Off-line task processing method and device, electronic equipment and storage medium

Abstract

The invention discloses an offline task processing method and device, electronic equipment and a storage medium, and relates to the field of new science and technology and the technical field of data processing, and the method comprises the steps: obtaining a face image and task information; based on the face image and the first information, executing a target operation associated with the task information; the first information is used for indicating that at least one of the first link and the second link is in an interrupted state, the first link is used for transmitting face-related data, and the second link is used for transmitting task-related data. According to the embodiment of the invention, different target operations are executed to process the task information according to different connection states of the first link and the second link, so that when at least one of the first link and the second link is in an interrupted state, the situation that the first link and the second link do not depend on network, server running states and the like any more is realized; and the task content indicated by the task information can still be processed, so that normal execution of the task is ensured without depending on a network environment, and the user experience is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to new technology fields and data processing technology fields, and in particular to a method, device, electronic device, and storage medium for processing offline tasks. Background Art

[0002] As people's lives become increasingly intelligent, facial recognition-based tasks, such as paying for food, dining at the cafeteria, and clocking in, are highly dependent on the network environment and place high demands on network stability. A network unavailability can prevent tasks from being completed, leading to queue congestion and other issues, impacting the user experience.

[0003] Therefore, how to ensure the normal execution of tasks without relying on the network environment is an urgent problem to be solved. Summary of the Invention

[0004] The present application provides a method, device, electronic device and storage medium for processing offline tasks, which can ensure the normal execution of offline tasks in offline mode without relying on the network environment, thereby improving user experience.

[0005] In a first aspect, an embodiment of the present application provides a method for processing an offline task, the method comprising:

[0006] Obtain facial images and task information;

[0007] executing a target operation associated with the task information based on the facial image and the first information;

[0008] The first information is used to indicate that at least one of the first link and the second link is in an interrupted state, the first link is used to transmit face-related data, and the second link is used to transmit task-related data.

[0009] In a second aspect, an embodiment of the present application further provides an offline task processing device, the device comprising:

[0010] Acquisition module, used to obtain face images and task information;

[0011] an execution module, configured to execute a target operation associated with the task information based on the facial image and the first information;

[0012] The first information is used to indicate that at least one of the first link and the second link is in an interrupted state, the first link is used to transmit face-related data, and the second link is used to transmit task-related data.

[0013] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0014] one or more processors;

[0015] a memory for storing one or more programs,

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the offline task processing method described in any embodiment of the present application.

[0017] In a fourth aspect, an embodiment of the present application provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for processing offline tasks described in any embodiment of the present application is implemented.

[0018] The embodiments of the present application propose a method, device, electronic device, and storage medium for processing offline tasks, including obtaining a facial image and task information; executing a target operation associated with the task information based on the facial image and first information; wherein the first information is used to indicate that at least one of the first link and the second link is in an interrupted state, the first link is used to transmit facial-related data, and the second link is used to transmit task-related data. In other words, in the technical solution of the present application, different target operations are executed to process the task information according to the different connection states of the first link and the second link, so that when at least one of the first link and the second link is in an interrupted state, it is no longer dependent on the network, the server operating status, etc., and the task content indicated by the task information can still be processed, thereby ensuring normal execution of the task without relying on the network environment and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a flowchart of a method for processing an offline task provided in one embodiment of the present application;

[0020] Figure 2 A logical diagram of payment based on face recognition at a dining machine provided in one embodiment of the present application;

[0021] Figure 3 This is a second flow chart of a method for processing offline tasks provided in one embodiment of the present application;

[0022] Figure 4 A schematic diagram of the structure of an offline task processing device provided in one embodiment of the present application;

[0023] Figure 5 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] In order to facilitate a clearer understanding of the various embodiments of the present application, some relevant knowledge is first introduced as follows.

[0027] As office parks become increasingly intelligent, facial recognition-based task scenarios, such as facial recognition dining machines, facial recognition clock-in machines, and facial recognition payment machines, have high requirements for system stability. Any slight instability in the system will cause queue congestion and affect the user experience.

[0028] Due to the network status and occasional downtime of face edge services and task processing services (such as payment services, clock-in services, access control services, etc.), local terminal devices become unavailable, resulting in payment failures, clock-in failures, inability to open doors, and other problems.

[0029] Taking the facial recognition payment method used at a restaurant kiosk as an example, this solution enables offline payment even when the network is down, ensuring smooth operation of the smart dining experience. Both facial recognition and payment can be performed locally on the device, independent of the network. Consumption data is recorded locally and then uploaded in batches once the network is restored.

[0030] Taking the facial recognition clock-in scenario as an example, this solution provides offline clock-in services even when the network is unavailable. Both facial recognition and clock-in are performed locally on the client, independent of the network. Clock-in records are stored locally and can be uploaded in batches once the network is restored.

[0031] For example, this solution provides offline facial recognition access control, even when the network is disconnected. Both facial recognition and access control records are processed locally on the terminal, independent of the network. Access control records are stored locally and can be uploaded in batches once the network is restored.

[0032] The above scenarios are merely examples of applicable scenarios of offline tasks and do not limit the scope of protection of the present invention.

[0033] The following uses the facial recognition restaurant machine to deduct payment by face recognition as an example to further explain:

[0034] In related technologies, online face-scanning payment scenarios cannot solve the dining needs when the server is down or the network is unavailable. Once the above situation occurs, there will be congestion in the dining queue, low dining efficiency, and even staff will have to record data by hand and collect the bill later.

[0035] In response to scenarios such as network disconnection that occur in online dining payment scenarios and the rigid demand for high availability of canteen consumption, the present invention proposes to realize automatic face recognition and payment in offline mode; it realizes that it is no longer dependent on the network and can achieve the same dining experience in offline mode as in online mode.

[0036] In response to the above-mentioned problems, the embodiments of the present application propose a method, device, electronic device and storage medium for processing offline tasks, which are independent of the network, server operating status, etc., and can still process the task content indicated by the task information, thereby ensuring normal execution of the task without relying on the network environment, thereby improving the user experience.

[0037] Figure 1 This is one of the flow charts of the offline task processing method provided by an embodiment of the present application. The method can be executed by an offline task processing device or electronic device. The device or electronic device can be implemented by software and / or hardware. The device or electronic device can be integrated into any smart device with network communication function. Figure 1 As shown, the offline task processing method may include the following steps:

[0038] S110: Obtaining facial images and task information.

[0039] In the embodiment of the present application, the processing device of the offline task can be a face-scanning dining machine, a face-scanning clock-in machine, a face-scanning payment machine, a face-scanning access control machine, etc. When the user approaches the processing device of the offline task, the device automatically captures the user's facial image.

[0040] In practical applications, task information can be pre-set or user-entered into the processing device. For example, for a facial recognition dining kiosk, the task information could be the user-entered deduction amount. For another example, for a facial recognition access control system, the task information could be a pre-set door unlocking task. For another example, for a facial recognition clock-in machine, the task information could be a pre-set clock-in recording task.

[0041] S120. Based on the facial image and the first information, perform a target operation associated with the task information; wherein the first information is used to indicate that at least one of the first link and the second link is in an interrupted state, the first link is used to transmit face-related data, and the second link is used to transmit task-related data.

[0042] Take the face-scanning dining machine as an example. Figure 2 This is a logical diagram of payment based on face recognition dining machine provided in one embodiment of this application. Figure 2 As shown, the face recognition module of the face-scanning dining machine is used to capture the user's face and transmit the captured face to the face edge server (also known as the face recognition server) via link A (i.e., the first link). The face edge server performs face comparison and sends it to the face-scanning dining machine. Then, the payment module requests payment from the payment settlement server (also known as the task execution server) via link B (i.e., the second link), and the user's account is deducted.

[0043] In the above embodiment, if the first link and / or the second link is in an interrupted state, the user is unable to deduct money from his account.

[0044] Therefore, in the embodiment of the present application, different target operations are performed on the task information according to the connection status of at least one of the first link and the second link, and the task content indicated by the task information can be successfully executed without relying on the network.

[0045] An embodiment of the present application proposes a method for processing offline tasks, which performs different target operations to process task information according to the different connection states of the first link and the second link. This achieves that when at least one of the first link and the second link is in an interrupted state, it no longer depends on the network, the server operating status, etc., and the task content indicated by the task information can still be processed. This ensures that the task is executed normally without relying on the network environment, thereby improving the user experience.

[0046] Optionally, in the embodiment of the present application, executing the target operation associated with the task information based on the facial image and the first information can be achieved by any of the following methods:

[0047] Method 1 specifically includes the following steps:

[0048] Step 1): When the first information indicates that the first link and the second link are in an interrupted state, the face image is recognized based on the face database to determine the user information corresponding to the face image.

[0049] In the embodiment of the present application, the processing device of the offline task has a face recognition model deployed locally. It should be noted that the face recognition model deployed in the processing device of the offline task must be consistent with the face recognition model deployed in the face recognition server.

[0050] If both the first link and the second link are recorded as disconnected for N consecutive times, it is determined that both the first link and the second link are in an interrupted state, where N is an integer greater than or equal to 1.

[0051] When both the first link and the second link are in an interrupted state, it means that the face image cannot be recognized by the face recognition server, and the task information cannot be processed by the task execution server.

[0052] In the above case, the offline task processing device needs to call the locally deployed face recognition model to recognize the face image, so as to determine the user information corresponding to the face image.

[0053] For example, the face-scanning dining machine takes a snapshot of an approaching user, obtains the user's facial image and identifies it, and determines that the user information corresponding to the facial image includes at least one of the following: 1. Name: User A; 2. Account balance: 100 yuan.

[0054] Step 2) Execute the task content indicated by the task information to obtain task execution information; the task execution information includes the execution result of the task content and the association between the task content and user information.

[0055] The offline task processing device executes the task content indicated by the task information. For example, using a facial recognition dining kiosk as an example, if the task content is: Debit 20 yuan, the offline task processing device will locally debit 20 yuan from User A's account. The task content of 20 yuan is associated with User A's user information.

[0056] That is, only when it is determined that user A is associated with the task information, the corresponding operation is performed on the task content indicated by the task information.

[0057] Step 3) When the second link is disconnected and reconnected, a first indication message is sent to the task execution server via the second link; the first indication message carries the task execution information, and the first indication message is used to instruct the task execution server to execute the task content based on the task execution information.

[0058] In the embodiment of the present application, after the second link resumes communication with the network, the task execution information needs to be uploaded to the task execution server for actual payment deduction.

[0059] In actual applications, if the deduction fails due to insufficient user balance, the user can be forced to complete the previous unsettled deduction by disabling the next consumption or recovering the money through management means.

[0060] The following is a further explanation of the above method 1 with reference to a specific embodiment, taking a face-scanning dining machine as an example:

[0061] If both the first and second links are disconnected three times in a row, facial recognition is performed using the local recognition API. The corresponding relationship between the consumption amount and the person is recorded. Once the second link is restored, the corresponding relationship between the consumption amount and the person is uploaded to the task execution server one by one, which then performs the actual payment deduction.

[0062] Method 2 specifically includes the following steps:

[0063] Step 1): When the first information indicates that the second link is in an interrupted state, the facial image is sent to the face recognition server via the first link; the face recognition server is used to recognize the facial image based on the face database.

[0064] If the second link is recorded as being disconnected N times in a row, it is determined that the second link is in an interrupted state, where N is an integer greater than or equal to 1.

[0065] When the second link is in an interrupted state, it means that the face image can be recognized by the face recognition server, but the task information cannot be processed by the task execution server.

[0066] In the above case, the offline task processing device needs to send the facial image to the face recognition server through the first link.

[0067] Step 2) Receive user information corresponding to the face image sent by the face recognition server;

[0068] In an embodiment of the present application, user information may be stored in an encrypted manner, for example, by encrypting the user information using the Advanced Encryption Standard (AES).

[0069] Step 3) executing the task content indicated by the task information to obtain task execution information; the task execution information includes the execution result of the task content and the association between the task content and the user information;

[0070] Step 4) When the second link is disconnected and reconnected, a first indication message is sent to the task execution server via the second link; the first indication message carries the task execution information, and the first indication message is used to instruct the task execution server to execute the task content based on the task execution information.

[0071] It should be noted that the task execution information carried in the first instruction information may be encrypted data. After receiving the task execution information, the task execution server needs to decrypt it before executing the task content.

[0072] The specific implementation process of the above steps 3) to 4) is similar to the implementation process of steps 2) to 3) in method 1. To avoid repetition, they will not be repeated here.

[0073] The following is a further explanation of the above method 2 using a face-scanning dining machine as an example in conjunction with a specific embodiment:

[0074] If the second link records three consecutive disconnections, the backend facial recognition server is called to identify the facial image and obtain the recognition result. The corresponding relationship between the consumption amount and the person is then recorded locally and encrypted, for example, using AES encryption. After the network is restored, the encrypted data is uploaded. The task execution server decrypts the data according to the agreed encryption algorithm and then processes the transaction, resulting in the actual payment deduction on the task execution server.

[0075] Method 3 specifically includes the following steps:

[0076] Step 1): When the first information indicates that the first link is in an interrupted state, the facial image is recognized based on the facial database to determine user information corresponding to the facial image.

[0077] In an embodiment of the present application, if the first link is recorded as being disconnected N times in a row, it is determined that the first link is in an interrupted state, where N is an integer greater than or equal to 1.

[0078] When the first link is in an interrupted state, it means that the face image cannot be recognized by the face recognition server, but the task information can be processed by the task execution server.

[0079] In this case, the offline task processing device needs to call the locally deployed face recognition model to recognize the face image, thereby determining the user information corresponding to the face image. The specific implementation process is similar to step 1) in method 1, and will not be repeated here to avoid repetition.

[0080] Step 2) Send a second indication message to the task execution server through the second link; wherein the second indication message carries user information and task information, and the second indication message is used to instruct the task execution server to execute the task content indicated by the task information based on the user information and task information.

[0081] In the embodiment of the present application, after obtaining the user information, the user information needs to be sent to the task execution server via the second link. The task server executes the task content indicated by the task information.

[0082] The following is a further explanation of the above method 3 with reference to a specific embodiment, taking a face-scanning dining machine as an example:

[0083] If the first link records three consecutive failures, facial recognition is performed through the local recognition API. Then, the payment interface is called to transmit the recognition result and payment amount to the task server through the second link for deduction.

[0084] Combining the above methods 1 to 3 can ensure that offline tasks can be executed normally without any impact on users even if the face recognition service is unavailable, the task execution service is unavailable, or the network is unavailable.

[0085] Optionally, when the first link and the second link are disconnected and reconnected, executing the target operation associated with the task information can also be achieved by the following steps:

[0086] Step 1) sending the facial image to the face recognition server via the first link;

[0087] Step 2) Receive user information corresponding to the face image sent by the face recognition server;

[0088] Step 3) Send a second indication message to the task execution server through the second link; wherein the second indication message carries user information and task information, and the second indication message is used to instruct the task execution server to execute the task content indicated by the task information based on the user information and task information.

[0089] In an embodiment of the present application, if the first link and the second link are disconnected and reconnected to restore communication, the face image is recognized by the face recognition server, and the task information is processed by the task execution server.

[0090] Optionally, this application provides a method for processing offline tasks, which also requires preserving the face database and regularly updating the local and server face databases to ensure the accuracy of face recognition. This can be achieved through the following steps:

[0091] Step 1) Obtain incremental face images;

[0092] Step 2) extracting features from the incremental face image to obtain feature values ​​corresponding to the incremental face image; the feature values ​​are used to identify the face image;

[0093] Step 3) Save the feature value to the face database.

[0094] In actual applications, the offline task processing device pulls incremental face images after it is turned on for the first time every day to keep the face database fresh.

[0095] It should be noted that due to the sensitivity of facial images, the offline processing device only stores the extracted feature values, not the original facial images. The feature values ​​are encrypted before storage to ensure data security. Furthermore, local data is deleted before the device is sent for repair, ensuring that no sensitive data is stored externally on the device.

[0096] Figure 3 The second flow chart of the method for processing offline tasks provided in one embodiment of the present application is as follows: Figure 3 As shown, Figure 3 The present invention shows a method for processing an offline task, taking the face-scanning payment scenario at a dining machine as an example, which specifically includes the following steps.

[0097] 1. Start.

[0098] 2. Face capture at the terminal (face recognition dining machine).

[0099] 3. Cloud recognition: That is, the client calls the face recognition server to perform face recognition.

[0100] 4. Determine whether facial recognition is successful. If so, the client calls the task execution server to make a cloud payment. If not, the client performs local recognition and, after obtaining the facial recognition result, calls the task execution server to make a cloud payment.

[0101] 5. Determine if the payment was successful. If so, the process ends; otherwise, the client saves the payment locally. Once the network is restored, the payment is uploaded to the task execution server via the batch payment interface, allowing the task execution server to perform the actual deduction.

[0102] 6. End.

[0103] Figure 4 This is a schematic diagram of the structure of an offline task processing device provided by an embodiment of the present application. Figure 4 As shown, the offline task processing device includes:

[0104] Acquisition module 401, used to acquire face images and task information;

[0105] An execution module 402 is configured to execute a target operation associated with the task information based on the facial image and the first information;

[0106] The first information is used to indicate that at least one of the first link and the second link is in an interrupted state, the first link is used to transmit face-related data, and the second link is used to transmit task-related data.

[0107] The embodiment of the present application proposes a device for processing offline tasks, which obtains a facial image and task information; based on the facial image and the first information, executes a target operation associated with the task information; wherein the first information is used to indicate that at least one of the first link and the second link is in an interrupted state, the first link is used to transmit face-related data, and the second link is used to transmit task-related data. In other words, in the technical solution of the present application, the device for processing offline tasks executes different target operations to process the task information according to the different connection states of the first link and the second link, thereby achieving the situation that when at least one of the first link and the second link is in an interrupted state, it no longer depends on the network, the server operation status, etc., and can still process the task content indicated by the task information, thereby achieving the goal of ensuring the normal execution of the task without relying on the network environment, thereby improving the user experience.

[0108] Optionally, the execution module 402 is further configured to:

[0109] When the first information indicates that the first link and the second link are in an interrupted state, identifying the facial image based on a facial database to determine user information corresponding to the facial image;

[0110] Executing the task content indicated by the task information to obtain task execution information; the task execution information includes the execution result of the task content and the association between the task content and the user information;

[0111] When the second link is disconnected and reconnected, a first indication message is sent to the task execution server via the second link; the first indication message carries the task execution information, and the first indication message is used to instruct the task execution server to execute the task content based on the task execution information.

[0112] Optionally, the execution module 402 is further configured to:

[0113] When the first information indicates that the second link is in an interrupted state, sending the facial image to a face recognition server via the first link; the face recognition server is configured to recognize the facial image based on a face database;

[0114] Receiving user information corresponding to the face image sent by the face recognition server;

[0115] Executing the task content indicated by the task information to obtain task execution information; the task execution information includes the execution result of the task content and the association between the task content and the user information;

[0116] When the second link is disconnected and reconnected, a first indication message is sent to the task execution server via the second link; the first indication message carries the task execution information, and the first indication message is used to instruct the task execution server to execute the task content based on the task execution information.

[0117] Optionally, the execution module 402 is further configured to:

[0118] When the first information indicates that the first link is in an interrupted state, identifying the facial image based on a facial database to determine user information corresponding to the facial image;

[0119] A second indication message is sent to the task execution server through the second link; wherein the second indication message carries the user information and the task information, and the second indication message is used to instruct the task execution server to execute the task content indicated by the task information based on the user information and the task information.

[0120] Optionally, the device further comprises:

[0121] a first sending module, configured to send the facial image to a face recognition server via the first link when the first link and the second link are disconnected and reconnected;

[0122] A receiving module, configured to receive user information corresponding to the face image sent by the face recognition server;

[0123] The second sending module is used to send a second indication message to the task execution server through the second link; wherein, the second indication message carries the user information and the task information, and the second indication message is used to instruct the task execution server to execute the task content indicated by the task information based on the user information and the task information.

[0124] Optionally, the device further comprises:

[0125] An incremental face image acquisition module, used for acquiring incremental face images;

[0126] a feature extraction module, configured to extract features from the incremental facial image to obtain feature values ​​corresponding to the incremental facial image; the feature values ​​are used to identify the facial image;

[0127] A saving module is used to save the feature value to the face database.

[0128] The above-mentioned offline task processing device can execute the method provided by any embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not fully described in this embodiment, please refer to the offline task processing method provided by any embodiment of the present application.

[0129] Figure 5 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application. Figure 5 A block diagram of an exemplary electronic device suitable for implementing the embodiments of the present application is shown. Figure 5 The electronic device 12 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0130] like Figure 5 As shown, electronic device 12 is implemented as a general-purpose computing device. Components of electronic device 12 may include, but are not limited to, one or more processors or processing units 16, system memory 28, and a bus 18 that connects various system components (including system memory 28 and processing unit 16).

[0131] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures. Examples of these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0132] The electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0133] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be configured to read and write non-removable, non-volatile magnetic media ( Figure 5 Not shown, often called a "hard drive"). Although Figure 5Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the various embodiments of the present application.

[0134] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may include an implementation of a network environment. Program modules 42 generally implement the functions and / or methods of the embodiments described herein.

[0135] The electronic device 12 may also communicate with one or more external devices 14 (e.g., a keyboard, a pointing device, a display 24, etc.), one or more devices that enable a user to interact with the electronic device 12, and / or any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). Such communication may be performed through an input / output (I / O) interface 22. Furthermore, the electronic device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 20. As shown, the network adapter 20 communicates with the other modules of the electronic device 12 via the bus 18. It should be understood that although Figure 5 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 12, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0136] The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, such as implementing the offline task processing method provided in the embodiment of the present application.

[0137] An embodiment of the present application also provides a computer storage medium.

[0138] The computer-readable storage medium of the embodiment of the present application can adopt any combination of one or more computer-readable media.Computer-readable media can be computer-readable signal media or computer-readable storage media.Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or components, or any combination thereof.More specific examples (non-exhaustive list) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROMs), optical storage devices, magnetic storage devices, or any suitable combination thereof.In this document, computer-readable storage media can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0139] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0140] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0141] The computer program code for performing the operations of the present application can be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0142] The embodiment of the present application also provides a computer program product.

[0143] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer program products, which can include one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0144] Note that the above are only preferred embodiments of the present application and the technical principles employed. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, readjustments, and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments and may include many other equivalent embodiments without departing from the scope of the present application. The scope of the present application is determined by the scope of the appended claims.

Claims

1. A method for processing an offline task, characterized in that: The method comprises: Obtain facial images and task information; Based on the facial image and the first information, executing a target operation associated with the task information; The first information is used to indicate that at least one of the first link and the second link is in an interrupted state, the first link is used to transmit face-related data, and the second link is used to transmit task-related data.

2. The offline task processing method according to claim 1, characterized in that: The performing of a target operation associated with the task information based on the facial image and the first information includes: When the first information indicates that the first link and the second link are in an interrupted state, identifying the facial image based on a facial database to determine user information corresponding to the facial image; Executing the task content indicated by the task information to obtain task execution information; the task execution information includes the execution result of the task content and the association between the task content and the user information; When the second link is disconnected and reconnected, a first indication message is sent to the task execution server via the second link; the first indication message carries the task execution information, and the first indication message is used to instruct the task execution server to execute the task content based on the task execution information.

3. The offline task processing method according to claim 1, characterized in that: The performing of a target operation associated with the task information based on the facial image and the first information includes: When the first information indicates that the second link is in an interrupted state, sending the facial image to a face recognition server via the first link; the face recognition server is configured to recognize the facial image based on a face database; Receiving user information corresponding to the face image sent by the face recognition server; Executing the task content indicated by the task information to obtain task execution information; the task execution information includes the execution result of the task content and the association between the task content and the user information; When the second link is disconnected and reconnected, a first indication message is sent to the task execution server via the second link; the first indication message carries the task execution information, and the first indication message is used to instruct the task execution server to execute the task content based on the task execution information.

4. The offline task processing method according to claim 1, characterized in that: The performing of a target operation associated with the task information based on the facial image and the first information includes: When the first information indicates that the first link is in an interrupted state, identifying the facial image based on a facial database to determine user information corresponding to the facial image; A second indication message is sent to the task execution server through the second link; wherein the second indication message carries the user information and the task information, and the second indication message is used to instruct the task execution server to execute the task content indicated by the task information based on the user information and the task information.

5. The method for processing an offline task according to any one of claims 1 to 4, characterized in that: The method further comprises: When the first link and the second link are disconnected and reconnected, sending the facial image to a face recognition server through the first link; Receiving user information corresponding to the face image sent by the face recognition server; A second indication message is sent to the task execution server through the second link; wherein the second indication message carries the user information and the task information, and the second indication message is used to instruct the task execution server to execute the task content indicated by the task information based on the user information and the task information.

6. The method for processing an offline task according to any one of claims 2 to 4, characterized in that: The method further comprises: Get incremental face images; Performing feature extraction on the incremental facial image to obtain a feature value corresponding to the incremental facial image; the feature value is used to identify the facial image; The feature value is saved in the face database.

7. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the computer program implements the offline task processing method according to any one of claims 1 to 6.

8. An offline task processing device, characterized in that: The device comprises: Acquisition module, used to obtain face images and task information; an execution module, configured to execute a target operation associated with the task information based on the facial image and the first information; The first information is used to indicate that at least one of the first link and the second link is in an interrupted state, the first link is used to transmit face-related data, and the second link is used to transmit task-related data.

9. An electronic device, characterized in that: include: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the offline task processing method according to any one of claims 1 to 6.

10. A storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the offline task processing method according to any one of claims 1 to 6 is implemented.

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