol address returned by the node evaluation device; wherein the obtained The Internet Protocol address indicates an edge node in the content distribution network.

Alternatively, the above computer-readable medium carries one or more programs, and when the above one or more programs are executed by the electronic device, the electronic device: receives a node evaluation request including at least two Internet Protocol addresses; From the at least two Internet Protocol addresses, the Internet Protocol address is selected; the selected Internet Protocol address is returned; wherein, the received Internet Protocol address indicates an edge node in the content distribution network.

Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including object-oriented programming languages—such as Java, Smalltalk, C++, but also conventional Procedural programming language - such as the "C" language or similar programming language. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (eg, using an Internet service provider through Internet connection).

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code that contains one or more logical functions for implementing the specified functions executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It is also noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented in dedicated hardware-based systems that perform the specified functions or operations , or can be implemented in a combination of dedicated hardware and computer instructions.

The units involved in the embodiments of the present disclosure may be implemented in a software manner, and may also be implemented in a hardware manner. Wherein, the name of the unit does not constitute a limitation of the unit itself under certain circumstances, for example, the first obtaining unit may also be described as "a unit that obtains at least two Internet Protocol addresses".

The present application provides a face recognition non-inductive attendance method, device and storage medium, which does not have an attendance checkpoint, which can greatly speed up the time for attendance personnel to enter the office space and save time; attendance personnel do not need to queue for face capture, saving effort ; Save time attendance equipment and space, and save money; Data access to the attendance system is reduced and safe; It can directly verify whether the attendance personnel are on duty, which is accurate.

It should be understood that the above-mentioned specific embodiments of the present invention are only used to illustrate or explain the principle of the present invention, but not to limit the present invention. Therefore, any modifications, equivalent replacements, improvements, etc. made without departing from the spirit and scope of the present invention should be included within the protection scope of the present invention. Furthermore, the appended claims of this invention are intended to cover all changes and modifications that fall within the scope and boundaries of the appended claims, or the equivalents of such scope and boundaries.

Claims (10)

1. a face recognition non-sensing attendance method, is characterized in that, described method comprises the steps: Get the partition tree code of the office area; Obtain the face recognition database of the office area; Obtain the attendance partition set according to the partition tree code; Obtain the attendance source data of the office area; generate attendance credentials according to the attendance source data; An attendance result is generated according to the face recognition database and the attendance credential. 2. face recognition non-sensing time attendance method according to claim 1, is characterized in that, described obtaining the partition tree coding of office area comprises the steps: partitioning the office area and obtaining office partitions; Obtain the number of workstations in each of the office partitions; creating a partition tree of the office area; Create a root node on the partition tree according to the number of the office areas; Create branch nodes on the root node according to the number of office partitions; Create a leaf node on the corresponding branch node according to the number of the workstations in each of the office partitions; All the root nodes, the branch nodes and the leaf nodes are sequentially encoded to obtain the partition tree encoding. 3. The face recognition non-sensing attendance method according to claim 1, wherein the acquisition of the face recognition database of the office area comprises the steps: Create an empty database; Obtain all attendance personnel in the said office area; Acquiring a face collection image of each of the attendance personnel; performing facial feature extraction on each of the face collection images and obtaining facial feature recognition data; establishing a mapping between the attendance personnel and the corresponding facial feature recognition data; The mapping is stored in the database and the face recognition database is obtained. 4. face recognition non-sensing attendance method according to claim 1, is characterized in that, described obtaining attendance partition set according to described partition tree coding comprises the steps: Get the actual attendance personnel; Obtain the office partition and workstation corresponding to each of the actual attendance personnel; obtain the partition tree code; Obtain all branch nodes and all corresponding leaf nodes in the partition tree encoding; An attendance partition set of the actual attendance personnel is generated according to the office partition and the branch node, as well as the work station and the leaf node. 5. The sensorless attendance method for face recognition according to claim 1, wherein the acquiring the attendance source data of the office area comprises the steps of: Set attendance data collection equipment in the office area according to the partition tree code; Obtain attendance pictures in the corresponding office partition through the attendance data collection device; Collect time processing for each of the attendance pictures; Collect and partition each of the attendance pictures; The attendance source data is generated according to the collection time processing and the collection partition processing. 6. The face recognition non-inductive attendance method according to claim 1, wherein the generation of attendance credentials according to the attendance source data comprises the steps of: Perform face detection and screening on the attendance source data to obtain a candidate face image; Performing live detection and screening on the candidate face image to obtain a candidate face image; generating a standard frontal face image according to the candidate face image; obtaining the acquisition time and the acquisition zone corresponding to the standard frontal face image; Carrying out acquisition time processing on each of the standard frontal face images; Collecting and partitioning each of the standard frontal face images; The attendance credential is generated according to the collection time processing and the collection partition processing. 7. The face recognition non-sensing attendance method according to claim 1, wherein the generating an attendance result according to the face recognition database and the attendance credential comprises the steps: obtaining a standard frontal face image in the attendance credential; performing facial feature extraction on the standard frontal face image and obtaining facial features; comparing the facial features with the facial recognition database; Obtain all remaining standard frontal face images that are successfully compared; Obtain the attendance personnel, collection time and collection area corresponding to all the remaining standard frontal face images; The attendance result is generated according to the attendance personnel, the collection time and the collection zone. 8. A sensorless time attendance device for face recognition, characterized in that the device comprises: The partition tree code acquisition module is used to obtain the partition tree code of the office area; a face recognition database acquisition module for acquiring the face recognition database of the office area; an attendance partition set acquisition module, used for acquiring the attendance partition set according to the partition tree code; an attendance source data acquisition module, used to acquire the attendance source data of the office area; an attendance credential generating module, used for generating an attendance credential according to the attendance source data; An attendance result generating module, configured to generate an attendance result according to the face recognition database and the attendance credential. 9. An electronic device, characterized in that the electronic device comprises: at least one processor; and, a memory communicatively coupled to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor, to enable the at least one processor to execute the person described in any of the preceding claims 1-7. Face recognition sensorless attendance method. 10. A non-transitory computer-readable storage medium, the non-transitory computer-readable storage medium storing computer instructions, the computer instructions being used to make the computer perform the face recognition insensitivity of any one of the preceding claims 1-7. Attendance method.

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