Online attribute acceptance method and device, electronic equipment and storage medium
Through the online attribute acceptance method, acceptance services, task scheduling services and script services are used to process data labeling acceptance tasks, the problem of inefficient offline acceptance is solved, efficient and accurate data labeling acceptance is achieved, and the construction of a closed-loop data is promoted.
Patent Information
- Application Number
- CN202510008509.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-03
- Publication Date
- 2025-05-02
AI Technical Summary
In the existing data labeling acceptance process, the offline attribute acceptance mechanism is inefficient, the repair errors are complicated and there are data security risks.
The online attribute acceptance method is adopted to generate attribute acceptance tasks through the acceptance service, the task scheduling service regularly scans and submits tasks to the thread pool, and the script service processes and passes the acceptance results back, realizing the cutting and classification of data annotation processing results.
It significantly improves acceptance efficiency and accuracy, reduces the error rate caused by manual operations, avoids the dependence of third-party tools, and realizes a closed-loop data.
Smart Images
Figure CN119917241A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of data annotation and acceptance, and in particular to an online attribute acceptance method, device, electronic device, and storage medium. Background Art
[0002] In the current data labeling acceptance process, after the labeling task is completed and passes the preliminary acceptance, in order to meet the growing demand for refined data quality and speed, an offline attribute acceptance mechanism is introduced in related projects.
[0003] The offline attribute acceptance mechanism exports labeled datasets from the data acceptance platform. Customized scripts are then used to process these datasets, categorizing them by label into multiple folders. Each folder contains small images cut from the labeled data within that category. The acceptance team conducts a detailed review of each image to ensure that the labels are correct and that the bounding boxes accurately fit the objects, ensuring high data accuracy and consistency.
[0004] However, the offline attribute acceptance process also exposes some significant limitations. If annotation errors are discovered during the review process, the repair process becomes cumbersome and time-consuming. Data often needs to be exported, modified, and then imported repeatedly, creating an inefficient cycle. Furthermore, error correction often relies on third-party tools, which not only increases operational complexity but also introduces additional data security risks, hindering overall work efficiency. Summary of the Invention
[0005] The embodiments of the present application provide an online attribute acceptance method, device, electronic device, and storage medium to improve acceptance efficiency and quality.
[0006] The embodiments of this application adopt the following technical solutions:
[0007] In a first aspect, an embodiment of the present application provides an online attribute acceptance method, wherein the method includes:
[0008] Generate an attribute acceptance task based on the acceptance service, wherein the acceptance service is used to execute the first microservice of data annotation processing;
[0009] A task scheduling service is used to periodically scan the attribute acceptance tasks to be processed and submit them to a thread pool; and the task scheduling service is used to execute a second microservice for data annotation processing;
[0010] According to the thread pool, the script service is called to process the attribute acceptance result and return it to the acceptance service. The script service is used to cut and classify the data annotation processing results.
[0011] In some embodiments, the attribute acceptance task is generated based on the acceptance service, and the acceptance service is used to perform the first microservice of data annotation processing, including:
[0012] In response to the first microservice that performs data annotation processing, generating an attribute acceptance task;
[0013] Accept the task according to the attribute and obtain the extracted question set;
[0014] According to the question set, a corresponding attribute acceptance subtask is generated for each extracted question and the question flow is transferred to the attribute acceptance task.
[0015] In some embodiments, the attribute acceptance task includes at least one of the following information: attribute acceptance task name, task flow ID, total number of questions, number of extracted questions, and task processing status.
[0016] In some embodiments, the task scheduling service is used to periodically scan the attribute acceptance tasks to be processed and submit them to the thread pool; and the task scheduling service is used to perform the second microservice of data annotation processing, including:
[0017] In response to the second microservice performing data annotation processing, a scheduled task is used to query the attribute acceptance subtask to be processed;
[0018] Submit the pending attribute acceptance subtask to the thread pool to complete the thread pool processing, which includes locking, changing the subtask status to being processed, calling script processing, and releasing the lock.
[0019] In some embodiments, the thread pool is used to call a script service to obtain the attribute acceptance result and return it to the acceptance service. The script service is used to cut and classify the data annotation processing results, including:
[0020] According to the thread pool, the script service is called to classify the data annotation processing results by label;
[0021] Based on the interface provided by the acceptance service, the data annotation processing results are transmitted to the acceptance service according to the label classification.
[0022] In some embodiments, it further includes:
[0023] Determine whether the subtask status in the callback result is completed. The callback result includes the attribute acceptance total task ID, question ID, label, the storage address of the processing result classified by label, the size of the processing result classified by label, and the annotation data;
[0024] If the subtask status in the callback result is completed, update the subtask status to completed;
[0025] If the subtasks under the overall task are completed, update the overall task status to completed.
[0026] In a second aspect, an embodiment of the present application further provides a data labeling task acceptance method, which includes the online attribute acceptance method described in the first aspect.
[0027] In a third aspect, an embodiment of the present application further provides an online attribute acceptance device, wherein the device includes:
[0028] An acceptance module, configured to generate an attribute acceptance task based on an acceptance service, wherein the acceptance service is configured to execute a first microservice for data annotation processing;
[0029] a task scheduling module, configured to periodically scan the attribute acceptance tasks to be processed using a task scheduling service and submit them to a thread pool; and a second microservice configured to execute data annotation processing by the task scheduling service;
[0030] The script module is used to call the script service according to the thread pool to obtain the attribute acceptance result and return it to the acceptance service. The script service is used to cut and classify the data annotation processing results.
[0031] In a third aspect, an embodiment of the present application further provides an electronic device, comprising: a processor; and a memory arranged to store computer-executable instructions, wherein the executable instructions, when executed, enable the processor to perform the above method.
[0032] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, which stores one or more programs. When the one or more programs are executed by an electronic device including multiple application programs, the electronic device executes the above method.
[0033] At least one of the above-mentioned technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects: generating attribute acceptance tasks based on the acceptance service, since the acceptance service and the task scheduling service are microservices, the acceptance service is used to perform the first microservice of data annotation processing, which mainly starts and generates attribute acceptance tasks. The task scheduling service is used to periodically scan the attribute acceptance tasks to be processed and submit them to the thread pool, and the task scheduling service is used to perform the second microservice of data annotation processing, which mainly performs the scheduling of online tasks during data annotation processing. Finally, according to the thread pool, the script service is called to process the attribute acceptance results and return them to the acceptance service, thus promoting the online data closed loop and finally returning to the acceptance service. Among them, the script service mainly classifies the data annotation processing results by label for easy acceptance. Through the above method, the online attribute acceptance method is adopted to replace the traditional offline acceptance, which effectively solves the problems of low efficiency and high error rate caused by manual operation of the latter, thereby significantly improving the efficiency and accuracy of acceptance. BRIEF DESCRIPTION OF THE DRAWINGS
[0034] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:
[0035] Figure 1 This is a schematic diagram of the architecture of the online attribute acceptance method in an embodiment of the present application;
[0036] Figure 2 This is a flow chart of the online attribute acceptance method in an embodiment of the present application;
[0037] Figure 3 This is a timing diagram of the online attribute acceptance method in an embodiment of the present application;
[0038] Figure 4 This is a structural diagram of an online attribute acceptance device in an embodiment of the present application;
[0039] Figure 5 This is a structural diagram of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION
[0040] To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the specific embodiments of this application and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.
[0041] The following describes in detail the technical solutions provided by various embodiments of the present application in conjunction with the accompanying drawings.
[0042] like Figure 1As shown, after the acceptance service generates the attribute acceptance task, it interacts with the task scheduling service. The task scheduling task then interacts with the Python service. After being processed by the Python service, the acceptance service is called back. Specifically, the acceptance service and the task scheduling service are microservices in the same platform. When a user generates an attribute acceptance task on the platform, the acceptance service first generates the attribute acceptance task and saves it to the database. After that, the task scheduling service periodically scans the tasks to be processed and submits them to the thread pool for processing. The processing logic of the thread pool is to call the Python script to generate a thumbnail (the result of cutting out the target object annotation data under the relevant category, checking whether the label result is correct and whether the border fits the target object accurately). After the Python service completes the processing, it calls the interface provided by the acceptance service to return the processing result to the acceptance service, and the acceptance service saves the processing result to the database. In this way, subsequent queries can be grouped according to the thumbnail labels, and users can also jump to the corresponding annotation page of the platform based on the thumbnail related information to make modifications, without the need to repeatedly export and modify with the help of third-party tools.
[0043] This application embodiment provides an online attribute acceptance method, such as Figure 2 As shown, a flow chart of the online attribute acceptance method in an embodiment of the present application is provided, and the method at least includes the following steps S210 to S230:
[0044] Step S210: Generate an attribute acceptance task based on the acceptance service, where the acceptance service is used to execute the first microservice of data annotation processing.
[0045] Generate attribute acceptance tasks through the acceptance service. Acceptance service is a microservice in the platform, which is mainly used to perform the first microservice of data annotation processing and generate acceptance tasks.
[0046] Step S220: Using a task scheduling service to periodically scan the attribute acceptance tasks to be processed and submit them to a thread pool; and the task scheduling service is used to execute a second microservice for data annotation processing.
[0047] The task scheduling service is used to perform regular scans on the attribute acceptance tasks and submit the acceptance tasks to the thread pool. The task scheduling service is mainly used to execute the second microservice of data annotation processing. Scheduling task scanning is an acceptance task.
[0048] In step S230, according to the thread pool, a script service is called to process and obtain the attribute acceptance result and return it to the acceptance service. The script service is used to cut and classify the data annotation processing result.
[0049] The thread pool then calls the script service to process the attribute acceptance results and sends the results back to the acceptance service. The script service classifies the data annotation processing results by label, that is, the annotation results under the same label classification are obtained, which facilitates the subsequent attribute acceptance.
[0050] The script service segments and categorizes the annotation results. When the original data is a complete image, the annotator first annotates the image, resulting in boxes with different labels. The script service then segments these boxes and categorizes them into different folders, or tags.
[0051] The above approach replaces traditional offline acceptance with online attribute acceptance, effectively addressing the latter's inefficiency and high error rates caused by manual operation, significantly improving acceptance efficiency and accuracy. Furthermore, the introduction of a thread pool mechanism accelerates task processing. Furthermore, the service-oriented approach of scripting not only avoids dependency issues that may arise from directly calling scripts, but also enables better handling of exceptions, further improving execution efficiency.
[0052] By calling the acceptance service's interface, the processing results are passed back to the acceptance service, which saves them. Subsequent queries can be grouped by thumbnail tags. Users can also modify the thumbnail information by jumping to the corresponding annotation page on the platform, eliminating the need for repeated export and modification using third-party tools. This eliminates reliance on offline processes and third-party tools, achieving seamless integration between data annotation, acceptance, correction, and feedback, and effectively promoting the construction and formation of an online data closed loop.
[0053] The above method splits the entire acceptance system into three independent service modules. This not only facilitates the horizontal expansion of the system, but also enables the rapid location of the specific faulty service through the task status when a problem occurs, thereby simplifying maintenance work and facilitating expansion and maintenance.
[0054] In one embodiment of the present application, the acceptance service is based on the generation of an attribute acceptance task, and the acceptance service is used to perform the first microservice of data annotation processing, including: generating an attribute acceptance task in response to the first microservice that performs data annotation processing; obtaining a set of extracted questions according to the attribute acceptance task; generating a corresponding attribute acceptance subtask for each extracted question according to the question set and transferring the question flow to the attribute acceptance task.
[0055] Microservices are a collection of loosely coupled, independently deployable small components or services within a single application. These services typically have their own technology stack, including databases and data management models, and communicate with each other through a combination of REST APIs, event streams, and message brokers.
[0056] First, the acceptance service generates the attribute acceptance task and saves it to the database.
[0057] Then, an extracted question set is obtained, which includes multiple questions, and each question includes the annotation results of a single frame or multiple frames.
[0058] Next, an attribute acceptance subtask is generated for each extracted question, including but not limited to the attribute acceptance task ID, question ID, processing status, and answer. The answer refers to the annotation result saved in JSON format. The attribute acceptance task ID serves as a unique identifier for the task, and the question ID serves as a unique identifier for the question.
[0059] Finally, the status of each extracted question is changed to "In Attribute Acceptance" and the question flow is transferred to the attribute acceptance. It can be understood that both the overall task and the subtasks have status, and the status of the overall task needs to be determined by determining whether all subtasks are completed.
[0060] In one embodiment of the present application, the attribute acceptance task includes at least one of the following information: attribute acceptance task name, task flow ID, total number of questions, number of extracted questions, and task processing status.
[0061] like Figure 3 As shown, when generating an attribute acceptance task, it includes but is not limited to the attribute acceptance task name, task flow id, total number of questions, number of extracted questions, processing status and other information.
[0062] It can be understood that the task flow id refers to a unique identifier, the total number of questions includes the total number of questions, each question includes a single frame or multiple frames, the number of extracted questions refers to the percentage of the question in the total number of questions, and the processing status refers to the processing status of the task.
[0063] In one embodiment of the present application, the task scheduling service is used to periodically scan the pending attribute acceptance tasks and submit them to the thread pool; and the task scheduling service is used to perform the second microservice for data annotation processing, including: in response to the second microservice that performs data annotation processing, a scheduled task is used to query the pending attribute acceptance subtasks; the pending attribute acceptance subtasks are submitted to the thread pool to complete the thread pool processing, and the thread pool processing includes locking, modifying the subtask status to processing, calling script processing, and releasing the lock.
[0064] like Figure 3 As shown, the second microservice performs the task scheduling service for data annotation processing. The task scheduling service initiates the scanning processing task: a scheduled task is used to query the pending attribute acceptance subtasks and submit them to the thread pool. The thread pool processing includes but is not limited to: locking the thread, changing the subtask status to "processing", calling the Python script for processing, and releasing the thread lock.
[0065] In one embodiment of the present application, according to the thread pool, the script service is called to obtain the attribute acceptance result and returned to the acceptance service. The script service is used to cut and classify the data annotation processing results, including: according to the thread pool, calling the script service to classify the data annotation processing results by label; based on the interface provided by the acceptance service, the data annotation processing results classified by label are transmitted to the acceptance service.
[0066] like Figure 3 As shown, a Python script is preferably used to generate thumbnails. This involves categorizing objects by label into multiple folders, each containing thumbnails cut from the labeled data for that category. Specifically, the script is used to generate thumbnails and upload them to an online cloud drive. The acceptance service provides an interface that is called back after the Python script completes processing, passing the processing results to the acceptance service.
[0067] In one embodiment of the present application, it also includes: judging whether the status of the subtask in the callback result is completed, the callback result includes the attribute acceptance total task id, question id, label, the storage address of the processing results classified by label, the size of the processing results classified by label, and the annotation data; if the status of the subtask in the callback result is completed, the subtask status is updated to completed; if the subtask under the total task has been completed, the total task status is updated to completed.
[0068] like Figure 3 As shown, the acceptance service saves the thumbnail. The acceptance personnel then use the thumbnail to determine whether the annotation results are correct, primarily determining whether the annotation type is correct and whether the annotation box accurately fits the target object. The saved callback result includes, but is not limited to, the attribute acceptance task ID, question ID, tags, thumbnail online cloud disk address, thumbnail size, and annotation data. The subtask status is updated to Completed. If all subtasks under the overall task are completed, the overall task status is updated to Completed.
[0069] The embodiment of the present application further provides a data labeling task acceptance method, which adopts the online attribute acceptance method. The online attribute acceptance method includes:
[0070] Generate an attribute acceptance task based on the acceptance service, wherein the acceptance service is used to execute the first microservice of data annotation processing;
[0071] A task scheduling service is used to periodically scan the attribute acceptance tasks to be processed and submit them to a thread pool; and the task scheduling service is used to execute a second microservice for data annotation processing;
[0072] According to the thread pool, the script service is called to process the attribute acceptance result and return it to the acceptance service. The script service is used to cut and classify the data annotation processing results.
[0073] The embodiment of the present application also provides an online attribute acceptance device 400, such as Figure 4 As shown, a schematic diagram of the structure of an online attribute acceptance device in an embodiment of the present application is provided. The online attribute acceptance device 400 includes at least: an acceptance module 410, a task scheduling module 420, and a script module 430, wherein:
[0074] In one embodiment of the present application, the acceptance module 410 is specifically used to generate an attribute acceptance task based on an acceptance service, where the acceptance service is used to execute a first microservice for data annotation processing.
[0075] Generate attribute acceptance tasks through the acceptance service. Acceptance service is a microservice in the platform, which is mainly used to perform the first microservice of data annotation processing and generate acceptance tasks.
[0076] In one embodiment of the present application, the task scheduling module 420 is specifically used to: use a task scheduling service to regularly scan the attribute acceptance tasks to be processed and submit them to a thread pool; and the task scheduling service is used to execute a second microservice for data annotation processing.
[0077] The task scheduling service is used to perform regular scans on the attribute acceptance tasks and submit the acceptance tasks to the thread pool. The task scheduling service is mainly used to execute the second microservice of data annotation processing. Scheduling task scanning is an acceptance task.
[0078] In one embodiment of the present application, the script module 430 is specifically used to: according to the thread pool, call the script service to obtain the attribute acceptance result and return it to the acceptance service, and the script service is used to cut and classify the data annotation processing results.
[0079] The thread pool then calls the script service to process the attribute acceptance results and sends the results back to the acceptance service. The script service classifies the data annotation processing results by label, that is, the annotation results under the same label classification are obtained, which facilitates the subsequent attribute acceptance.
[0080] The script service segments and categorizes the annotation results. When the original data is a complete image, the annotator first annotates the image, resulting in boxes with different labels. The script service then segments these boxes and categorizes them into different folders, or tags.
[0081] In one embodiment of the present application, the acceptance module 410 is further used to
[0082] In response to the first microservice that performs data annotation processing, generating an attribute acceptance task;
[0083] Accept the task according to the attribute and obtain the extracted question set;
[0084] According to the question set, a corresponding attribute acceptance subtask is generated for each extracted question and the question flow is transferred to the attribute acceptance.
[0085] In one embodiment of the present application, the attribute acceptance task includes at least one of the following information: attribute acceptance task name, task flow ID, total number of questions, number of extracted questions, and task processing status.
[0086] In one embodiment of the present application, the task scheduling module 420 is also used to
[0087] In response to the second microservice performing data annotation processing, a scheduled task is used to query the attribute acceptance subtask to be processed;
[0088] Submit the pending attribute acceptance subtask to the thread pool to complete the thread pool processing, which includes locking, changing the subtask status to being processed, calling script processing, and releasing the lock.
[0089] In one embodiment of the present application, the script module 430 is also used to
[0090] According to the thread pool, the script service is called to classify the data annotation processing results by label;
[0091] Based on the interface provided by the acceptance service, the data annotation processing results are transmitted to the acceptance service according to the label classification.
[0092] In one embodiment of the present application, it further includes: a task status update module for
[0093] Determine whether the subtask status in the callback result is completed. The callback result includes the attribute acceptance total task ID, question ID, label, the storage address of the processing result classified by label, the size of the processing result classified by label, and the annotation data;
[0094] If the subtask status in the callback result is completed, update the subtask status to completed;
[0095] If the subtasks under the overall task are completed, update the overall task status to completed.
[0096] It can be understood that the above-mentioned online attribute acceptance device can implement each step of the online attribute acceptance method provided in the above-mentioned embodiment. The relevant explanations about the online attribute acceptance method are applicable to the online attribute acceptance device and will not be repeated here.
[0097] Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. Figure 5 At the hardware level, the electronic device includes a processor and, optionally, an internal bus, a network interface, and memory. The memory may include internal memory, such as high-speed random-access memory (RAM), or non-volatile memory, such as at least one disk drive. Of course, the electronic device may also include other hardware required for its services.
[0098] The processor, network interface, and memory can be interconnected via an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or one type of bus.
[0099] The memory is used to store programs. Specifically, the program may include program code, which includes computer operating instructions. The memory may include internal memory and non-volatile memory, and provides instructions and data to the processor.
[0100] The processor reads the corresponding computer program from the non-volatile memory into the internal memory and then runs it, forming an online attribute acceptance device at the logical level. The processor executes the program stored in the memory and is specifically used to perform the following operations:
[0101] Generate an attribute acceptance task based on the acceptance service, wherein the acceptance service is used to execute the first microservice of data annotation processing;
[0102] A task scheduling service is used to periodically scan the attribute acceptance tasks to be processed and submit them to a thread pool; and the task scheduling service is used to execute a second microservice for data annotation processing;
[0103] According to the thread pool, the script service is called to process the attribute acceptance result and return it to the acceptance service. The script service is used to cut and classify the data annotation processing results.
[0104] The above application Figure 2The methods performed by the online attribute acceptance device disclosed in the illustrated embodiments can be applied to or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be performed by hardware integrated logic circuits in the processor or by software instructions. The above processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The methods, steps, and logic block diagrams disclosed in the embodiments of this application can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.
[0105] The electronic device may also perform Figure 2 The method for executing the online attribute acceptance device of CCCC, and realizing the online attribute acceptance device Figure 2 The functions of the illustrated embodiment will not be described in detail in the embodiments of the present application.
[0106] The embodiment of the present application also provides a computer-readable storage medium, which stores one or more programs, wherein the one or more programs include instructions, which, when executed by an electronic device including multiple application programs, can enable the electronic device to execute Figure 2 The method performed by the online attribute acceptance device in the embodiment shown is specifically used to perform:
[0107] Generate an attribute acceptance task based on the acceptance service, wherein the acceptance service is used to execute the first microservice of data annotation processing;
[0108] A task scheduling service is used to periodically scan the attribute acceptance tasks to be processed and submit them to a thread pool; and the task scheduling service is used to execute a second microservice for data annotation processing;
[0109] According to the thread pool, the script service is called to process the attribute acceptance result and return it to the acceptance service. The script service is used to cut and classify the data annotation processing results.
[0110] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0111] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0112] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.
[0113] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.
[0114] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.
[0115] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.
[0116] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.
[0117] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.
[0118] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0119] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.
Claims
1. An online attribute acceptance method, wherein: The method comprises: Generate an attribute acceptance task based on the acceptance service, wherein the acceptance service is used to execute the first microservice of data annotation processing; A task scheduling service is used to periodically scan the attribute acceptance tasks to be processed and submit them to a thread pool; and the task scheduling service is used to execute a second microservice for data annotation processing; According to the thread pool, the script service is called to process the attribute acceptance result and sent back to the acceptance service. The script service is used to cut and classify the data annotation processing result.
2. The method of claim 1, wherein: The attribute acceptance task is generated based on the acceptance service, and the acceptance service is used to perform the first microservice of data annotation processing, including: In response to the first microservice that performs data annotation processing, generating an attribute acceptance task; Accepting the task according to the attribute, obtaining a set of extracted questions; According to the question set, a corresponding attribute acceptance subtask is generated for each extracted question and the question flow is transferred to the attribute acceptance task.
3. The method of claim 2, wherein: The attribute acceptance task includes at least one of the following information: attribute acceptance task name, task flow ID, total number of questions, number of extracted questions, and task processing status.
4. The method of claim 2, wherein: The task scheduling service is used to periodically scan the attribute acceptance tasks to be processed and submit them to the thread pool; And, the task scheduling service is used to perform a second microservice for data annotation processing, including: In response to the second microservice executing the data annotation processing, a scheduled task is used to query the attribute acceptance subtask to be processed; Submit the pending attribute acceptance subtask to the thread pool to complete the thread pool processing, which includes locking, modifying the subtask status to being processed, calling script processing, and releasing the lock.
5. The method of claim 1, wherein: According to the thread pool, the script service is called to process and obtain the attribute acceptance result and return it to the acceptance service. The script service is used to cut and classify the data annotation processing result, including: According to the thread pool, a script service is called to classify the data annotation processing results by label; Based on the interface provided by the acceptance service, the data annotation processing results are transmitted to the acceptance service according to the label classification.
6. The method of claim 1, wherein: Also includes: Determine whether the subtask status in the callback result is completed, wherein the callback result includes the attribute acceptance total task id, question id, label, the storage address of the processing result classified by label, the size of the processing result classified by label, and the annotation data; If the subtask status in the callback result is completed, update the subtask status to completed; If the subtasks under the overall task have been completed, update the overall task status to completed.
7. A data annotation task acceptance method, wherein: It comprises the online attribute acceptance method as described in any one of claims 1 to 6.
8. An online attribute acceptance device, wherein: The device comprises: An acceptance module, used to generate an attribute acceptance task based on an acceptance service, wherein the acceptance service is used to execute a first microservice for data annotation processing; A task scheduling module, used to periodically scan the attribute acceptance tasks to be processed using a task scheduling service and submit them to a thread pool; and a second microservice for the task scheduling service to perform data annotation processing; The script module is used to call the script service to process the attribute acceptance result according to the thread pool and return it to the acceptance service. The script service is used to cut and classify the data annotation processing results.
9. An electronic device, comprising: processor; as well as A memory arranged to store computer executable instructions, which when executed cause the processor to perform the method of any one of claims 1 to 7.
10. A computer-readable storage medium storing one or more programs, which, when executed by an electronic device including a plurality of application programs, causes the electronic device to execute any one of the methods of claims 1 to 7.