Application data processing method, device, equipment and storage medium

Abstract

The present disclosure provides an application data processing method, device, equipment and storage medium. The application data processing method provided in this embodiment includes: determining the model information corresponding to the sticker; determining the model information of the target model that is missing locally based on the model information; sending a model download request to the cloud, wherein the model download request includes the model information of the target model; so that the cloud sends the target model to the terminal based on the model information of the target model; and receiving the target model sent by the cloud. The application data processing method provided in the embodiment of the present disclosure can effectively reduce the size of the application software and reduce the local storage space occupied by the application software.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to an application data processing method, device, equipment and storage medium. Background Art

[0002] With the development of terminal technology, more and more application software can be loaded into the terminal. Many application software will use recognition algorithms to perform image recognition, and then add corresponding stickers to the image according to the recognition results to achieve the effect of beautifying the image.

[0003] In the prior art, since different stickers require corresponding different recognition algorithms and model files, the sticker materials, recognition algorithms, and model files are packaged together in the application software.

[0004] However, the above method will increase the size of the application software, causing it to occupy a large amount of local storage space. Summary of the invention

[0005] The present disclosure provides an application data processing method, apparatus, device and storage medium, which can effectively reduce the size of application software and reduce the local storage space occupied by the application software.

[0006] In a first aspect, the present disclosure provides an application data processing method, comprising:

[0007] Determine the model information corresponding to the sticker;

[0008] Determining model information of the target model that is missing locally based on the model information;

[0009] Sending a model download request to the cloud, wherein the model download request includes model information of the target model; so that the cloud sends the target model to the terminal according to the model information of the target model;

[0010] Receive the target model sent by the cloud.

[0011] In one possible design, the model information corresponding to the sticker is determined, including:

[0012] The model information corresponding to the sticker is searched through a preset mapping relationship table, where the model information includes: a model name and / or a model number.

[0013] In one possible design, the model information corresponding to the sticker is determined, including:

[0014] Obtaining label information of the sticker; wherein the label information of the sticker is used to characterize the type of the sticker, and different types of stickers correspond to different recognition algorithms; the recognition algorithms include: face recognition algorithm, gesture recognition algorithm, and three-dimensional image recognition algorithm;

[0015] Determine a recognition algorithm corresponding to the sticker according to the label information of the sticker;

[0016] The model information matching the recognition algorithm is searched, wherein the model information includes: a model name and / or a model number.

[0017] In a possible design, when the number of recognition algorithms corresponding to the sticker is greater than 1, searching for model information matching the recognition algorithm includes:

[0018] Find the model information matched by each recognition algorithm respectively;

[0019] All model information matched by the recognition algorithm is deduplicated and merged to obtain model information corresponding to the sticker.

[0020] In a possible design, determining the model information of the locally missing target model according to the model information includes:

[0021] Get the model information of the local existing model;

[0022] The model information of the existing local model is compared one by one with the model information corresponding to the sticker to determine the model information of the target model that is missing locally.

[0023] In a possible design, the model download request also includes terminal model information and application software version information; so that the cloud can send the target model compatible with the terminal and application software to the terminal based on the terminal model information and application software version information.

[0024] In a possible design, before determining the model information corresponding to the sticker, it also includes:

[0025] Displaying the sticker options on the application interface;

[0026] Receive user operation information for the sticker option;

[0027] The sticker is determined according to the operation information.

[0028] In one possible design, it also includes:

[0029] After the target model is received, loading the target model;

[0030] Load said sticker.

[0031] In a second aspect, the present disclosure further provides an application data processing device, including:

[0032] A first determination module, used to determine model information corresponding to the sticker;

[0033] A second determination module determines model information of a target model that is missing locally based on the model information;

[0034] A sending module, used to send a model download request to the cloud, wherein the model download request includes model information of the target model; so that the cloud sends the target model to the terminal according to the model information of the target model;

[0035] A receiving module is used to receive the target model sent by the cloud.

[0036] In a possible design, the first determining module is specifically configured to:

[0037] The model information corresponding to the sticker is searched through a preset mapping relationship table, where the model information includes: a model name and / or a model number.

[0038] In a possible design, the first determining module is further used to:

[0039] Obtaining label information of the sticker; wherein the label information of the sticker is used to characterize the type of the sticker, and different types of stickers correspond to different recognition algorithms; the recognition algorithms include: face recognition algorithm, gesture recognition algorithm, and three-dimensional image recognition algorithm;

[0040] Determine a recognition algorithm corresponding to the sticker according to the label information of the sticker;

[0041] The model information matching the recognition algorithm is searched, wherein the model information includes: a model name and / or a model number.

[0042] In a possible design, when the number of recognition algorithms corresponding to the sticker is greater than 1, searching for model information matching the recognition algorithm includes:

[0043] Find the model information matched by each recognition algorithm respectively;

[0044] All model information matched by the recognition algorithm is deduplicated and merged to obtain model information corresponding to the sticker.

[0045] In a possible design, the second determining module is specifically configured to:

[0046] Get the model information of the local existing model;

[0047] The model information of the existing local model is compared one by one with the model information corresponding to the sticker to determine the model information of the target model that is missing locally.

[0048] In a possible design, the model download request also includes terminal model information and application software version information; so that the cloud can send the target model compatible with the terminal and application software to the terminal based on the terminal model information and application software version information.

[0049] In a possible design, the device further includes: a display module, configured to:

[0050] Displaying the sticker options on the application interface;

[0051] Receive user operation information for the sticker option;

[0052] The sticker is determined according to the operation information.

[0053] In a possible design, the system further includes: a loading module, configured to:

[0054] After the target model is received, loading the target model;

[0055] Load said sticker.

[0056] In a third aspect, the present disclosure further provides an electronic device, including:

[0057] processor; and,

[0058] A memory, configured to store executable instructions of the processor;

[0059] Wherein, the processor is configured to execute any one of the application data processing methods in the first aspect by executing the executable instructions.

[0060] In a fourth aspect, an embodiment of the present disclosure further provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements any one of the application data processing methods in the first aspect.

[0061] The present disclosure provides an application data processing method, device, equipment and storage medium, which can effectively reduce the size of application software and reduce the local storage space occupied by application software by determining the model information corresponding to the sticker; determining the model information of the target model missing locally according to the model information; sending a model download request to the cloud, wherein the model download request includes the model information of the target model; so that the cloud sends the target model to the terminal according to the model information of the target model; and receiving the target model sent by the cloud. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0063] Figure 1 An application scenario diagram of an application data processing method according to an exemplary embodiment of the present disclosure;

[0064] Figure 2 A flowchart of an application data processing method according to an exemplary embodiment of the present disclosure is shown;

[0065] Figure 3 A schematic diagram showing the principle of algorithm matching model information according to an exemplary embodiment of the present disclosure;

[0066] Figure 4 A flowchart of an application data processing method according to another exemplary embodiment of the present disclosure is shown;

[0067] Figure 5 A flowchart of an application data processing method according to another exemplary embodiment of the present disclosure is shown;

[0068] Figure 6 A schematic diagram of the structure of an application data processing device according to an exemplary embodiment of the present disclosure;

[0069] Figure 7 It is a structural schematic diagram of an application data processing device according to another exemplary embodiment of the present disclosure;

[0070] Figure 8 It is a schematic diagram of the structure of an electronic device according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0071] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0072] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0073] With the development of terminal technology, more and more application software can be loaded in the terminal. In many application software, recognition algorithms are used for image recognition, and then corresponding stickers are added to the image according to the recognition results to achieve the effect of beautifying the image. For example, in a video or photo, a face can be recognized by a face recognition algorithm, and then stickers are added to the corresponding position of the face, and cat ears, cat whiskers and other materials are added to meet the user's needs for beautifying the picture. In the prior art, since different stickers need to correspond to different recognition algorithms and model files, the sticker materials, recognition algorithms, and model files are packaged together in the application software. However, the above method will increase the size of the application software, making it occupy a large amount of local storage space. Moreover, this method is not suitable for hot repair technology, which makes it impossible to achieve flexible updates of the model.

[0074] In response to the above technical problems, the present invention provides an application data processing method, device, equipment and storage medium, which can obtain the latest model from the cloud in a timely manner, thereby effectively reducing the size of the application software, reducing the local storage space occupied by the application software, and realizing flexible updating of the model. Figure 1 FIG. 1 is an application scenario diagram of an application data processing method according to an exemplary embodiment of the present disclosure, such as Figure 1As shown, all sticker options can be displayed on the terminal 10. Then, the user can determine the target sticker by touch or other operations. For example, sticker A, sticker B, and sticker C are displayed on the terminal display interface. When the user clicks sticker A, the sticker information is displayed, and sticker A is used as the target sticker. Then, the terminal 10 determines the model information corresponding to the sticker according to the sticker. There are many ways to determine the model according to the sticker. For example, a mapping relationship table between stickers and models can be built into the terminal, and the application model can be determined by looking up the table; or a matching algorithm can be set in the terminal to determine the corresponding application model according to the sticker. In a possible design, a mapping relationship table between stickers and models can be set in the terminal. When the terminal determines the sticker, the model corresponding to the sticker can be determined by looking up the mapping relationship table. The way to establish the mapping relationship table requires listing all the relationships between the sticker and the model one by one. If the mapping relationship table does not exist or needs to be updated, the latest mapping relationship table can also be downloaded from the cloud to upgrade and update the relationship between the sticker and the model. Therefore, for version upgrades, it is generally only necessary to upgrade the mapping relationship table, and the model information corresponding to the sticker is only upgraded from the cloud when the sticker is used. The advantage of this method is that there is no need to change the existing code structure, the memory space occupied by the program is reduced, and the upgrade and update are more flexible. In another possible design, the model information can be matched by a matching algorithm. The input of the matching algorithm is the sticker label, and the output of the matching algorithm is the model corresponding to the sticker label. Specifically, each sticker is provided with a label, and the algorithm can determine the recognition algorithm corresponding to the sticker according to the category indicated by the label. The recognition algorithm refers to an algorithm that recognizes an image and applies the model to the sticker, such as a face recognition algorithm, a gesture recognition algorithm, a three-dimensional image recognition algorithm, and the like. Different recognition algorithms can match different models. Therefore, the recognition algorithm can be first determined by the label information of the sticker, and then the corresponding model information is determined according to the recognition algorithm. Then, the terminal 10 obtains the model information of the local existing model. Then, the model information of the local existing model is compared one by one with the model information corresponding to the sticker to determine the model information of the target model missing locally. For example, there are models a, b, and c locally, and the models corresponding to the stickers are determined to be models a, c, and d in step 101. Then, by comparing one by one, the missing model is determined to be model d, and only model d needs to be used as the target model. Then, the terminal 10 can send a download request containing target model information, terminal model information, and application software version information to the cloud 20. After receiving the download request, the cloud 20 extracts identification information such as model name and number, terminal model information, and application software version information, and then sends the corresponding target model to the terminal 10. After receiving the target model sent by the cloud 20, the terminal 10 updates the local model library and can load the target model and stickers.

[0075] It should be noted that the cloud can receive model download requests sent by multiple terminals and send the target model to the corresponding cloud.

[0076] Figure 2 FIG. 1 is a flow chart of an application data processing method according to an exemplary embodiment of the present disclosure. Figure 2 As shown, the application data processing method provided in this embodiment includes:

[0077] Step 101: Determine the model information corresponding to the sticker.

[0078] In this embodiment, after the user selects a sticker in the terminal, the terminal determines the model information corresponding to the sticker based on the sticker. There are many ways to determine the model based on the sticker. For example, a mapping relationship table between stickers and models can be built into the terminal, and the application model can be determined by looking up the table; or a matching algorithm can be set in the terminal to determine the corresponding application model based on the sticker.

[0079] Optionally, determining the model information corresponding to the sticker includes: searching for the model information corresponding to the sticker through a preset mapping relationship table, where the model information includes: a model name and / or a model number.

[0080] Specifically, a mapping relationship table between stickers and models can be set in the terminal. When the terminal determines the sticker, the model corresponding to the sticker can be determined by looking up the mapping relationship table. To establish a mapping relationship table, all the relationships between stickers and models need to be listed one by one. If the mapping relationship table does not exist or needs to be updated, the latest mapping relationship table can also be downloaded from the cloud to upgrade the relationship between stickers and models. Therefore, for version upgrades, etc., it is generally only necessary to upgrade the mapping relationship table, and the model information corresponding to the sticker is only upgraded from the cloud when the sticker is used. The advantage of this method is that there is no need to change the existing code structure, reduce the memory space occupied by the program, and make upgrades and updates more flexible.

[0081] Optionally, determining the model information corresponding to the sticker includes: obtaining label information of the sticker; wherein the label information of the sticker is used to characterize the type of the sticker, and different types of stickers correspond to different recognition algorithms; the recognition algorithms include: face recognition algorithm, gesture recognition algorithm, and three-dimensional image recognition algorithm; according to the label information of the sticker, determining the recognition algorithm corresponding to the sticker; searching for model information matching the recognition algorithm, the model information includes: model name, and / or model number.

[0082] Specifically, the model information can also be matched by means of a matching algorithm. The input of the matching algorithm is the sticker label, and the output of the matching algorithm is the model corresponding to the sticker label. Specifically, each sticker is provided with a label, and the algorithm can determine the recognition algorithm corresponding to the sticker according to the category indicated by the label. A recognition algorithm refers to an algorithm that recognizes an image and applies a model to a sticker, such as a face recognition algorithm, a gesture recognition algorithm, a three-dimensional image recognition algorithm, and so on. Different recognition algorithms can match different models. Therefore, the recognition algorithm can be first determined by the label information of the sticker, and then the corresponding model information can be determined according to the recognition algorithm.

[0083] Optionally, when the number of recognition algorithms corresponding to the sticker is greater than 1, the model information matching the recognition algorithm is searched, including: searching for the model information matching each recognition algorithm separately; deduplicating and merging the model information matching all the recognition algorithms to obtain the model information corresponding to the sticker.

[0084] Specifically, when the number of recognition algorithms corresponding to the sticker is greater than 1, the terminal will obtain the model files required by each algorithm, merge and remove duplicates, and obtain the final set that needs to be downloaded. Figure 3 FIG. 1 is a schematic diagram showing the principle of algorithm matching model information according to an exemplary embodiment of the present disclosure, such as Figure 3 As shown in the figure, the recognition algorithms corresponding to sticker resources include: Algorithm A, Algorithm B, Algorithm C, and Algorithm D. Different recognition algorithms require different models. For example, Algorithm A corresponds to Model A and Model B, and Algorithm B corresponds to Model B and Model C. After deduplication and merging of model information, only Model B needs to be downloaded once.

[0085] Step 102: Determine the model information of the target model that is missing locally based on the model information.

[0086] In this embodiment, the model information of the existing local models can be first obtained. Then, the model information of the existing local models is compared one by one with the model information corresponding to the stickers to determine the model information of the target model that is missing locally. For example, there are models a, b, and c locally, and the models corresponding to the stickers are determined to be models a, c, and d in step 101. Then, through one-to-one comparison, it is determined that the missing model is model d, and only model d needs to be used as the target model. Therefore, it is only necessary to download and update model d. This method saves network resources and can implement updates more flexibly.

[0087] Step 103: Send a model download request to the cloud, where the model download request includes model information of the target model.

[0088] In this embodiment, the terminal can send a download request containing target model information to the cloud. After receiving the download request, the cloud extracts identification information such as the model name and number, and then sends the corresponding target model to the terminal.

[0089] Optionally, the model download request also includes terminal model information and application software version information, so that the cloud can send a target model that is compatible with the terminal and the application software to the terminal based on the terminal model information and the application software version information.

[0090] Specifically, the download request may also include terminal model information and application software version information. The cloud sends a target model that is compatible with the terminal and application software to the terminal based on the terminal model information and application software version information. For example, Android and Apple systems may have different models, and the model suitable for the Android system is sent to the terminal of the Android system.

[0091] Step 104: Receive the target model sent from the cloud.

[0092] In this embodiment, the terminal receives the target model sent from the cloud and updates the local model library.

[0093] In this embodiment, by determining the model information corresponding to the sticker; determining the model information of the target model missing locally according to the model information; sending a model download request to the cloud, the model download request includes the model information of the target model; so that the cloud sends the target model to the terminal according to the model information of the target model; and receiving the target model sent by the cloud. This can effectively reduce the size of the application software and reduce the local storage space occupied by the application software.

[0094] Figure 4 FIG. 1 is a flow chart of an application data processing method according to another exemplary embodiment of the present disclosure. Figure 4 As shown, the application data processing method provided in this embodiment includes:

[0095] Step 201: Display sticker options on the application interface.

[0096] Step 202: Receive user operation information for sticker options.

[0097] Step 203: Determine the sticker according to the operation information.

[0098] In this embodiment, all sticker options can be displayed on the terminal. Then, the user can determine the sticker by touch or other operations. For example, sticker A, sticker B, and sticker C are displayed on the terminal display interface. When the user clicks sticker A, the sticker information is displayed and sticker A is used as the target sticker. In this way, only the model corresponding to sticker A needs to be downloaded through subsequent steps, and the models corresponding to sticker B and sticker C do not need to be downloaded, which can save local storage space, and also save network resources, and realize more flexible upgrades and updates.

[0099] Step 204: Determine the model information corresponding to the sticker.

[0100] Step 205: Determine the model information of the target model that is missing locally based on the model information.

[0101] Step 206: Send a model download request to the cloud, where the model download request includes model information of the target model.

[0102] Step 207: Receive the target model sent from the cloud.

[0103] In this embodiment, the specific implementation process and technical principles of steps 204 to 207 can be found in Figure 2 The relevant descriptions in steps 101 to 104 in the method shown are not repeated here.

[0104] In this embodiment, by determining the model information corresponding to the sticker; determining the model information of the target model missing locally according to the model information; sending a model download request to the cloud, the model download request includes the model information of the target model; so that the cloud sends the target model to the terminal according to the model information of the target model; and receiving the target model sent by the cloud. This can effectively reduce the size of the application software and reduce the local storage space occupied by the application software.

[0105] In addition, the present implementation can also display sticker options on the application interface and receive user operation information on sticker options to determine the target sticker. Therefore, only the model corresponding to the target sticker needs to be downloaded, which can save local storage space and network resources, and realize more flexible upgrade and update.

[0106] Figure 5 FIG. 1 is a flow chart of an application data processing method according to another exemplary embodiment of the present disclosure. Figure 5 As shown, the application data processing method provided in this embodiment includes:

[0107] Step 301: Determine the model information corresponding to the sticker.

[0108] Step 302: Determine the model information of the target model that is missing locally based on the model information.

[0109] Step 303: Send a model download request to the cloud, where the model download request contains model information of the target model.

[0110] Step 304: Receive the target model sent from the cloud.

[0111] In this embodiment, the specific implementation process and technical principles of steps 301 to 304 are shown in Figure 2 The relevant descriptions in steps 101 to 104 in the method shown are not repeated here.

[0112] Step 305: After the target model is received, load the target model.

[0113] Step 306: Load stickers.

[0114] In this embodiment, after the target model is received, the target model can be loaded, and then the stickers can be loaded, thereby realizing flexible updating of the model. For example, a cartoon sticker includes a cat ear model and a cat whisker model. After the version upgrade, a cat tail model is added to the cartoon sticker. After downloading the cat tail model, the cat tail model is loaded and the stickers are loaded to display the complete sticker pattern, that is, an image including cat ears, cat whiskers, and cat tails.

[0115] In this embodiment, by determining the model information corresponding to the sticker; determining the model information of the target model missing locally according to the model information; sending a model download request to the cloud, the model download request includes the model information of the target model; so that the cloud sends the target model to the terminal according to the model information of the target model; and receiving the target model sent by the cloud. This can effectively reduce the size of the application software and reduce the local storage space occupied by the application software.

[0116] In addition, this embodiment can also load the target model and the sticker after the target model is received, thereby effectively reducing the size of the application software and the local storage space occupied by the application software.

[0117] Figure 6 FIG. 1 is a schematic diagram of a structure of an application data processing device according to an exemplary embodiment of the present disclosure. Figure 6 As shown, the application data processing device 30 provided in this embodiment includes:

[0118] A first determination module 301, used to determine model information corresponding to the sticker;

[0119] The second determination module 302 determines the model information of the target model that is missing locally according to the model information;

[0120] The sending module 303 is used to send a model download request to the cloud, where the model download request includes model information of the target model; so that the cloud sends the target model to the terminal according to the model information of the target model;

[0121] The receiving module 304 is used to receive the target model sent from the cloud.

[0122] In a possible design, the first determining module 301 is specifically configured to:

[0123] The model information corresponding to the sticker is searched through a preset mapping relationship table, where the model information includes: model name and / or model number.

[0124] In a possible design, the first determining module 301 is further configured to:

[0125] Obtaining label information of the sticker; wherein the label information of the sticker is used to characterize the type of the sticker, and different types of stickers correspond to different recognition algorithms; the recognition algorithms include: face recognition algorithm, gesture recognition algorithm, and three-dimensional image recognition algorithm;

[0126] According to the label information of the sticker, determine the recognition algorithm corresponding to the sticker;

[0127] Find the model information that matches the recognition algorithm, where the model information includes: model name and / or model number.

[0128] In a possible design, when the number of recognition algorithms corresponding to the sticker is greater than 1, the model information matching the recognition algorithm is searched, including:

[0129] Find the model information matched by each recognition algorithm respectively;

[0130] The model information matched by all recognition algorithms is deduplicated and merged to obtain the model information corresponding to the sticker.

[0131] In a possible design, the second determining module 302 is specifically configured to:

[0132] Get the model information of the local existing model;

[0133] The model information of the existing local model is compared one by one with the model information corresponding to the sticker to determine the model information of the target model that is missing locally.

[0134] In a possible design, the model download request also includes terminal model information and application software version information, so that the cloud can send a target model that is compatible with the terminal and the application software to the terminal based on the terminal model information and the application software version information.

[0135] The device provided in this embodiment can be used to perform Figure 2 The technical solution of the method embodiment shown has similar implementation principles and technical effects, which will not be repeated here.

[0136] In this embodiment, by determining the model information corresponding to the sticker; determining the model information of the target model missing locally according to the model information; sending a model download request to the cloud, the model download request includes the model information of the target model; so that the cloud sends the target model to the terminal according to the model information of the target model; and receiving the target model sent by the cloud. This can effectively reduce the size of the application software and reduce the local storage space occupied by the application software.

[0137] exist Figure 6 Based on the embodiment shown, Figure 7 FIG. 1 is a schematic diagram of a structure of an application data processing device according to another exemplary embodiment of the present disclosure. Figure 7 As shown, the application data processing device provided in this embodiment also includes:

[0138] The display module 305 is used for:

[0139] Show sticker options on the app interface;

[0140] Receive user operation information on sticker options;

[0141] Determine the sticker based on the operation information.

[0142] In a possible design, the system further includes a loading module 306, configured to:

[0143] After the target model is received, load the target model;

[0144] Loading stickers.

[0145] The device provided in this embodiment can be used to perform Figure 2 , Figure 4 , Figure 5 The technical solution of the method embodiment shown has similar implementation principles and technical effects, which will not be repeated here.

[0146] In this embodiment, by determining the model information corresponding to the sticker; determining the model information of the target model missing locally according to the model information; sending a model download request to the cloud, the model download request includes the model information of the target model; so that the cloud sends the target model to the terminal according to the model information of the target model; and receiving the target model sent by the cloud. This can effectively reduce the size of the application software and reduce the local storage space occupied by the application software.

[0147] In addition, this embodiment can also load the target model and the sticker after the target model is received, thereby effectively reducing the size of the application software and the local storage space occupied by the application software.

[0148] Figure 8 FIG. 1 is a schematic diagram of the structure of an electronic device according to an exemplary embodiment of the present disclosure. Figure 8 As shown, this embodiment provides an electronic device 40, including:

[0149] Processor 401; and

[0150] Memory 402, used to store executable instructions of the processor, and the memory may also be flash (flash memory);

[0151] The processor 401 is configured to execute the various steps in the above method by executing executable instructions. For details, please refer to the relevant description in the above method embodiment.

[0152] Optionally, the memory 402 may be independent or integrated with the processor 401 .

[0153] When the memory 402 is a device independent of the processor 401, the electronic device 40 may further include:

[0154] The bus 403 is used to connect the processor 401 and the memory 402 .

[0155] This embodiment further provides a readable storage medium, in which a computer program is stored. When at least one processor of an electronic device executes the computer program, the electronic device executes the methods provided in the above-mentioned various implementation modes.

[0156] This embodiment also provides a program product, which includes a computer program stored in a readable storage medium. At least one processor of the electronic device can read the computer program from the readable storage medium, and at least one processor executes the computer program so that the electronic device implements the methods provided in the above various embodiments.

[0157] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present disclosure, rather than to limit them. Although the present disclosure has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. An application data processing method, characterized in that: include: Determine model information corresponding to the sticker, wherein the sticker corresponds to at least two pieces of model information; Determining model information of the target model that is missing locally based on the model information; Sending a model download request to the cloud, wherein the model download request includes model information of the target model; so that the cloud sends the target model to the terminal according to the model information of the target model; Receiving the target model sent by the cloud; Determining model information of a target model that is missing locally based on the model information includes: Get the model information of the local existing model; The model information of the existing local model is compared one by one with the model information corresponding to the sticker to determine the model information of the target model that is missing locally.

2. The method according to claim 1, characterized in that Determine the model information corresponding to the sticker, including: The model information corresponding to the sticker is searched through a preset mapping relationship table, where the model information includes: a model name and / or a model number.

3. The method according to claim 1, characterized in that Determine the model information corresponding to the sticker, including: Obtaining label information of the sticker; wherein the label information of the sticker is used to characterize the type of the sticker, and different types of stickers correspond to different recognition algorithms; the recognition algorithms include: face recognition algorithm, gesture recognition algorithm, and three-dimensional image recognition algorithm; Determine a recognition algorithm corresponding to the sticker according to the label information of the sticker; The model information matching the recognition algorithm is searched, wherein the model information includes: a model name and / or a model number.

4. The method according to claim 3, characterized in that When the number of recognition algorithms corresponding to the sticker is greater than 1, searching for model information matching the recognition algorithm includes: Find the model information matched by each recognition algorithm respectively; All model information matched by the recognition algorithm is deduplicated and merged to obtain model information corresponding to the sticker.

5. The method according to claim 1, characterized in that The model download request also includes terminal model information and application software version information, so that the cloud can send the target model compatible with the terminal and application software to the terminal according to the terminal model information and application software version information.

6. The method according to any one of claims 1 to 5, characterized in that Before determining the model information corresponding to the sticker, it also includes: Displaying the sticker options on the application interface; Receive user operation information for the sticker option; The sticker is determined according to the operation information.

7. The method according to any one of claims 1 to 5, characterized in that Also includes: After the target model is received, loading the target model; Load said sticker.

8. An application data processing device, characterized in that: include: A first determination module is used to determine model information corresponding to a sticker, wherein the sticker corresponds to at least two pieces of model information; A second determination module determines model information of a target model that is missing locally based on the model information; A sending module, used to send a model download request to the cloud, wherein the model download request includes model information of the target model; so that the cloud sends the target model to the terminal according to the model information of the target model; A receiving module, used for receiving the target model sent from the cloud; The second determination module is specifically used to obtain model information of the local existing model; compare the model information of the local existing model with the model information corresponding to the sticker one by one, and determine the model information of the target model that is missing locally.

9. An electronic device, characterized in that: include: processor; as well as, A memory, configured to store executable instructions of the processor; Wherein, the processor is configured to perform the application data processing method according to any one of claims 1 to 7 by executing the executable instructions.

10. A storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the application data processing method according to any one of claims 1 to 7 is implemented.

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