Light effect data processing method, apparatus, device, and medium

Abstract

The application provides a lamp effect data processing method, device, equipment and medium. The method comprises the following steps: acquiring lamp effect parameter data of a target lamp effect displayed by a source device; performing feature extraction on the lamp effect parameter data to obtain lamp effect extraction features for the lamp effect parameter data, and generating a standard lamp effect configuration file based on the lamp effect extraction features; performing feature extraction on device form data of a target device to obtain form extraction features for the device form data; and performing lamp effect migration using the form extraction features and the standard lamp effect configuration file to obtain a target lamp effect configuration file suitable for the target device. The application can improve the migration efficiency of lamp effects across devices.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method, apparatus, device and medium for processing lighting effect data. Background Technology

[0002] Currently, existing lighting effect configuration schemes can achieve different lighting effects on different devices by configuring lighting effect profiles for different devices, such as breathing, gradient, and flashing effects. For example, for device A equipped with a circular light strip, a certain lighting effect profile (e.g., lighting effect code file A1) can be configured for device A to make the circular light strip on device A provide a rainbow rotating breathing lighting effect; as another example, for device B equipped with a non-circular light strip (e.g., a diamond-shaped light strip), a different lighting effect profile (e.g., lighting effect code file B1) can be configured for device B to make the diamond-shaped light strip on device B provide a gradient lighting effect.

[0003] However, the inventors discovered in practice that existing lighting effect configuration schemes require different lighting effect configuration files for different devices to ensure that different devices can achieve different lighting effects through the configured lighting effect configuration files. Based on this, if a certain lighting effect implemented on one device (e.g., device A mentioned above) needs to be migrated to another device (e.g., device B mentioned above), considering that the light strip shapes on these two devices are different, if device B needs to achieve the same lighting effect as device A, it is necessary to manually rewrite new lighting effect code data for device B's own light strip shape. This requires a significant amount of coding time to reconfigure a new lighting effect configuration file (e.g., lighting effect code data B1) for device B, resulting in low efficiency and high difficulty in migrating lighting effects. Summary of the Invention

[0004] This application provides a method, apparatus, device, and medium for processing lighting effect data, which can improve the efficiency of transferring lighting effects across devices and reduce the difficulty of transfer.

[0005] One embodiment of this application provides a method for processing lighting effect data, the method including:

[0006] Obtain the lighting effect parameter data of the target lighting effect displayed on the source device; the target lighting effect refers to the lighting effect to be migrated from the source device to the target device; the lighting effect parameter data refers to the data of the target lighting effect parameters corresponding to the target lighting effect;

[0007] Feature extraction is performed on the lighting effect parameter data to obtain lighting effect extraction features for the lighting effect parameter data, and a standard lighting effect configuration file is generated based on the lighting effect extraction features;

[0008] Obtain the device form data of the target device, extract features from the device form data, and obtain the form extraction features based on the device form data;

[0009] Lighting effect migration is performed using morphological extraction features and standard lighting effect configuration files to obtain a target lighting effect configuration file adapted to the target device. The target lighting effect configuration file is used to instruct the target device to display the target lighting effect based on the target lighting effect parameters when the target lighting effect parameters are parsed.

[0010] One embodiment of this application provides a lighting effect data processing device, the device comprising:

[0011] The parameter data acquisition module is used to acquire the lighting effect parameter data of the target lighting effect displayed by the source device; the target lighting effect refers to the lighting effect to be migrated from the source device to the target device; the lighting effect parameter data refers to the data of the target lighting effect parameters corresponding to the target lighting effect.

[0012] The lighting effect feature extraction module is used to extract features from the lighting effect parameter data, obtain the lighting effect extracted features for the lighting effect parameter data, and generate a standard lighting effect configuration file based on the lighting effect extracted features;

[0013] The morphological feature extraction module is used to acquire the device morphological data of the target device, extract features from the device morphological data, and obtain morphological features extracted from the device morphological data.

[0014] The configuration file generation module is used to perform lighting effect migration using morphological extraction features and standard lighting effect configuration files to obtain a target lighting effect configuration file adapted to the target device. The target lighting effect configuration file is used to instruct the target device to display the target lighting effect based on the target lighting effect parameters when the target lighting effect parameters are parsed.

[0015] Among them, the lighting effect parameter data is the lighting effect video data recorded when the source device displays the target lighting effect based on the target lighting effect parameters;

[0016] The lighting effect feature extraction module includes:

[0017] The lighting effect feature extraction unit is used to obtain the lighting effect configuration model for lighting effect migration. The lighting effect video data is input into the lighting effect configuration model, and the lighting effect configuration model extracts N lighting effect video frames from the lighting effect video data; N is a positive integer.

[0018] The lighting effect feature extraction unit is also used to obtain the target lighting effect video frame from N lighting effect video frames and to obtain the first color channel data of the target lighting effect video frame in the first color space.

[0019] The lighting effect feature extraction unit is also used to convert the first color channel data into the second color channel data in the second color space through the color conversion relationship between the first color space and the second color space, and use the second color channel data as the color extraction feature of the target lighting effect video frame.

[0020] The lighting effect feature extraction unit is also used to obtain the color extraction features of each lighting effect video frame when each of the N lighting effect video frames is selected as the target lighting effect video frame, and to use the color extraction features of each lighting effect video frame as the lighting effect extraction features.

[0021] Among them, the lighting effect extraction features are generated by the lighting effect configuration model used for lighting effect migration;

[0022] The lighting effect feature extraction module includes:

[0023] The first feature fusion unit is used to fuse the standard form extraction features and the lighting effect extraction features when the standard form extraction features of the standard device are obtained through the lighting effect configuration model, and generate the first fused feature.

[0024] The standard file generation unit is used to generate a standard lighting effect configuration file adapted to standard devices based on the first fusion feature.

[0025] Among them, the device morphology data is the device image data of the target device;

[0026] The morphological feature extraction module is specifically used for:

[0027] Obtain the device adaptation model for lighting effect migration, input the device form data into the device adaptation model for lighting effect migration, the device adaptation model performs device LED positioning processing on the device image data, and generates the positioning coordinates of the device LED when locating the device LED on the target device from the device image data; the device LED is used to display the target lighting effect;

[0028] The positioning coordinates of the device's LED beads are used as morphological extraction features.

[0029] Among them, the morphological extraction features are generated by the device adaptation model used for lighting effect migration;

[0030] The configuration file generation module includes:

[0031] The second feature fusion unit is used to encode the morphological extraction features through the device adaptation model to obtain the morphological encoding features of the morphological extraction features, and to encode the standard lighting effect configuration file to obtain the file encoding features of the standard lighting effect configuration file.

[0032] The target file generation unit is used to perform feature fusion on morphological encoding features and file encoding features to obtain a second fused feature, and generate a target lighting effect configuration file based on the second fused feature.

[0033] Among them, the lighting effect extraction features are generated by the lighting effect configuration model used for lighting effect migration; the morphology extraction features are generated by the device adaptation model used for lighting effect migration.

[0034] The lighting effect data processing device also includes a model training module, which includes:

[0035] The sample data acquisition unit is used to acquire the sample lighting effect parameter data of the sample lighting effect displayed on the sample device, the sample lighting effect configuration file of the sample lighting effect for the sample device, the sample device form data of the sample device, the standard device form data of the standard device, and the sample standard lighting effect configuration file of the sample lighting effect for the standard device.

[0036] The model processing unit is used to input the sample lighting effect parameter data and the standard lighting effect configuration file into the lighting effect configuration model to be trained. The lighting effect configuration model to be trained determines the sample lighting effect extraction features of the sample lighting effect parameter data and the standard shape extraction features of the standard equipment shape data.

[0037] The loss determination unit is used to determine the first loss value for the lighting effect configuration model to be trained based on the sample lighting effect extraction features and the standard shape extraction features when generating a predicted standard lighting effect configuration file adapted to standard equipment.

[0038] The model training unit is used to train the lighting effect configuration model and the device adaptation model to be trained based on the first loss value, the prediction standard lighting effect configuration file, the sample lighting effect configuration file, and the sample device shape data, so as to obtain the trained lighting effect configuration model and the trained device adaptation model.

[0039] Specifically, the model training unit is used for:

[0040] The predicted standard lighting effect configuration file, sample lighting effect configuration file, and sample device morphology data are input into the device adaptation model to be trained. The device adaptation model to be trained determines the sample morphology extraction features of the sample device morphology data and the sample file encoding features of the predicted standard lighting effect configuration file.

[0041] When generating a predicted lighting effect configuration file adapted to the sample device based on the sample file encoding features and sample morphology extraction features, a second loss value for the device adaptation model to be trained is determined based on the sample lighting effect configuration file and the predicted lighting effect configuration file.

[0042] The target loss value, determined by the first loss value and the second loss value, is used to train the lighting configuration model and the device adaptation model to be trained.

[0043] Specifically, the loss determination unit is used for:

[0044] Parse the sample lighting effect parameters corresponding to the sample lighting effect on the standard device from the sample standard lighting effect configuration file, and use the sample lighting effect parameters as the first representation vector of the sample standard lighting effect configuration file; then parse the predicted lighting effect parameters corresponding to the sample lighting effect on the standard device from the predicted standard lighting effect configuration file, and use the predicted lighting effect parameters as the second representation vector of the sample standard lighting effect configuration file; or...

[0045] The sample standard lighting effect configuration file is represented by a file to obtain the first file conversion vector of the sample standard lighting effect configuration file. The first file conversion vector is used as the first representation vector. The predicted standard lighting effect configuration file is represented by a file to obtain the second file conversion vector of the predicted standard lighting effect configuration file. The second file conversion vector is used as the second representation vector.

[0046] The first loss value is determined based on the vector difference between the first representation vector and the second representation vector.

[0047] The model training module also includes:

[0048] The model testing unit is used to acquire the actual lighting effect parameter data of the test lighting effect displayed on the test equipment, the actual lighting effect configuration file of the test lighting effect for the test equipment, and the test equipment form data of the test equipment;

[0049] The model testing unit is used to input real lighting effect parameter data into the lighting effect configuration model. The lighting effect configuration model determines the test lighting effect extraction features for the real lighting effect parameter data, and generates a standard lighting effect configuration file based on the test lighting effect extraction features and standard form extraction features.

[0050] The model testing unit is used to input the standard lighting effect configuration file and the test equipment form data into the device adaptation model. The device adaptation model determines the test form extraction features of the test equipment form data and the file encoding features of the standard lighting effect configuration file.

[0051] The model testing unit is used to extract features based on file encoding features and test patterns to generate test lighting configuration files that are adapted to the test equipment.

[0052] The test information determination unit is used to determine the model test information of the lighting effect configuration model and the device adaptation model after training, based on the test lighting effect configuration file, the real lighting effect configuration file, and the real lighting effect parameter data.

[0053] Specifically, the test information determination unit is used for:

[0054] Determine the file deviation data between the actual lighting effect configuration file and the test lighting effect configuration file;

[0055] The test lighting effect configuration file is parsed to obtain the test lighting effect parameters corresponding to the test lighting effect. When the test lighting effect is displayed on the test device based on the test lighting effect parameters, the test lighting effect parameter data of the test lighting effect is determined.

[0056] Determine the parameter deviation data between the actual lighting effect parameter data and the tested lighting effect parameter data;

[0057] Model test information is determined based on file deviation data and parameter deviation data.

[0058] The configuration file generation module also includes:

[0059] The lighting effect analysis unit is used to obtain the display progress bar for displaying the target lighting effect;

[0060] The lighting effect parsing unit is also used to parse the target lighting effect parameters corresponding to the display progress from the target lighting effect configuration file according to the display progress indicated by the display progress bar; the target lighting effect parameters corresponding to the display progress are used to indicate the color parameters and brightness parameters of the device LEDs on the target device at the display progress.

[0061] The lighting effect display unit is used to instruct the device's LED beads to display according to the color and brightness parameters corresponding to the display progress.

[0062] The target lighting effect configuration file includes a brightness display progress array, a color display progress array, a brightness display parameter table, and a color display parameter table. The brightness display progress array is used to define the progress information of the brightness change displayed by the device LEDs. The color display progress array is used to define the progress information of the color change displayed by the device LEDs. The brightness display parameter table is used to define the brightness parameters displayed by the device LEDs. The color display parameter table is used to define the color parameters displayed by the device LEDs.

[0063] The lighting effect analysis unit is specifically used for:

[0064] The progress information in the brightness display configuration table is queried according to the display progress. If the progress information that matches the display progress is found in the brightness display configuration table, the brightness parameter that matches the display progress is obtained from the brightness display parameter table.

[0065] The progress information in the color display configuration table is queried according to the display progress. If the progress information that matches the display progress is found in the color display configuration table, the color parameter that matches the display progress is obtained from the color display parameter table.

[0066] The brightness parameter and color parameter that match the display progress are used as the target lighting effect parameters corresponding to the display progress.

[0067] One aspect of this application provides a computer device, including a memory and a processor. The memory is connected to the processor, the memory is used to store computer programs, and the processor is used to call the computer programs so that the computer device executes the method provided in one aspect of this application.

[0068] One aspect of this application provides a computer-readable storage medium storing a computer program adapted to be loaded and executed by a processor, so that a computer device having a processor performs the method provided in one aspect of this application.

[0069] According to one aspect of this application, a computer program product is provided, the computer program product including a computer program that, when executed by a processor, implements the methods provided in any of the above aspects of the embodiments of this application.

[0070] In this embodiment, the target lighting effect parameter data on the source device can be obtained. This lighting effect parameter data refers to the data of the target lighting effect parameters implemented on the source device. When determining the lighting effect extraction features of the lighting effect parameter data, a standard lighting effect configuration file can be generated based on these features. That is, based on the relationship between lighting effect and lighting effect configuration, the lighting effect parameter data can be converted into a standard lighting effect configuration file first. Then, the lighting effect migration for the device form of the target device can be performed based on the standard lighting effect configuration file. That is, the form extraction features for device form data and the standard lighting effect configuration file can be used to perform lighting effect migration, resulting in a target lighting effect configuration file adapted to the target device. This target lighting effect configuration file can be used to implement the target lighting effect on the target device. This allows for understanding the lighting effect of the target lighting effect on the source device and performing lighting effect migration step by step, thereby compiling a corresponding lighting effect configuration file for the target device. This not only enables rapid adaptation and migration of lighting effects but also reduces the difficulty of cross-device migration of lighting effects and improves migration efficiency. Attached Figure Description

[0071] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0072] Figure 1 This is a schematic diagram of a network architecture provided in an embodiment of this application;

[0073] Figure 2 This is a schematic diagram illustrating a lighting effect data processing procedure provided in an embodiment of this application;

[0074] Figure 3 This is a flowchart illustrating a lighting effect data processing method provided in an embodiment of this application;

[0075] Figures 4-6 This is a schematic diagram of a lighting effect migration scenario provided in an embodiment of this application;

[0076] Figure 7 This is a flowchart illustrating another lighting effect data processing method provided in an embodiment of this application;

[0077] Figures 8-12 This is a schematic diagram of a lighting effect playback scenario provided in an embodiment of this application;

[0078] Figure 13 This is a flowchart illustrating another lighting effect data processing method provided in the embodiments of this application;

[0079] Figures 14-21 This is a schematic diagram of a model-based lighting effect migration scenario provided in an embodiment of this application;

[0080] Figure 22 This is a schematic diagram of the structure of a lighting effect data processing device provided in an embodiment of this application;

[0081] Figure 23 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0082] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0083] Please see Figure 1 , Figure 1 This is a schematic diagram of a network architecture provided in an embodiment of this application. For example... Figure 1 As shown, the system architecture may include a business server 100 and a business terminal cluster. The business terminal cluster may include one or more business terminals (e.g., user terminals). The number of business terminals in the business terminal cluster is not limited here. Figure 1As shown, the multiple service terminals in the service terminal cluster may specifically include: service terminal 200a, service terminal 200b, ..., service terminal 200n. Communication connections can exist between the service terminals in the cluster; for example, there is a communication connection between service terminal 200a and service terminal 200b, and between service terminal 200a and service terminal 200n. Simultaneously, any service terminal in the service terminal cluster can have a communication connection with the service server 100, so that each service terminal in the cluster can interact with the service server 100 through this communication connection. For example, there is a communication connection between service terminal 200a and service server 100. The above communication connection is not limited to a specific method; it can be established directly or indirectly through wired communication, wireless communication, or other methods. This application does not impose any restrictions on this method.

[0084] It should be understood that, such as Figure 1 Each business terminal in the shown business terminal cluster can have an application client installed for lighting effect migration. When the application client runs on each business terminal, it can interact with the aforementioned... Figure 1 The business servers 100 shown interact with each other. The application client can be any type of client, such as a social networking client, image processing client, instant messaging client (e.g., conferencing client), entertainment client (e.g., game client, live streaming client), multimedia client (e.g., video client), information client (e.g., news client), shopping client, in-vehicle client, multimedia client, application download client (a client used to provide users with various downloadable application resources), etc., clients with the ability to display text, images, audio, and video data. The specific type of application client is not limited here.

[0085] For example, an application client refers to a client that can send and receive Internet messages in real time and has information search functions. Business object X can upload the lighting effect parameter data of the target lighting effect displayed by the source device and the device form data of the target device in the application client on business terminal 200a. Business server 100 can generate a target lighting effect configuration file adapted to the target device through the technical solution of this application and send it to the target device (such as business terminal 200b) so that the target device can display the target lighting effect based on the target lighting effect configuration file.

[0086] It is understood that the computer equipment involved in the embodiments of this application may be a server (e.g., Figure 1 The business server 100 shown can also be a terminal (e.g., Figure 1(Any one of the business terminals in the business terminal cluster shown). The server can be an independent physical server, a server cluster composed of multiple physical servers, or a distributed system. It can also be a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. The terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smart TV, smartwatch, vehicle terminal, aircraft, etc., but is not limited to these. This application's embodiments can be applied to various scenarios, including but not limited to cloud technology, artificial intelligence, smart transportation, and assisted driving.

[0087] Understandable, Figure 1 This is merely an example to characterize the possible network architectures of the technical solutions in this application, and does not limit the specific architecture of the technical solutions in this application. That is, the technical solutions in this application can also provide other forms of network architecture.

[0088] Further, please see Figure 2 , Figure 2 This is a schematic diagram illustrating a lighting effect data processing procedure provided in an embodiment of this application. Specifically, when it is necessary to migrate a target lighting effect already implemented on a source device to a target device, the lighting effect parameter data (lighting effect data) of the target lighting effect displayed on the source device can be obtained. This lighting effect parameter data refers to the data obtained on the source device regarding the target lighting effect parameters, such as lighting effect video data recorded when the source device displays the target lighting effect.

[0089] This involves acquiring the device form data of the target device (such as the device image of the target device), and then generating a target lighting effect configuration file adapted to the target device based on the lighting effect parameter data and the device form data.

[0090] The target lighting effect configuration file refers to the configuration file that can display the target lighting effect on the target device. When the target device parses the target lighting effect configuration file, it can obtain the target lighting effect parameters. When displaying according to the target lighting effect parameters, the displayed lighting effect is the target lighting effect (the effect of the displayed lighting effect is the same as or approximately the same as the display effect of the target lighting effect), thereby realizing cross-device lighting effect migration and improving migration efficiency.

[0091] In this process, feature extraction is performed on the lighting effect parameter data to obtain lighting effect extraction features 21a for the lighting effect parameter data, and a standard lighting effect configuration file for the target lighting effect is generated based on the lighting effect extraction features.

[0092] This process involves acquiring device shape data (such as an image of the target device) and extracting features from the device shape data to obtain shape extraction features 22a. These shape extraction features and a standard lighting effect configuration file can then be used for lighting effect migration to obtain a target lighting effect configuration file adapted to the target device.

[0093] Optionally, the computer equipment can execute the lighting effect data processing method according to actual business needs to improve the lighting effect migration effect. The technical solution of this application can be applied to lighting effect migration scenarios on any device. For example, when migrating a rainbow rotating breathing lighting effect implemented on one device to another, the other device can also implement the rainbow rotating breathing lighting effect. Furthermore, both the source and target devices involved have the ability to parse lighting effect configuration files of the same format to display the corresponding lighting effect; that is, a common lighting effect configuration format can be used to obtain the corresponding lighting effect configuration file to achieve the display or migration of the lighting effect.

[0094] It should be noted that when the computer device in this application embodiment acquires relevant data, such as lighting effect parameter data uploaded by a business object, it may display a prompt interface or pop-up window. The prompt interface or pop-up window is used to prompt the user that the aforementioned lighting effect-related data is being acquired. The data acquisition steps will only begin after the user confirms the prompt interface or pop-up window; otherwise, the process will end.

[0095] It is understood that user data (e.g., the aforementioned lighting effect related data) may be involved in the specific implementation of this application. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant regions.

[0096] It is understood that the above scenarios are merely examples and do not constitute a limitation on the application scenarios of the technical solutions provided in the embodiments of this application. The technical solutions of this application can also be applied to other scenarios. For example, as those skilled in the art will know, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0097] For further details, please see Figure 3 , Figure 3 This is a flowchart illustrating a lighting effect data processing method provided in an embodiment of this application, as shown below. Figure 3 As shown, the method can be executed by the aforementioned computer devices, such as... Figure 1 For any of the service terminals or service servers shown, the method may specifically include the following steps S101-S104:

[0098] S101. Obtain the lighting effect parameter data of the target lighting effect displayed by the source device.

[0099] In this context, "lighting effect" refers to the effect produced by the device's LED beads (such as LEDs, light-emitting diodes) according to specific programming logic. For example, the device's LED beads may trigger the display of lighting effect 1 (such as being constantly lit and green) under specific conditions, or trigger the display of lighting effect 2 (such as flashing and displaying red) under specific conditions, and so on.

[0100] The target lighting effect refers to the lighting effect to be migrated from the source device to the target device. That is, a target lighting effect already implemented on the source device can be migrated to the target device, allowing the target device to also achieve the same target lighting effect. For example, lighting effect 2 on the source device can be migrated to the target device, so that the device LEDs on the target device can also achieve lighting effect 2, which flashes red.

[0101] Among them, the lighting effect parameter data refers to the data of the target lighting effect parameters corresponding to the target lighting effect. The target lighting effect parameters corresponding to the target lighting effect are used to indicate the color parameters and / or brightness parameters that the device's LEDs should display. That is, the lighting effect obtained by the device displaying according to the target lighting effect parameters is the target lighting effect.

[0102] In this context, the target lighting effect parameters corresponding to the target lighting effect can be the same or different on different devices. For example, the target lighting effect parameters used to implement the target lighting effect on the source device (lighting effect parameters extracted from the lighting effect configuration file of the target lighting effect for the source device) can be parameters that indicate the device LEDs (such as device LEDs 11-13) on the source device should display at each moment.

[0103] For example, the target lighting effect parameters (lighting effect parameters extracted from the lighting effect configuration file for the target device) used to achieve the target lighting effect on the target device can be parameters that indicate the device LEDs (such as device LEDs 21-25) on the target device should display at each moment.

[0104] For ease of understanding, the lighting effect parameters that achieve the target lighting effect on the source device can be referred to as the first lighting effect parameters, and the lighting effect parameters that achieve the target lighting effect on the target device can be referred to as the second lighting effect parameters.

[0105] The lighting effect parameter data describes the complete display process of the target lighting effect. For example, it can be parameters extracted from the source lighting effect configuration file adapted to the source device, such as the target lighting effect parameters for the source device (e.g., the color and brightness parameters involved in displaying the target lighting effect by the device LEDs on the source device). Optionally, it can also include other parameters related to the target lighting effect parameters, such as display duration parameters and change time parameters for the source device. No limitations are imposed here.

[0106] Alternatively, the lighting effect parameter data can also be data obtained from the target lighting effect parameters.

[0107] For example, the lighting effect parameter data can be the lighting effect video data (or the lighting effect image data captured) recorded when the source device displays the target lighting effect based on the target lighting effect parameters. In this case, the lighting effect parameter data not only implies the target lighting effect parameters, but also contains the device information of the source device (such as device shape, device LEDs, etc.), and can characterize the dynamic change rules of the target lighting effect and other related visual effects.

[0108] For example, lighting effect parameter data can be text data describing the display effect and display method of the target lighting effect (such as specifically including color, brightness, change method, refresh rate, display duration, etc.). For example, "always on is green, and the displayed color parameter is xx, and the brightness is xx", "displayed as red by flashing once per minute, and the displayed color parameter is xx, and the brightness is xx", etc.

[0109] The specific type of lighting effect parameter data is not limited here. Optionally, the lighting effect parameter data may include one or more of the above-mentioned data (such as lighting effect video data and lighting effect description text data).

[0110] S102. Extract features from the lighting effect parameter data to obtain lighting effect extraction features for the lighting effect parameter data, and generate a standard lighting effect configuration file based on the lighting effect extraction features.

[0111] Among these features, feature extraction can be performed on lighting effect parameter data to generate standard lighting effect configuration files.

[0112] For example, features can be extracted from lighting effects and processed to output a standard lighting effect configuration file. This standard lighting effect configuration file is adapted to standard devices. This configuration file enables standard devices to achieve the target lighting effect.

[0113] For example, a lighting effect configuration model can be obtained for lighting effect migration. The relationship between lighting effects and lighting effect configuration can be learned using the lighting effect configuration model to generate a lighting effect configuration file for a specified device.

[0114] The standard device is a pre-defined, designated device (intermediate device). Lighting effect extraction features are first used to generate a lighting effect configuration file for the fixed standard device, which is then used to further generate the target lighting effect configuration file. This step-by-step approach to lighting effect migration reduces the difficulty and complexity of the migration process, while also improving its controllability.

[0115] This means that the lighting effect configuration model learns the configuration file of the lighting effect on the standard device, and then the device adaptation model can generate the lighting effect configuration file on other devices based on the lighting effect configuration file on the standard device. This allows for a phased learning process from lighting effect to lighting effect configuration, thereby solving the difficulty of lighting effect migration caused by different device forms.

[0116] The specific method for generating standard lighting effect configuration files using the lighting effect configuration model can be found in the relevant description of the following embodiments.

[0117] Feature extraction can be performed either within or outside the lighting effect configuration model. The specific method of feature extraction can vary depending on the type of lighting effect parameter data.

[0118] For example, taking lighting effect parameter data as lighting effect video data (the same applies to lighting effect image data), the specific method for determining the lighting effect extraction features is as follows: extract N lighting effect video frames from the lighting effect video data (for example, obtain a lighting effect configuration model for lighting effect migration, input the lighting effect video data into the lighting effect configuration model, and have the lighting effect configuration model extract N lighting effect video frames), and perform color space conversion on each of the N lighting effect video frames to obtain the color extraction features of each lighting effect video frame; N is a positive integer; use the color extraction features of the N lighting effect video frames as the lighting effect extraction features.

[0119] For example, video frames from the lighting effect video data can be extracted sequentially at specified time intervals to obtain N lighting effect video frames. Alternatively, N video frames can be extracted randomly.

[0120] Specifically, this can involve obtaining the target lighting effect video frame from N lighting effect video frames, obtaining the first color channel data of the target lighting effect video frame in the first color space (i.e., the color value of each pixel of the target lighting effect video frame in the color space); converting the first color channel data into the second color channel data in the second color space (i.e., the HSV value of each pixel of the target lighting effect video frame in the HSV space) through the color conversion relationship between the first color space and the second color space, and using the second color channel data as the color extraction feature of the target lighting effect video frame; when each of the N lighting effect video frames is selected as the target lighting effect video frame, obtaining the color extraction feature of each lighting effect video frame, and using the color extraction feature of each lighting effect video frame as the lighting effect extraction feature.

[0121] Color space conversion refers to the conversion from a first color space to a second color space. The first color space is the RGB (red, green, blue) color space, and the second color space is the HSV (hue, saturation, value) color space.

[0122] Among them, the color extraction features of N lighting effect video frames can characterize the color and brightness temporal features of the target lighting effect during the display process.

[0123] For example, N lighting effect video frames can be converted into the HSV color space, where hue can represent color. The color extraction features of a single lighting effect video frame include features from three color spaces. The matrix formed by the color extraction features of the N lighting effect video frames can be used as the lighting effect extraction features.

[0124] For example, N lighting effect video frames can be converted into video frames with the same resolution (128x128 as an example) (optionally, normalization processing can also be performed, such as through convolution processing or blur processing).

[0125] Taking the lighting effect video frame at frame t as an example, its corresponding hue feature H t For example, it is represented as follows:

[0126]

[0127] Among them, H t This represents the color characteristics corresponding to each pixel in the video frame of the lighting effect.

[0128] Wherein, the saturation feature corresponding to the lighting effect video frame of frame t is S t The brightness characteristic corresponding to the lighting effect video frame t is V. t .

[0129] Therefore, the color extraction feature of the lighting effect video frame t is C. t =[H t ,S t V t ]∈R 128x128x3 .

[0130] Optionally, the lighting effect extraction features may include not only the color extraction features of the lighting effect video frames, but also color extraction features (such as features extracted in a color space), or encoded features obtained by image encoding of the lighting effect video frames, etc. No limitation is made here.

[0131] Optionally, when the lighting effect parameter data is the parameters extracted from the source lighting effect configuration file, the matrix composed of the extracted parameters can be used as the lighting effect extraction feature.

[0132] Alternatively, when the lighting effect parameter data is the lighting effect description text data, the encoded features obtained by text encoding the lighting effect description text data can be used as the lighting effect extraction features. No restrictions are imposed here.

[0133] If the lighting effect parameter data includes one or more of the above types of data, the lighting effect extraction features of each type of lighting effect parameter data can be determined in the above manner and used as the lighting effect extraction features for generating the standard lighting effect configuration file.

[0134] S103. Obtain the device form data of the target device, extract features from the device form data, and obtain the form extraction features for the device form data.

[0135] The device form data can be device image data (such as images or videos taken of the target device). Alternatively, it can be form description text data describing the form of the target device (such as describing the layout and quantity of LEDs on the target device, like "circular, including xx LEDs"). Alternatively, the device form data can be the target device's specification document (which defines the device form, such as shape, number and position of LEDs, etc.).

[0136] The specific type of equipment form data is not limited here. Optionally, equipment form data may include one or more of the above-mentioned data (such as equipment image data and specifications).

[0137] This process involves extracting features from device form data to generate a target lighting effect configuration file. For example, a hardware adaptation model used for lighting effect migration can be obtained to generate the target lighting effect configuration file. In this case, the feature extraction process for device form data can be performed within the hardware adaptation model or outside of it.

[0138] Optionally, the hardware adaptation model and the lighting effect configuration model used for lighting effect migration can be two independent models, or they can be two sub-models within the same model (lighting effect migration model).

[0139] The specific method of feature extraction can vary depending on the type of lighting effect parameter data.

[0140] For example, taking device shape data as device image data, the specific way to determine the shape extraction features is as follows: perform device LED bead positioning processing on the device image data. When locating the device LED bead on the target device from the device image data (for example, obtaining the device adaptation model used for lighting effect migration, inputting the device shape data into the device adaptation model used for lighting effect migration, and locating it by the device adaptation model), the positioning coordinates of the device LED bead are generated; the device LED bead is used to display the target lighting effect; the positioning coordinates of the device LED bead are used as shape extraction features, such as using the matrix formed by the positioning coordinates of the device LED bead as shape extraction features.

[0141] Therefore, the LED beads located in the target device can be identified and located from the device image data, and the positioning coordinates of the LED beads on the device image data (or target device) can be generated. At this time, the positioning coordinates of the LED beads can be used as morphological extraction features. In this case, the morphological extraction features include the physical characteristics of the LED beads, including structural information such as quantity, position, and arrangement.

[0142] The positioning device LED can be configured to perform edge detection on the device image data to obtain the object edge detection result; determine the detection edge region (such as a circular region) corresponding to the device LED from the object edge detection result; and determine the positioning coordinates of the device LED based on the detection edge region corresponding to the device LED.

[0143] Since the size of the device LED beads is usually within a specified range, the edge region can be extracted from the object edge detection results to obtain the edge region associated with the device LED beads (such as all circular regions). If the size of the edge region associated with the device LED beads is within a specified range, the edge region associated with the device LED beads will be used as the detection edge region corresponding to the device LED beads, that is, the detection edge region represents a device LED bead.

[0144] At this point, the center of the detection edge area corresponding to the device LED can be determined, and the coordinate information corresponding to the center of the area can be used as the positioning coordinates of the device LED.

[0145] Therefore, the physical arrangement of the device LEDs can be directly described by defining their coordinates in three-dimensional space (or projected coordinates on a two-dimensional plane) for each device LED.

[0146] For example, a unique positioning coordinate is generated for each LED in the target device, and the matrix formed by the positioning coordinates of all LEDs (number n) is used as the morphological feature S for extraction.

[0147]

[0148] Optionally, the morphological extraction features may include not only the positioning coordinates of the device's LEDs, but also coded features obtained by image encoding the device's image data, etc. No limitation is made here.

[0149] Optionally, when the device form data is a specification document or form description text data, the encoded features obtained by text encoding the specification document or form description text data can be used as the form extraction features. No limitation is imposed here.

[0150] If the device form data includes one or more of the above types of data, the form extraction features of each type of device form data can be determined in the above manner and used as form extraction features for generating the target lighting effect configuration file.

[0151] S104. Use morphological extraction features and standard lighting effect profiles to perform lighting effect migration, and obtain a target lighting effect profile adapted to the target device.

[0152] The target lighting effect configuration file instructs the target device to display the target lighting effect based on the target lighting effect parameters obtained through parsing. In other words, when the target device obtains the target lighting effect parameters adapted to its specifications, it can instruct the device LEDs on the target device to display the target lighting effect.

[0153] For example, the server can send the target lighting effect configuration file to the target device, or the target device can directly generate the target lighting effect configuration file from the source device's lighting effect parameter data.

[0154] In the device adaptation model, morphological extraction features and standard lighting effect configuration files are used to generate target lighting effect configuration files. Lighting effect migration refers to migrating the target lighting effect from the source device to the target device. This involves generating a target lighting effect configuration file on the target device using the lighting effect parameter data of the target lighting effect on the source device. In other words, it involves performing configuration-level lighting effect migration on the standard equivalent configuration file using morphological extraction features to obtain a lighting effect configuration file that can be migrated to the target device. This can be viewed as adapting the standard lighting effect configuration file (such as the target lighting effect parameters it contains) to the target device's configuration (i.e., adjusting the relevant lighting effect configurations in the lighting effect configuration file) to obtain the target lighting effect configuration file (i.e., adjusting the target lighting effect parameters it contains to adapt to the device's LEDs on the target device).

[0155] The specific method for generating the target lighting effect configuration file in the device adaptation model can be found in the relevant description of the following embodiments.

[0156] For example, such as Figures 4-6 As shown, Figures 4-6 This is a schematic diagram of a lighting effect migration scenario provided in an embodiment of this application; wherein, in Figure 4 In this context, the target lighting effect displayed on device a41 can be generated by encoding adaptation to generate a lighting effect configuration file adapted to the target device. For example, a lighting effect configuration file b41 adapted to device a42, a lighting effect configuration file b42 adapted to device a43, and a lighting effect configuration file b43 adapted to device a44.

[0157] When device a42 obtains the lighting effect configuration file b41, it can parse the lighting effect configuration file b41 through the lighting effect parsing layer on device a42 to obtain the lighting effect parameter c41 adapted to device a42. Device a42 can then notify the device LEDs to display the target lighting effect adapted to device a42 based on the lighting effect parameter c41.

[0158] When device a43 obtains the lighting effect configuration file b42, it can parse the lighting effect configuration file b42 through the lighting effect parsing layer on device a43 to obtain the lighting effect parameters c42 adapted to device a43. Device a43 can then notify the device LEDs to display the target lighting effect adapted to device a43 based on the lighting effect parameters c42.

[0159] When device a44 obtains the lighting effect configuration file b43, it can parse the lighting effect configuration file b43 through the lighting effect parsing layer on device a44 to obtain the lighting effect parameters c43 adapted to device a44. Device a44 can then notify the device LEDs to display the target lighting effect adapted to device a44 based on the lighting effect parameters c43.

[0160] Therefore, a universal lighting effect configuration format can be defined to generate lighting effect configuration files that can be recognized and parsed by devices, meaning the lighting effects are implemented in configuration form. A unified lighting driver layer can be deployed in the device, which is responsible for parsing the lighting effect configuration files and playing the corresponding lighting effects, enabling flexible lighting effect configuration. Lighting effect parameter data (i.e., lighting effect data) and the target device's device shape data (i.e., the appearance shape of the light strip) can be input into the trained intelligent model (such as the aforementioned lighting effect configuration model and device adaptation model). Based on the learned relationship between lighting effects and lighting effect configurations, the intelligent model understands the display logic of the target lighting effect through the lighting effect parameter data. Then, utilizing the target device's device shape and the model's reasoning capabilities, it generates an adapted target lighting effect configuration file for the target device. In this way, the target device can use a unified lighting effect parsing logic to display the target lighting effect, achieving rapid adaptation and migration of lighting effects, greatly reducing difficulty and cost. That is, the target lighting effect configuration file adapted to the target device can be obtained quickly and efficiently without re-compiling the configuration file.

[0161] Therefore, in Figure 5 In the process, the target lighting effect on device a41 (such as displaying specific lighting effects in a sequential loop) can be migrated through coding adaptation, and the same (or similar) target lighting effect can be displayed on device a43.

[0162] For example, in Figure 6 In this system, the lighting effect configuration file b43 can be sent to device a44, for example, via network, Bluetooth, wired transmission, or direct internal connection. Device a44 supports the reception, storage, and parsing of lighting effect configurations and has certain logical calculation capabilities. Device a44 can parse the lighting effect configuration file based on the lighting driver layer (such as a CPU (Central Processing Unit) or MCU (Microcontroller Unit) chip). For example, after device a11 parses the lighting effect configuration file and obtains the lighting effect parameters, it can instruct the device's LEDs to display the target lighting effect.

[0163] In this embodiment, the target lighting effect parameter data on the source device can be obtained. This lighting effect parameter data refers to the data of the target lighting effect parameters implemented on the source device. When determining the lighting effect extraction features of the lighting effect parameter data, a standard lighting effect configuration file can be generated based on these features. That is, based on the relationship between lighting effect and lighting effect configuration, the lighting effect parameter data can be converted into a standard lighting effect configuration file first. Then, the lighting effect migration for the device form of the target device can be performed based on the standard lighting effect configuration file. That is, the form extraction features for device form data and the standard lighting effect configuration file can be used to perform lighting effect migration, resulting in a target lighting effect configuration file adapted to the target device. This target lighting effect configuration file can be used to implement the target lighting effect on the target device. This allows for understanding the lighting effect of the target lighting effect on the source device and performing lighting effect migration step by step, thereby compiling a corresponding lighting effect configuration file for the target device. This not only enables rapid adaptation and migration of lighting effects but also reduces the difficulty of cross-device migration of lighting effects and improves migration efficiency.

[0164] For further details, please see Figure 7 , Figure 7 This is a flowchart illustrating a lighting effect data processing method provided in an embodiment of this application, as shown below. Figure 7 As shown, the method can be executed by the aforementioned computer devices, such as... Figure 1 For any of the service terminals or service servers shown, the method may specifically include the following steps S201-S205:

[0165] S201. Obtain the lighting effect parameter data of the target lighting effect displayed by the source device. The specific implementation of step S201 can be found in the relevant description of the above embodiments, and will not be repeated here.

[0166] S202. The lighting effect parameter data is feature extracted through the lighting effect configuration model to obtain the lighting effect extraction features for the lighting effect parameter data, and a standard lighting effect configuration file is generated based on the lighting effect extraction features and the standard form extraction features.

[0167] Specifically, lighting effect parameter data can be input into the lighting effect configuration model, which then extracts features to obtain the lighting effect extracted features. For a description of the lighting effect parameter data and the method of extracting the lighting effect features, please refer to the relevant descriptions in the above embodiments.

[0168] Among them, the lighting effect extraction features can be generated by the lighting effect configuration model used for lighting effect migration.

[0169] One method for generating a standard lighting effect configuration file is to perform feature fusion on the standard form extraction features and lighting effect extraction features when the standard form extraction features of the standard device are obtained through the lighting effect configuration model, and generate a first fused feature; and generate a standard lighting effect configuration file adapted to the standard device based on the first fused feature.

[0170] The standard morphology extraction features can be fixed vectors generated by the lighting effect configuration model using the device morphology data of standard devices and deployed within the lighting effect configuration model. For details, please refer to the description above regarding the morphology extraction features for determining the device morphology data of the target device.

[0171] In this model, the standard morphology extraction features can be considered as predefined constants in the lighting effect configuration model. Therefore, the feature fusion method can be to use the vector product (or vector sum) between the standard morphology extraction features and the lighting effect extraction features as the first fusion feature. The specific method is not limited. In this way, a standard lighting effect configuration file can be predicted and output based on the first fusion feature.

[0172] Among them, the lighting effect configuration model can learn the relationship between lighting effect (i.e. the effect reflected by lighting effect parameter data) and lighting effect configuration based on the device form of standard equipment. In other words, the lighting effect configuration model can understand the lighting effect and generate the corresponding lighting effect configuration file.

[0173] S203. Obtain the device form data of the target device, and extract features from the device form data using a device adaptation model to obtain the form extraction features specific to the device form data. The specific implementation of step S203 can be found in the relevant descriptions of the above embodiments, and will not be repeated here.

[0174] S204. Using the device adaptation model, extract features and standard lighting effect configuration files to perform lighting effect migration, and obtain a target lighting effect configuration file adapted to the target device.

[0175] The morphological extraction features are generated by a device adaptation model used for lighting effect migration. This device adaptation model can adjust the lighting effect configuration file output by the lighting effect configuration model based on different device morphologies, achieving cross-device adaptive generation of lighting effect configuration files.

[0176] The specific method for generating the target lighting effect configuration file can be as follows: the morphological extraction features are feature-encoded through the device adaptation model to obtain the morphological encoding features of the morphological extraction features, and the standard lighting effect configuration file is feature-encoded to obtain the file encoding features of the standard lighting effect configuration file; the morphological encoding features and the file encoding features are feature-fused to obtain the second fused features, and the target lighting effect configuration file is generated based on the second fused features.

[0177] In this process, feature encoding can be performed on the morphological extraction features to generate morphological encoding features that can represent the spatial features of the target device's shape. For example, GNN (Graph Neural Network) can be used to encode the morphological extraction features.

[0178] In this process, feature encoding can be performed on the standard lighting effect configuration file to obtain file encoding features that represent the global features of the standard lighting effect configuration file. For example, the encoder in Transformer (a sequence model based on an attention mechanism) can be used to perform feature encoding of file encoding features.

[0179] Feature fusion of morphological and document-encoded features can employ an attention mechanism (Key / Value / Query mechanism, also known as the attention mechanism). For example, morphological features can be used to determine the Key vector (first-class vector) and Value vector (second-class vector) in the attention mechanism. These Key and Value vectors serve as the query vector (where the Key vector represents the source to be matched or compared with the query vector, and the Value vector represents the information to be weighted and summed based on the degree of matching between the query vector and the Key vector). Document-encoded features can be used to determine the Query vector (third-class vector) in the attention mechanism. This Query vector serves as the vector for querying related information (representing the target to be focused on or retrieved).

[0180] Then, the Key vector, Value vector, and Query vector are used for relevant processing in the attention mechanism, and the resulting vector is used as the second fusion feature. Alternatively, the Key vector and Value vector can be determined through file encoding features, and the Query vector can be determined through morphological encoding features to obtain the second fusion feature. In this way, the target lighting effect configuration file can be obtained by decoding the second fusion feature.

[0181] Alternatively, feature fusion of morphological encoding features and file encoding features can also involve feature concatenation, weighted summation, etc. No limitation is placed on the feature fusion method here.

[0182] The target lighting effect configuration file instructs the target device to display the target lighting effect based on the target lighting effect parameters obtained through parsing. In other words, when the target device needs to display the target lighting effect, it can parse the target lighting effect configuration file to obtain the target lighting effect parameters for the device's LEDs (such as indicating the color and brightness parameters for each LED). This ensures that when the LEDs on the target device are displayed according to the color and brightness parameters, the target lighting effect can be displayed identically to that on the source device.

[0183] S205. Obtain the display progress bar used to display the target lighting effect, parse the target lighting effect parameters corresponding to the display progress indicated by the display progress bar from the target lighting effect configuration file, and notify the device LEDs to display based on the target lighting effect parameters.

[0184] The implementation of lighting effect playback is similar to that of animation playback, clearly describing the specified color and brightness displayed by each device LED at a given time. That is, the target lighting effect can be associated with a display progress bar. Playing the target lighting effect through this progress bar allows the target lighting effect parameters for each device LED to be parsed from the target lighting effect configuration file for each display progress point. For example, at display progress k, the target lighting effect parameters corresponding to display progress k are parsed from the target lighting effect configuration file, and the device LEDs are notified to display accordingly.

[0185] Therefore, the target lighting effect parameters corresponding to the display progress indicated by the progress bar can be parsed from the target lighting effect configuration file. These target lighting effect parameters indicate the color and brightness parameters of the device LEDs on the target device at the corresponding display progress. This instructs the device LEDs to display according to the color and brightness parameters corresponding to the display progress.

[0186] The target lighting effect configuration file can be parsed to show the completion progress. When the progress bar indicates the completion progress, it means that the target lighting effect has completed one playback. At this point, the playback of the target lighting effect can be stopped. Alternatively, if it is specified that it needs to be played multiple times or continuously, the display progress bar will be looped, and the target lighting effect parameters will be parsed again based on the current display progress to loop the playback of the target lighting effect.

[0187] For example, such as Figures 8-9 As shown, Figures 8-9 This is a schematic diagram of a lighting effect playback scene provided in an embodiment of this application; wherein, in Figure 8 In the implementation, the progress bar is displayed using a lookup table method and an interpolator pattern.

[0188] Taking the lookup table method as an example, a polling logic can be maintained to obtain the display progress bar used to display the target lighting effect, and a time interval for querying the target lighting effect parameters can be defined (e.g., 25 milliseconds). One time interval represents one step, or one display progress. Each time a step is reached, the target lighting effect configuration file can be parsed. This configuration file describes the color and brightness that the device's LEDs should display for each step.

[0189] Therefore, the target device can query the target lighting effect configuration file based on the display progress indicated by the display progress bar (i.e., the current step), obtain the target lighting effect parameters of the device LED at this time, and then notify the device LED to execute the display.

[0190] For example, the target lighting effect configuration file can define relevant information about the target lighting effect. If the target lighting effect is constant color and variable brightness, color parameters (i.e., rbg values) and brightness parameters (which can be used to represent rbg values, i.e., the brightness corresponding to each color value, such as the brightness level corresponding to the color parameter r) can be defined. For example, the brightness parameter corresponding to each step can be defined.

[0191] The progress bar includes steps 0, 1, 2, ..., and step_end (representing the end point of one display cycle of the target lighting effect). When the progress bar is activated, the specific process is as follows: S81. When a display progress point (e.g., step 2) is reached, the target lighting effect configuration file is queried; S82. The lighting effect parameters corresponding to step 2 are determined based on the query results; S83. The device LEDs are notified to display. When the progress bar reaches step_end, it indicates that the target lighting effect playback is complete. S84. If it indicates that the target lighting effect needs to continue displaying, the process jumps back to the beginning of the progress bar (step 0) to loop the target lighting effect.

[0192] The interpolator mode works similarly to the lookup table method. The interpolator mode is used to define the display progress bar from 0% to 100%. Therefore, it can look up the target lighting effect parameters corresponding to the display progress of 20% in the target lighting effect configuration file based on the current progress indicated by the display progress bar (such as 20%).

[0193] Therefore, in Figure 9 In the process of parsing the target lighting effect configuration file and displaying the target lighting effect, the steps are as follows: S91, the target device parses the lighting effect configuration file, that is, it queries the lighting effect configuration file according to step; S92, when the lighting effect parameters are obtained, the target device can display the lighting effect, that is, it can notify the device LEDs to display according to the parsed lighting effect parameters, which indicates the display effect of the target lighting effect at this step.

[0194] Specifically, for S91, the steps are as follows: S9101, when playing the target lighting effect, maintain the display progress bar of the target lighting effect; S9102, according to the current step indicated by the display progress bar, query the lighting effect parameters corresponding to the current step in the lighting effect configuration file.

[0195] Among them, Figure 10In this system, each device (such as device A, device B, and device C) can deploy a unified hardware abstraction layer, which serves as the driver layer for parsing lighting effect configuration files. Logic for parsing lighting effect configuration files can be embedded in the hardware abstraction layer, and the software abstraction layer is used to parse these files. Each device has the capability to parse lighting effect configuration files in the same format, allowing the same lighting effect to be configured to adapt to different devices, thus enabling cross-device migration of lighting effects.

[0196] Among them, Figure 11 In this process, the specific method for migrating lighting effects across devices is as follows: input the lighting effect parameter data of the target lighting effect on the source device (the device that has already implemented the target lighting effect) (such as obtaining the lighting effect effect to be migrated through video or image) and the device form data of the target device (the device to be adapted) into the lighting effect orchestration model (such as specifically including the lighting effect configuration model and the hardware device model).

[0197] The lighting effect configuration model can learn and understand the lighting effects on the source device to construct an abstract representation of the lighting effects (i.e., lighting effect extraction features, which can characterize the dynamic change rules of the lighting effects and other related visual effects). Furthermore, the device form data of the target device (such as shape, number of LEDs, etc.) can be input into the hardware device model. Using the model's inference capabilities, a target lighting effect configuration file adapted to the target device's form can be generated. This target lighting effect configuration file retains the visual effects and dynamic change rules of the target lighting effect on the source device. Therefore, based on the lighting effects on the source device, an adapted lighting effect configuration file can be intelligently compiled for the target device.

[0198] At this point, the target lighting effect configuration file can be sent to the target device, which then parses the configuration file and displays the lighting effect. In other words, the target device's underlying driver (such as the hardware abstraction layer mentioned above) can parse and display the sent target lighting effect configuration file, thus enabling the target lighting effect to be displayed on the target device.

[0199] Among them, Figure 12 For example, the lighting effects to be migrated include lighting effect 1, lighting effect 2, ..., lighting effect m. The lighting effect parameter data of each lighting effect from the source device can be input into the lighting effect orchestration model. Based on the lighting effect parameter data and the device configuration data of the target device (such as device A and device B), the lighting effect orchestration model can generate lighting effect configuration files adapted to device A (e.g., one lighting effect corresponds to one configuration file, or a configuration file containing the relevant lighting effect configurations from lighting effect 1 to lighting effect m) and lighting effect configuration files adapted to device B.

[0200] Specifically, a lighting effect configuration file adapted to device A can be sent to device A, and a lighting effect configuration file adapted to device B can be sent to device B.

[0201] Device A may include lighting effect configurations for the lighting effects to be migrated, such as a lighting effect configuration file corresponding to each of the lighting effects 1, 2, ..., m. Alternatively, a single lighting effect configuration file may contain the lighting effect configurations corresponding to lighting effect 1, 2, ..., m.

[0202] Specifically, when device A needs to display lighting effect 1, it can obtain the lighting effect configuration (file) corresponding to lighting effect 1, and obtain the lighting effect parameters for lighting effect 1 by cyclically parsing the lighting effect configuration, and then cyclically display lighting effect 1. The processing method in device B is the same.

[0203] The target lighting effect configuration file includes a brightness display parameter table and a color display parameter table. The brightness display parameter table records the brightness parameters displayed by the device's LEDs at each display progress. The color display parameter table records the color parameters displayed by the device's LEDs at each display progress. Therefore, the lighting effect parameters can be obtained by parsing the configuration file: query the brightness display parameter table according to the display progress, and obtain the brightness parameters matching the display progress; query the color display parameter table according to the display progress, and obtain the color parameters matching the display progress; use the brightness and color parameters matching the display progress as the target lighting effect parameters corresponding to the display progress.

[0204] Optionally, the brightness display parameter table can directly define the brightness parameter corresponding to each progress level. Alternatively, if the brightness remains constant, only one brightness parameter can be defined. Or, if the brightness variation follows a pattern, a brightness function describing this pattern can be defined (e.g., defining the relationship between progress and the brightness parameter), and the brightness parameter can be determined based on this function. No restrictions are imposed here. The definition of the color parameter follows the same principle.

[0205] Alternatively, the target lighting effect configuration file may include a display progress array and a display parameter table. The display progress array is used to define the progress information when the display parameters of the device LEDs change, and the display parameter table is used to define the lighting effect parameters displayed by the device LEDs.

[0206] One method for obtaining lighting effect parameters by parsing the lighting effect configuration file is as follows: query the progress information in the display configuration table according to the display progress. If a progress information matching the display progress is found in the display configuration table, then obtain the lighting effect parameters matching the display progress from the display parameter table and use them as the target lighting effect parameters corresponding to the display progress.

[0207] If no progress information matching the display progress is found in the display configuration table, no lighting effect parameter will be obtained from the display parameter table. Instead, the lighting effect parameter corresponding to the previous progress adjacent to the display progress will be used as the lighting effect parameter corresponding to the current display progress.

[0208] Specifically, the target lighting effect configuration file may include a brightness display progress array, a color display progress array, a brightness display parameter table, and a color display parameter table. The brightness display progress array is used to define the progress information of the brightness change displayed by the device LEDs. The color display progress array is used to define the progress information of the color change displayed by the device LEDs. The brightness display parameter table is used to define the brightness parameters displayed by the device LEDs. The color display parameter table is used to define the color parameters displayed by the device LEDs.

[0209] The method for parsing the lighting effect configuration file to obtain the lighting effect parameters can be as follows: Query the progress information in the brightness display configuration table according to the display progress. If a progress information matching the display progress is found in the brightness display configuration table, then obtain the brightness parameter matching the display progress from the brightness display parameter table; Query the progress information in the color display configuration table according to the display progress. If a progress information matching the display progress is found in the color display configuration table, then obtain the color parameter matching the display progress from the color display parameter table; Use the brightness parameter and color parameter matching the display progress as the target lighting effect parameters corresponding to the display progress.

[0210] If no progress information matching the display progress is found in the brightness display configuration table, no brightness parameter will be obtained from the brightness display parameter table. Instead, the brightness parameter corresponding to the previous progress adjacent to the display progress will be used as the brightness parameter corresponding to the current display progress.

[0211] If no matching progress information is found in the color display configuration table, no color parameter is retrieved from the color display parameter table. Instead, the color parameter corresponding to the previous progress adjacent to the current progress is used as the color parameter for the current progress. This yields the target lighting effect parameter corresponding to the current progress.

[0212] Since the target lighting effect display may experience changes in color and brightness during the process, or it may remain unchanged, for progress steps that do not change, it is not necessary to obtain the lighting effect parameters; instead, the display can be directly based on the previous lighting effect parameters. Therefore, the lighting effect configuration file can be configured to specify when the brightness (color) displayed by the device's LEDs changes (i.e., progress information, such as which step the brightness changed, or which step the color changed). In other words, a brightness (color) display progress array can be defined to record each progress step that changes.

[0213] At this point, the brightness display parameter table can define the brightness parameters when the brightness of the device's LED beads changes. For example, if the brightness display progress array includes element 10 (indicating that the brightness will change in the 10th step), the brightness display parameter table can define the brightness parameters corresponding to element 10 (such as the values ​​of r, g, and b). That is, the brightness parameters in the brightness display parameter table correspond one-to-one with the progress parameters in the brightness display progress array. The definition of color parameters follows the same principle. This allows color or brightness parameters to be retrieved only when the color or brightness changes, improving the parsing efficiency of the lighting effect configuration file and the display efficiency of the target lighting effect.

[0214] Optionally, the brightness display parameter table can directly define the brightness parameter corresponding to each changing progress (and the brightness parameter corresponding to the initial progress step0). For example, the brightness parameter corresponding to each progress can be directly defined. Alternatively, if the brightness change follows a pattern, a brightness function describing this pattern can be defined (e.g., defining the relationship between progress and brightness parameters), and the brightness parameter can be determined based on this brightness function. No further limitations are imposed here. The definition of the color parameter is similar.

[0215] Therefore, when obtaining lighting effect parameters, for the initial progress, they can be directly obtained from the brightness display parameter table and the color display parameter table. For other progresses, the brightness display progress array and the color display progress array can be queried first. When it is determined that the brightness or color has changed under the current display progress (i.e., when progress information matching the display progress is found, such as progress information including a progress indicating step 10, and the current display progress is the 10th step, indicating a match), the corresponding lighting effect parameters can then be obtained from the brightness display parameter table or the color display parameter table. If there is no change, the previously displayed lighting effect parameters (such as the lighting effect parameters corresponding to the previous progress, such as the lighting effect parameters corresponding to the 9th step) can be used as the lighting effect parameters corresponding to the current progress.

[0216] If the current progress is found to be at the end of its cycle, it means that the target lighting effect has completed one round of playback. This end progress can be defined in the brightness display progress array and the color display progress array, and the end progress in the brightness display progress array and the color display progress array must be consistent.

[0217] This can be achieved by using a universal lighting effect definition and a common lighting effect configuration format, allowing for a single format to describe all lighting effects. For example, lighting effect parameters can be defined at the granularity of individual device LEDs.

[0218] The display of a single LED in a device typically consists of RGB values ​​and a brightness value. Therefore, the control method for a single-color LED is to specify the color and brightness values. An example configuration structure is shown below:

[0219] typedef struct{

[0220] uint8_t r;

[0221] uint8_t g;

[0222] uint8_t b;

[0223] }LED_STRUCT; / / Represents the parameters (r, g, b) involved in defining color and brightness values. typedef struct {

[0224] uint16_t*pts_arr; / / Time array, which can be used to define progress information to obtain the display progress array (such as the initial progress, and the progress of brightness or color changes after the initial progress). The length of the brightness display progress array must be consistent with bri_length, and the length of the color display progress array must be consistent with col_length.

[0225] uint16_t end_pts; / / End time, which can be used to define the end progress. When the end is reached, the progress bar can be reset to restart the looping of the light effect.

[0226] }EFFECT_PTS_GUIDE;

[0227] typedef struct{

[0228] LED_STRUCT*col_single_arr; / / Defines the brightness parameter of the device LED (this brightness parameter can be used if there is only one device LED, or if each device LED displays the same brightness).

[0229] LED_STRUCT*bri_single_arr; / / Defines the color parameter of the device LED (this color parameter can be used if there is only one device LED, or if each device LED displays the same color).

[0230] LED_STRUCT**col_full_arr; / / *col_arr[LED_AMOUNT], defines the brightness parameter of the device LED. [LED_AMOUNT] represents the LED identifier corresponding to each device LED, such as device LED1, device LED2, etc. Each device LED corresponds to a brightness parameter.

[0231] LED_STRUCT**bri_full_arr; / / *col_arr[LED_AMOUNT], defines the color parameters of the device LEDs. [LED_AMOUNT] represents the LED identifier corresponding to each device LED, such as device LED 1, device LED 2, etc. Each device LED corresponds to a color parameter.

[0232] uint16_t col_length; / / The length of the color display progress array.

[0233] uint16_t bri_length; / / Length of the brightness display progress array.

[0234] EFFECT_PTS_GUIDE col_pts_guide; / / Color display progress array. Each progress (and the initial progress) defined in the color display progress array corresponds to a color parameter mentioned above, thus obtaining the color display parameter table.

[0235] EFFECT_PTS_GUIDE bri_pts_guide; / / Brightness display progress array. Each progress (and the initial progress) defined in the brightness display progress array corresponds to a brightness parameter as described above, thus obtaining the brightness display parameter table.

[0236] }led_effect_param;

[0237] Among them, the color display progress array, brightness display progress array, and lighting effect parameters (color display parameter table, brightness display parameter table) mentioned above can be used as relevant configuration parameters of the target lighting effect in the target lighting effect configuration file.

[0238] Therefore, the lighting effect parameters can be configured using the aforementioned general configuration structure, resulting in a lighting effect configuration file. This allows the device to parse the lighting effect parameters to be displayed from the configuration file. In other words, by designing a lighting effect migration scheme that supports cross-device operation, and through a reasonable migration architecture, the lighting effect configuration and parsing scheme can be made compatible with multiple devices.

[0239] Therefore, the technical solution of this application can improve cross-device capabilities, reduce adaptation costs, and improve adaptation efficiency. Furthermore, by describing the display logic of lighting effects through configurable lighting effects, different lighting effects can be achieved by distributing different lighting effect configuration files. Adjusting the lighting effects only requires modifying the lighting effect parameters and other configuration information in the configuration file, resulting in high efficiency in adjusting and migrating lighting effects. Moreover, devices can uniformly use the same lighting effect driver. Since the device's parsing driver can be unified, strong cross-device capabilities can be ensured.

[0240] In this embodiment, the target lighting effect parameter data on the source device can be obtained. This lighting effect parameter data refers to the data of the target lighting effect parameters implemented on the source device. When the lighting effect extraction features of the lighting effect parameter data are determined by the lighting effect configuration model, a standard lighting effect configuration file can be generated based on these features. The intelligent model can first convert the lighting effect parameter data into a standard lighting effect configuration file based on the relationship between the lighting effect and the lighting effect configuration. Then, the device adaptation model can be used to perform lighting effect migration based on the standard lighting effect configuration file for the device form of the target device. For example, using the form extraction features of the device form data and the standard lighting effect configuration file to perform lighting effect migration, a target lighting effect configuration file adapted to the target device is obtained. This target lighting effect configuration file can be used to implement the target lighting effect on the target device. In this way, the model reasoning ability can be used to understand the lighting effect of the target lighting effect on the source device, and the lighting effect migration can be carried out step by step. This allows for the compilation of a corresponding lighting effect configuration file for the target device, which not only enables rapid adaptation and migration of lighting effects, but also reduces the difficulty of cross-device migration of lighting effects and improves migration efficiency.

[0241] For further details, please see Figure 13 , Figure 13 This is a flowchart illustrating a lighting effect data processing method provided in an embodiment of this application, as shown below. Figure 13 As shown, the method can be executed by the aforementioned computer devices, such as... Figure 1 For any of the service terminals or service servers shown, the method may specifically include the following steps S301-S306:

[0242] S301. Obtain the sample lighting effect parameter data of the sample lighting effect displayed on the sample device, the sample lighting effect configuration file of the sample lighting effect for the sample device, the sample device form data of the sample device, the standard device form data of the standard device, and the sample standard lighting effect configuration file of the sample lighting effect for the standard device.

[0243] Specifically, the lighting effect extraction features are generated by a lighting effect configuration model used for lighting effect migration. The morphological extraction features are generated by a device adaptation model used for lighting effect migration.

[0244] Among these methods, relevant lighting effect data from sample devices can be used to train the lighting effect configuration model and the device adaptation model.

[0245] The sample lighting effect parameter data refers to the data obtained when the sample lighting effect is displayed on the sample device. Specifically, it refers to the data of the sample lighting effect parameters corresponding to the sample lighting effect.

[0246] The sample lighting effect configuration file is used to implement sample lighting effects on sample devices; that is, it is the actual lighting effect configuration file for sample devices. The sample standard lighting effect configuration file is used to implement sample lighting effects on standard devices; that is, it is the actual standard lighting effect configuration file for standard devices.

[0247] S302. Input the sample lighting effect parameter data and the standard lighting effect configuration file into the lighting effect configuration model to be trained. The lighting effect configuration model to be trained determines the sample lighting effect extraction features of the sample lighting effect parameter data and the standard morphology extraction features of the standard equipment morphology data.

[0248] The lighting effect configuration model to be trained (initial lighting effect configuration model) can extract features from sample lighting effect parameter data to obtain sample lighting effect extraction features based on the sample lighting effect parameter data. It can also extract features from standard device shape data to obtain standard shape extraction features. The specific methods for determining the sample lighting effect extraction features and standard shape extraction features can be found in the relevant descriptions of the above embodiments.

[0249] S303. When generating a predicted standard lighting effect configuration file adapted to standard equipment based on the sample lighting effect extraction features and the standard shape extraction features, determine the first loss value for the lighting effect configuration model to be trained based on the sample standard lighting effect configuration file and the predicted standard lighting effect configuration file.

[0250] In this process, feature fusion can be performed on the extracted features of sample lighting effects and the extracted features of standard morphology to obtain the first sample fusion feature, and then the predicted standard lighting effect configuration file for standard equipment can be generated based on the first sample fusion feature.

[0251] For example, extracting features F from sample lighting effects effect Extracting features F from standard morphology shape_dst Perform feature fusion:

[0252] F combined1 =f fusion1 (F effect ,F shape_dst )

[0253] Among them, F combined1 This represents the fusion function.

[0254] Among them, the first fusion feature F can be used combined Generate a predictive standard lighting effect profile F that matches the sample lighting effect and is suitable for standard equipment. pred_config .

[0255] At this point, the standard lighting effect configuration file F can be used as a reference. true_config and predictive standard lighting profile F pred_configDetermine the first loss value L for the initial lighting configuration model. config :

[0256] L config =||F pred_config -F true_config || 2

[0257] Where, ||x|| 2 represents the square of the Euclidean distance to x, and represents the error between the sample standard lighting profile and the predicted standard lighting profile.

[0258] For example, the first representation vector and the second representation vector of the sample standard lighting effect configuration file can be determined, and the first loss value can be determined based on the vector difference between the first representation vector and the second representation vector, such as using the square of the Euclidean distance determined by the first representation vector and the second representation vector as the first loss value.

[0259] Specifically, determining the first representation vector can be achieved by parsing the sample lighting effect parameters corresponding to the sample lighting effect on a standard device from the sample standard lighting effect configuration file, and using these sample lighting effect parameters as the first representation vector of the sample standard lighting effect configuration file. For example, a matrix composed of the sample lighting effect parameters corresponding to all display progress can be used as the first representation vector (such as lighting effect parameters obtained from the brightness display parameter table and color display parameter table). Optionally, the brightness display progress array and the color display progress array can be further combined to form a matrix as the first representation vector. That is, the relevant configuration parameters are parsed from the sample standard lighting effect configuration file as the first representation vector.

[0260] The second representation vector can be determined by parsing the predicted lighting effect parameters corresponding to the sample lighting effect on the standard device from the predicted standard lighting effect configuration file, and using these predicted lighting effect parameters as the second representation vector of the sample standard lighting effect configuration file. Optionally, the second representation vector can be determined in the same way as the first representation vector. This allows the final first loss value to be obtained by averaging the display differences between the lighting effect parameters of each device's LEDs.

[0261] Alternatively, determining the first representation vector can be done by representing the sample standard lighting effect configuration file as a file, obtaining a first file conversion vector of the sample standard lighting effect configuration file, and using the first file conversion vector as the first representation vector. For example, feature encoding can be performed on the sample standard lighting effect configuration file, and the obtained file encoding features can be used as the first file conversion vector. This can be done using a transformer encoder or one-hot encoding.

[0262] Specifically, determining the second representation vector can be achieved by representing the predicted standard lighting effect configuration file as a file, obtaining a second file conversion vector for the predicted standard lighting effect configuration file, and using this second file conversion vector as the second representation vector. The method for determining the second file conversion vector is the same as the method for determining the first file conversion vector.

[0263] Therefore, based on the first loss value, the predicted standard lighting effect configuration file, the sample lighting effect configuration file, and the sample device form data, the lighting effect configuration model to be trained and the device adaptation model to be trained (initial device adaptation model) can be trained to obtain the trained lighting effect configuration model and the trained device adaptation model.

[0264] For example, a second loss value can be determined for the device adaptation model. The initial lighting effect configuration model and the initial device adaptation model can be trained using the first and second loss values ​​until the models converge, resulting in the trained lighting effect configuration model (target lighting effect configuration model) and the trained device adaptation model (target device adaptation model). Therefore, it can be divided into two sub-tasks, and the lighting effect transfer can be achieved through the models corresponding to each sub-task.

[0265] S304. Input the predicted standard lighting effect configuration file, the sample lighting effect configuration file, and the sample device morphology data into the device adaptation model to be trained. The device adaptation model to be trained determines the sample morphology extraction features of the sample device morphology data and the sample file encoding features of the predicted standard lighting effect configuration file.

[0266] The device adaptation model to be trained can extract features from the sample device morphology data to obtain sample morphology extraction features. It can also extract features from the predicted standard lighting effect configuration file to obtain sample file encoding features of the predicted standard lighting effect configuration file. The specific methods for determining the sample morphology extraction features and sample file encoding features can be found in the relevant descriptions of the above embodiments.

[0267] S305. When generating a predicted lighting effect configuration file adapted to the sample device based on the sample file encoding features and sample morphology extraction features, a second loss value for the device adaptation model to be trained is determined based on the sample lighting effect configuration file and the predicted lighting effect configuration file.

[0268] In this process, feature fusion can be performed on the encoding features of the sample file and the extracted features of the sample morphology to obtain a second sample fusion feature, which is then used to predict and generate a lighting effect configuration file for the sample device.

[0269] For example, the encoding feature F of the sample file config_enc Extracting features F from standard morphology shape_enc Perform feature fusion:

[0270] F combined2 =f fusion2 (F config_enc ,F shape_enc )

[0271] Among them, F combined2 This represents the fusion function.

[0272] Among them, the second fusion feature F can be used. combined2 Generate a predictive lighting profile F that matches the sample lighting effects and is suitable for the sample device. config_dst .

[0273] At this point, you can refer to the sample lighting effect configuration file F. config_std and predictive lighting profile F config_dst Determine the second loss value L for the initial device adaptation model. config :

[0274] L adapt =||F config_std -F config_dst || 2

[0275] Where, ||x|| 2 Let represent the squared Euclidean distance to x, and let represent the error between the sample lighting effect profile and the predicted lighting effect profile. In this case, the method for determining the second loss value can be the same as the method for determining the first loss value.

[0276] Alternatively, the second loss value can also be determined as follows:

[0277]

[0278] in, This represents the Frobenius norm (a type of matrix norm). Where F... config_std It can be represented as the first representation vector of the sample lighting effect configuration file. F config_dst It can be represented as the second representation vector of the predicted lighting effect profile.

[0279] In this case, the method for determining the first loss value can be the same as the method for determining the second loss value.

[0280] S306. Using the target loss value determined by the first loss value and the second loss value, train the lighting effect configuration model and the device adaptation model to be trained to obtain the trained lighting effect configuration model and the trained device adaptation model.

[0281] Among them, the first loss value L can be... config Second loss value L adaptThe target loss value L is obtained by weighted summation:

[0282] L=λ config L config +λ adapt L adapt

[0283] Where, λ adapt , λ config This represents hyperparameters.

[0284] At this point, multi-task learning is adopted to jointly train the two models. The first task learns the mapping relationship between lighting effects and standard equipment configuration, and the second task learns the mapping relationship between standard equipment configuration and target device.

[0285] After training, the prediction performance of the trained lighting configuration model and the trained device adaptation model can be tested.

[0286] For example, it can obtain the actual lighting effect parameter data of the test lighting effect displayed on the test equipment, the actual lighting effect configuration file of the test lighting effect for the test equipment, and the test equipment form data.

[0287] The process involves inputting real lighting effect parameter data into the lighting effect configuration model. The model then determines the test lighting effect extraction features based on the real lighting effect parameter data and generates a standard lighting effect configuration file based on these features and the standard form extraction features. For details on how the lighting effect configuration model generates the standard lighting effect configuration file, please refer to the relevant descriptions above.

[0288] The process involves inputting the standard lighting effect configuration file and test equipment form data into the device adaptation model. The model then determines the test form extraction features of the test equipment form data and the file encoding features of the standard lighting effect configuration file. Based on these file encoding features and test form extraction features, a test lighting effect configuration file adapted to the test equipment is generated. For details on how the device adaptation model generates the test lighting effect configuration file, please refer to the above description.

[0289] At this point, the post-training model testing information for the lighting effect configuration model and the device adaptation model can be determined based on the test lighting effect configuration file, the actual lighting effect configuration file, and the actual lighting effect parameter data. This model testing information can be used to verify the training effect of the lighting effect configuration model and the device adaptation model, i.e., the model accuracy.

[0290] If the verification model training effect is good, the lighting effect configuration model and device adaptation model can be deployed on the server or on the target device to achieve lighting effect migration.

[0291] The test set consists of actual lighting effect parameter data and test equipment configuration data, used to obtain the predicted data to be tested. The validation set consists of actual lighting effect parameter data and actual lighting effect configuration files, used to validate the obtained test data.

[0292] The process of determining model test information may include: determining the file deviation data between the actual lighting effect configuration file and the test lighting effect configuration file; parsing the test lighting effect configuration file to obtain the test lighting effect parameters corresponding to the test lighting effect; determining the test lighting effect parameter data when the test lighting effect is displayed on the test device based on the test lighting effect parameters; determining the parameter deviation data between the actual lighting effect parameter data and the test lighting effect parameter data; and determining the model test information based on the file deviation data and the parameter deviation data.

[0293] The method for determining the file deviation data can be the same as the method for determining the first loss value or the second loss value mentioned above.

[0294] Alternatively, determine the file deviation data MES config The method can be:

[0295]

[0296] Among them, the file deviation data represents the difference between the prediction and the reality at the lighting effect configuration level, that is, the error between the generated lighting effect configuration file and the actual lighting effect configuration file.

[0297] Among them, F pred_config The representation vector representing the test lighting effect configuration file. F true_config This represents the representation vector of the actual lighting effect configuration file. 'n' represents the total number of elements in the representation vector of the test lighting effect configuration file (the representation vector of the actual lighting effect configuration file).

[0298] The method for obtaining test lighting effect parameter data can be the same as the method for obtaining actual lighting effect parameter data. For example, test lighting effect parameter data is the video data of the lighting effect recorded when the test equipment displays the test lighting effect based on the test lighting effect parameters in the test lighting effect configuration file. Actual lighting effect parameter data is the video data of the lighting effect recorded when the test equipment displays the actual lighting effect based on the test lighting effect parameters in the actual lighting effect configuration file, thus determining the consistency between the actual effect and the predicted effect.

[0299] The parameter deviation between the actual lighting effect parameter data and the test lighting effect parameter data can be determined by the lighting effect extraction features (first lighting effect extraction features) obtained by feature extraction of the actual lighting effect parameter data and the lighting effect extraction features (second lighting effect extraction features) obtained by feature extraction of the test lighting effect parameter data.

[0300] For example, the Dynamic Time Warping (DTW) algorithm can be used to determine the optimal matching path error between the first and second light effect extracted features.

[0301] That is, parameter deviation data = DTW(first lighting effect extracted features, second lighting effect extracted features). This represents the difference between the prediction and the reality at the level of lighting effect effect, that is, to evaluate the error between the lighting effect effect obtained from the generated lighting effect profile and the lighting effect effect obtained from the real lighting effect profile.

[0302] Specifically, model test information can be determined based on file deviation data and parameter deviation data. For example, the average value of the file deviation data and parameter deviation data of the test equipment can be used as model test information.

[0303] Alternatively, based on the file deviation data and parameter deviation data of the test equipment, the target test equipment that has successfully adapted can be determined. The ratio between the target test equipment and the test equipment is used as the adaptation success rate on different devices.

[0304] That is, the adaptation success rate = the number of target test devices that were successfully adapted / the number of test devices.

[0305] Among them, the test equipment whose file deviation data is lower than a first preset value and whose parameter deviation data is lower than a second preset value can be used as the target test equipment.

[0306] Once the lighting effect configuration model and device adaptation model have been successfully trained (e.g., with a preset adaptation success rate), they can be deployed. This can be done on a server or on edge devices, such as embedded devices and mobile devices, or mobile devices and small hardware devices.

[0307] For example, such as Figures 14-21 , Figures 14-21 This is a schematic diagram of a model-based lighting effect migration scenario provided in an embodiment of this application; wherein, in Figure 14 In this process, sample lighting effect parameter data 1401a is input into the initial lighting effect configuration model (the lighting effect configuration model to be trained), and the sample lighting effect extraction feature 1401b is obtained by the feature encoding layer. Similarly, standard device shape data 1402a is input into the initial lighting effect configuration model, and the standard shape extraction feature 1402b is obtained by the feature encoding layer. The standard shape extraction feature can be deployed in the initial lighting effect configuration model.

[0308] In the lighting effect configuration model, the feature fusion layer performs feature fusion on the standard form extraction feature 1402b and the sample lighting effect extraction feature 1401b to obtain the first sample fusion feature 1403a. Then, the feature decoding layer decodes the first sample fusion feature 1403a to obtain the predicted standard lighting effect configuration file 1404a.

[0309] Specifically, the first loss value 1405a for the lighting effect configuration model to be trained is determined based on the sample standard lighting effect configuration file 1404b and the prediction standard lighting effect configuration file 1404a.

[0310] Specifically, the device morphology data 1406a (sample device morphology data) of the sample device is input into the initial device adaptation model (the device adaptation model to be trained), and the sample morphology extraction feature 1406b of the sample device morphology data is obtained by the feature encoding layer. The sample morphology extraction feature is then feature-encoded to obtain the morphology encoding feature. The prediction standard lighting effect configuration file 1404a is input into the initial device adaptation model, and the sample file encoding feature 1404c of the prediction standard lighting effect configuration file is obtained by the feature encoding layer.

[0311] Specifically, the feature fusion layer fuses the morphological encoding features corresponding to the sample morphological extraction feature 1406b and the sample file encoding feature 1404c to obtain the second sample fusion feature 1403b. Then, the feature decoding layer decodes the second sample fusion feature to obtain the predicted lighting effect configuration file 1407a. Based on the sample lighting effect configuration file 1407b and the predicted lighting effect configuration file 1407a, a second loss value 1405b can be determined for the device adaptation model to be trained.

[0312] Specifically, the target loss value can be determined by the first loss value 1405a and the second loss value 1405b, and the initial lighting effect configuration model and the initial device adaptation model can be trained to obtain the target lighting effect configuration model (the trained lighting effect configuration model) and the target device adaptation model (the trained device adaptation model).

[0313] This can be achieved by jointly training the initial lighting effect configuration model and the initial device adaptation model, or by training them independently. For example, the initial lighting effect configuration model can be trained using a first loss value, and the initial device adaptation model can be trained using a second loss value.

[0314] Among them, Figure 15 The technical solution of this application is divided into three parts.

[0315] I. Lighting Effect Configuration and Parsing. Among them, (1) Lighting effect definition: a general lighting effect configuration format can be defined to obtain a lighting effect configuration file, realizing a single format that satisfies the description of all lighting effects. (2) Configuration management: lighting effect configurations can be set to the device through various methods such as network distribution, built-in configuration, and Bluetooth transmission. (3) Parsing and display: the lighting effect configuration file is parsed in a loop to realize the playback of the specified lighting effect. (4) Cross-device solution: a reasonable model architecture is designed, and a lighting effect configuration and parsing solution is set to support the cross-device migration of lighting effects.

[0316] II. Lighting effect configuration across devices and adaptive model training. Among them, (1) data collection and processing, collecting a wide range of lighting effect samples, as well as the performance of lighting effects on various devices.

[0317] For example, data collection mainly includes: collecting common lighting effect examples (such as breathing light, gradient light, flashing light, etc.) on multiple devices, lighting effect configuration files, device form data, such as form parameters of different devices (such as the number of LED beads, arrangement: matrix, ring, linear), lighting effect parameter data, and actual display effect data of the same lighting effect on different devices (which can be recorded by a camera).

[0318] Optionally, data augmentation can also be performed. For example, sample diversity can be increased by manually generating or transforming existing samples: such as modifying lighting effect parameters (e.g., color, time interval, brightness gradient rate) to enrich the lighting effects. Alternatively, various device forms (light strip forms) can be simulated, such as rings, strips, or transforming a 5×5 matrix into a 10×2 linear arrangement. Furthermore, lighting effect configurations can be manually adapted for different devices to enrich both the devices and the lighting effect configurations.

[0319] (2) Model design and training: Define reasonable inputs and outputs, and select a suitable model architecture for training. (3) Model testing and deployment: Verify the model's performance after training, select a suitable inference framework, and then deploy the model to a server or device.

[0320] III. Implementation of the Solution. Among them, (1) Lighting effect input can include lighting effect parameter data and the device form of the target device. (2) Model reasoning can output a lighting effect configuration file adapted to the target device. (3) Lighting effect configuration distribution can distribute the lighting effect configuration file to the target device, and the target device can parse and display the target lighting effect.

[0321] Among them, Figure 16The model design concept is as follows: 1. Train the ability to infer and configure lighting effects: Understand the relationship between lighting effects and lighting effect configuration (i.e., be able to generate corresponding lighting effect configuration files based on the lighting effect parameter data). For the lighting effect configuration model, different standard lighting effect configuration files can be generated for standard equipment based on different lighting effect parameter data. At this point, only the equipment form of standard equipment needs to be designed.

[0322] 2. Training Lighting Effect Device Adaptability: Understanding the impact of device form factor on lighting effect configuration. For the device adaptation model, it's possible to generate lighting effect configuration files for the same lighting effect on different devices. This involves the different device forms.

[0323] Among them, Figure 17 In the process of transferring lighting effects using the model, the lighting effect parameter data can be input into the lighting effect configuration model, and the output can be a standard lighting effect configuration file under the standard device. The standard lighting effect configuration file and the device form data of the target device can be input into the device adaptation model, and the output can be a target lighting effect configuration file under the target device.

[0324] Among them, Figure 18 Therefore, the training process for the lighting effect configuration model is as follows: Sample lighting effect parameter data (such as video / image / text), standard device form data, and sample standard lighting effect configuration files for the standard device are input into the lighting effect configuration model to be trained. The model is then trained based on the output predicted standard lighting effect configuration files for the standard device and the sample standard lighting effect configuration files to understand the relationship between the lighting effect parameter data and the standard device's lighting effect configuration files. The resulting lighting effect configuration model takes the lighting effect parameter data of the lighting effect to be transferred as input and outputs the standard lighting effect configuration files for the standard device.

[0325] Among them, Figure 19 In this process, the training of the device adaptation model involves inputting the predicted standard lighting effect configuration file output by the lighting effect configuration model and the sample device form data of the sample device into the device adaptation model to be trained. The model is then trained based on the output sample lighting effect configuration file and predicted lighting effect configuration file for the sample device to understand the relationship between the lighting effect configuration file and the device form. The resulting device adaptation model takes the device form data of the target device and the standard lighting effect configuration file output by the lighting effect configuration model as input, and outputs the target lighting effect configuration file for the target device.

[0326] Among them, Figure 20In the diagram, the relationship between lighting effect parameter data, device form data, and lighting effect configuration files is as follows: the lighting effect parameter data of N lighting effects and the device form data of device A can generate N lighting effect configuration files (including N lighting effect configurations) adapted to device A; the lighting effect parameter data of N lighting effects and the device form data of device B can generate N lighting effect configuration files (including N lighting effect configurations) adapted to device B.

[0327] Among them, Figure 21 In the above, the specific scenarios for light effect migration can be as follows: S2001, the user sends the light effect, sending the light effect parameter data and the device form data of the target device to the server; S2002, model inference, which can generate the target light effect configuration file for the target device based on the light effect parameter data and the device form data of the target device through the light effect configuration model and the device adaptation model; S2003, light effect configuration distribution, which can distribute the target light effect configuration file to the target device, which will then parse and display it.

[0328] The technical solution of this application can reduce the time cost of developing and migrating lighting effect configurations, and improve the coverage of device adaptation. It supports device lighting effect adaptation for various LED bead arrangements, from regular shapes (such as straight light strips) to irregular shapes (such as grid-type and ring-type light strips). The consistency of lighting effects is enhanced. By utilizing model reasoning capabilities, the lighting effect display logic can be automatically learned, ensuring that the adaptation and performance on different devices remain highly consistent.

[0329] Among them, based on a common lighting effect configuration format and a common lighting effect parsing logic, lighting effect migration can be adapted to a variety of devices, realizing the universality of lighting effect configuration and migration, and using model reasoning to achieve adaptive adaptation.

[0330] In this embodiment, relevant sample data (such as sample lighting effect parameter data and standard lighting effect configuration files) can be obtained to train a lighting effect configuration model. This allows the lighting effect configuration model to learn the relationship between lighting effects and lighting effect configurations through the reasoning capabilities of the intelligent model, thus converting sample lighting effect parameter data into standard lighting effect configuration files. Furthermore, a device adaptation model can be trained using relevant sample data (such as predicted standard lighting effect configuration files, sample lighting effect configuration files, and sample device form data). This allows the device adaptation model to learn lighting effect migration based on the predicted standard lighting effect configuration files for the device form of the sample device, obtaining a predicted lighting effect configuration file adapted to the sample device. Thus, the trained lighting effect configuration model and device adaptation model can understand the lighting effect of sample lighting effects on sample devices, enabling step-by-step lighting effect migration. This not only achieves rapid adaptation and migration of lighting effects but also reduces the difficulty of cross-device migration and improves migration efficiency.

[0331] For further details, please see Figure 22 , Figure 22 This is a schematic diagram of the structure of a lighting effect data processing device provided in an embodiment of this application. Figure 22 As shown, the lighting effect data processing device 1 can be applied to a computer device. It should be understood that the lighting effect data processing device 1 can be a computer program (including program code) running on the computer device; for example, the lighting effect data processing device 1 can be an application software. It is understood that the lighting effect data processing device 1 can be used to execute the corresponding steps in the methods provided in the embodiments of this application. Figure 22 As shown, the lighting effect data processing device 1 may include: a parameter data acquisition module 11, a lighting effect feature extraction module 12, a morphological feature extraction module 13, a configuration file generation module 14, and a model training module 15. Wherein:

[0332] The parameter data acquisition module 11 is used to acquire the lighting effect parameter data of the target lighting effect displayed by the source device; the target lighting effect refers to the lighting effect to be migrated from the source device to the target device; the lighting effect parameter data refers to the data of the target lighting effect parameters corresponding to the target lighting effect.

[0333] The lighting effect feature extraction module 12 is used to extract features from the lighting effect parameter data, obtain the lighting effect extraction features for the lighting effect parameter data, and generate a standard lighting effect configuration file based on the lighting effect extraction features.

[0334] The morphological feature extraction module 13 is used to acquire the device morphological data of the target device, extract features from the device morphological data, and obtain morphological features extracted from the device morphological data.

[0335] The configuration file generation module 14 is used to perform lighting effect migration using morphological extraction features and standard lighting effect configuration files to obtain a target lighting effect configuration file adapted to the target device. The target lighting effect configuration file is used to instruct the target device to display the target lighting effect based on the target lighting effect parameters when the target lighting effect parameters are parsed.

[0336] Among them, the lighting effect parameter data is the lighting effect video data recorded when the source device displays the target lighting effect based on the target lighting effect parameters;

[0337] The lighting effect feature extraction module 12 includes:

[0338] The lighting effect feature extraction unit 121 is used to obtain a lighting effect configuration model for lighting effect migration. The lighting effect video data is input into the lighting effect configuration model, and the lighting effect configuration model extracts N lighting effect video frames from the lighting effect video data; N is a positive integer.

[0339] The lighting effect feature extraction unit 121 is also used to obtain the target lighting effect video frame from N lighting effect video frames and to obtain the first color channel data of the target lighting effect video frame in the first color space.

[0340] The lighting effect feature extraction unit 121 is also used to convert the first color channel data into the second color channel data in the second color space through the color conversion relationship between the first color space and the second color space, and use the second color channel data as the color extraction feature of the target lighting effect video frame.

[0341] The lighting effect feature extraction unit 121 is also used to obtain the color extraction features of each lighting effect video frame when each of the N lighting effect video frames is selected as the target lighting effect video frame, and to use the color extraction features of each lighting effect video frame as the lighting effect extraction features.

[0342] Among them, the lighting effect extraction features are generated by the lighting effect configuration model used for lighting effect migration;

[0343] The lighting effect feature extraction module 12 includes:

[0344] The first feature fusion unit 122 is used to perform feature fusion on the standard form extraction feature and the lighting effect extraction feature when the standard form extraction feature of the standard device is obtained through the lighting effect configuration model, and generate the first fused feature.

[0345] The standard file generation unit 123 is used to generate a standard lighting effect configuration file adapted to standard devices based on the first fusion feature.

[0346] Among them, the device morphology data is the device image data of the target device;

[0347] The morphological feature extraction module 13 is specifically used for:

[0348] Obtain the device adaptation model for lighting effect migration, input the device form data into the device adaptation model for lighting effect migration, the device adaptation model performs device LED positioning processing on the device image data, and generates the positioning coordinates of the device LED when locating the device LED on the target device from the device image data; the device LED is used to display the target lighting effect;

[0349] The positioning coordinates of the device's LED beads are used as morphological extraction features.

[0350] Among them, the morphological extraction features are generated by the device adaptation model used for lighting effect migration;

[0351] Configuration file generation module 14 includes:

[0352] The second feature fusion unit 141 is used to encode the morphology extraction features through the device adaptation model to obtain the morphology encoding features of the morphology extraction features, and to encode the standard lighting effect configuration file to obtain the file encoding features of the standard lighting effect configuration file.

[0353] The target file generation unit 142 is used to perform feature fusion on morphological encoding features and file encoding features to obtain a second fused feature, and generate a target lighting effect configuration file based on the second fused feature.

[0354] Among them, the lighting effect extraction features are generated by the lighting effect configuration model used for lighting effect migration; the morphology extraction features are generated by the device adaptation model used for lighting effect migration.

[0355] The lighting effect data processing device 1 also includes a model training module 15, which includes:

[0356] The sample data acquisition unit 151 is used to acquire the sample lighting effect parameter data of the sample lighting effect displayed on the sample device, the sample lighting effect configuration file of the sample lighting effect for the sample device, the sample device form data of the sample device, the standard device form data of the standard device, and the sample standard lighting effect configuration file of the sample lighting effect for the standard device.

[0357] The model processing unit 152 is used to input the sample lighting effect parameter data and the standard lighting effect configuration file into the lighting effect configuration model to be trained, and the lighting effect configuration model to be trained determines the sample lighting effect extraction features of the sample lighting effect parameter data and the standard shape extraction features of the standard equipment shape data.

[0358] The loss determination unit 153 is used to determine the first loss value for the lighting effect configuration model to be trained based on the sample standard lighting effect configuration file and the predicted standard lighting effect configuration file when generating a predicted standard lighting effect configuration file adapted to the standard equipment based on the sample lighting effect extraction features and the standard shape extraction features.

[0359] The model training unit 154 is used to train the lighting effect configuration model and the device adaptation model to be trained based on the first loss value, the prediction standard lighting effect configuration file, the sample lighting effect configuration file, and the sample device shape data, so as to obtain the trained lighting effect configuration model and the trained device adaptation model.

[0360] Specifically, model training unit 154 is used for:

[0361] The predicted standard lighting effect configuration file, sample lighting effect configuration file, and sample device morphology data are input into the device adaptation model to be trained. The device adaptation model to be trained determines the sample morphology extraction features of the sample device morphology data and the sample file encoding features of the predicted standard lighting effect configuration file.

[0362] When generating a predicted lighting effect configuration file adapted to the sample device based on the sample file encoding features and sample morphology extraction features, a second loss value for the device adaptation model to be trained is determined based on the sample lighting effect configuration file and the predicted lighting effect configuration file.

[0363] The target loss value, determined by the first loss value and the second loss value, is used to train the lighting configuration model and the device adaptation model to be trained.

[0364] Specifically, the loss determination unit 153 is used for:

[0365] Parse the sample lighting effect parameters corresponding to the sample lighting effect on the standard device from the sample standard lighting effect configuration file, and use the sample lighting effect parameters as the first representation vector of the sample standard lighting effect configuration file; then parse the predicted lighting effect parameters corresponding to the sample lighting effect on the standard device from the predicted standard lighting effect configuration file, and use the predicted lighting effect parameters as the second representation vector of the sample standard lighting effect configuration file; or...

[0366] The sample standard lighting effect configuration file is represented by a file to obtain the first file conversion vector of the sample standard lighting effect configuration file. The first file conversion vector is used as the first representation vector. The predicted standard lighting effect configuration file is represented by a file to obtain the second file conversion vector of the predicted standard lighting effect configuration file. The second file conversion vector is used as the second representation vector.

[0367] The first loss value is determined based on the vector difference between the first representation vector and the second representation vector.

[0368] The model training module 15 also includes:

[0369] The model test unit 155 is used to acquire the actual lighting effect parameter data of the test lighting effect displayed on the test equipment, the actual lighting effect configuration file of the test lighting effect for the test equipment, and the test equipment form data of the test equipment.

[0370] The model testing unit 155 is used to input real lighting effect parameter data into the lighting effect configuration model, and the lighting effect configuration model determines the test lighting effect extraction features for the real lighting effect parameter data, and generates a standard lighting effect configuration file based on the test lighting effect extraction features and standard form extraction features.

[0371] The model testing unit 155 is used to input the standard lighting effect configuration file and the test equipment form data into the device adaptation model. The device adaptation model determines the test form extraction features of the test equipment form data and the file encoding features of the standard lighting effect configuration file.

[0372] Model test unit 155 is used to generate a test lighting configuration file adapted to the test equipment based on file encoding features and test pattern features extracted.

[0373] The test information determination unit 156 is used to determine the model test information of the lighting effect configuration model and the device adaptation model after training, based on the test lighting effect configuration file, the real lighting effect configuration file, and the real lighting effect parameter data.

[0374] Specifically, the test information determination unit 156 is used for:

[0375] Determine the file deviation data between the actual lighting effect configuration file and the test lighting effect configuration file;

[0376] The test lighting effect configuration file is parsed to obtain the test lighting effect parameters corresponding to the test lighting effect. When the test lighting effect is displayed on the test device based on the test lighting effect parameters, the test lighting effect parameter data of the test lighting effect is determined.

[0377] Determine the parameter deviation data between the actual lighting effect parameter data and the tested lighting effect parameter data;

[0378] Model test information is determined based on file deviation data and parameter deviation data.

[0379] The configuration file generation module 14 also includes:

[0380] The lighting effect analysis unit 143 is used to obtain the display progress bar for displaying the target lighting effect;

[0381] The lighting effect parsing unit 143 is also used to parse the target lighting effect parameters corresponding to the display progress from the target lighting effect configuration file according to the display progress indicated by the display progress bar; the target lighting effect parameters corresponding to the display progress are used to indicate the color parameters and brightness parameters of the device LEDs on the target device at the display progress.

[0382] The lighting effect analysis unit 143 is also used to instruct the device LEDs to display according to the color and brightness parameters corresponding to the display progress.

[0383] The target lighting effect configuration file includes a brightness display progress array, a color display progress array, a brightness display parameter table, and a color display parameter table. The brightness display progress array is used to define the progress information of the brightness change displayed by the device LEDs. The color display progress array is used to define the progress information of the color change displayed by the device LEDs. The brightness display parameter table is used to define the brightness parameters displayed by the device LEDs. The color display parameter table is used to define the color parameters displayed by the device LEDs.

[0384] The lighting effect analysis unit 143 is specifically used for:

[0385] The progress information in the brightness display configuration table is queried according to the display progress. If the progress information that matches the display progress is found in the brightness display configuration table, the brightness parameter that matches the display progress is obtained from the brightness display parameter table.

[0386] The progress information in the color display configuration table is queried according to the display progress. If the progress information that matches the display progress is found in the color display configuration table, the color parameter that matches the display progress is obtained from the color display parameter table.

[0387] The brightness parameter and color parameter that match the display progress are used as the target lighting effect parameters corresponding to the display progress.

[0388] The specific implementation methods of the parameter data acquisition module, lighting effect feature extraction module, morphological feature extraction module, configuration file generation module, and model training module can be found in the relevant descriptions in the above embodiments, and will not be repeated here. It should be understood that the beneficial effects obtained using the same method will also not be repeated here.

[0389] In this application embodiment, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0390] Further, please see Figure 23 , Figure 23 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Figure 23 As shown, the computer device 1400 can be a business terminal or a server; this is not a limitation. For ease of understanding, this application takes a computer device as a server as an example. The computer device 1400 may include: a processor 1401, a network interface 1404, and a memory 1405. Furthermore, the computer device 1400 may also include: a user interface 1403, and at least one communication bus 1402. The communication bus 1402 is used to implement communication between these components. The user interface 1403 may also include a standard wired interface and a wireless interface. The network interface 1404 may optionally include a standard wired interface and a wireless interface (such as a Wi-Fi interface). The memory 1405 may be high-speed RAM or non-volatile memory, such as at least one disk storage device. Optionally, the memory 1405 may also be at least one storage device located remotely from the aforementioned processor 1401. Figure 13As shown, the memory 1405, which is a computer-readable storage medium, may include an operating system, a network communication module, a user interface module, and a device control application.

[0391] The network interface 1404 in the computer device 1400 can also provide network data interaction functionality. Figure 23 In the computer device 1400 shown, the network interface 1404 provides network data interaction functionality; the user interface 1403 is mainly used to provide an input interface for the user; and the processor 1401 can be used to call the device control application stored in the memory 1405 to execute the above-mentioned functions. Figure 3 , Figure 7 , Figure 13 The description of the lighting effect data processing method in the corresponding embodiment can also be executed as described above. Figure 22 The description of the lighting effect data processing device 1 in the corresponding embodiments will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be repeated here.

[0392] Furthermore, it should be noted that this application embodiment also provides a computer-readable storage medium, which stores a computer program executed by the aforementioned lighting effect data processing device 1. The computer program includes a computer program that, when executed by a processor, can execute the aforementioned... Figure 3 , Figure 7 , Figure 13 The description of the lighting effect data processing method in the corresponding embodiments is already provided and will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be repeated. For technical details not disclosed in the computer-readable storage medium embodiments related to this application, please refer to the description of the method embodiments of this application. As an example, a computer program can be deployed and executed on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network. These multiple computing devices distributed across multiple locations and interconnected via a communication network can constitute a blockchain system.

[0393] Furthermore, it should be noted that this application also provides a computer program product, which includes a computer program that can be stored in a computer-readable storage medium. The processor of a computer device reads the computer program from the computer-readable storage medium, and the processor can execute the computer program, causing the computer device to perform the aforementioned... Figure 3 , Figure 7 , Figure 13The description of the lighting effect data processing method in the corresponding embodiments is already provided and will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be repeated. For technical details not disclosed in the computer program product embodiments related to this application, please refer to the description of the method embodiments of this application.

[0394] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0395] The steps in the method of this application embodiment can be adjusted, combined, or deleted according to actual needs.

[0396] The modules in the device of this application embodiment can be merged, divided, and deleted according to actual needs.

[0397] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0398] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.

Claims

1. A method for processing lighting effect data, characterized in that, The method includes: Obtain the lighting effect parameter data of the target lighting effect displayed by the source device; the target lighting effect refers to the lighting effect to be migrated from the source device to the target device; the lighting effect parameter data refers to the data of the target lighting effect parameters corresponding to the target lighting effect; Feature extraction is performed on the lighting effect parameter data to obtain lighting effect extraction features for the lighting effect parameter data, and a standard lighting effect configuration file is generated based on the lighting effect extraction features; Obtain the device form data of the target device, perform feature extraction on the device form data, and obtain the form extraction features for the device form data; The morphological extraction features and the standard lighting effect configuration file are used to perform lighting effect migration to obtain a target lighting effect configuration file adapted to the target device; the target lighting effect configuration file is used to instruct the target device to display the target lighting effect based on the target lighting effect parameters when the target lighting effect parameters are parsed.

2. The method according to claim 1, characterized in that, The lighting effect parameter data is the lighting effect video data recorded when the source device displays the target lighting effect based on the target lighting effect parameters; The step of extracting features from the lighting effect parameter data to obtain lighting effect extraction features for the lighting effect data includes: Obtain a lighting effect configuration model for lighting effect migration, input the lighting effect video data into the lighting effect configuration model, and have the lighting effect configuration model extract N lighting effect video frames from the lighting effect video data; N is a positive integer; Obtain the target lighting effect video frame from the N lighting effect video frames, and obtain the first color channel data of the target lighting effect video frame in the first color space; By using the color conversion relationship between the first color space and the second color space, the first color channel data is converted into the second color channel data in the second color space, and the second color channel data is used as the color extraction feature of the target lighting effect video frame. When each of the N lighting effect video frames is selected as the target lighting effect video frame, the color extraction features of each lighting effect video frame are obtained, and the color extraction features of each lighting effect video frame are used as the lighting effect extraction features.

3. The method according to claim 1, characterized in that, The extracted lighting effects features are generated by a lighting effect configuration model used for lighting effect migration; The step of generating a standard lighting effect configuration file based on the extracted lighting effect features includes: When the standard form extraction features of the standard device are obtained through the lighting effect configuration model, the standard form extraction features and the lighting effect extraction features are fused to generate a first fused feature. Based on the first fusion feature, a standard lighting effect configuration file adapted to the standard device is generated.

4. The method according to claim 1, characterized in that, The device morphology data is the device image data of the target device; The step of extracting features from the device morphology data to obtain morphology extraction features for the device morphology data includes: A device adaptation model for lighting effect migration is obtained. The device shape data is input into the device adaptation model for lighting effect migration. The device adaptation model performs device LED positioning processing on the device image data. When the device LED is located on the target device from the device image data, the positioning coordinates of the device LED are generated. The device LED is used to display the target lighting effect. The positioning coordinates of the device's LED beads are used as the morphological extraction features.

5. The method according to claim 1, characterized in that, The morphological extraction features are generated by a device adaptation model used for lighting effect migration; The step of using the extracted morphological features and the standard lighting effect profile to perform lighting effect migration, resulting in a target lighting effect profile adapted to the target device, includes: The morphology extraction features are feature-encoded using the device adaptation model to obtain the morphology encoding features of the morphology extraction features, and the standard lighting effect configuration file is feature-encoded to obtain the file encoding features of the standard lighting effect configuration file. The morphological encoding feature and the file encoding feature are fused to obtain a second fused feature, and the target lighting effect configuration file is generated based on the second fused feature.

6. The method according to claim 1, characterized in that, The lighting effect extraction features are generated by a lighting effect configuration model used for lighting effect migration; the morphology extraction features are generated by a device adaptation model used for lighting effect migration. The method further includes: Acquire the sample lighting effect parameter data of the sample lighting effect displayed on the sample device, the sample lighting effect configuration file of the sample lighting effect for the sample device, the sample device form data of the sample device, the standard device form data of the standard device, and the sample standard lighting effect configuration file of the sample lighting effect for the standard device. The sample lighting effect parameter data and the standard lighting effect configuration file are input into the lighting effect configuration model to be trained. The lighting effect configuration model to be trained determines the sample lighting effect extraction features of the sample lighting effect parameter data and the standard shape extraction features of the standard device shape data. When generating a predicted standard lighting effect configuration file adapted to the standard device based on the sample lighting effect extraction features and the standard shape extraction features, a first loss value is determined for the lighting effect configuration model to be trained based on the sample standard lighting effect configuration file and the predicted standard lighting effect configuration file. Based on the first loss value, the predicted standard lighting effect configuration file, the sample lighting effect configuration file, and the sample device form data, the lighting effect configuration model to be trained and the device adaptation model to be trained are trained to obtain the trained lighting effect configuration model and the trained device adaptation model.

7. The method according to claim 6, characterized in that, The step of training the lighting effect configuration model and the device adaptation model to be trained based on the first loss value, the predicted standard lighting effect configuration file, the sample lighting effect configuration file, and the sample device form data includes: The predicted standard lighting effect configuration file, the sample lighting effect configuration file, and the sample device morphology data are input into the device adaptation model to be trained. The device adaptation model to be trained determines the sample morphology extraction features of the sample device morphology data and the sample file encoding features of the predicted standard lighting effect configuration file. When generating a predicted lighting effect configuration file adapted to the sample device based on the sample file encoding features and the sample morphology extraction features, a second loss value is determined for the device adaptation model to be trained based on the sample lighting effect configuration file and the predicted lighting effect configuration file. The lighting configuration model and the device adaptation model to be trained are trained using the target loss value determined by the first loss value and the second loss value.

8. The method according to claim 7, characterized in that, The step of determining the first loss value for the lighting effect configuration model to be trained based on the sample standard lighting effect configuration file and the predicted standard lighting effect configuration file includes: The sample lighting effect parameters corresponding to the sample lighting effect on the standard device are parsed from the sample standard lighting effect configuration file, and these sample lighting effect parameters are used as the first representation vector of the sample standard lighting effect configuration file. Similarly, the predicted lighting effect parameters corresponding to the sample lighting effect on the standard device are parsed from the predicted standard lighting effect configuration file, and these predicted lighting effect parameters are used as the second representation vector of the sample standard lighting effect configuration file. Alternatively... The sample standard lighting effect configuration file is represented by a file to obtain a first file conversion vector of the sample standard lighting effect configuration file. The first file conversion vector is used as the first representation vector. The predicted standard lighting effect configuration file is represented by a file to obtain a second file conversion vector of the predicted standard lighting effect configuration file. The second file conversion vector is used as the second representation vector. The first loss value is determined based on the vector difference between the first representation vector and the second representation vector.

9. The method according to claim 7, characterized in that, The method further includes: Obtain the actual lighting effect parameter data of the test lighting effect displayed on the test device, the actual lighting effect configuration file of the test lighting effect for the test device, and the test device form data of the test device; The actual lighting effect parameter data is input into the lighting effect configuration model, the lighting effect configuration model determines the test lighting effect extraction features for the actual lighting effect parameter data, and the standard lighting effect configuration file is generated based on the test lighting effect extraction features and the standard form extraction features. The standard lighting effect configuration file and the test device form data are input into the device adaptation model. The device adaptation model determines the test form extraction features of the test device form data and the file encoding features of the standard lighting effect configuration file. A test lighting effect configuration file adapted to the test equipment is generated based on the file encoding features and the test pattern extraction features. Based on the test lighting effect configuration file, the real lighting effect configuration file, and the real lighting effect parameter data, determine the model test information of the lighting effect configuration model and the device adaptation model after training.

10. The method according to claim 9, characterized in that, The step of determining the model test information of the lighting effect configuration model and the device adaptation model after training based on the test lighting effect configuration file, the real lighting effect configuration file, and the real lighting effect parameter data includes: Determine the file deviation data between the actual lighting effect configuration file and the test lighting effect configuration file; The test lighting effect configuration file is parsed to obtain the test lighting effect parameters corresponding to the test lighting effect. When the test lighting effect is displayed on the test device based on the test lighting effect parameters, the test lighting effect parameter data of the test lighting effect is determined. Determine the parameter deviation data between the actual lighting effect parameter data and the tested lighting effect parameter data; The model test information is determined based on the file deviation data and the parameter deviation data.

11. The method according to claim 1, characterized in that, The method further includes: Obtain a display progress bar for displaying the target lighting effect; According to the display progress indicated by the display progress bar, the target lighting effect parameters corresponding to the display progress are parsed from the target lighting effect configuration file; the target lighting effect parameters corresponding to the display progress are used to indicate the color parameters and brightness parameters of the device LEDs on the target device at the display progress. The device LEDs are instructed to display according to the color parameters and brightness parameters corresponding to the display progress.

12. The method according to claim 11, characterized in that, The target lighting effect configuration file includes a brightness display progress array, a color display progress array, a brightness display parameter table, and a color display parameter table. The brightness display progress array is used to define the progress information of the brightness change displayed by the device LEDs. The color display progress array is used to define the progress information of the color change displayed by the device LEDs. The brightness display parameter table is used to define the brightness parameters displayed by the device LEDs. The color display parameter table is used to define the color parameters displayed by the device LEDs. The step of parsing the target lighting effect parameters corresponding to the display progress indicated by the display progress bar from the target lighting effect configuration file includes: According to the display progress, query the progress information in the brightness display configuration table. If the progress information that matches the display progress is found in the brightness display configuration table, then obtain the brightness parameter that matches the display progress from the brightness display parameter table. According to the display progress, query the progress information in the color display configuration table. If the progress information that matches the display progress is found in the color display configuration table, then obtain the color parameter that matches the display progress from the color display parameter table. The brightness parameter and color parameter that match the display progress are used as the target lighting effect parameters corresponding to the display progress.

13. A lighting effect data processing device, characterized in that, The device includes: The parameter data acquisition module is used to acquire the lighting effect parameter data of the target lighting effect displayed by the source device; the target lighting effect refers to the lighting effect to be migrated from the source device to the target device; the lighting effect parameter data refers to the data of the target lighting effect parameters corresponding to the target lighting effect. The lighting effect feature extraction module is used to extract features from the lighting effect parameter data, obtain lighting effect extraction features for the lighting effect parameter data, and generate a standard lighting effect configuration file based on the lighting effect extraction features. The morphological feature extraction module is used to acquire the device morphological data of the target device, perform feature extraction on the device morphological data, and obtain morphological extraction features for the device morphological data. The configuration file generation module is used to perform lighting effect migration using the morphological extraction features and the standard lighting effect configuration file to obtain a target lighting effect configuration file adapted to the target device; the target lighting effect configuration file is used to instruct the target device to display the target lighting effect based on the target lighting effect parameters when the target lighting effect parameters are parsed.

14. A computer device, characterized in that, Including memory and processor; The memory is connected to the processor, the memory is used to store computer programs, and the processor is used to invoke the computer programs so that the computer device performs the method according to any one of claims 1-12.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted to be loaded and executed by a processor to cause a computer device having the processor to perform the method of any one of claims 1-12.

16. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1-12.

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