CN111679811A - Web service construction method and device - Google Patents
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Abstract
The application provides a Web service construction method and a Web service construction device, wherein the method comprises the following steps: receiving a target Web service construction request corresponding to the current service, wherein the target Web service construction request comprises: target node information and connection relation information among all target nodes; acquiring a current target node according to the target node information; and constructing a target Web service for processing the current business based on each target node and the connection relation information between the target nodes. The method and the device can improve the efficiency, flexibility and accuracy of constructing the Web service, and further can improve the accuracy of processing the relevant business process by applying the Web service.
Description
Technical Field
The present application relates to the field of Web services, and in particular, to a method and an apparatus for constructing a Web service.
Background
Web services are a platform-independent, low-coupling, self-contained and programmable Web-based application; after training is completed, the deep learning model cannot directly provide services for the outside, and the deep learning model needs to be packaged through a Web service technology and can provide related deep learning services for a calling party after related business logic processing is added.
From model construction to external service provision, one Web service package is needed, one Web service can be connected with a plurality of trained deep learning models in series, and business logic operation or other special preprocessing operation information can be added. In the prior art, the Web service codes need to be developed in a customized manner for different scenes, so that each scene corresponds to one independent Web service code, and the Web service codes are not easy to maintain. Meanwhile, when the Web service interfaces the same model, the interface codes are basically the same, which results in repeated development of the interface codes.
Disclosure of Invention
Aiming at the problems in the prior art, the application provides a Web service construction method and a Web service construction device, which can improve the efficiency, flexibility and accuracy of constructing Web services, and further can improve the accuracy of processing related business processes by applying the Web services.
In a first aspect, the present application provides a Web service construction method, including:
receiving a target Web service construction request corresponding to the current service, wherein the target Web service construction request comprises: target node information and connection relation information among all target nodes;
acquiring a current target node according to the target node information;
and constructing a target Web service for processing the current business based on each target node and the connection relation information between the target nodes.
Further, each target node is provided with different code group information; correspondingly, the constructing a target Web service for processing the current service based on the target nodes and the connection relationship information between the target nodes includes: and combining the code group information in each target node according to the connection relation information among the target nodes to construct and obtain the target Web service for processing the current service.
Further, if the service includes: the image recognition service, after the constructing the target Web service for processing the current service, further includes: applying each target node in the target Web service and the connection relation information between the target nodes to execute a processing process aiming at the current image recognition service; wherein, the processing procedure for the current image recognition service comprises: receiving an image to be recognized, and determining the information of a region to be recognized corresponding to the image to be recognized based on a preset image positioning model, wherein the image positioning model is a deep learning model which is obtained by pre-training and is used for determining the information of the region to be recognized corresponding to the image; cutting the image to be recognized based on the information of the area to be recognized to obtain an image of the area to be recognized; and performing image text recognition on the image of the area to be recognized by using a preset image text recognition model, wherein the image text recognition model is a deep learning model which is obtained by training in advance and is used for recognizing the image text.
Further, the image positioning model is a deep learning model based on a Deeptext algorithm.
Further, the image text recognition model is a convolution cyclic neural network model.
In a second aspect, the present application provides a Web service building apparatus, including:
a receiving module, configured to receive a target Web service construction request corresponding to a current service, where the target Web service construction request includes: target node information and connection relation information among all target nodes;
the target node obtaining module is used for obtaining the current target node according to the target node information;
and the construction module is used for constructing the target Web service for processing the current business based on the target nodes and the connection relation information between the target nodes.
Further, each target node is provided with different code group information; correspondingly, the building module comprises: and the construction unit is used for combining the code group information in each target node according to the connection relation information among the target nodes so as to construct and obtain the target Web service for processing the current service.
Further, if the service includes: and in the image recognition service, the Web service construction device further comprises: the service processing module is used for executing a processing process aiming at the current image recognition service by applying each target node in the target Web service and the connection relation information among the target nodes; wherein, the processing procedure for the current image recognition service comprises: receiving an image to be recognized, and determining the information of a region to be recognized corresponding to the image to be recognized based on a preset image positioning model, wherein the image positioning model is a deep learning model which is obtained by pre-training and is used for determining the information of the region to be recognized corresponding to the image; cutting the image to be recognized based on the information of the area to be recognized to obtain an image of the area to be recognized; and performing image text recognition on the image of the area to be recognized by using a preset image text recognition model, wherein the image text recognition model is a deep learning model which is obtained by training in advance and is used for recognizing the image text.
Further, the image positioning model is a deep learning model based on a Deeptext algorithm.
Further, the image text recognition model is a convolution cyclic neural network model.
In a third aspect, the present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the Web service construction method when executing the program.
In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon computer instructions that, when executed, implement the Web service construction method.
According to the technical scheme, the Web service construction method and the Web service construction device are provided. Wherein, the method comprises the following steps: receiving a target Web service construction request corresponding to the current service, wherein the target Web service construction request comprises: target node information and connection relation information among all target nodes; acquiring a current target node according to the target node information; based on the connection relation information between each target node and each target node, a target Web service for processing the current business is constructed, so that the efficiency, flexibility and accuracy of constructing the Web service can be improved, and the accuracy of processing the related business process by applying the Web service can be further improved; the method can avoid the problems of accuracy and efficiency caused by repeated development, and reduce the cost for maintaining the Web service and constructing the Web service.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a Web service construction method in an embodiment of the present application;
FIG. 2 is a schematic flow chart diagram illustrating a Web service construction method according to another embodiment of the present application;
FIG. 3 is a schematic structural diagram of a Web service building apparatus in an embodiment of the present application;
FIG. 4 is a schematic structural diagram of a Web service building apparatus according to another embodiment of the present application;
FIG. 5 is a flowchart illustrating a Web service construction method in an embodiment of the present application;
FIG. 6 is a schematic diagram of detailed information of different nodes in a Web service and a logic sequence between the nodes in a specific application example of the present application;
FIG. 7 is a schematic diagram of a page for uploading a custom algorithm in an embodiment of the present application;
FIG. 8 is a schematic diagram of a page for constructing a Web service in an exemplary application of the present application;
FIG. 9 is a schematic diagram of a page for modifying or updating published Web services in an example of an application of the present application;
FIG. 10 is a flow chart illustrating a container control process according to an exemplary embodiment of the present disclosure;
FIG. 11 is a flowchart illustrating a method for constructing a Web service in another embodiment of the present application;
fig. 12 is a block diagram schematically illustrating a system configuration of an electronic device 9600 according to an embodiment of the present application.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Considering the conditions that each scene corresponds to a set of independent Web service codes in the prior art, the docking codes when the Web services dock the same model are basically the same, and the like, the application provides a technical scheme which can customize a scene business process in a front-end page dragging mode and automatically build the Web services from the change of the existing Web service building mode. Respectively abstracting codes or general preprocessing codes for butting different models into different nodes, adding related modifiable parameters to the nodes, establishing a connection relation between the nodes in a mode of dragging a front-end node icon, and establishing a flow of the whole Web service calling model; therefore, under a new business scene, only a new business process needs to be customized, and the customized Web service can be automatically constructed without writing codes. Therefore, the problems of poor accuracy and low efficiency of Web service construction caused by repeated code development and the problems of high cost of Web service construction and maintenance are solved.
Based on this, in order to improve efficiency, flexibility, and accuracy of constructing a Web service, and further improve accuracy of processing a relevant business process by applying the Web service, an embodiment of the present application provides a Web service construction apparatus, which may be a server or a client device, where the client device may include a smart phone, a tablet electronic device, a network set top box, a portable computer, a desktop computer, a Personal Digital Assistant (PDA), a vehicle-mounted device, an intelligent wearable device, and the like. Wherein, intelligence wearing equipment can include intelligent glasses, intelligent wrist-watch and intelligent bracelet etc..
In practical applications, the part for constructing the Web service may be executed on the server side as described in the above, or all operations may be completed in the client device. The selection may be specifically performed according to the processing capability of the client device, the limitation of the user usage scenario, and the like. This is not a limitation of the present application. The client device may further include a processor if all operations are performed in the client device.
The client device may have a communication module (i.e., a communication unit), and may be communicatively connected to a remote server to implement data transmission with the server. The server may include a server on the task scheduling center side, and in other implementation scenarios, the server may also include a server on an intermediate platform, for example, a server on a third-party server platform that is communicatively linked to the task scheduling center server. The server may include a single computer device, or may include a server cluster formed by a plurality of servers, or a server structure of a distributed apparatus.
The server and the client device may communicate using any suitable network protocol, including network protocols not yet developed at the filing date of this application. The network protocol may include, for example, a TCP/IP protocol, a UDP/IP protocol, an HTTP protocol, an HTTPS protocol, or the like. Of course, the network Protocol may also include, for example, an RPC Protocol (Remote Procedure Call Protocol), a REST Protocol (Representational State Transfer Protocol), and the like used above the above Protocol.
The following examples are intended to illustrate the details.
As shown in fig. 1, in order to improve efficiency, flexibility, and accuracy of constructing a Web service, and further improve accuracy of processing a relevant business process by applying the Web service, the embodiment provides a Web service construction method whose execution subject is a Web service construction device, which specifically includes the following contents:
step 100: receiving a target Web service construction request corresponding to the current service, wherein the target Web service construction request comprises: target node information and connection relation information between the target nodes.
Specifically, a Web service build request based on a click event of a front-end page may be received. The target node information may be identification information of a node for distinguishing different nodes.
Step 200: and acquiring the current target node according to the target node information.
Specifically, the target node may be downloaded from a pre-stored node component library according to the target node information, where the node component library includes each optional node, and the node component library may be stored locally or in an independent server.
Step 300: and constructing a target Web service for processing the current business based on each target node and the connection relation information between the target nodes.
Specifically, the target Web service may be a complete set of Web service codes, and may be set in an independent Web server or in the Web service building apparatus.
In order to obtain accurate code group information and further improve the efficiency, flexibility and accuracy of constructing the Web service, in one embodiment of the application, each target node is respectively provided with different code group information; correspondingly, step 300 includes:
step 301: and combining the code group information in each target node according to the connection relation information among the target nodes to construct and obtain the target Web service for processing the current service.
Specifically, the code group information may be a group of code information corresponding to a deep learning model, or may also be a group of code information corresponding to a business logic operation or other special preprocessing operations.
In order to improve the accuracy of processing the related business process by the Web service, especially the accuracy of processing the image recognition business, referring to fig. 2, in an embodiment of the present application, if the business includes: the image recognition service, after step 300, further includes:
step 400: and executing a processing process aiming at the current image recognition service by applying each target node in the target Web service and the connection relation information between the target nodes.
The processing procedure for the current image recognition service in step 400 includes:
step 401: receiving an image to be recognized, and determining the information of the area to be recognized corresponding to the image to be recognized based on a preset image positioning model, wherein the image positioning model is a deep learning model which is obtained by pre-training and is used for determining the information of the area to be recognized corresponding to the image.
Step 402: and cutting the image to be recognized based on the information of the area to be recognized to obtain the image of the area to be recognized.
Specifically, the information of the area to be recognized may be coordinate information of the area to be recognized in the image to be recognized. In order to further improve the accuracy of obtaining the image of the area to be identified, the image of the area to be identified may be filled and/or scaled according to a preset clipping rule, where the preset clipping rule may be set according to an actual situation.
Step 403: and performing image text recognition on the image of the area to be recognized by using a preset image text recognition model, wherein the image text recognition model is a deep learning model which is obtained by training in advance and is used for recognizing the image text.
The image positioning model can be a deep learning model based on a Deeptext algorithm; the image text recognition model may be a convolutional recurrent neural network crnn model.
Specifically, Deeptext can process textual information at speeds approaching human thoughts, up to thousands of articles per second, support more than 20 languages, and learn at the word and letter level using multiple deep neural network architectures, including convolutional and recurrent neural networks.
In one example, the target Web service includes a data receiving node, an image positioning node, a cropping node and an image text recognition node; receiving an image to be recognized by using the data receiving node, and determining the information of the area to be recognized corresponding to the image to be recognized by using an image positioning model preset in an image positioning node connected with the data receiving node, wherein the image positioning model is a deep learning model obtained by pre-training and used for determining the information of the area to be recognized corresponding to the image; applying a cutting node connected with the image positioning node and cutting the image to be recognized based on the information of the area to be recognized to obtain an image of the area to be recognized; and performing image text recognition on the image of the area to be recognized by using an image text recognition model preset in an image text recognition node connected with the cutting node, wherein the image text recognition model is a deep learning model obtained by pre-training and used for recognizing the image text.
In terms of software, in order to improve efficiency, flexibility, and accuracy of constructing a Web service and further improve accuracy of processing a relevant business process by applying the Web service, the present application provides an embodiment of a Web service construction apparatus for implementing all or part of contents in the Web service construction method, and referring to fig. 3, the Web service construction apparatus specifically includes the following contents:
a receiving module 10, configured to receive a target Web service construction request corresponding to a current service, where the target Web service construction request includes: target node information and connection relation information between the target nodes.
And an obtaining target node module 20, configured to obtain a current target node according to the target node information.
And the building module 30 is configured to build a target Web service for processing the current service based on each target node and the connection relationship information between the target nodes.
In an embodiment of the present application, each target node is respectively provided with different code group information; correspondingly, the building module comprises:
and the construction unit is used for combining the code group information in each target node according to the connection relation information among the target nodes so as to construct and obtain the target Web service for processing the current service.
Referring to fig. 4, in an embodiment of the present application, if the service includes: and in the image recognition service, the Web service construction device further comprises:
a service processing module 40, configured to apply the target nodes in the target Web service and connection relationship information between the target nodes to execute a processing procedure for a current image recognition service; wherein, the processing procedure for the current image recognition service comprises:
receiving an image to be recognized, and determining the information of the area to be recognized corresponding to the image to be recognized based on a preset image positioning model, wherein the image positioning model is a deep learning model which is obtained by pre-training and is used for determining the information of the area to be recognized corresponding to the image.
And cutting the image to be recognized based on the information of the area to be recognized to obtain the image of the area to be recognized.
And performing image text recognition on the image of the area to be recognized by using a preset image text recognition model, wherein the image text recognition model is a deep learning model which is obtained by training in advance and is used for recognizing the image text.
Specifically, the image positioning model is a deep learning model based on a Deeptext algorithm; the image text recognition model is a convolution cyclic neural network model.
For further explanation of the present solution, referring to fig. 5, the present application further provides a specific application example of a Web service construction method, which includes S11: customizing the service flow, S12: defining parameters of each node in the process; s13: automatically constructing Web service; s14: calling Web service; the specific process is as follows:
1) each node in the Web service needs to be customized first, and relevant parameter information is added to the node.
2) And determining the processing flow of the whole Web service through the connection relation between the nodes.
3) And automatically constructing the deep learning Web service according to the whole Web service processing flow, and accessing the Web service in an http mode after the construction is finished.
In the process of customizing the deep learning Web service, the core part lies in the determination of nodes in the Web service, the customization of node parameters and the connection between the nodes.
To further illustrate the present solution, the present application provides a specific application example for customizing detailed information of different nodes of a Web service and a connection relationship between the nodes in an image recognition application scene, where the specific application example includes a deep learning model for positioning and a deep learning model for recognizing an image text, and the specific description is as follows:
s21: adding a data preprocessing node in the target Web service, wherein the data preprocessing node is provided with relevant parameters of a preprocessing process, such as parameters corresponding to basic preprocessing processes of image enhancement, image rotation, image binarization and the like.
S22: after the image is preprocessed, calling a deep learning positioning model to obtain a region to be identified in the image; a deep learning positioning model processing node is required to be added in the target Web service, and the deep learning positioning model which is trained and an algorithm and a version adopted by the deep learning positioning model are arranged in the node.
S23: and if the code corresponding to the image is not cut in the preset deep learning code library, editing and uploading related codes according to certain specifications, adding a user group definition cut picture node corresponding to the code in a target Web service, and customizing parameters of the user group definition cut picture node.
S24: calling a recognition service of deep learning after cutting the image; a deep learning identification model processing node is required to be added into the target Web service, and the deep learning identification model processing node is provided with a deep learning identification algorithm and a model version number. The deep learning recognition model processing node can be used for obtaining an Optical Character Recognition (OCR) result of the image.
S25: and finally, defining a result processing node, customizing a processing mode of the output result of the deep learning identification model by self, and outputting the processed result.
Specifically, fig. 6 shows detailed information of different nodes of the Web service and a logic sequence between the nodes in this specific application example, where the logic sequence is formed by sequentially connecting a data preprocessing node, a deep learning positioning model processing node, a user group definition cutting picture node, a deep learning identification model processing node, and a result processing node.
The specific operation steps of the user on the page are as follows:
s31: as shown in fig. 7, there are some predefined common node component icons on the right side of the page, if the user needs to upload the customized algorithm, the user can select a button "upload customized algorithm" on the upper left of the page, and then the user can upload the local algorithm to the node component library, and the node component icons can be dragged for use.
S32: as shown in FIG. 8, the custom algorithm uploaded by the user is displayed in the node component icon on the right side of the page and is available. When a user needs to start building services, a 'build services' button on the upper left of a page can be selected, then the whole processing flow of the services can be built in a mode of dragging node component icons on the right side of the page, and when the user drags the node component icons, node attributes of the components need to be formulated. Different node attributes are different, for example, nodes related to the deep learning model must select the algorithm used by the model and the version number of the deep learning model which is trained.
S33: after the connection relation of the node components in the Web service is determined, a 'publishing' button at the upper right of the page can be clicked to publish the customized service.
S34: in the published service, if there is an update of the deep learning model version or a modification of the parameters in the node, the "modify service" button on the upper left of the page may be clicked, and the parameters of the node to be modified are modified, as shown in fig. 9, the model version of the positioning model in fig. 8 is modified, and the model version is modified from "20190101124000" to "202000211153400". After the modification is finished, the service can be updated by clicking the 'issue' button at the upper right of the page again.
As shown in fig. 10, after receiving a customization request sent by a user from a page, the container control interface sends a container start request to Kubernets, and when resources meet requirements, Kubernets start a container of a Web service according to requirements and allocate required resources to the container of the Web service, so that a customized Web service code is automatically constructed in the container.
Kubernets is a container arrangement engine of Google open source, and supports automatic deployment, large-scale scalability and application containerization management.
FIG. 11 is a flow diagram illustrating the automatic construction of customized deep learning Web service code. The core of the method is that each node is regarded as an independent module code through a modularization concept, and then the module codes are combined together in a specific mode according to a customized process to form the Web service, wherein the specific process is as follows:
s41: and acquiring the deep learning model and the docking code from the deep learning model library and the deep learning code library.
Specifically, when a customized Web service request is received, customized detailed information of related nodes is received, a deep learning model selected by a user is downloaded from a deep learning model library through the detailed information of the related nodes, and related codes of corresponding algorithms are downloaded from a deep learning code library.
S42: and loading the downloaded deep learning model into a start service TF Serving (TensorFlow Serving) of the deep learning model for hosting.
The TensorFlow Serving is a service system of Google open source and is suitable for deploying machine learning models.
S43: and constructing Web service according to a flash + gunicorn mode and a user customized process, and calling a corresponding model in the TF Serving if model processing exists.
Wherein, the flash is a lightweight Web application framework written by Python; guiicorn is a high performance Web Server Gateway Interface (WSGI) server.
Specifically, according to the detailed information of the relevant nodes, Web service codes are constructed based on a flash + gunicorn mode, and when parts needing model calling are met, the corresponding models in the TF Serving are automatically called. In a service framework based on a flash + gunicorn + TF Serving mode, the TF Serving is used as a starting service of a deep learning model and is responsible for loading the deep learning model and distributing corresponding GPU or CPU resources for the deep learning model; and the flash + gunicorn is used for providing a service interface for the outside and calling a related deep learning model in the TF Serving according to the service logic inside.
S44: customized Web services are provided to users. Specifically, the service interface is exposed to the outside for the user to call.
According to the description, the method and the device for constructing the Web service are provided, the required trained deep learning model is determined in a front-end page configuration mode, the processing flow inside the service is determined in a dragging frame mode, and finally the multiple deep learning models are combined and customized Web service is provided to the outside, so that the efficiency, flexibility and accuracy of constructing the Web service can be improved, and the accuracy of processing the related business process by applying the Web service can be improved; the method can avoid the problems of accuracy and efficiency caused by repeated development, and reduce the cost for maintaining the Web service and constructing the Web service.
In terms of hardware, in order to improve efficiency, flexibility, and accuracy of constructing a Web service and further improve accuracy of processing a relevant business process by applying the Web service, the present application provides an embodiment of an electronic device for implementing all or part of contents in the Web service construction method, where the electronic device specifically includes the following contents:
a processor (processor), a memory (memory), a communication Interface (Communications Interface), and a bus; the processor, the memory and the communication interface complete mutual communication through the bus; the communication interface is used for realizing information transmission between the Web service construction device and relevant equipment such as a user terminal and the like; the electronic device may be a desktop computer, a tablet computer, a mobile terminal, and the like, but the embodiment is not limited thereto. In this embodiment, the electronic device may be implemented with reference to the embodiment for implementing the Web service construction method and the embodiment for implementing the Web service construction apparatus in the embodiments, and the contents of the embodiments are incorporated herein, and repeated details are not described herein.
Fig. 12 is a schematic block diagram of a system configuration of an electronic device 9600 according to an embodiment of the present application. As shown in fig. 12, the electronic device 9600 can include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. Notably, this fig. 12 is exemplary; other types of structures may also be used in addition to or in place of the structure to implement telecommunications or other functions.
In one or more embodiments of the present application, the Web service construction function can be integrated into the central processor 9100. The central processor 9100 may be configured to control as follows:
step 100: receiving a target Web service construction request corresponding to the current service, wherein the target Web service construction request comprises: target node information and connection relation information between the target nodes.
Step 200: and acquiring the current target node according to the target node information.
Step 300: and constructing a target Web service for processing the current business based on each target node and the connection relation information between the target nodes.
As can be seen from the above description, the electronic device provided in the embodiment of the present application can improve efficiency, flexibility, and accuracy of constructing the Web service, and further can improve accuracy of processing a relevant business process by applying the Web service.
In another embodiment, the Web service constructing apparatus may be configured separately from the central processor 9100, for example, the Web service constructing apparatus may be configured as a chip connected to the central processor 9100, and the Web service constructing function is realized by the control of the central processor.
As shown in fig. 12, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is noted that the electronic device 9600 also does not necessarily include all of the components shown in fig. 12; further, the electronic device 9600 may further include components not shown in fig. 12, which can be referred to in the related art.
As shown in fig. 12, a central processor 9100, sometimes referred to as a controller or operational control, can include a microprocessor or other processor device and/or logic device, which central processor 9100 receives input and controls the operation of the various components of the electronic device 9600.
The memory 9140 can be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information relating to the failure may be stored, and a program for executing the information may be stored. And the central processing unit 9100 can execute the program stored in the memory 9140 to realize information storage or processing, or the like.
The input unit 9120 provides input to the central processor 9100. The input unit 9120 is, for example, a key or a touch input device. Power supply 9170 is used to provide power to electronic device 9600. The display 9160 is used for displaying display objects such as images and characters. The display may be, for example, an LCD display, but is not limited thereto.
The memory 9140 can be a solid state memory, e.g., Read Only Memory (ROM), Random Access Memory (RAM), a SIM card, or the like. There may also be a memory that holds information even when power is off, can be selectively erased, and is provided with more data, an example of which is sometimes called an EPROM or the like. The memory 9140 could also be some other type of device. Memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application/function storage portion 9142, the application/function storage portion 9142 being used for storing application programs and function programs or for executing a flow of operations of the electronic device 9600 by the central processor 9100.
The memory 9140 can also include a data store 9143, the data store 9143 being used to store data, such as contacts, digital data, images, sounds, and/or any other data used by an electronic device. The driver storage portion 9144 of the memory 9140 may include various drivers for the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging applications, contact book applications, etc.).
The communication module 9110 is a transmitter/receiver 9110 that transmits and receives signals via an antenna 9111. The communication module (transmitter/receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as in the case of a conventional mobile communication terminal.
Based on different communication technologies, a plurality of communication modules 9110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, may be provided in the same electronic device. The communication module (transmitter/receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and receive audio input from the microphone 9132, thereby implementing ordinary telecommunications functions. The audio processor 9130 may include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 9130 is also coupled to the central processor 9100, thereby enabling recording locally through the microphone 9132 and enabling locally stored sounds to be played through the speaker 9131.
As can be seen from the above description, the electronic device provided in the embodiment of the present application can improve efficiency, flexibility, and accuracy of constructing the Web service, and further can improve accuracy of processing a relevant business process by applying the Web service.
An embodiment of the present application further provides a computer-readable storage medium capable of implementing all the steps in the Web service building method in the foregoing embodiment, where the computer-readable storage medium stores a computer program, and the computer program, when executed by a processor, implements all the steps in the Web service building method in the foregoing embodiment, for example, when the processor executes the computer program, implements the following steps:
step 100: receiving a target Web service construction request corresponding to the current service, wherein the target Web service construction request comprises: target node information and connection relation information between the target nodes.
Step 200: and acquiring the current target node according to the target node information.
Step 300: and constructing a target Web service for processing the current business based on each target node and the connection relation information between the target nodes.
As can be seen from the above description, the computer-readable storage medium provided in the embodiment of the present application can improve efficiency, flexibility, and accuracy of constructing a Web service, and can further improve accuracy of processing a relevant business process by applying the Web service.
In the present application, each embodiment of the method is described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. Reference is made to the description of the method embodiments.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principle and the implementation mode of the present application are explained by applying specific embodiments in the present application, and the description of the above embodiments is only used to help understanding the method and the core idea of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (12)
1. A Web service construction method is characterized by comprising the following steps:
receiving a target Web service construction request corresponding to the current service, wherein the target Web service construction request comprises: target node information and connection relation information among all target nodes;
acquiring a current target node according to the target node information;
and constructing a target Web service for processing the current business based on each target node and the connection relation information between the target nodes.
2. The Web service construction method according to claim 1, wherein each of the target nodes is provided with different code group information;
correspondingly, the constructing a target Web service for processing the current service based on the target nodes and the connection relationship information between the target nodes includes:
and combining the code group information in each target node according to the connection relation information among the target nodes to construct and obtain the target Web service for processing the current service.
3. The Web service construction method according to claim 1, wherein if the service includes: the image recognition service, after the constructing the target Web service for processing the current service, further includes:
applying each target node in the target Web service and the connection relation information between the target nodes to execute a processing process aiming at the current image recognition service;
wherein, the processing procedure for the current image recognition service comprises:
receiving an image to be recognized, and determining the information of a region to be recognized corresponding to the image to be recognized based on a preset image positioning model, wherein the image positioning model is a deep learning model which is obtained by pre-training and is used for determining the information of the region to be recognized corresponding to the image;
cutting the image to be recognized based on the information of the area to be recognized to obtain an image of the area to be recognized;
and performing image text recognition on the image of the area to be recognized by using a preset image text recognition model, wherein the image text recognition model is a deep learning model which is obtained by training in advance and is used for recognizing the image text.
4. The Web service construction method according to claim 3, wherein the image localization model is a deep learning model based on a Deeptext algorithm.
5. The Web service construction method according to claim 3, wherein the image text recognition model is a convolutional recurrent neural network model.
6. A Web service construction apparatus, characterized by comprising:
a receiving module, configured to receive a target Web service construction request corresponding to a current service, where the target Web service construction request includes: target node information and connection relation information among all target nodes;
the target node obtaining module is used for obtaining the current target node according to the target node information;
and the construction module is used for constructing the target Web service for processing the current business based on the target nodes and the connection relation information between the target nodes.
7. The Web service construction apparatus according to claim 6, wherein each of the target nodes is provided with different code group information;
correspondingly, the building module comprises:
and the construction unit is used for combining the code group information in each target node according to the connection relation information among the target nodes so as to construct and obtain the target Web service for processing the current service.
8. The Web service creation apparatus of claim 6, wherein if the service includes: and in the image recognition service, the Web service construction device further comprises:
the service processing module is used for executing a processing process aiming at the current image recognition service by applying each target node in the target Web service and the connection relation information among the target nodes;
wherein, the processing procedure for the current image recognition service comprises:
receiving an image to be recognized, and determining the information of a region to be recognized corresponding to the image to be recognized based on a preset image positioning model, wherein the image positioning model is a deep learning model which is obtained by pre-training and is used for determining the information of the region to be recognized corresponding to the image;
cutting the image to be recognized based on the information of the area to be recognized to obtain an image of the area to be recognized;
and performing image text recognition on the image of the area to be recognized by using a preset image text recognition model, wherein the image text recognition model is a deep learning model which is obtained by training in advance and is used for recognizing the image text.
9. The Web service construction apparatus according to claim 8, wherein the image localization model is a deep learning model based on a Deeptext algorithm.
10. The Web service construction apparatus according to claim 8, wherein the image text recognition model is a convolutional recurrent neural network model.
11. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the Web service construction method of any one of claims 1 to 5 when executing the program.
12. A computer-readable storage medium having computer instructions stored thereon, wherein the instructions, when executed, implement the Web service construction method of any one of claims 1 to 5.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112528562A (en) * | 2020-12-07 | 2021-03-19 | 北京理工大学 | Intelligent haptic system and monitoring method for structural health monitoring |
| CN113298343A (en) * | 2021-03-31 | 2021-08-24 | 阿里巴巴新加坡控股有限公司 | Task generation method, task execution method and device |
| CN113326090A (en) * | 2021-06-18 | 2021-08-31 | 麦克方程(北京)科技有限责任公司 | Visual configuration method and device, electronic equipment and storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030233631A1 (en) * | 2002-06-13 | 2003-12-18 | Ambrose Curry | Web services development method |
| CN101246646A (en) * | 2008-03-03 | 2008-08-20 | 北京航空航天大学 | E-Police system structure based on Web service |
| CN101605141A (en) * | 2008-08-05 | 2009-12-16 | 天津大学 | Web service relational network system based on semanteme |
| CN108427550A (en) * | 2018-02-13 | 2018-08-21 | 深圳太极云软技术股份有限公司 | A kind of Web service generation method, device and equipment |
| CN109753281A (en) * | 2017-11-01 | 2019-05-14 | 北京德意新能电气有限公司 | A kind of microgrid energy management strategy visualization toolkit based on graphic programming |
| CN110457011A (en) * | 2019-08-15 | 2019-11-15 | 苏州思必驰信息科技有限公司 | Software application method for customizing and exploitation server-side |
-
2020
- 2020-05-26 CN CN202010454280.9A patent/CN111679811B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030233631A1 (en) * | 2002-06-13 | 2003-12-18 | Ambrose Curry | Web services development method |
| CN101246646A (en) * | 2008-03-03 | 2008-08-20 | 北京航空航天大学 | E-Police system structure based on Web service |
| CN101605141A (en) * | 2008-08-05 | 2009-12-16 | 天津大学 | Web service relational network system based on semanteme |
| CN109753281A (en) * | 2017-11-01 | 2019-05-14 | 北京德意新能电气有限公司 | A kind of microgrid energy management strategy visualization toolkit based on graphic programming |
| CN108427550A (en) * | 2018-02-13 | 2018-08-21 | 深圳太极云软技术股份有限公司 | A kind of Web service generation method, device and equipment |
| CN110457011A (en) * | 2019-08-15 | 2019-11-15 | 苏州思必驰信息科技有限公司 | Software application method for customizing and exploitation server-side |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112528562A (en) * | 2020-12-07 | 2021-03-19 | 北京理工大学 | Intelligent haptic system and monitoring method for structural health monitoring |
| CN112528562B (en) * | 2020-12-07 | 2022-11-15 | 北京理工大学 | Intelligent haptic system and monitoring method for structural health monitoring |
| CN113298343A (en) * | 2021-03-31 | 2021-08-24 | 阿里巴巴新加坡控股有限公司 | Task generation method, task execution method and device |
| CN113298343B (en) * | 2021-03-31 | 2023-11-14 | 阿里巴巴新加坡控股有限公司 | Task generation method, task execution method and device |
| CN113326090A (en) * | 2021-06-18 | 2021-08-31 | 麦克方程(北京)科技有限责任公司 | Visual configuration method and device, electronic equipment and storage medium |
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