Resource dynamic loading method and device, electronic equipment and storage medium

Abstract

The application provides a resource dynamic loading method and device, electronic equipment and a storage medium. The resource dynamic loading method comprises the following steps: after obtaining a starting signal of a first application, determining a corresponding scene feature according to scene information acquired in real time; determining resource data corresponding to the scene information according to the scene feature; determining configuration data corresponding to the scene information according to the scene feature; and loading the resource data according to the configuration data. The application relates to the technical field of augmented reality, and can enhance the accuracy of resource data loading of augmented reality.

Description

Technical Field

[0001] This application relates to the field of augmented reality technology, and in particular to a method, apparatus, electronic device, and storage medium for dynamically loading resources. Background Technology

[0002] With the continuous development of the industrial sector, augmented reality (AR) technology has been widely applied in various industrial scenarios, such as equipment maintenance, operation training, fault diagnosis, and repair. However, as AR technology becomes more deeply integrated into industrial applications, the dynamic changes and real-time requirements of AR virtual simulation scenarios in the industrial field are becoming increasingly stringent. Traditional resource tree management and loading technologies have revealed problems such as a single resource loading method, low efficiency, and inability to meet the construction needs of large-scale real-time rendering scenes when addressing these challenges. Loading all required resource files at once results in excessively long initial loading times, consumes a large amount of storage space, leads to decreased device performance, and results in a poor user experience. Summary of the Invention

[0003] In view of the above, it is necessary to propose a method, device, electronic device and storage medium for dynamic loading of resources in order to solve the technical problem of low efficiency in loading resource data.

[0004] This application provides a method for dynamically loading resources, applied to an electronic device. The method includes: after receiving a startup signal of a first application, determining corresponding scene features based on real-time acquired scene information; determining resource data corresponding to the scene information based on the scene features; determining configuration data corresponding to the scene information based on the scene features; and loading the resource data based on the configuration data.

[0005] In some embodiments, the method further includes: before loading the resource data according to the configuration data, traversing the resource data, and if multiple resource data are the same, retaining any one of the multiple resource data.

[0006] In some embodiments, determining the corresponding scene feature based on the scene information acquired in real time includes: determining at least one candidate scene feature based on the identifier of the scene information; and determining the scene feature corresponding to the scene information from the at least one candidate scene feature in response to the selection instruction corresponding to the identifier of the scene information.

[0007] In some embodiments, the selection instructions include one or more of the following: touch instructions and voice instructions.

[0008] In some embodiments, determining the resource data corresponding to the scene information based on the scene features includes: classifying the scene features to obtain a scene category corresponding to the scene information; determining candidate resource data from multiple initial resource data based on the scene category; performing semantic analysis on the scene features to obtain a first semantic of the scene features; performing semantic analysis on the candidate resource data to obtain a second semantic of the candidate resource data; and determining the resource data from the candidate resource data based on the first semantic and the second semantic.

[0009] In some embodiments, determining the configuration data corresponding to the scene information based on the scene features includes: classifying the scene features to obtain the scene category corresponding to the scene information; determining the priority of the scene information based on the scene category; and determining the configuration data corresponding to the scene information from multiple initial configuration data based on the priority.

[0010] In some embodiments, loading the resource data according to the configuration data includes: determining the loading time of the resource data according to the configuration data; generating a loading strategy for the resource data according to the loading time, the loading strategy being used to characterize the loading order of multiple resource data; and loading the resource data according to the loading strategy.

[0011] This application embodiment also provides a resource dynamic loading device, the device comprising: an acquisition module, configured to determine corresponding scene features based on real-time acquired scene information after receiving a startup signal of a first application; a determination module, configured to determine resource data corresponding to the scene information based on the scene features; the determination module is further configured to determine configuration data corresponding to the scene information based on the scene features; and the determination module is further configured to load the resource data based on the configuration data.

[0012] This application also provides an electronic device, which includes: a memory storing at least one instruction; and a processor executing the instructions stored in the memory to implement the aforementioned resource dynamic loading method.

[0013] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the resource dynamic loading method.

[0014] As can be seen from the above technical solutions, the real-time monitoring in this application embodiment is used to implement the first application of augmented reality. After receiving the start signal of the first application, the corresponding scene features are determined based on the scene information acquired in real time. This allows for the identification of key information in the augmented reality application scene based on the scene features, providing data support for subsequent dynamic loading of resource data and improving the accuracy of resource data loading. Then, resource data and configuration data corresponding to the scene information are determined based on the scene features, and the resource data is loaded based on the configuration data. In this way, the matching degree between resource data and scene information can be improved during the resource data loading process, thereby improving the accuracy of resource data loading. Attached Figure Description

[0015] Figure 1 This is an application scenario diagram of a resource dynamic loading method provided in an embodiment of this application.

[0016] Figure 2 This is a flowchart of a resource dynamic loading method provided in an embodiment of this application.

[0017] Figure 3 This is a flowchart of a method for determining scene features provided in an embodiment of this application.

[0018] Figure 4 This is a flowchart of a method for determining resource data provided in an embodiment of this application.

[0019] Figure 5 This is a flowchart of a method for determining configuration data provided in an embodiment of this application.

[0020] Figure 6 This is a flowchart of a method for loading resource data based on configuration data according to an embodiment of this application.

[0021] Figure 7 This is a functional block diagram of a resource dynamic loading device provided in an embodiment of this application.

[0022] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0023] To better understand the purpose, features, and advantages of this application, a detailed description of the application is provided below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of this application can be combined with each other. Numerous specific details are set forth in the following description to provide a thorough understanding of this application; the described embodiments are only a part of the embodiments of this application, and not all of them.

[0024] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "a plurality of" means two or more, unless otherwise explicitly specified.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0026] This application provides a method for dynamically loading resources, which can be applied to one or more electronic devices. An electronic device is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions. Its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0027] Electronic devices can be any electronic product that allows human-computer interaction with a customer, such as personal computers, tablets, smartphones, personal digital assistants (PDAs), game consoles, interactive network television (IPTV), smart wearable devices, etc.

[0028] Electronic devices may also include network devices and / or client devices. The network devices include, but are not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of hosts or network servers.

[0029] The networks in which electronic devices are located include, but are not limited to, the Internet, wide area networks, metropolitan area networks, local area networks, and virtual private networks (VPNs).

[0030] like Figure 1The diagram illustrates an application scenario of a resource dynamic loading method according to an embodiment of this application. This method can be applied to an electronic device 100 capable of implementing augmented reality functionality. The electronic device 100 can be a wearable electronic device, a handheld electronic device, etc., and this application does not limit the specific form of the electronic device 100. After the first application for augmented reality functionality is launched in the electronic device 100, the electronic device 100 loads virtual scene information in real time according to the launch signal of the first application. The virtual scene information can be a digital image composed of images rendered by the electronic device 100. For example, the virtual scene information may include... Figure 1 The building 200 shown may also include, for example: Figure 1 The plant 300 is shown. Specifically, after receiving the activation signal of the first application, the electronic device 100 determines the user's position, posture, and line of sight, thereby determining the position and direction of the target in the real-world scene. It identifies and tracks the real-world scene, achieving the fusion of virtual objects and the real-world scene. It creates virtual objects or information and merges them with the real-world scene, allowing the user to see the interaction between virtual objects and the real-world scene. It projects virtual images or information into the real-world scene, allowing the user to see the virtual objects or information. The user can then interact with the virtual objects or information, such as through gestures, voice, or touch, thus obtaining virtual scene information associated with the real-world scene.

[0031] In related technologies, when loading resource data for augmented reality scenarios, all resource data in the database is typically loaded when the electronic device 100 starts up, which may result in a high load on the electronic device 100 or the first application.

[0032] In this application, after receiving the start signal of the first application, the corresponding scene features are determined based on the scene information acquired in real time (e.g., such as...). Figure 1 (The building 200 and the plants 300 are shown). For example, as... Figure 1 As shown, when the virtual scene information includes building 200 and plant 300, it can be determined that the virtual scene is an outdoor scene, and the scene features of the virtual scene can be determined as the features of building 200 and plant 300. Based on the scene features, the resource data corresponding to the scene information is determined, for example, such as... Figure 1 The animals 400 and the target person 500 are shown. When the electronic device 100 determines that the virtual scene output to the user is an outdoor scene based on scene characteristics, it can be determined that the virtual scene output by the electronic device 100 includes scene features related to the outdoor scene. Therefore, when loading resource data subsequently, it can be determined that the resource data to be loaded is resource data related to the outdoor scene (e.g., outdoor scene features). Figure 1(The animals shown are 400 and the target person is 500). The electronic device 100 also determines the configuration data corresponding to the scene information based on the scene characteristics, and then loads the resource data based on the configuration data.

[0033] like Figure 2 The diagram shown is a flowchart of a dynamic resource loading method according to an embodiment of this application. The order of the steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements. The dynamic resource loading method provided in this embodiment includes the following steps.

[0034] S20: After receiving the start signal of the first application, determine the corresponding scene characteristics based on the scene information acquired in real time.

[0035] In one embodiment of this application, the first application may be an application for implementing augmented reality functionality. Augmented Reality (AR) technology is a technique that merges pre-stored virtual information with scenes captured in real time by a camera device, enabling the application of virtual information such as text, images, 3D models, music, and videos from electronic devices into real-world scenes.

[0036] In one embodiment of this application, the activation signal of the first application is used to characterize the need to realize augmented reality functions through the first application. After receiving the activation signal of the first application, the electronic device determines the user's position, posture, and gaze direction based on the scene information captured in real time by the camera device, thereby determining the position and direction of the target in the scene, thus acquiring scene information in real time, and accurately locating and rendering virtual information based on the user's position and direction. The scene information can be surveillance video or surveillance images of actual objects in the scene, or any audio data that can be collected in the scene.

[0037] In one embodiment of this application, different scene features can be extracted for different types of scene information. Specifically, for a method to determine the corresponding scene features based on real-time acquired scene information, please refer to [link to relevant documentation]. Figure 3 The corresponding detailed explanation.

[0038] S21, determine the resource data corresponding to the scene information based on the scene characteristics.

[0039] In one embodiment of this application, during the dynamic loading of resource data, the resource data to be loaded can be determined based on the scene characteristics in the virtual scene output by the electronic device. This allows for the selection of resource data from multiple sources before loading, avoiding the loading of resource data irrelevant to the scene, thereby improving the loading efficiency and preventing resource waste. Furthermore, determining the resource data to be loaded based on scene characteristics avoids loading all resource data in the database at once when the first application starts, reducing memory usage and improving the stability and efficiency of the resource data loading process. In addition, for scenes containing various objects and complex environments, resources can be dynamically loaded and optimized based on scene characteristics, ensuring that the loaded resource data adapts to the needs of different scenes, thus improving the stability of the augmented reality effects provided by the first application. For example, when the scene characteristics in the virtual scene indicate that the virtual scene is an outdoor scene, resource data associated with the outdoor scene can be loaded. Exemplarily, the resource data can be image data representing outdoor sports equipment, target person data representing outdoor pedestrians, or vehicle target data representing outdoor transportation. This application does not limit the specific content of the resource data. For example, when scene features in a virtual scene indicate that the virtual scene is a classroom scene, resource data associated with the classroom scene can be loaded. For instance, the resource data could be image data representing the interior decoration of the classroom, target character data representing students or teachers in the classroom, or audio data representing students reading aloud in the classroom. This application does not limit the specific content of the resource data.

[0040] In one embodiment of this application, for a specific method of determining the resource data corresponding to scene information based on scene features, please refer to [link to relevant documentation]. Figure 4 The corresponding detailed explanation.

[0041] S22, determine the configuration data corresponding to the scene information based on the scene characteristics.

[0042] In one embodiment of this application, the configuration data is recorded in the parameters of the configuration file, which characterize the strategy for loading resource data. In the configuration file, different resource data correspond to different categories, and different categories of resource data correspond to different priorities. For example, when the resource data is image data, if the resource data is used to characterize the texture of the foreground area or target in the scene, then the resource data can be determined to have a higher priority; if the resource data is used to characterize the color of the background area or target in the scene, then the resource data can be determined to have a lower priority. Thus, by determining the priority of different categories of data, resource data that has a greater impact on the scene can be loaded first during the resource data loading process, thereby improving the accuracy of implementing basic functions and visual effects in the scene.

[0043] In one embodiment of this application, in order to ensure that the strategy for loading resource data conforms to the scene information during the process of loading resource data, configuration data corresponding to the scene information can be determined based on scene characteristics. For details, please refer to [link to specific method]. Figure 5 The corresponding detailed explanation.

[0044] S23, Load the resource data according to the configuration data.

[0045] In one embodiment of this application, before loading the resource data according to the configuration data, the resource data is traversed. If multiple resource data are found to be identical, any one of the multiple resource data is retained. This allows for the identification of duplicate or redundant data in the resource data before loading, thereby reducing the number of resource data to be loaded and improving the efficiency of resource data loading.

[0046] In one embodiment of this application, for details on the method of loading resource data according to configuration data in the configuration file, please refer to [link to relevant documentation]. Figure 6 The corresponding detailed explanation.

[0047] As can be seen from the above technical solutions, the real-time monitoring in this application embodiment is used to implement the first application of augmented reality. After receiving the start signal of the first application, the corresponding scene features are determined based on the scene information acquired in real time. This allows for the identification of key information in the augmented reality application scene based on the scene features, providing data support for subsequent dynamic loading of resource data and improving the accuracy of resource data loading. Then, resource data and configuration data corresponding to the scene information are determined based on the scene features, and the resource data is loaded based on the configuration data. In this way, the matching degree between resource data and scene information can be improved during the resource data loading process, thereby improving the accuracy of resource data loading.

[0048] like Figure 3 The diagram shown is a flowchart of a method for determining scene features according to an embodiment of this application. The order of steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements. The method for determining scene features provided in this embodiment includes the following steps.

[0049] S30, determine at least one corresponding candidate scene feature based on the identifier of the scene information.

[0050] In one embodiment of this application, when the scene information is image data, to improve the accuracy of determining scene features based on the scene information, at least one corresponding candidate scene feature can be determined based on the identifier of the scene information. The identifier of the scene information is used to characterize the candidate scene features associated with the scene information. For example, when the scene information is a game scene, the candidate scene features corresponding to the scene information can be multiple levels in the game scene, and the identifier of the scene information can be used to indicate different levels in the game scene.

[0051] S31, in response to the selection instruction corresponding to the identifier of the scene information, determine the scene feature corresponding to the scene information from the at least one candidate scene feature.

[0052] In one embodiment of this application, after determining the candidate scene features corresponding to scene information, the electronic device (e.g., a virtual reality device) can output an identifier of the scene information and receive a selection instruction input by the user corresponding to the identifier of the scene information. The selection instruction can be one or more combinations of the following: touch instructions, voice instructions. In response to the selection instruction corresponding to the identifier of the scene information, the scene feature corresponding to the scene information is determined from at least one candidate scene feature. For example, when the scene information is a game scene, the candidate scene features corresponding to the scene information can be multiple levels in the game scene, and the identifier of the scene information can be used to indicate different levels in the game scene. The selection instruction can be a voice instruction input by the user to the electronic device, used to select a level corresponding to the game scene from at least one game level. For example, the voice instruction can be "select the first level," or it can be "select the first level and the second level."

[0053] like Figure 4 The diagram shown is a flowchart of a method for determining resource data according to an embodiment of this application. The order of steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements. The method for determining resource data provided in this embodiment includes the following steps.

[0054] S40, classify the scene features to obtain the scene category corresponding to the scene information.

[0055] In one embodiment of this application, a pre-trained classification model can be used to classify scene features and determine the scene category corresponding to the scene information. The classification model can be a convolutional neural network model, a perceptron model, a support vector machine model, etc., and this application does not limit this to any particular model.

[0056] For example, when the scene features are the image features corresponding to the image data, if the image features represent that the image data includes monitors, telephones, work tools, etc., then the scene category corresponding to the classification result output by the classification model can be "work scene"; if the image features represent that the image data includes blackboards, desks and chairs, podiums, etc., then the scene category corresponding to the classification result output by the classification model can be "teaching scene"; if the image features represent that the image data includes blood pressure monitors, eye charts, etc., then the scene category corresponding to the classification result output by the classification model can be "medical scene".

[0057] S41, determine candidate resource data from multiple initial resource data according to the scene category.

[0058] In one embodiment of this application, the initial resource data may be resource data pre-stored in a server or database that is communicatively connected to the electronic device. Each initial resource data corresponds to a category, and if the category of any initial resource data matches the scene category of the scene information, that initial resource data is determined as candidate resource data.

[0059] S42, perform semantic analysis on the scene features to obtain the first semantics of the scene features.

[0060] In one embodiment of this application, a pre-trained semantic recognition model can be used to perform semantic analysis on scene features. The semantic recognition model can be a word embedding model, a transfer learning model, etc., and this application does not limit it.

[0061] In one embodiment of this application, the first semantic of the scene feature is used to characterize the meaning of the content contained in the scene information. For example, the semantic of the scene feature could be "This is a work scene, which includes work supplies such as computers, monitors, and telephones".

[0062] S43, perform semantic analysis on the candidate resource data to obtain the second semantics of the candidate resource data.

[0063] In one embodiment of this application, a semantic recognition model can be used to perform semantic analysis on resource data. The second semantic of the resource data is used to characterize the meaning of the content contained in the resource data. For example, the second semantic of the resource data could be "the resource data includes work supplies such as staplers, paper and pens, and monitors, as well as the sound of typing on a keyboard."

[0064] S44, determine the resource data from the candidate resource data based on the first semantics and the second semantics.

[0065] In one embodiment of this application, the similarity between the first semantic and the second semantic can be determined, and the candidate resource data corresponding to the highest similarity can be determined as the resource data corresponding to the scene information. Furthermore, the candidate resource data can be sorted according to the order of similarity from high to low, and the multiple candidate resource data with the highest order can be determined as the resource data corresponding to the scene information.

[0066] like Figure 5 The diagram shown is a flowchart of a method for determining configuration data according to an embodiment of this application. The order of steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements. The method for determining configuration data provided in this embodiment includes the following steps.

[0067] S50, classify the scene features to obtain the scene category corresponding to the scene information.

[0068] In one embodiment of this application, a pre-trained classification model can be used to classify scene features and determine the scene category corresponding to the scene information. The classification model can be a convolutional neural network model, a perceptron model, a support vector machine model, etc., and this application does not limit this to any particular model.

[0069] For example, when the scene features are the image features corresponding to the image data, if the image features represent that the image data includes monitors, telephones, work tools, etc., then the scene category corresponding to the classification result output by the classification model can be "work scene"; if the image features represent that the image data includes blackboards, desks and chairs, podiums, etc., then the scene category corresponding to the classification result output by the classification model can be "teaching scene"; if the image features represent that the image data includes blood pressure monitors, eye charts, etc., then the scene category corresponding to the classification result output by the classification model can be "medical scene".

[0070] S51, determine the priority of the scene information according to the scene category.

[0071] In one embodiment of this application, the priority of scene information can be determined according to a pre-set correspondence between scene categories and priorities.

[0072] S52, determine the configuration data corresponding to the scene information from multiple initial configuration data according to the priority.

[0073] In one embodiment of this application, the initial configuration data with the highest priority can be determined as the configuration data corresponding to the scene information. Alternatively, multiple initial configuration data sets with higher priority can be determined as the configuration data corresponding to the scene information.

[0074] like Figure 6The diagram shown is a flowchart of a method for loading resource data according to an embodiment of this application. The order of steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements. An embodiment of this application provides a method for loading resource data, including the following steps.

[0075] S60, determine the loading time of the resource data based on the configuration data.

[0076] In one embodiment of this application, the configuration file is used to store configuration data related to the resource data loading strategy. The configuration data includes at least time parameters for controlling the resource data loading time, and asynchronous or synchronous loading parameters for controlling the resource data loading method.

[0077] S61, Generate a loading strategy for the resource data based on the loading time, wherein the loading strategy is used to characterize the loading order of multiple resource data.

[0078] In one embodiment of this application, each resource data is arranged in ascending order of loading time, and the loading method of the resource data is determined according to the configuration file, confirming whether the loading method corresponding to each resource data is asynchronous or synchronous. The arrangement order and loading method of the arranged resource data constitute the resource data loading strategy.

[0079] S62, Load the resource data according to the loading strategy.

[0080] In one embodiment of this application, when any resource data is loaded asynchronously, it indicates that the resource is loaded without blocking the main thread of the first application, ensuring that the scene can still respond to user input and operations while loading resources. When any resource data is loaded synchronously, it indicates that subsequent data loading tasks or user-input instructions will be executed only after the resource data has been loaded.

[0081] Please see Figure 7 , Figure 7 This is a functional block diagram of a resource dynamic loading device according to an embodiment of this application. The resource dynamic loading device 71 includes an acquisition module 711 and a determination module 712. The module / unit referred to in this application refers to a series of computer-readable instruction segments that can be executed by the processor 13 and perform a fixed function, and which are stored in the memory 12. In this embodiment, the functions of each module / unit will be described in detail in subsequent embodiments.

[0082] The acquisition module 711 is used to determine the corresponding scene features based on the scene information acquired in real time after receiving the start signal of the first application.

[0083] The determining module 712 is used to determine the resource data corresponding to the scene information based on the scene features.

[0084] The determining module 712 is further configured to determine the configuration data corresponding to the scene information based on the scene features.

[0085] The determining module 712 is further configured to load the resource data according to the configuration data.

[0086] In some embodiments, the acquisition module 711 is further configured to determine at least one corresponding candidate scene feature based on the identifier of the scene information; and in response to the selection instruction corresponding to the identifier of the scene information, determine the scene feature corresponding to the scene information from the at least one candidate scene feature.

[0087] In some embodiments, the determining module 712 is further configured to classify the scene features to obtain the scene category corresponding to the scene information; determine candidate resource data from multiple initial resource data according to the scene category; perform semantic analysis on the scene features to obtain the first semantic of the scene features; perform semantic analysis on the candidate resource data to obtain the second semantic of the candidate resource data; and determine the resource data from the candidate resource data according to the first semantic and the second semantic.

[0088] In some embodiments, the determining module 712 is further configured to classify the scene features to obtain the scene category corresponding to the scene information; determine the priority of the scene information according to the scene category; and determine the configuration data corresponding to the scene information from multiple initial configuration data according to the priority.

[0089] In some embodiments, the determining module 712 is further configured to determine the loading time of the resource data based on the configuration data; generate a loading strategy for the resource data based on the loading time, the loading strategy being used to characterize the loading order of multiple resource data; and load the resource data according to the loading strategy.

[0090] In some embodiments, the determining module 712 is further configured to traverse the resource data before loading the resource data according to the configuration data, and retain any one of the multiple resource data if the traversed multiple resource data are the same.

[0091] Please see Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 100 includes a memory 12 and a processor 13. The memory 12 is used to store computer-readable instructions, and the processor 13 executes the computer-readable instructions stored in the memory to implement a resource dynamic loading method as described in any of the above embodiments.

[0092] In one embodiment of this application, the electronic device 100 further includes a bus and a computer program stored in the memory 12 and executable on the processor 13, such as a resource dynamic loader.

[0093] Figure 8 Only an electronic device 100 with memory 12 and processor 13 is shown; those skilled in the art will understand that... Figure 8 The structure shown does not constitute a limitation on the electronic device 100, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0094] Combination Figure 8 The memory 12 in the electronic device 100 stores a plurality of computer-readable instructions to implement the dynamic resource loading method. The processor 13 can execute the plurality of instructions to achieve the following: after receiving the start signal of the first application, determining the corresponding scene features based on the scene information acquired in real time; determining the resource data corresponding to the scene information based on the scene features; determining the configuration data corresponding to the scene information based on the scene features; and loading the resource data based on the configuration data.

[0095] Specifically, the processor 13's implementation method for the above instructions can be found in [reference needed]. Figure 8 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0096] Those skilled in the art will understand that the schematic diagram is merely an example of the electronic device 100 and does not constitute a limitation on the electronic device 100. The electronic device 100 may be a bus-type structure or a star-type structure. The electronic device 100 may also include more or fewer other hardware or software than shown in the diagram, or different component arrangements. For example, the electronic device 100 may also include input / output devices, network access devices, etc.

[0097] It should be noted that electronic device 100 is only an example. Other existing or future electronic products that are suitable for this application should also be included within the scope of protection of this application and are incorporated herein by reference.

[0098] The memory 12 includes at least one type of readable storage medium, which can be non-volatile or volatile. The readable storage medium includes flash memory, portable hard drives, multimedia cards, card-type memory (e.g., SD or DX memory), magnetic storage, magnetic disks, optical disks, etc. In some embodiments, the memory 12 can be an internal storage unit of the electronic device 100, such as the portable hard drive of the electronic device 100. In other embodiments, the memory 12 can also be an external storage device of the electronic device 100, such as a plug-in portable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 100. The memory 12 can be used not only to store application software and various types of data installed on the electronic device 100, such as the code of a resource dynamic loader, but also to temporarily store data that has been output or will be output.

[0099] In some embodiments, the processor 13 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits packaged with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 13 is the control unit of the electronic device 100, connecting to various components of the electronic device 100 via various interfaces and lines. It executes programs or modules stored in the memory 12 (e.g., executing dynamic resource loading programs) and calls data stored in the memory 12 to perform various functions of the electronic device 100 and process data.

[0100] The processor 13 executes the operating system of the electronic device 100 and various installed applications. The processor 13 executes the applications to implement the steps in the above-described embodiments of the dynamic resource loading method, for example... Figure 8 The steps are shown.

[0101] For example, the computer program may be divided into one or more modules / units, which are stored in the memory 12 and executed by the processor 13 to complete this application. The one or more modules / units may be a series of computer-readable instruction segments capable of performing a specific function, which describe the execution process of the computer program in the electronic device 100. For example, the computer program may be divided into an acquisition module 711 and a determination module 712.

[0102] The integrated unit implemented as a software functional module described above can be stored in a computer-readable storage medium. This software functional module, stored in a storage medium, includes several instructions to cause a computer device (which may be a personal computer, computer equipment, or network device, etc.) or processor to execute portions of the resource dynamic loading method described in the various embodiments of this application.

[0103] If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware devices. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above.

[0104] The computer program includes computer program code, which may be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory, and other memory.

[0105] Furthermore, the computer-readable storage medium may primarily include a stored program area and a stored data area, wherein the stored program area may store the operating system, an application program required for at least one function, etc.; and the stored data area may store data created based on the use of blockchain nodes, etc.

[0106] The bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, in... Figure 8 The symbol is represented by only one arrow, but this does not indicate that there is only one bus or one type of bus. The bus is configured to enable communication between the memory 12 and at least one processor 13, etc.

[0107] This application also provides a computer-readable storage medium (not shown), which stores computer-readable instructions that are executed by a processor in an electronic device to implement the resource dynamic loading method described in any of the above embodiments.

[0108] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0109] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0110] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0111] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices described in the specification may also be implemented by a single unit or device through software or hardware. Terms such as "first," "second," etc., are used to indicate names and do not indicate any specific order.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this application without departing from the spirit and scope of the technical solutions of this application.

Claims

1. A method for dynamically loading resources, applied to electronic devices, characterized in that, The method includes: After receiving the startup signal of the first application, the corresponding scene characteristics are determined based on the scene information acquired in real time; Determine the resource data corresponding to the scene information based on the scene characteristics; The configuration data corresponding to the scene information is determined based on the scene characteristics; The resource data is loaded based on the configuration data.

2. The resource dynamic loading method as described in claim 1, characterized in that, The method further includes: Before loading the resource data according to the configuration data, the resource data is traversed. If multiple resource data are the same, any one of the multiple resource data is retained.

3. The resource dynamic loading method as described in claim 1, characterized in that, The step of determining the corresponding scene features based on the real-time acquired scene information includes: Based on the identifier of the scene information, at least one corresponding candidate scene feature is determined; In response to the selection instruction corresponding to the identifier of the scene information, a scene feature corresponding to the scene information is determined from the at least one candidate scene feature.

4. The resource dynamic loading method as described in claim 3, characterized in that, The selection instructions include one or more of the following: touch instructions and voice instructions.

5. The resource dynamic loading method as described in claim 3, characterized in that, The step of determining the resource data corresponding to the scene information based on the scene features includes: The scene features are classified to obtain the scene category corresponding to the scene information; Candidate resource data are determined from multiple initial resource data based on the scenario category; Semantic analysis is performed on the scene features to obtain the first semantics of the scene features; Semantic analysis is performed on the candidate resource data to obtain the second semantics of the candidate resource data; The resource data is determined from the candidate resource data based on the first semantic and the second semantic.

6. The resource dynamic loading method as described in claim 3, characterized in that, The step of determining the configuration data corresponding to the scene information based on the scene features includes: The scene features are classified to obtain the scene category corresponding to the scene information; The priority of the scene information is determined based on the scene category; The configuration data corresponding to the scenario information is determined from multiple initial configuration data based on the priority.

7. The resource dynamic loading method as described in claim 1, characterized in that, The step of loading the resource data according to the configuration data includes: The loading time of the resource data is determined based on the configuration data; A loading strategy for the resource data is generated based on the loading time, and the loading strategy is used to characterize the loading order of multiple resource data. The resource data is loaded according to the loading strategy.

8. A resource dynamic loading device, characterized in that, The device includes: The acquisition module is used to determine the corresponding scene features based on the real-time acquired scene information after receiving the startup signal of the first application. The determination module is used to determine the resource data corresponding to the scene information based on the scene characteristics; The determining module is further configured to determine the configuration data corresponding to the scene information based on the scene features; The determining module is further configured to load the resource data based on the configuration data.

9. An electronic device, characterized in that, The electronic device includes a processor and a memory, wherein the processor is used to implement the resource dynamic loading method as described in any one of claims 1 to 7 when executing a computer program stored in the memory.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the resource dynamic loading method as described in any one of claims 1 to 7.

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