Joint control lamp effect adaptation method and device, equipment and medium

Abstract

The invention relates to a joint control lamp effect adaptation method and device, equipment and a medium. The method comprises the following steps: acquiring a target image of a planar lamp in a lamp effect joint control system according to the applied lamp effect; extracting a feature color set based on the target image, and determining a lamp effect color matching scheme applied by a non-planar lamp in a lamp effect joint control system according to the feature color set; based on a content description text generated according to the target image, determining a lamp effect motion mode applied by the non-planar lamp; and sending the lamp effect movement mode and the lamp effect color matching scheme to the non-planar lamp, so that the non-planar lamp plays the corresponding lamp effect by applying the lamp effect movement mode and the lamp effect color matching scheme. The lamp effect color matching scheme and the lamp effect movement mode of the non-planar lamp are determined based on the planar lamp according to the target image of the applied lamp effect, it is ensured that the lamp effects of different types of lamps in the lamp effect joint control system can be coordinated and consistent, and therefore the coordination and aesthetic feeling of the overall lighting effect are improved.

Description

Technical Field

[0001] The present application relates to the field of lighting effect control technology, and in particular to a joint control lighting effect adaptation method and device, equipment, and medium. Background Art

[0002] In modern smart homes and lighting systems, lamps are no longer just tools for providing basic lighting, but have become key elements for creating a comfortable environment, enhancing the living experience, and even expressing personal emotions and style. With the development of technology, users' demand for lighting systems has changed from simple switch control to fine-tuning of lighting effects, including color, brightness, dynamic effects, etc. In order to meet these needs, a variety of smart lighting systems have appeared on the market, which can adjust the lighting effects according to user settings or preset modes to adapt to different scenes and atmospheres. However, existing lighting control systems generally have some shortcomings.

[0003] First, most systems lack the ability to plan and coordinate lighting effects as a whole, especially in environments that contain multiple types of lamps, such as when planar and non-planar lamps are mixed. These systems often fail to ensure that the lighting effects between different lamps are harmonious and unified, resulting in the overall lighting effect appearing chaotic and lacking coordination. Planar lamps, such as curtain lights or mesh lights, usually have a larger light-emitting area and can display continuous images or color gradients, while non-planar lamps, such as cube lights or linear lights, are composed of smaller light-emitting units and are suitable for displaying discrete colors and dynamic effects. The lack of consideration for these differences limits the potential for lighting effects and affects the user experience.

[0004] Secondly, when dealing with lighting effects, existing technologies often ignore the differences in lighting types and fail to fully utilize the characteristics of each type of lighting to optimize lighting effects. For example, planar lighting is suitable for displaying continuous color gradients and images, while non-planar lighting is more suitable for displaying discrete colors and dynamic effects. The lack of consideration for these differences limits the potential of lighting effects and affects user experience.

[0005] Furthermore, the existing lighting control system often requires complex settings and adjustments during the lighting effect configuration process. Users need to have a deep understanding of the technical parameters and interface specifications of different lamps in order to correctly configure the lighting effects. This process is not only cumbersome, but also raises the threshold for use, which is not conducive to convenient operation for ordinary users.

[0006] Finally, existing lighting effect configuration methods also have deficiencies in the semantic correspondence between lighting effect actions and color schemes. They are usually unable to intelligently generate lighting effect actions and color schemes that correspond to the semantics of the text or image content entered by the user, but rely on the user's manual selection or preset mode, which limits the personalization and dynamic adaptability of lighting effects.

[0007] It can be seen that the existing technology has obvious deficiencies in the overall coordination of lighting effects, utilization of lighting characteristics, convenience of user operation, and intelligent correspondence of lighting effect semantics. These problems limit the development of intelligent lighting systems and the improvement of user experience. Summary of the invention

[0008] The primary purpose of the present application is to solve at least one of the above problems and provide a joint control lighting effect adaptation method and device, equipment, and medium.

[0009] In order to meet the various objectives of this application, this application adopts the following technical solutions: A method, device, equipment, and medium for joint control lighting effect adaptation provided to meet one of the purposes of this application include the following steps: Acquire a target image for applying lighting effects to planar lighting fixtures in a lighting effect joint control system; Extracting a characteristic color set based on the target image, and determining a lighting effect color scheme applied to non-planar lamps in the lighting effect joint control system according to the characteristic color set; Determining a lighting effect motion mode applied to the non-planar lamp based on a content description text generated according to the target image; The lighting effect motion mode and the lighting effect color scheme are sent to the non-planar lamp, so that the non-planar lamp applies the lighting effect motion mode and the lighting effect color scheme to play the corresponding lighting effect.

[0010] A joint control lighting effect adaptation device is proposed to meet one of the purposes of the present application, and includes: An image acquisition module, configured to acquire a target image for applying lighting effects to a planar lighting fixture in a lighting effect linkage control system; A color matching determination module, configured to extract a characteristic color set based on the target image, and determine a lighting effect color matching scheme applied to a non-planar lamp in a lighting effect joint control system according to the characteristic color set; a mode determination module, configured to determine a lighting effect motion mode applied to the non-planar lamp based on a content description text generated according to the target image; The lighting effect application module is configured to send the lighting effect motion mode and the lighting effect color scheme to the non-planar lamp, so that the non-planar lamp applies the lighting effect motion mode and the lighting effect color scheme to play the corresponding lighting effect.

[0011] On the other hand, a joint control lighting effect adaptation device is provided to meet one of the purposes of the present application, including a controller, which is electrically connected to the planar lamps and the non-planar lamps respectively, and the controller is used to execute the steps of the joint control lighting effect adaptation method to control the planar lamps and the non-planar lamps to display corresponding lighting effects.

[0012] On the other hand, a computer-readable storage medium is provided to meet another purpose of the present application, which stores a computer program implemented according to the joint control lighting effect adaptation method in the form of computer-readable instructions. When the computer program is called and executed by a computer, the steps included in the corresponding method are executed.

[0013] This application provides innovative solutions to the problems existing in the prior art, so as to achieve the harmonious unification of the lighting effects of planar lamps and non-planar lamps in the lighting effect joint control system, and achieves many technical advantages, including but not limited to: First of all, the present application determines the lighting effect color scheme of non-planar lamps by extracting feature color sets based on the target image to which the lighting effects are applied by the planar lamps, and determines the lighting effect movement mode of the non-planar lamps based on the content description text of the target image, thereby defining the lighting effects applied by the non-planar lamps, ensuring the coordination and consistency of lighting effects between different types of lamps in the lighting effect linkage control system, while allowing the lighting effect linkage control system to create a harmonious and unified color tone, and also ensuring that the action semantics implied in the target image are simulated through the lighting effect movement mode of the non-planar lamps, thereby optimizing the overall lighting effect atmosphere rendered by the entire lighting effect linkage control system, thereby enhancing the coordination and beauty of the overall lighting effect.

[0014] Secondly, this application analyzes the target image and extracts key color information so that the lighting effect color scheme of non-planar lamps can match the image content displayed by planar lamps. It not only enhances the overall coordination of the lighting effect, but also optimizes the utilization of lamp characteristics, so that each lamp can exert its maximum potential and obediently determine its lighting effect. In addition, this application reduces the complexity of user operations through intelligent color extraction and color scheme generation. Users can easily achieve personalized lighting effects without in-depth understanding of technical parameters and interface specifications.

[0015] In addition, this application determines the lighting effect motion mode of non-planar lamps based on the content description text generated by the target image, so that the dynamic performance of the lamps can be coordinated with the image content, providing users with a richer and more coordinated lighting experience. This intelligent corresponding lighting effect configuration not only improves the personalization of the lighting effect, but also enables the lighting effect to dynamically adapt to different scenes and user needs, providing users with a more flexible and intelligent lighting solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which: Figure 1 The schematic diagram of the principle of the exemplary lighting effect joint control system of the present application includes a joint control lighting effect adapter device and multiple lamps; Figure 2 A flowchart of a typical embodiment of the joint control lighting effect adaptation method of the present application; Figure 3 This is a principle block diagram of the joint control lighting effect adaptation device of the present application; Figure 4 A schematic diagram of the structure of a computer device used in this application. DETAILED DESCRIPTION

[0017] like Figure 1 As shown, in the structure of the exemplary lighting effect joint control system of the present application, the lighting effect joint control system includes a joint control lighting effect adapter device 80 and a plurality of lamps (82, 84), which include a planar lamp 82 and a non-planar lamp 84. The joint control lighting effect adapter device 80 is responsible for managing and controlling all connected lamps to achieve unified lighting effect control and coordination.

[0018] The joint-control lighting effect adapter device 80 is connected to various lamps through wireless communication. This connection method provides flexibility and scalability, allowing the system to easily add or remove lamps without complicated wiring. Through this wireless connection, the joint-control lighting effect adapter device 80 can obtain data such as the lamp identification, lamp type, and lighting effect motion mode data set of each lamp. The lamp identification is a unique identifier for each lamp, which is used to distinguish different lamps in the system. The lamp type refers to the physical form and function of the lamp. For example, the planar lamp 82 can include any one or any combination of curtain lights, mesh lights, pixel screens, etc., while the non-planar lamp 84 can include any one or any combination of square lights, linear lights, eaves lights, wall lights, etc. The lighting effect motion mode data set contains one or more lighting effect motion modes preset for the corresponding lamps. These modes define how the lamps display changes in color and brightness.

[0019] The joint-control lighting effect adapter device 80 determines the lighting effect corresponding to each lamp according to the interface call information of each lamp and the type of lamp. The interface call information includes the interface name and its corresponding encapsulation format specification, which guides the joint-control lighting effect adapter device 80 on how to encapsulate the lighting effect motion mode and color scheme into instructions that the lamp can understand and execute. The joint-control lighting effect adapter device 80 can encapsulate the lighting effect motion mode and lighting effect color scheme into a message body, and then construct it into a lighting effect playback instruction, and send it to the corresponding lamp to control it to play the corresponding lighting effect.

[0020] In the lighting effect joint control system, the planar lamps 82 usually have a large light-emitting area and can display continuous images or color gradients, such as curtain lights and mesh lights. These lamps are suitable for creating a wide visual impact and atmosphere rendering. Non-planar lamps 84 usually have smaller light-emitting units, and the color and brightness of each unit can be independently controlled, such as square lights and linear lights. These lamps are suitable for creating rich and varied visual effects.

[0021] The joint control lighting effect adaptation device 80 determines the lighting effect of the non-planar lamp 84 by adaptation, ensuring that the overall lighting effect atmosphere played by each lamp in the lighting effect joint control system is more harmonious and coordinated. This means that regardless of whether the system includes planar lamps 82, the joint control lighting effect adaptation device 80 can generate unified lighting effect action semantics and lighting effect color matching semantics based on the input material (such as text or image) and the characteristics of the lamp, so that the lighting effect performance of the entire system is both unified and diverse.

[0022] In some embodiments, the joint control lighting effect adaptation device 80 includes a control chip, a control panel, a communication component, and a display screen. The control chip can be implemented using various embedded chips, such as Bluetooth SoC (System on Chip), WiFi SoC, MCU (Micro Controller Unit), DSP (Digital Signal Processing) and other types of chips. The control chip usually includes a central processing unit and a memory. The memory and the central processing unit are used to store and execute program instructions respectively to achieve corresponding functions. The control panel usually provides one or more buttons for implementing switch control of the controller 1, selecting various preset lighting effects, etc. The communication component is used to achieve wireless communication connection with each lamp. The display screen can be used to display various control information so as to cooperate with the buttons in the control panel to support the implementation of human-computer interaction functions. In some embodiments, the control panel and the display screen can be integrated into the same touch display screen.

[0023] In some embodiments, the joint-control lighting effect adapter device 80 of the present application can be implemented in an independent computer device, as long as the computer device is equipped with the corresponding hardware of the joint-control lighting effect adapter device 80, and the corresponding business logic of the joint-control lighting effect adapter device 80, including the business logic executed by the corresponding method of the present application, is implemented as a computer program installed in the computer device for operation. When the joint-control lighting effect adapter device 80 is implemented in a computer device, various resources inherent in the computer device can be shared to save the overall implementation cost. The computer device referred to here can be any terminal device for use by the user, such as a smart phone, a personal computer, a laptop computer, a tablet computer, etc.

[0024] In some embodiments, the joint-control lighting effect adaptation device of the present application can be directly integrated with the lamp into the same product, that is, the same business logic of the joint-control lighting effect adaptation device is implemented in the lamp, so that the lamp itself can determine its lighting effect color scheme after acquiring the target image.

[0025] According to the product architecture and working principle of the above-mentioned joint-control lighting effect adaptation device 80, the joint-control lighting effect adaptation method of the present application can be implemented as a computer program, stored in the storage medium of the controller of the joint-control lighting effect adaptation device 80, and called from the storage medium by the control chip of the controller to run, so as to control each lamp in the entire lighting effect joint control system to play the corresponding lighting effects.

[0026] The lighting effect joint control system of the present application realizes precise control of various types of lamps through wireless communication connection and intelligent adaptation, so that both planar lamps 82 and non-planar lamps 84 can work together in the same system to provide users with a unified and coordinated lighting effect experience.

[0027] See also Figure 2 In some embodiments, the joint control lighting effect adaptation method of the present application includes: Step S5100, obtaining a target image for applying lighting effects to planar lighting fixtures in the lighting effect joint control system; The purpose of acquiring the target image for applying lighting effects to the planar lamps is to enable the lighting effect linkage control system to adjust and control the lighting effects of the lamps according to specific image content, thereby achieving a more personalized and coordinated lighting environment.

[0028] The acquisition of the target image can be achieved in a variety of ways. In one embodiment, the image file is received directly from a user device such as a smartphone or tablet. Users can upload images of their choice through an application connected to the joint control lighting effect adaptation device. These images can be landscape photos, art paintings, or any other pictures with specific colors and content. After uploading, the joint control lighting effect adaptation device processes these images and sends them to the planar lamp to present the corresponding lighting effect.

[0029] Another embodiment of obtaining the target image is to obtain it through the joint control lighting effect adaptation device itself or an image library on the Internet. The joint control lighting effect adaptation device can be pre-installed or obtain a set of image libraries through online updates. Users can select images from these libraries, or the system can automatically select suitable images for display based on preset themes or scenes.

[0030] In some embodiments, the acquisition of the target image can also be achieved through a built-in or external camera unit of the joint control lighting effect adaptation device. For example, if the joint control lighting effect adaptation device is outdoors, the real-time outdoor scenery can be directly captured through the camera unit as the basis for the lighting effect; if it is indoors, the indoor decorations or artworks can be photographed, and the lighting effect can be adjusted based on this to match the environment.

[0031] After acquiring the target image, the joint control lighting effect adaptation device will process the image to adapt it to the display capability of the planar lamp. Image processing may include any one or more steps such as adjusting the image resolution, color correction, format conversion, pixelation processing, etc. to ensure that the target image can be accurately and effectively displayed on the planar lamp. The processed image or its processing result will be sent to the planar lamp to achieve the expected lighting effect.

[0032] It is not difficult to understand that the lighting effects of planar lamps are defined based on the target image. When the joint-control lighting effect adapter device is able to drive the planar lamps in the lighting effect joint-control system to play their corresponding lighting effects, it means that the target image already exists in the joint-control lighting effect adapter device. In this case, the subsequent steps can directly call this target image for processing.

[0033] Step S5200, extracting a characteristic color set based on the target image, and determining a lighting effect color scheme applied to the non-planar lamp in the lighting effect joint control system according to the characteristic color set; The purpose of extracting a characteristic color set based on a target image is to identify key colors from the target image so as to define a corresponding lighting effect color scheme for non-planar lamps. Therefore, pixel clustering can be performed on the target image to obtain multiple pixel clusters and their representative colors, which can be flexibly selected as needed to form a characteristic color set.

[0034] Perform pixel clustering on the target image, that is, divide the pixels in the image into multiple groups, that is, pixel clusters, according to color similarity. The pixel with the most typical color in each pixel cluster, that is, the cluster center pixel, is selected as the representative color of the cluster. This process can be achieved through a variety of clustering algorithms, such as the K-means algorithm and the DBSCAN algorithm. These algorithms can perform multiple iterative clustering of the pixel data in the image according to the preset number of clusters until the optimal clustering result is found.

[0035] In some embodiments, multiple representative colors in the clustering results are prioritized. First, the area ratio of the pixel cluster to which each representative color belongs in the target image and the prominence of each representative color in the target image are determined. The area ratio reflects the distribution range of each color in the image, while the prominence measures the degree of difference between the color and the average color of the image. This information together constitutes a candidate color set, which provides a basis for subsequent feature color set screening.

[0036] In the candidate color set, representative colors are selected based on area ratio and prominence to form the characteristic color set used for the lighting effect color scheme of non-planar lamps. Specifically, representative colors with a higher area ratio are selected as the lighting effect background colors of non-planar lamps, which usually means that these colors dominate the image and can provide the basic tone for the lighting effect. Then, colors with a higher degree of prominence are selected from the remaining representative colors as accent colors. Although these colors are less distributed in the image, they are more different from the average color of the target image, so they can provide visual focus and increase color levels in the lighting effect.

[0037] For example, if the target image is a seascape, after clustering, the blue representing the sky, the yellow representing the beach, and the green representing the seawater may be obtained. By calculating the area proportion and prominence of these colors, it can be determined that blue is used as the background color, and yellow and green are used as the embellishment colors, thereby constructing a lighting color scheme that is coordinated with the seascape.

[0038] In some embodiments, in order to improve the visual impact and coordination of the lighting effect color scheme, representative colors close to black in the target image can be excluded. This is because colors close to black usually do not have a significant visual impact in lighting effects and may cause the color scheme to be too dim or monotonous. Therefore, when determining the characteristic color set, a preset threshold range is first defined to define what is a "close to black" color. In image processing, black is usually defined as (0, 0, 0) in the RGB color space, but in actual applications, because the image may contain shadows or other dark tones, the "close to black" color can be defined as a range, such as colors with RGB values ​​between (0, 0, 0) and (20, 20, 20).

[0039] To this end, before calculating the area share and prominence, all pixel clusters whose representative colors fall within this preset range are identified, and the total number of pixels of these pixel clusters is excluded from the total number of pixels. In this way, only those pixel clusters with higher brightness and color saturation will be taken into account, thereby ensuring that the lighting effect color scheme is more focused on the visually significant parts of the image. For example, if the representative color of a pixel cluster is very close to black, and the total number of pixels of the cluster accounts for 5% of the total number of pixels of the entire image, but according to the preset threshold, these pixels are identified as non-visually significant parts, so when calculating the area share, this 5% will not be included. The final area share will be calculated only based on the remaining pixel clusters with higher brightness and color saturation, which can more accurately reflect the main color distribution in the image and provide more meaningful reference data for selecting background colors and embellishment colors. Through this embodiment, the lighting effect color scheme can more accurately reflect the color characteristics of the target image, while avoiding the problem that the color scheme is too dim or monotonous due to the inclusion of a large number of black or dark-tone pixels, thereby improving the overall coordination and visual appeal of the lighting effect.

[0040] Step S5300: determining a lighting effect motion mode applied to the non-planar lamp based on the content description text generated according to the target image; The motion mode of the lighting effect of non-planar lamps is usually expressed through description information, which describes the motion effect of the lamp in text form, such as "flowing", "flickering" or "gradual". Compared with images, this text description can convey the motion characteristics of the lighting effect more intuitively and clearly. Therefore, in order to determine the appropriate motion mode of the lighting effect according to the target image, it is necessary to convert the target image into a text description that can represent its content and obtain the corresponding content description text.

[0041] The conversion of the target image to its content description text can be achieved by calling a large language model, which can understand and generate natural language text and belongs to the image-to-text technology. The large language model predicts and generates descriptive text of the image content in the target image by analyzing the input target image. In the specific implementation, the target image is first input into the large language model, and the model generates content description text after analyzing the image content. For example, if the target image is a beach at sunset, the generated text may be "golden beach at sunset".

[0042] In some embodiments, in order to enable the large language model to accurately generate content description text according to the target image, it can be fine-tuned in advance. Fine-tuning training is to further use a specific data set for training on the basis of the original pre-training of the large language model to adapt to specific tasks or application scenarios. In this application, the purpose of fine-tuning training is to enable the large language model to understand and describe the image content more accurately so as to generate content description text that matches the semantics of the target image. In specific implementation, first collect and prepare a data set containing an image and its corresponding content description text, which will be used to fine-tune the large language model so that it can understand and generate descriptions related to the image content. Through training, the large language model learns how to extract key information from the image and convert it into content description text. For example, if the input image is a beach under the sunset, the trained model can generate content description text such as "golden beach under the sunset". After the fine-tuning training is completed, the large language model can receive the target image as input and output text describing the content of the image, thereby providing accurate semantic information for determining the lighting effect motion mode.

[0043] The content description text generated by the large language model is then used to determine the lighting effect motion mode of non-planar lamps. To this end, the lighting effect motion mode dataset of non-planar lamps whose lighting effects need to be determined is first called. The dataset contains multiple preset lighting effect motion modes, each with corresponding description information. By comparing the content description text with the description information of the lighting effect motion mode, the lighting effect motion mode that is closest to the semantics of the content description text can be determined.

[0044] For example, if the content description text is "golden beach under sunset", the lighting effect motion mode description information related to "sunset", "golden" and "beach" may be searched, such as "warm", "gradient" or "serene". During the matching process, the semantic similarity between the content description text and each lighting effect motion mode description information can be evaluated, and the lighting effect motion mode corresponding to the description information with the closest semantic similarity can be selected. This selection can be based on preset matching rules, such as selecting the mode with the highest keyword overlap or the highest semantic similarity score.

[0045] By determining the lighting effect motion mode of non-planar lamps based on the target image content description text, the lighting effect can be personalized and dynamically adaptable, so that the lighting effect of the non-planar lamps not only matches the target image in color, but also can be coordinated with the image content in dynamic performance, thereby providing users with a richer and more coordinated lighting experience.

[0046] Step S5400: Send the lighting effect motion mode and the lighting effect color scheme to the non-planar lamp, so that the non-planar lamp applies the lighting effect motion mode and the lighting effect color scheme to play the corresponding lighting effect.

[0047] After determining the lighting effect color scheme and lighting effect motion mode of the non-plane luminaire, these settings can be transmitted to the non-plane luminaire so that the non-plane luminaire can play the corresponding lighting effects according to these parameters.

[0048] In some embodiments, before transmitting the lighting effect motion mode and lighting effect color scheme to the non-planar lamp, the interface call information of the non-planar lamp is first obtained, including the interface name and the packaging format specification. This information guides how to package the lighting effect motion mode and color scheme into instructions that the lamp can understand and execute. The interface call information can be obtained through a pre-set protocol manual, or identified through an automatic discovery process with the lamp.

[0049] After obtaining the interface call information, the lighting effect motion mode and lighting effect color scheme are encapsulated according to the encapsulation format specification to form the corresponding message body. For example, if the lighting interface requires receiving data in JSON format, the parameters of the lighting effect motion mode and lighting effect color scheme need to be organized into a JSON object containing all necessary key-value pairs. During the encapsulation process, the specific parameters of the lighting effect motion mode and lighting effect color scheme, such as color value, brightness level, change speed, etc., are converted into the specified format and arranged according to the requirements of the interface.

[0050] After the message body is correctly encapsulated, a lighting effect play instruction is constructed, combining the interface name and the message body to form a complete lighting effect play instruction. This instruction contains all the information required for non-planar lamps to execute lighting effects, such as the mode identifier of the light movement mode, the characteristic color sequence composed of background color and dot color in the lighting effect color scheme, etc.

[0051] Finally, the lighting effect playback instruction is sent to the corresponding target lamp through the wireless communication network. After the target lamp receives the lighting effect playback instruction, it will execute the corresponding lighting effect playback according to the data in the lighting effect playback instruction. This means that the non-planar lamp will display light according to the predetermined lighting effect motion mode and lighting effect color scheme, thereby rendering the expected lighting effect atmosphere in the user's environment.

[0052] In different embodiments, the interface call information and encapsulation format specifications may vary. For example, some lamps may support RESTful APIs, in which case the instructions may need to be sent in the form of HTTP requests, including a specific URL and HTTP method (such as GET or POST). Other lamps may use the MQTT protocol for communication, in which case the encapsulation and sending of instructions need to follow the MQTT specification. Regardless of the specific communication protocol, the core goal is to ensure that the lighting effect motion mode and color scheme can be correctly understood and executed by the lamp to achieve precise lighting effect control.

[0053] By precisely docking the interface call information and packaging format specifications of the target lamps, highly customized lighting effect motion modes and color schemes are transmitted, ensuring seamless communication with the lamps and accurate execution of instructions. Compared with other embodiments, the unique technical advantage of this embodiment lies in its strong adaptability and compatibility. It can cope with the interface differences of lamps of different brands and models. Through flexible packaging and instruction construction mechanisms, the same lighting effect configuration method can be widely used in a variety of lamps, greatly expanding the scope of application. In addition, by ensuring the integrity and correctness of information, the accuracy and reliability of lighting effect control are improved, and the risk of lighting effect configuration failure due to communication errors or instruction misunderstandings is reduced, thereby providing users with a more stable and efficient intelligent lighting solution.

[0054] It can be understood from the above embodiments that the present application provides an innovative solution to the problems existing in the prior art, so as to achieve the harmonious unification of the lighting effects of planar lamps and non-planar lamps in the lighting effect joint control system, and obtain multiple technical advantages, including but not limited to: First of all, the present application determines the lighting effect color scheme of non-planar lamps by extracting feature color sets based on the target image to which the lighting effects are applied by the planar lamps, and determines the lighting effect movement mode of the non-planar lamps based on the content description text of the target image, thereby defining the lighting effects applied by the non-planar lamps, ensuring the coordination and consistency of lighting effects between different types of lamps in the lighting effect linkage control system, while allowing the lighting effect linkage control system to create a harmonious and unified color tone, and also ensuring that the action semantics implied in the target image are simulated through the lighting effect movement mode of the non-planar lamps, thereby optimizing the overall lighting effect atmosphere rendered by the entire lighting effect linkage control system, thereby enhancing the coordination and beauty of the overall lighting effect.

[0055] Secondly, this application analyzes the target image and extracts key color information so that the lighting effect color scheme of non-planar lamps can match the image content displayed by planar lamps. It not only enhances the overall coordination of the lighting effect, but also optimizes the utilization of lamp characteristics, so that each lamp can exert its maximum potential and obediently determine its lighting effect. In addition, this application reduces the complexity of user operations through intelligent color extraction and color scheme generation. Users can easily achieve personalized lighting effects without in-depth understanding of technical parameters and interface specifications.

[0056] In addition, this application determines the lighting effect motion mode of non-planar lamps based on the content description text generated by the target image, so that the dynamic performance of the lamps can be coordinated with the image content, providing users with a richer and more coordinated lighting experience. This intelligent corresponding lighting effect configuration not only improves the personalization of the lighting effect, but also enables the lighting effect to dynamically adapt to different scenes and user needs, providing users with a more flexible and intelligent lighting solution.

[0057] Based on any embodiment of the method of the present application, extracting a characteristic color set based on the target image includes: Step S5210, clustering pixels in the target image to obtain multiple pixel clusters and a representative color of each pixel cluster, where the representative color is the color of the central pixel of the corresponding pixel cluster; After acquiring the target image, pixel clustering can be performed on the target image to achieve image analysis. The purpose is to divide the pixels in the image into multiple groups, namely pixel clusters, according to color similarity.

[0058] In different embodiments, one of the multiple clustering algorithms can be flexibly selected to implement this process. Optional clustering algorithms include but are not limited to K-means algorithm, DBSCAN algorithm, Gaussian mixture model clustering algorithm, etc. K-means clustering algorithm is a commonly used method, which randomly selects K points as initial cluster centers, then iteratively assigns each pixel to the nearest cluster center, and updates the position of the cluster center until the convergence condition is met or the preset number of iterations is reached. In addition, the density-based DBSCAN algorithm can also be used, which determines the clustering results based on the density of the pixel points rather than the preset number of clusters. This method is suitable for processing clustering problems of different shapes and sizes. There is also a model-based Gaussian mixture model (GMM) clustering algorithm, which assumes that the data is a mixture of multiple Gaussian distributions, and the clustering results are determined by estimating the parameters of these distributions.

[0059] In practical applications, the choice of clustering algorithm depends on the specific application scenario and performance requirements. For example, for scenarios that require fast processing of a large number of images, methods with higher computational efficiency can be preferred. For scenarios that require high-precision color analysis, algorithms that can provide more detailed color information can be selected.

[0060] Although these clustering algorithms work in different ways, their common goal is to divide the pixels into multiple clusters and determine the representative color of each cluster, that is, the color of the cluster center. This representative color can be the pixel value of the cluster center or the average color of all pixel values ​​in the cluster. In this way, key color information can be extracted from the target image, providing a basis for subsequent lighting effect color schemes. For example, if the target image is a landscape photo, the clustering algorithm can identify the main colors of different elements such as the sky, grass, and flowers, and use these colors as representative colors for the configuration of lighting effects.

[0061] It should be noted that in the process of pixel clustering and subsequent representative color screening in this embodiment, various color data operations can be performed based on the RGB color space, or related operations can be performed based on the LAB color space. In order to make the selected representative color more consistent with the visual field effect of the human eye, it is preferably recommended to perform related operations based on the LAB color space. For this purpose, the target image can be first converted from the RGB color space to an image in the LAB color space.

[0062] Step S5220, determining the area ratio of the pixel cluster to which each representative color belongs in the target image and the prominence of each representative color in the target image, and constructing a candidate color set; The candidate color set is constructed by first determining the area proportion and prominence of each representative color, and then screening the colors accordingly. In order to make the selected colors closer to the human eye's field of vision, By determining the area ratio of the total number of pixels in each pixel cluster relative to the total number of pixels in the target image, the distribution of each color in the image can be identified, thus providing a basis for the subsequent selection of background and accent colors. Specifically, the area ratio reflects the relative importance of each color in the target image, helps to distinguish between primary and secondary colors, and thus affects the overall atmosphere of the lighting effect.

[0063] In order to calculate the area ratio, we first need to count the number of pixels in each pixel cluster. This can be done by traversing the clustering results and counting the pixels in each cluster. After obtaining the number of pixels in each pixel cluster, divide it by the total number of pixels in the target image to get the area ratio of each pixel cluster.

[0064] In different embodiments, different methods can be used to process pixel data and calculate area percentage. An optional embodiment is to perform calculations directly at the original resolution of the image, so that all detail information of the image can be retained. Another embodiment is to first downsample the image, that is, reduce the resolution of the image to reduce the amount of calculation and increase the processing speed. In the process of downsampling, different algorithms can be used to achieve, such as nearest neighbor interpolation, bilinear interpolation or cubic spline interpolation.

[0065] In some embodiments, as disclosed above, pixel clusters corresponding to representative colors close to black in the target image can be additionally excluded, thereby filtering out colors that contribute less to the lighting effect color scheme, because pixel clusters close to black will not have a significant visual impact on the final lighting effect, while also reducing the complexity of subsequent processing. Through this embodiment, the lighting effect color scheme can more accurately reflect the color characteristics of the target image, while avoiding the problem of the color scheme being too dim or monotonous due to the inclusion of a large number of black or dark-tone pixels, thereby improving the overall coordination and visual appeal of the lighting effect.

[0066] By accurately determining the area ratio of each pixel cluster, key data support is provided for building lighting effect color schemes. This is the basis for achieving the conversion from image to lighting effect color, ensuring that the lighting effect can truly reflect the color characteristics of the image and enhance the visual effect and user experience of the lighting effect.

[0067] Determining the data distance between each representative color and the average color of the target image can quantify the prominence of these representative colors in the color effect of the target image. Therefore, it is necessary to determine the average color and quantify the data distance in order to identify the prominence of each representative color in the image, thereby providing a scientific basis for selecting background colors and accent colors.

[0068] First, the average color of the target image is determined by counting the color values ​​of all pixels in the target image. In the LAB color space, the average color is determined by calculating the average of the L, a, and b values ​​of all pixels in the image. The L value represents brightness, while the a and b values ​​represent the color's counterpart channel, where the a channel ranges from green to red and the b channel ranges from blue to yellow. By calculating the average of these values, a LAB value is obtained that represents the average color of the entire target image.

[0069] Next, the data distance between each representative color and the average color is calculated. This distance can be calculated using a preset data distance formula, and commonly used data distance formulas include but are not limited to Euclidean distance, Manhattan distance, cosine similarity, or CIEDE2000 color difference formula. These formulas can quantify the degree of difference between two color values ​​and can be applied at will. For example, Euclidean distance is obtained by calculating the straight-line distance between two points in the LAB color space, while the CIEDE2000 color difference formula is specifically used to measure the human eye's perception of color differences.

[0070] After calculating the data distance between each representative color and the average color, these distances are normalized to ensure that they are in the same dimension so that the prominence of different colors can be compared. Normalization can be done by dividing the data distance by the maximum value of all data distances or a preset benchmark value, so that the prominence of each color can be represented by a value between 0 and 1. The larger the value, the greater the difference between the color and the average color, and the higher the prominence.

[0071] Based on this, a candidate color set can be constructed, in which each representative color is accompanied by its area share and prominence. This set provides important information for determining the lighting effect color scheme of the target lamp. For example, if a representative color occupies a large area in the target image and has a high degree of prominence compared to the average color, then this color may be selected as the background color; while those colors with a small area share but high prominence may be selected as accent colors to increase the visual impact of the lighting effect.

[0072] In specific implementations, different algorithms and parameter settings can be used to implement this step. For example, different color spaces (such as RGB, LAB, or HSV) can be selected for calculation. In addition, the normalization method and the threshold of the significance level can be adjusted according to the needs of actual applications to adapt to different images and lighting scenarios. Through these specific implementations, technicians in this field can achieve precise control of the conversion from image to lighting effect color according to specific technical requirements and conditions.

[0073] Step S5230: Select representative colors based on the area ratio and prominence of the candidate color set to form a characteristic color set used for determining a lighting effect color scheme for a non-planar lamp.

[0074] In the process of extracting the characteristic color set from the target image, the purpose of screening the representative colors is to select the most representative colors from the candidate color set based on area proportion and prominence, so as to form a characteristic color set for the lighting effect color scheme of non-planar lamps.

[0075] Area ratio and saliency are two core parameters that together determine the importance of a color in the candidate color set. Area ratio refers to the relative area occupied by a color in the image, which directly reflects the widespread distribution of the color in the image. The saliency measures the difference between the color and the average color of the image, and is quantified by calculating the data distance between each representative color and the average color. The greater the difference, the higher the saliency of the color, which means that the color is more visually prominent. In practice, according to the actual needs of widespread and saliency, a number of representative colors can be selected to obtain a characteristic color set.

[0076] In some embodiments, the background color and the dotted color can be automatically selected to meet the needs of non-planar lamps to specify the background color and the dotted color. Specifically, first select the color with a relatively high area as the background color. The background color plays a dominant role in the lighting effect, and it provides the basic tone for the lighting effect. For example, if the blue sky occupies most of the area in an image, then the color representing the blue sky may be selected as the background color. Then, from the remaining representative colors, the dotted colors are selected according to the degree of prominence. Although the distribution area of ​​the dotted color in the image is not large, due to its large difference from the average color, it can provide a visual focus and increase the color level in the lighting effect. For example, a red flower in the image is very conspicuous among the green grass, and its representative color may be selected as the dotted color. The number of background colors and dotted colors can be determined as needed.

[0077] In some embodiments, a fixed area ratio threshold and a prominence threshold may be set, and colors exceeding these thresholds are considered as candidates for background colors and accent colors. In addition, color psychology effects may be introduced to select colors that can trigger specific emotional responses as background colors or accent colors to enhance the emotional expression of the lighting effect.

[0078] Through this color screening method based on area ratio and prominence, we can ensure that the selected colors not only capture the visual essence of the image, but also convey the atmosphere and emotions that the image wants to express, thereby constructing a lighting color scheme that is layered and visually impactful.

[0079] This embodiment achieves efficient conversion from target image to feature color set through precise image analysis and color extraction technology, and has significant and unique technical advantages, including but not limited to: First, this embodiment can divide the pixels in the image into multiple pixel clusters according to color similarity and determine the representative color of each cluster through pixel clustering processing. It can not only capture the key color information in the image, but also select the color with high area ratio and high significance to construct the characteristic color set for making the lighting effect color scheme, so that the lighting effect color scheme is closer to the visual characteristics of the image, and the authenticity and coordination of the lighting effect are enhanced.

[0080] Secondly, this embodiment has flexibility in the selection of color space, and can perform calculations based on the RGB color space or the LAB color space. In particular, when the LAB color space is recommended, it can more accurately reflect the human eye's perception of color, making the selected representative color more consistent with the human eye's visual field effect, further enhancing the visual appeal of the lighting effect color scheme.

[0081] In addition, this embodiment uses normalization processing and multiple data distance formulas when determining the area ratio and prominence, which allows the prominence of colors to be compared on the same dimension, ensuring the objectivity and standardization of the color selection process. In this way, this embodiment can identify the most visually significant color in the image, providing a scientific basis for the lighting effect color scheme.

[0082] Finally, this embodiment reduces the complexity of user operations through intelligent color extraction and color scheme generation, and users can easily achieve personalized lighting effects without in-depth understanding of technical parameters and interface specifications. At the same time, this embodiment also takes into account the psychological impact and visual beauty of color, ensuring that the generated lighting effects match the user's expectations, and enhancing the personalization and dynamic adaptability of the lighting effects.

[0083] Based on any embodiment of the method of the present application, representative colors are selected based on the area ratio and prominence of the candidate color set to form a characteristic color set for determining a lighting effect color scheme for a non-planar lamp, including: Step S5231: Based on the candidate color set, select a representative color with a relatively high area ratio as the background color of the lighting effect of the non-planar lamp; In the process of selecting representative colors from the candidate color set to form a non-planar lamp lighting effect color scheme, the first step is to select some representative colors with a relatively high area as the background color of the lighting effect, so as to identify the dominant color in the image based on the basic tone and atmosphere of the image.

[0084] In this step, one or more colors with the highest area percentage can be selected as the background color. For example, if a cluster of pixels of a color occupies more than half of the pixels in the image, then this color is likely to be the dominant color of the image and is suitable for selection as the background color. The background color plays a fundamental role in the lighting effect, providing the main visual background for the lamp. This selection ensures that the lighting effect of the lamp can reflect the main color characteristics of the image, enhancing the overall coordination and beauty of the lighting effect.

[0085] In practical applications, a specific area ratio threshold can be set according to the characteristics of the lamps and the needs of the lighting scene. For example, colors that account for more than 15% of the total number of pixels will be considered as background colors. In addition, the psychological effects of colors can be combined to give priority to colors that can trigger specific emotional responses, such as warm colors for creating a comfortable atmosphere and cool colors for creating a calm atmosphere.

[0086] Step S5232: Selecting some representative colors with relatively high significance from the remaining representative colors as decorative colors for the lighting effect of the non-planar lamp; After determining the background color of non-planar lamps, we can further determine the accent color. Although the accent color occupies a small area in the image, it is very different from the average color and can provide visual focus and increase color levels in the lighting effect. The purpose of selecting the accent color is to select a relatively high-significance color from the remaining representative colors in the candidate color set except the background color.

[0087] The quantification of the saliency is achieved by calculating the data distance between each representative color and the average color of the target image. This data distance can be calculated using different formulas, such as Euclidean distance, Manhattan distance, cosine similarity or CIEDE2000 color difference formula. After normalization, the saliency of each color can be represented by a value between 0 and 1. The larger the value, the greater the difference between the color and the average color, and the higher the saliency.

[0088] In actual applications, the accent colors can be selected based on the preset significance threshold. For example, a rule can be set to select the colors with the top 10% significance values ​​as the accent colors. Such colors are usually visually attractive and expressive, and can add vitality and focus to the lighting effects. The number of accent colors can also be determined according to actual needs, which can be either a single color or a combination of several colors.

[0089] For example, if the target image is a landscape painting of an autumn forest, the background color may be brown or green, which occupies most of the picture, while the accent color may be bright orange or red, which represents fallen leaves. Although these colors are not large in area, they are very prominent visually, attracting the observer's attention and providing a visual focus for the lighting effect. By selecting such accent colors, the lighting effect of the lamp can be made richer and more vivid, enhancing the expressiveness and visual impact of the lighting effect.

[0090] Step S5233: construct the background color and the accent color into a characteristic color set for determining a lighting effect color scheme.

[0091] Combining the background color and the accent color can form a characteristic color set, which will be used to directly define the lighting effect color scheme of the lamp.

[0092] As the basic color in the lighting effect, the background color provides the main visual background, while the accent color is used as a supplement to increase the visual focus and color level of the lighting effect. Combining these two colors can ensure that the lighting effect of the lamp not only reflects the main color characteristics of the image, but also adds the necessary visual impact and appeal.

[0093] When constructing a characteristic color set, each color in the characteristic color set will be represented by its specific value in the LAB or RGB color space to ensure accurate communication of the color.

[0094] The construction of the characteristic color set can also consider the matching and transition between colors. In some cases, it may be necessary to consider the harmony and complementarity of colors to ensure that the transition between colors in the lighting effect is natural while maintaining sufficient visual impact. For example, if the background color is blue, the accent color may be orange or yellow, because these colors form a strong contrast with blue and can provide a stronger visual contrast effect.

[0095] In one embodiment, after selecting the top three representative colors with the highest area percentage as the background colors, the top five representative colors with the highest significance are selected from the remaining representative colors as the embellishment colors, thereby forming an eight-color color matching table. The construction of a lighting effect color matching scheme based on an eight-color color matching table has unique advantages. This is mainly because such a color matching relationship not only makes the lighting effect show a colorful effect, but also enables each representative color to be effectively distinguished by the user, and therefore is more unique. In this color matching relationship, for the arrangement and combination of 8 colors, each background color can be further placed in a candidate color matching sequence between two embellishment colors, so that each background color and each embellishment color are alternately arranged. For candidate color matching sequences that are not arranged according to this relationship, it is not necessary to calculate the sum of their color differences, and they can be directly deleted.

[0096] In practical applications, the construction of the characteristic color set can be adjusted according to different lighting scenarios and needs. For example, for a lighting environment that needs to create a warm atmosphere, warm background colors and accent colors can be selected; while for an environment that needs to create a calm atmosphere, cool colors may be selected. In addition, the characteristic color set can also be optimized according to the physical characteristics and functions of the lamp to ensure that the lamp can accurately reproduce these colors.

[0097] This embodiment forms a comprehensive feature color set by accurately selecting background colors and dot colors from the candidate color set, and provides a detailed and coordinated lighting effect color scheme for non-planar lamps. The unique technical advantage of this method is that it can ensure that the lighting effect of the lamp truly reflects the color characteristics of the target image, while providing a rich and coordinated visual experience. By selecting background colors with a high area ratio and dot colors with a high degree of significance, this embodiment not only captures the visual essence of the image, but also conveys the atmosphere and emotions to be expressed by the image, and enhances the overall coordination and beauty of the lighting effect. In addition, this embodiment also takes into account the psychological effects and visual beauty of color, ensures that the generated lighting effects match the user's expectations, and enhances the personalization and dynamic adaptability of the lighting effects. Through intelligent color extraction and color scheme generation, the complexity of user operations is reduced, so that users can easily achieve personalized lighting effects without in-depth understanding of technical parameters and interface specifications. Therefore, this embodiment not only improves the overall coordination of lighting effects and optimizes the use of lamp characteristics, but also simplifies the user operation process, enhances the intelligent correspondence of lighting effect semantics, and provides users with a richer and more convenient lighting experience.

[0098] Based on any embodiment of the method of the present application, determining the lighting effect color scheme applied to the non-planar lamp in the lighting effect joint control system according to the characteristic color set includes: Step S5240, determining the data distance between each pair of colors in the characteristic color set to construct a corresponding distance matrix, and representing the color difference between each pair of colors through the data distance; Based on the characteristic color set consisting of background color and dot color obtained by color feature extraction based on the target image, the color difference between them can be determined by analyzing the colors in the characteristic color set. The colors in the characteristic color set can accurately reflect the user's intention and preference for color, thereby constructing a lighting effect color scheme that meets the user's expectations.

[0099] Specifically, the feature color set contains a set of selected representative colors that represent the main color features of the target image. In order to quantify the relationship between these colors, the concept of data distance is further introduced to represent the color difference between any two representative colors. Color difference refers to the degree of difference between two colors, which can be determined by calculating the data distance between two color values. In color space, this distance can be calculated in a variety of ways, such as using Euclidean distance, Minkowski distance, cosine similarity, CIELAB color difference formula, etc. Preferably, the calculation of the data distance corresponding to the color difference can be performed in the LAB color space to more accurately quantify the color difference effect of the human eye.

[0100] In order to more intuitively represent the color difference between these colors, we can use a distance matrix to show it. The distance matrix is ​​a two-dimensional array, where the rows and columns represent different colors in the feature color set, and each element in the matrix represents the color difference between the corresponding two colors. By calculating the color difference between each pair of colors and filling it into the matrix, we get a complete distance matrix, which describes in detail the relationship between all colors in the feature color set.

[0101] Step S5250: Arrange and combine the representative colors to obtain multiple candidate color matching sequences; Based on the characteristic color set and the color difference relationship between each representative color, these colors can be arranged and combined to generate multiple candidate color matching sequences. The candidate color matching sequences are used to explore the visual effects of different color combinations so as to select the best lighting effect color matching scheme.

[0102] In the specific implementation, we first need to determine the number of colors contained in the characteristic color set, and then use the method of permutation and combination to generate all possible candidate color sequences. For example, if the characteristic color set contains three colors A, B and C, then the possible color matching sequences include ABC, ACB, BAC, BCA, CAB, CBA. These sequences represent the order in which the colors are displayed on the lamps, and different sequences may bring different visual effects.

[0103] Step S5260: Based on the color difference of the distance matrix, the sum of the color differences between each two adjacent colors in each candidate color matching sequence is calculated, and the candidate color matching sequence with the largest sum of color differences is determined as the lighting effect color matching scheme of the non-planar lamp.

[0104] After determining the characteristic color set and its color difference relationship, we can continue to calculate the sum of the color differences between two adjacent representative colors in each candidate color sequence to determine the best lighting color scheme. The core of this step is to evaluate the visual impact and coordination of each candidate color sequence, and select the sequence with the largest sum of color differences as the final lighting color scheme, because a larger sum of color differences usually means a more vivid and dynamic visual effect.

[0105] Specifically, for each candidate color sequence, treat it as a color arrangement, such as the sequence ABC. In this sequence, it is necessary to calculate the color difference between colors A and B (denoted as d(A,B)), and the color difference between colors B and C (denoted as d(B,C)). These color difference values ​​can be directly obtained from the distance matrix constructed previously. Then, add these two color difference values ​​to get the total color difference of the sequence ABC.

[0106] For all candidate color matching sequences, the above process is repeated to calculate the sum of the color differences of each sequence. For example, for the sequence ACB, d(A,C) and d(C,B) are calculated and added to get the sum of the color differences of the sequence ACB. Similarly, the sum of the color differences of all other sequences such as BAC, BCA, CAB and CBA is also calculated.

[0107] After the color difference sum of all candidate color matching sequences is calculated, the color difference sum values ​​of these sequences are compared, and the candidate color matching sequence with the largest color difference sum is selected as the lighting effect color scheme of the non-planar lamp. The reason for this is that the sequence with a larger color difference sum provides a stronger contrast and change visually, which is more likely to attract the attention of the observer and create a more vivid and interesting lighting effect atmosphere.

[0108] For example, suppose the sum of color differences of the following candidate color matching sequences is obtained: the sum of ABC is 10, the sum of ACB is 12, the sum of BAC is 9, the sum of BCA is 11, the sum of CAB is 8, and the sum of CBA is 14. Among these sequences, the sum of color differences of CBA is the largest, so CBA is selected as the final lighting effect color scheme for non-planar lamps.

[0109] This embodiment achieves a series of unique technical advantages by accurately calculating the color difference between representative colors and determining the lighting effect color scheme of the lamp based on this. These advantages not only improve the visual effect of the lighting effect, but also enhance the user experience.

[0110] First, this embodiment quantifies the differences between colors by constructing a distance matrix, making the color matching more scientific and accurate. This data-based method ensures that the color matching scheme is not just based on subjective judgment, but has a clear mathematical basis, thereby improving the professionalism and reliability of the color matching scheme.

[0111] Secondly, this embodiment calculates the sum of the color differences of all possible color combinations and selects the sequence with the largest sum of color differences as the final lighting color scheme, which can maximize the visual effect. In this way, non-planar lamps can show more vivid and dynamic color changes, providing users with a richer and more attractive visual experience.

[0112] Furthermore, this embodiment is technically highly flexible and adaptable. It is not limited to a specific color space or color difference calculation method, and the most suitable color space and color difference calculation formula can be selected according to different needs and conditions. This flexibility enables this embodiment to be widely used in different scenarios and needs, and has strong practicality.

[0113] In addition, this embodiment has obvious advantages in improving the overall coordination of lighting effects, optimizing the use of non-planar lamp characteristics, simplifying user operation processes, and enhancing the intelligent correspondence between lighting effect semantics and target images. This embodiment not only improves the personalization of lighting effects, but also enables lighting effects to dynamically adapt to different scenes and user needs, providing users with a more flexible and intelligent lighting solution.

[0114] On the basis of any embodiment of the method of the present application, determining the lighting effect motion mode applied by the non-planar lamp based on the content description text generated according to the target image includes: Step S5310: input the target image into the large language model to generate a content description text describing the image content of the target image; Based on the target image, a large language model can be used to generate text describing the content of the target image, that is, content description text. The large language model can understand and generate natural language text. It predicts and generates text by analyzing input data (in this application, the target image).

[0115] In order to enable the large language model to generate the content description text required for this application with high quality based on the target image, it can be fine-tuned in advance. Fine-tuning training means further training with a specific data set based on the original pre-training of the model to adapt to specific tasks or application scenarios. In this application, the purpose of fine-tuning training is to enable the model to understand and describe the image content more accurately so as to generate description text that matches the image semantics.

[0116] In the specific implementation, we first collect and prepare a dataset containing images and their corresponding content description text. This dataset will be used to train and fine-tune the large language model so that it can understand and generate descriptions related to the image content. Through training, the model learns how to extract key information from the image and convert it into text descriptions. For example, if the input image is a beach at sunset, the trained model can generate a description text such as "golden beach at sunset".

[0117] After fine-tuning training is completed, the large language model can receive the target image as input and output text describing the content of the image. For example, if the target image is a landscape painting, the large language model that has been fine-tuned can accurately identify elements such as mountains, water, and trees in the image and generate descriptive text "A tranquil landscape painting with mountains and water." Such a descriptive text not only captures the main visual elements of the image, but also conveys the overall atmosphere and emotion of the image.

[0118] In this way, the large language model provides semantic supplement to the lighting effect color scheme, so that the lighting effects of the lamps not only match the target image in color, but also coordinate with the image content in dynamic performance, thus providing users with a richer and more coordinated lighting experience.

[0119] Step S5320: call the description information in the lighting effect motion mode data set of the target non-planar lamp, and determine the lighting effect motion mode corresponding to the description information that is closest in semantics to the content description text.

[0120] When this step is executed, the lighting effect color scheme has been constructed based on the background color and the accent color, and the content description text corresponding to the target image has been generated through the large language model. This content description text actually carries the semantics of the lighting effect action, so the lighting effect motion mode dataset of the target non-planar lamp can be called, and the lighting effect motion mode corresponding to the description information closest to the semantics of the content description text can be determined. Based on this, the semantic understanding of the image content is matched with the dynamic performance of the non-planar lamp to achieve a more personalized and emotional lighting effect.

[0121] As mentioned above, each non-planar lamp is associated with a lighting effect motion mode dataset, which contains multiple preset lighting effect motion modes, and each mode has corresponding description information. These description information is a textual expression of the lighting effect motion characteristics, such as "flowing", "flashing" or "stationary", which defines how non-planar lamps display color and brightness over time. Since the content description text generated by the large language model has a stronger expressive function, it is more effective to match the content description text with the description information.

[0122] In order to achieve this matching process, it is first necessary to compare the content description text generated by the large language model with the description information of each lighting effect motion mode in the lighting effect motion mode dataset. This comparison can be achieved through keyword matching, semantic similarity calculation or other natural language processing technologies. For example, if the content description text is "golden beach under the sunset", the system may look for lighting effect motion mode description information related to "sunset", "golden" and "beach", such as "warm", "gradient" or "tranquil".

[0123] During the matching process, the semantic similarity between the content description text and each lighting effect motion mode description information can be evaluated, and the lighting effect motion mode corresponding to the description information with the closest semantic similarity can be selected. This selection can be based on preset matching rules, such as selecting the mode with the highest keyword overlap or the highest semantic similarity score. For example, if the semantic similarity between "golden beach under sunset" and the description information of "warmth" and "gradual change" is the highest, the corresponding lighting effect motion mode is selected.

[0124] In addition, the selection of lighting effect motion mode can also take into account the physical characteristics of the lamp and the usage scenario. For example, for a smart lamp that can display complex color changes, a dynamically changing lighting effect motion mode can be selected; while for a simple ambient light, a more static mode may be selected.

[0125] The above embodiments achieve deep integration of lighting effect color scheme and lighting effect motion mode by combining the content description text and lighting effect motion mode dataset generated by the large language model, providing a richer and more dynamic lighting experience. Compared with other embodiments, the unique technical advantage of this method is that it can convert the semantic understanding of image content into specific lighting effects, thereby achieving seamless connection between image content and lighting effects. First, by using the content description text generated by the large language model, this embodiment can capture the main visual elements and overall atmosphere of the target image, and convert these abstract concepts into specific content text descriptions. This text description not only contains the key information of the image, but also can convey the emotion and atmosphere of the image, providing rich semantic information for the dynamic performance of the lighting effect. Secondly, this embodiment realizes intelligent selection of lighting effect motion mode by calling the lighting effect motion mode dataset of the target lamp and determining the lighting effect motion mode corresponding to the description information that is closest to the semantics of the content description text. This selection is not only based on the semantic similarity of the image content, but also takes into account the physical characteristics and usage scenarios of the lamp, so that the selected lighting effect motion mode can match the characteristics and application environment of the lamp, improving the adaptability and coordination of the lighting effect. Finally, the determined lighting effect motion mode and lighting effect color scheme are sent to the target lamp. This embodiment ensures that the lamp can play the corresponding lighting effect according to these settings.

[0126] On the basis of any embodiment of the method of the present application, before obtaining the target image for applying the lighting effect to the planar lighting fixture in the lighting effect joint control system, the method includes: Step S4110: obtaining original user input material, where the original user input material includes or indicates a target image; There are many ways to obtain the user's original input materials. A common way is for the user to directly upload image files to the application or device connected to the lighting effect control system. These image files can come from the user's smartphone, tablet, personal computer and other devices, and are transmitted to the lighting effect control system through a wireless network or wired connection. In some cases, the user may also select images from an image library on the Internet, or use a built-in or external camera unit of the lighting effect adapter device to capture images in real time.

[0127] After users upload or select images, the lighting effect joint control system needs to process these images to ensure that they can adapt to the display requirements of planar lamps. This may include pre-processing steps such as adjusting the image resolution, color correction, and format conversion. These processing steps ensure that the target image can be accurately and effectively displayed on the planar lamps to meet the user's lighting needs and aesthetic preferences.

[0128] In addition, the user's original input material can also be a description text of the image content. The user guides the lighting effect control system to generate the corresponding image by describing the scene or style they want to show. In this case, the system will use a large language model to generate the target image based on the text description, and then perform subsequent processing and application.

[0129] Step S4120: pixelate the target image to obtain a pixelated image, and send the pixelated image as a lighting effect to a planar lamp of a lighting effect joint control system for application.

[0130] Considering that the planar lamps used to render lighting effects usually form a frame with multiple point light sources arranged in a matrix, before the target image is applied to the planar lamp in the lighting effect control system, the target image can be pixelated to obtain a corresponding pixelated image to make it more match the display frame of the planar lamp.

[0131] Pixel processing refers to breaking down an image into multiple pixel units and assigning specific color values ​​to each pixel unit in order to reproduce the image on a planar luminaire. This process begins with parsing the original target image, converting it from complex image data into a series of discrete pixels. Each pixel is processed individually according to its position and color in the image and converted into a form that matches the pixel layout of the planar luminaire.

[0132] In the pixelization process, multiple factors can be considered, including the resolution of the image, the color depth, and the display capability of the luminaire. For example, if the resolution of the planar luminaire is low, the image can be downsampled to reduce the number of pixels to accommodate the display limitations of the luminaire. Conversely, if the planar luminaire supports high-resolution display, more pixel details can be retained to provide a clearer image display.

[0133] Color correction is also an optional processing step that ensures the color accuracy of the image when it is displayed on a planar luminaire. Since the color gamut and color performance of different display devices may vary, color correction can help adjust the color of the pixelated image to make it more realistic and natural when displayed on a planar luminaire.

[0134] Format conversion is the process of converting an image into a format that a planar luminaire can recognize and process. Specifically, it can include converting from common image formats such as JPEG or PNG to a luminaire-specific pixel data format. During the format conversion process, each pixel of the image is converted into a set of electronic signals that can directly control the color and brightness of the corresponding pixel on the planar luminaire.

[0135] Through these processing steps, the target image is converted into a pixelated image suitable for planar lamps, and then these pixelated images are sent as lighting effects to the planar lamps of the lighting effect joint control system for application. In this way, the planar lamps can accurately display the image according to the received pixelated image data to provide users with the desired lighting effects. Whether it is a static image or a dynamic scene, the pixelation process ensures that the image content can be accurately and effectively presented on the lamps, enhancing the visual appeal and expressiveness of the lighting environment. Since the lighting effects of non-planar lamps and planar lamps are subject to the same user's original input material, the overall lighting effect atmosphere obtained by the entire lighting effect joint control system is harmonious and unified.

[0136] This embodiment achieves accurate presentation of image content in the lighting effect joint control system by directly acquiring the target image from the original input material of the user and pixelating it to adapt to the display requirements of the planar lamp. The technical advantage of this method is that it can ensure that the accuracy and consistency of the image content are maintained in the whole process from user input to lighting effect display, thereby providing a highly personalized and coordinated lighting experience. Compared with other embodiments, this embodiment not only improves the adaptability and flexibility of the lighting effect, but also enhances the visual appeal and expressiveness of the lighting effect through diversified image acquisition methods and intelligent image processing technology. In addition, by converting the original input material of the user into a pixelated image that the lamp can understand, this embodiment ensures that the planar lamp can accurately reproduce the image, whether it is a static image or a dynamic scene, it can be accurately and effectively presented on the lamp, greatly improving the overall coordination and beauty of the lighting environment. This seamless connection from user input to lighting effect display makes the overall lighting effect atmosphere of the entire lighting effect joint control system harmonious and unified, providing users with a richer and more coordinated lighting experience.

[0137] On the basis of any embodiment of the method of the present application, before obtaining the target image for applying the lighting effect to the planar lighting fixture in the lighting effect joint control system, the method includes: Step S4210: obtaining original input material from the user, wherein the original input material from the user is a content description text of the image content; In this embodiment, the user's original input material provided by the user through the application connected to the lighting effect joint control system or the joint control lighting effect adaptation device can be a natural language description, which is used as a content description text indicating the image content. In this case, this content description text usually gives the semantics corresponding to the overall lighting effect atmosphere that the user wants to render, and this semantics contains implicit information about the color scheme and image applied to the overall lighting effect atmosphere.

[0138] Step S4220: calling a large language model to generate a target image corresponding to the content description text; It is not difficult to understand that the content description text provided by the user may be imprecise, incomplete, or unclear. In this case, the text-generated image technology can be used to first generate the corresponding target image based on the content description text, so as to provide richer lighting effect semantics through the target image.

[0139] Generating the corresponding target image based on the content description text can be achieved with the help of a large language model. The large language model has the ability to understand and generate the corresponding target image from the natural language description. The large language model has been properly trained and fine-tuned in advance, and can understand the keywords and context in the content description text, and then generate an image that matches the description. For example, if the description entered by the user is "quiet summer night", the large language model will generate an image that reflects this scene, which may include elements such as the starry sky and the scenery under the moonlight.

[0140] Since the text provided by users may be inaccurate or incomplete, the large language model's image-to-text technology can fill in the information gaps based on its pre-trained knowledge base and language understanding capabilities, create images that can represent the text description, and obtain image data that can be used for lighting effect adaptation.

[0141] The generated target image not only provides visual information about the image content, but also contains semantic information corresponding to the user's description text. This information can be used to subsequently determine the lighting color scheme and lighting motion mode of non-planar lamps, so that their final lighting effects are consistent with the user's original intention.

[0142] Step S4230: pixelate the target image to obtain a pixelated image, and send the pixelated image as a lighting effect to a planar lamp of a lighting effect joint control system for application.

[0143] After the target image is obtained, the target image can be pixelated to obtain a corresponding pixelated image, and sent to the corresponding planar lamp to play the corresponding lighting effect. The implementation of step S4230 is exactly the same as step S4120, and will not be repeated here.

[0144] This embodiment introduces a large language model to generate a target image corresponding to the user's original input material, and performs pixelation processing to adapt to the display requirements of planar lamps, thereby realizing a seamless conversion from user text description to specific lighting effects, and significantly improving the intelligence and flexibility of the lighting effect joint control system. Compared with other embodiments, the unique technical effect of this embodiment is that it can directly convert the user's text intention into visual image content, and further convert it into lighting effects, thereby ensuring the consistency of the lighting effects with user expectations. Through the text-based graph technology of the large language model, even if the user's description text is inaccurate or incomplete, it can intelligently fill in the information gap, generate an image that can represent the text description, and then obtain image data that can be used for lighting effect adaptation. This method not only improves the accuracy and convenience of lighting effect configuration, but also enhances the overall coordination and beauty of the lighting effect, providing users with a richer and more coordinated lighting experience. In addition, this embodiment also reduces the complexity of user operations, so that users can easily achieve personalized lighting effects without in-depth understanding of technical parameters and interface specifications, greatly improving the flexibility and interactivity of user experience.

[0145] See also Figure 3 A joint control lighting effect adaptation device provided to meet one of the purposes of the present application is a functional embodiment of the joint control lighting effect adaptation method of the present application, and the device includes an image acquisition module 5100, a color matching determination module 5200, a mode determination module 5300, and a lighting effect application module 5400, wherein the image acquisition module 5100 is configured to acquire a target image for applying lighting effects to a planar lighting fixture in a lighting effect joint control system; the color matching determination module 5200 is configured to extract a feature color set based on the target image, and determine a lighting effect color scheme applied to a non-planar lighting fixture in the lighting effect joint control system according to the feature color set; the mode determination module 5300 is configured to determine a lighting effect motion mode applied to the non-planar lighting fixture based on a content description text generated according to the target image; and the lighting effect application module 5400 is configured to send the lighting effect motion mode and the lighting effect color scheme to the non-planar lighting fixture, so that the non-planar lighting fixture can apply the lighting effect motion mode and the lighting effect color scheme to play the corresponding lighting effect.

[0146] Based on any embodiment of the device of the present application, the color determination module 5200 includes: a clustering processing module, which is configured to perform pixel clustering on the target image to obtain multiple pixel clusters and a representative color of each pixel cluster, wherein the representative color is the color of the central pixel of the corresponding pixel cluster; a statistical processing module, which is configured to determine the area ratio of the pixel cluster to which each representative color belongs in the target image and the prominence of each representative color in the target image, and construct a candidate color set; a feature extraction module, which is configured to screen representative colors based on the area ratio and prominence in the candidate color set to form a feature color set used for determining the lighting effect color scheme for non-planar lamps.

[0147] On the basis of any embodiment of the device of the present application, representative colors are screened based on the area percentage and prominence in the candidate color set to form a characteristic color set used for determining the lighting effect color scheme of the non-planar lamp, including: a background color selection module, configured to select some representative colors with a relatively high area percentage based on the candidate color set as the background colors of the lighting effect of the non-planar lamp; an embellishment color selection module, configured to select some representative colors with a relatively high prominence from the remaining representative colors as the embellishment colors of the lighting effect of the non-planar lamp; a combined representation module, configured to construct the background color and the embellishment color into a characteristic color set for determining the lighting effect color scheme.

[0148] Based on any embodiment of the device of the present application, the color determination module 5200 includes: a matrix construction module, which is configured to determine the data distance between each pair of colors in the characteristic color set to construct a corresponding distance matrix, and express the color difference between each pair of colors through the data distance; an arrangement and combination module, which is configured to arrange and combine each representative color to obtain multiple candidate color sequences; a scheme construction module, which is configured to calculate the sum of the color differences between each two adjacent colors in each candidate color sequence based on the color difference of the distance matrix, and determine the candidate color sequence with the largest sum of color differences as the lighting effect color scheme of the non-planar lamp.

[0149] Based on any embodiment of the device of the present application, the pattern determination module 5300 includes: a text generation module, configured to input the target image into a large language model to generate a content description text describing the image content of the target image; a pattern matching module, configured to call the description information in the lighting effect motion pattern data set of the target non-planar lamp, and determine the lighting effect motion pattern corresponding to the description information that is closest in semantics to the content description text.

[0150] On the basis of any embodiment of the device of the present application, prior to the image acquisition module 5100, the device includes: an image input module, configured to obtain original input material from a user, wherein the original input material from the user includes or indicates a target image; a surface control module, configured to pixelate the target image to obtain a pixelated image, and send the pixelated image as a lighting effect to a surface lamp of a lighting effect linkage control system for application.

[0151] On the basis of any embodiment of the device of the present application, prior to the image acquisition module 5100, the device includes: a text input module, configured to obtain original input material from a user, wherein the original input material from the user is a content description text of the image content; an image generation module, configured to call a large language model to generate a target image corresponding to the content description text; a surface control module, configured to pixelate the target image to obtain a pixelated image, and send the pixelated image as a lighting effect to a surface lamp of a lighting effect linkage control system for application.

[0152] In order to solve the above technical problems, the present application also provides a computer device. Figure 4 As shown, a schematic diagram of the internal structure of a computer device. The computer device includes a processor, a computer-readable storage medium, a memory, and a network interface connected via a system bus. Among them, the computer-readable storage medium of the computer device stores an operating system, a database, and computer-readable instructions. The database may store a control information sequence. When the computer-readable instructions are executed by the processor, the processor can implement a joint control lighting effect adaptation method. The processor of the computer device is used to provide computing and control capabilities to support the operation of the entire computer device. The memory of the computer device may store computer-readable instructions. When the computer-readable instructions are executed by the processor, the processor can execute the joint control lighting effect adaptation method of the present application. The network interface of the computer device is used to connect and communicate with a terminal. Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0153] In this embodiment, the processor is used to execute Figure 3 The memory stores the program code and various data required to execute the above modules or submodules. The network interface is used to transmit data between user terminals or servers. The memory in this embodiment stores the program code and data required to execute all modules / submodules in the joint control lighting effect adaptation device of this application, and the server can call the program code and data of the server to execute the functions of all submodules.

[0154] The present application also provides a storage medium storing computer-readable instructions. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the joint control lighting effect adaptation method of any embodiment of the present application.

[0155] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments of the present application can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a computer-readable storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0156] It will be understood by those skilled in the art that the various operations, methods, steps, measures, and schemes in the processes discussed in this application may be alternated, changed, combined, or deleted. Furthermore, other steps, measures, and schemes in the various operations, methods, and processes discussed in this application may also be alternated, changed, rearranged, decomposed, combined, or deleted. Furthermore, the steps, measures, and schemes in the various operations, methods, and processes in the prior art that are open source and in this application may also be alternated, changed, rearranged, decomposed, combined, or deleted.

[0157] The above description is only a partial implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A joint control lighting effect adaptation method, characterized in that: include: Acquire a target image for applying lighting effects to planar lighting fixtures in a lighting effect joint control system; Extracting a characteristic color set based on the target image, and determining a lighting effect color scheme applied to non-planar lamps in the lighting effect joint control system according to the characteristic color set; Determining a lighting effect motion mode applied to the non-planar lamp based on a content description text generated according to the target image; The lighting effect motion mode and the lighting effect color scheme are sent to the non-planar lamp, so that the non-planar lamp applies the lighting effect motion mode and the lighting effect color scheme to play the corresponding lighting effect.

2. The joint control lighting effect adaptation method according to claim 1, characterized in that: Extracting a characteristic color set based on the target image includes: Perform pixel clustering on the target image to obtain multiple pixel clusters and a representative color of each pixel cluster, wherein the representative color is the color of the central pixel of the corresponding pixel cluster; Determine the area ratio of the pixel cluster to which each representative color belongs in the target image and the prominence of each representative color in the target image, and construct a candidate color set; Based on the area proportion and prominence of the candidate color set, representative colors are selected to form a characteristic color set used for determining the lighting effect color scheme of non-planar lamps.

3. The joint control lighting effect adaptation method according to claim 2, characterized in that: Determine the area ratio of the pixel cluster to which each representative color belongs in the target image and the prominence of each representative color in the target image, and construct a candidate color set, including: Exclude the pixel clusters whose representative colors belong to the threshold range corresponding to the color close to black, and divide the total number of pixels of each remaining pixel cluster by the total number of pixels of all remaining pixel clusters to obtain the area ratio corresponding to each representative color; The data distance between the representative color of each remaining pixel cluster and the average color of the target image is calculated and normalized to obtain the saliency corresponding to each representative color.

4. The joint control lighting effect adaptation method according to claim 2, characterized in that: Based on the area proportion and prominence of the candidate color set, representative colors are selected to form a characteristic color set used by non-planar lamps to determine the lighting effect color scheme, including: Based on the candidate color set, select representative colors with relatively high area proportion as background colors of the lighting effect of the non-planar lamp; Selecting some representative colors with relatively high significance from the remaining representative colors as decorative colors for the lighting effects of non-planar lamps; The background color and the accent color are constructed as a characteristic color set for determining a lighting effect color scheme.

5. The joint control lighting effect adaptation method according to claim 2, characterized in that: The lighting effect color scheme applied to the non-planar lamps in the lighting effect joint control system is determined according to the characteristic color set, including: Determine the data distance between each pair of colors in the characteristic color set to construct a corresponding distance matrix, and express the color difference between each pair of colors through the data distance; Arrange and combine the representative colors to obtain multiple candidate color matching sequences; Based on the color difference of the distance matrix, the sum of the color differences between each two adjacent colors in each candidate color matching sequence is calculated, and the candidate color matching sequence with the largest sum of the color differences is determined as the lighting effect color matching scheme of the non-planar lamp.

6. The joint control lighting effect adaptation method according to claim 2, characterized in that: Based on the area proportion and prominence of the candidate color set, representative colors are selected to form a characteristic color set used by non-planar lamps to determine the lighting effect color scheme, including: Select the top three colors with the highest area percentage as the background colors of the lighting effect of the non-planar lamp; Selecting the top five colors with the highest significance as decorative colors for the lighting effect of the non-planar lamp; The background color and the accent color are constructed into a characteristic color set for determining a lighting effect color scheme.

7. The joint control lighting effect adaptation method according to any one of claims 1 to 6, characterized in that: Determining the lighting effect motion mode applied to the non-planar lamp based on the content description text generated according to the target image includes: Inputting the target image into a large language model to generate a content description text describing the image content of the target image; The description information in the lighting effect motion mode data set of the target non-planar lamp is called to determine the lighting effect motion mode corresponding to the description information that is closest in semantics to the content description text.

8. The joint control lighting effect adaptation method according to any one of claims 1 to 6, characterized in that: Before obtaining the target image for applying the lighting effect to the planar lighting fixture in the lighting effect joint control system, the following steps are included: Acquire original user input material, where the original user input material includes or indicates a target image; The target image is pixelated to obtain a pixelated image, and the pixelated image is sent as a lighting effect to a planar lamp of a lighting effect joint control system for application.

9. The joint control lighting effect adaptation method according to any one of claims 1 to 6, characterized in that: Before obtaining the target image for applying the lighting effect to the planar lighting fixture in the lighting effect joint control system, the following steps are included: Acquire original input material from a user, where the original input material from the user is a content description text of the image content; Calling a large language model to generate a target image corresponding to the content description text; The target image is pixelated to obtain a pixelated image, and the pixelated image is sent as a lighting effect to a planar lamp of a lighting effect joint control system for application.

10. A joint control lighting effect adaptation device, characterized in that: include: An image acquisition module, configured to acquire a target image for applying lighting effects to a planar lighting fixture in a lighting effect linkage control system; A color matching determination module, configured to extract a characteristic color set based on the target image, and determine a lighting effect color matching scheme applied to a non-planar lamp in a lighting effect joint control system according to the characteristic color set; a mode determination module, configured to determine a lighting effect motion mode applied to the non-planar lamp based on a content description text generated according to the target image; The lighting effect application module is configured to send the lighting effect motion mode and the lighting effect color scheme to the non-planar lamp, so that the non-planar lamp applies the lighting effect motion mode and the lighting effect color scheme to play the corresponding lighting effect.

11. A joint control lighting effect adaptation device, comprising a controller, wherein the controller is electrically connected to a planar lamp and a non-planar lamp respectively, characterized in that: The controller is used to execute the steps of the joint control lighting effect adaptation method as described in any one of claims 1 to 9 to control planar lamps and non-planar lamps to display corresponding lighting effects.

12. A computer-readable storage medium, characterized in that: It stores a computer program implemented according to the method described in any one of claims 1 to 9 in the form of computer-readable instructions, and when the computer program is called and executed by a computer, the steps included in the corresponding method are executed.

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