Light effect display method and apparatus, device, and medium

Abstract

The present application relates to a light effect display method and apparatus, a device, and a medium in the field of lighting control. The method comprises: generating a corresponding light effect image on the basis of a light effect generating text, determining a target position corresponding to an original position of a color value of each pixel point in the light effect image on a hue circle, and resetting the color value of each pixel point on the basis of a target color value of the pixel point at the corresponding target position; determining a plurality of primary color values, in the light effect image, each having a total number of pixels meeting a preset condition, and resetting the color value of each pixel point on the basis of the primary color value closest to the color value of the pixel point; determining a different color value which meets a preset condition with an average hue value of the light effect image, and on the basis of the different color value, resetting the color value of the pixel point having a preset color value in main content of the light effect image; and reconstructing the light effect image into a target light effect image corresponding to a target resolution, and on the basis of the target light effect image, controlling a light screen device to play back a corresponding light effect. The present application achieves a high-quality light effect displayed on a matched light screen device.

Description

Lighting effect display methods, devices, equipment, and media Technical Field

[0001] This application relates to the field of lighting control, and in particular to a lighting effect display method and corresponding device, computer equipment, and computer-readable storage medium. Background Technology

[0002] With the improvement of people's economic level, light screen devices are becoming increasingly popular. As a type of intelligent lighting fixture, light screen devices can decorate interior spaces and display information. A key feature of light screen devices is their use of large-grained LEDs as basic pixels. Through different implementation methods, they can be presented in various forms, such as curtain lights, pixel screens, and splicing lights. One of the functions of light screen devices is to display corresponding lighting effects based on a given lighting effect image.

[0003] In traditional technologies, corresponding lighting effect images for a given light screen device are typically generated directly based on user requirements, and then the corresponding lighting effects are displayed on the light screen device according to these images. However, existing text-based image algorithms usually generate high-resolution images for lighting effects, which are unsuitable for displaying on light screen devices with limited pixels. This can easily lead to the loss of a large amount of necessary visual content, resulting in poor lighting effect display and a poor visual experience for the user.

[0004] It is evident that traditional light screen equipment has not achieved good results in terms of lighting effects, which hinders the promotion of light screen equipment. Therefore, it is necessary to upgrade the technology of light screen equipment.

[0005] Application content

[0006] The primary objective of this application is to solve at least one of the above-mentioned problems by providing a lighting effect display method and corresponding device, computer equipment, and computer program product.

[0007] To achieve the various objectives of this application, the following technical solution is adopted:

[0008] A lighting effect display method provided for one of the purposes of this application includes the following steps:

[0009] Generate a corresponding lighting effect image based on the lighting effect text, determine the target position corresponding to the original position of the color value of each pixel in the lighting effect image on the color wheel, and reset the color value of each pixel according to the target color value of the target position corresponding to the target position.

[0010] Determine multiple primary color values ​​in the lighting effect image that satisfy preset conditions for the total number of pixels, and reset the color value of each pixel based on the primary color value closest to its color value.

[0011] Determine the difference color value that satisfies the preset condition with the average hue value of the lighting effect image, and reset the color value of the pixel points belonging to the predetermined color value in the main content of the lighting effect image according to the difference color value;

[0012] The lighting effect image is reconstructed into a target lighting effect image corresponding to the target resolution. The corresponding lighting effect is then played by the light screen device based on the target lighting effect image, so as to display the target lighting effect image through the light screen device.

[0013] On the other hand, a lighting effect display device provided to meet one of the purposes of this application includes a first color reset module, a second color reset module, a third color reset module, and a lighting effect playback module. The first color reset module is used to generate a corresponding lighting effect image based on the lighting effect generating text, determine the target position corresponding to the original position of the color value of each pixel in the lighting effect image on the color wheel, and reset the color value of the pixel based on the target color value corresponding to the target position. The second color reset module is used to determine multiple primary color values ​​in the lighting effect image whose total number of pixels meets preset conditions, and reset the color value of each pixel based on the primary color value closest to its color value. The third color reset module is used to determine the difference color value that meets the preset conditions with the average hue value of the lighting effect image, and reset the color value of pixels belonging to a predetermined color value in the main content of the lighting effect image based on the difference color value. The lighting effect playback module is used to reconstruct the lighting effect image into a target lighting effect image corresponding to a target resolution, and control a light screen device to play corresponding lighting effects based on the target lighting effect image, so as to display the target lighting effect image through the light screen device.

[0014] In another aspect, a computer device provided to suit one of the purposes of this application includes a central processing unit and a memory, the central processing unit being used to invoke and run a computer program stored in the memory to perform the steps of the lighting effect display method described in this application.

[0015] In another aspect, a computer program product provided for another purpose of this application includes a computer program / instructions that, when executed by a processor, implement the steps of the method described in any embodiment of this application. Attached Figure Description

[0016] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0017] Figure 1 is a schematic diagram of the electrical structure of the light screen device in the embodiment of this application;

[0018] Figure 2 shows the structural form of an exemplary light screen device of this application, wherein the light screen in Figure 2 is arranged in the form of a curtain light.

[0019] Figure 3 is a flowchart illustrating a typical embodiment of the lighting effect display method of this application;

[0020] Figure 4 is a schematic diagram of the process of color transformation of the lighting effect image in an embodiment of this application;

[0021] Figure 5 is a schematic diagram of the inner region of the hue ring obtained by dividing the hue ring according to an example of this application.

[0022] Figure 6 is a schematic diagram of the process of color normalization of the lighting effect image in an embodiment of this application;

[0023] Figure 7 is a schematic diagram of the process of performing predetermined color differentiation on the lighting effect image in an embodiment of this application;

[0024] Figure 8 is a schematic diagram of the process of generating corresponding lighting effect images based on lighting effect generation text in an embodiment of this application;

[0025] Figure 9 is a schematic diagram of the process of generating corresponding lighting effect images based on lighting effect text in an embodiment of this application;

[0026] Figure 10 is a flowchart illustrating the process of resetting the color value of pixels whose transparency meets preset conditions in the lighting effect image in an embodiment of this application.

[0027] Figure 11 is a schematic diagram of the process of reconstructing a lighting effect image into a target lighting effect image corresponding to the target resolution in an embodiment of this application;

[0028] Figure 12 is a schematic block diagram of the lighting effect display device of this application;

[0029] Figure 13 is a schematic block diagram of the lighting effect display device of this application (II).

[0030] Figure 14 is a schematic diagram of the structure of a computer device used in this application. Embodiments of the present invention

[0031] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0032] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this application means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0033] Those skilled in the art will understand that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0034] Please refer to Figure 1, which is a schematic diagram of the structure of a light screen device provided in one embodiment of this application. As can be seen, the light screen device includes a controller 1 and a light screen 2. The light screen 2 is electrically connected to the controller 1 so as to receive control from the computer program running in the controller 1 and work together to realize the playback of light effects.

[0035] Controller 1 typically includes a control chip, communication components, and a bus connector. In some embodiments, controller 1 may also be configured with a power adapter, control panel, display screen, etc., as needed.

[0036] The power adapter is primarily used to convert AC power to DC power to supply power to the entire light display device. 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 typically includes a central processing unit (CPU) and memory. The memory and CPU are used to store and execute program instructions, respectively, to achieve the corresponding functions. All of these types of control chips can have built-in communication components or can be configured with additional communication components as needed. The communication component can be used to communicate with external devices, such as personal computers or various smartphones. After the user issues various configuration commands through their terminal device, the control chip of controller 1 can receive the configuration commands through the communication component, complete the basic configuration, and control the light display. Furthermore, controller 1 can also obtain lighting effect application packages that encapsulate multiple lighting effect layers through the communication component. The bus connector is mainly used to provide power to the light screen 2 connected to the bus and to provide lighting effect playback commands. Therefore, it provides corresponding pins for the power bus and signal bus. Thus, when the light screen 2 needs to be connected to the controller 1, it can be connected to the bus connector through the corresponding connector on the light screen. The control panel typically provides one or more buttons for controlling the controller 1 on and off, selecting various preset lighting effect control modes, etc. The display screen can be used to display various control information to cooperate with the buttons on the control panel and support the realization of human-machine interaction functions. In some embodiments, the control panel and the display screen can be integrated into the same touch display screen.

[0037] The specific form of the light screen can be designed according to the actual situation. Common product forms include, but are not limited to, curtain lights, pixel screens, and splicing lights.

[0038] For example, the light screen in Figure 2 is arranged like a curtain light. The light screen 2 includes multiple light strips 21 connected to a bus. Each light strip 21 includes multiple LED beads 210 connected in series. Each LED bead 210 is a light-emitting unit. Usually, the number of LED beads 210 in each light strip 21 is the same, and they are arranged at equal intervals. When the light screen 2 is used as a curtain light, its light strips 21 are usually unfolded according to the layout shown in Figure 2. This arranges all the LED beads in all the light strips 21 in an array to form an LED bead matrix structure. Since all the LED beads can provide a display effect when they emit light together, the surface where the entire LED bead matrix structure is located constitutes a display frame 4. When the lighting effect is played, a certain pattern effect can be formed within the display frame 4.

[0039] Each light-emitting strip 21 can be composed of multiple LED beads 210 connected in series. Each LED bead 210 is a light-emitting unit. The LED beads 210 in the same light-emitting strip 21 transmit operating current through the same set of cables connected to the bus. The LED beads 210 in the same light-emitting strip 21 can be connected in parallel in terms of electrical connection. In one embodiment, the light-emitting strips 21 in the same LED bead matrix structure can be arranged at equal intervals along the bus direction, and the LED beads 210 in each light-emitting strip 21 are also arranged in corresponding numbers and positions. In this way, when the entire display screen 4 is viewed from a distance, it acts like a screen and can form a pattern effect in the human eye.

[0040] Each LED bead 210 in each LED strip 21 of the light screen 2 is also equipped with a corresponding control chip. This control chip can be selected as described above, or other more economical control chips can be selected. Its main function is to extract the light emission color value corresponding to this LED bead 210 from the light effect playback command and control the light-emitting element in this LED bead 210 to emit the corresponding color light. The light-emitting element can be an LED.

[0041] The implementation principle of pixel screens is basically the same as that of curtain lights, but pixel screens provide a frame to fix each light-emitting unit, arranging the light-emitting units in a row and column matrix within the same rectangular frame to achieve a product form effect more similar to a daily display screen. Similar to curtain lights, pixel screens can organize the light-emitting units into a structure of multiple light strips arranged side-by-side, and can be controlled using the same control methods as curtains; therefore, further details will not be elaborated upon.

[0042] When the light screen device of this application is powered on, the controller chip can call and execute a computer program from the memory. Through the default initialization process of the computer program, the light screen is powered on and initialized, and the driver configuration of the light screen and other hardware devices is completed.

[0043] In one embodiment, when the controller starts the light screen, it can first send a self-test command to the light screen, driving each LED in each light strip or block of the light screen to return its position information in the light strip or block. Each LED is equipped with a corresponding control chip for data communication with the control chip in the controller. Therefore, according to a serial communication protocol, the LED's own characteristic information can be sequentially concatenated with the characteristic information of other LEDs to represent its own position information. The serial communication protocol executed between the controller and the LED can be any one of IIC (Inter-Integrated Circuit), SPI (Serial Peripheral Interface), or UART (Universal Asynchronous Receiver-Transmitter). After the controller obtains the self-test result data returned by each LED from the bus, it parses the data and determines the position of each LED in the display area 4 of the entire light screen based on the sorting of the characteristic information of each LED in the result data. Thus, each LED can be regarded as a light-emitting unit, which can be understood as a basic pixel. The position information of each LED can be constructed into the light source position distribution information. When the controller constructs the lighting effect control data, it can set the corresponding light emission color value of each basic pixel according to actual needs based on the position information of each LED, that is, each light-emitting unit, in the light source position distribution information.

[0044] In some embodiments, the controller 2 of this application can be implemented in a separate computer device, as long as the computer device is equipped with the corresponding hardware for the controller 2, and the corresponding business logic of the controller 2, including the business logic executed by the method of this application, is implemented as a computer program and installed and run on the computer device. When the controller 2 is implemented in a computer device, the various resources inherent in the computer device can be shared, which can save the overall implementation cost. The computer device referred to herein can be any terminal device for user use, such as a smartphone, personal computer, laptop, tablet computer, etc.

[0045] Based on the product architecture and working principle of the above-mentioned light screen equipment, the lighting effect generation method of this application can be implemented as a computer program product, stored in the memory of the controller of the light screen equipment, and executed by the central processing unit after being called from the memory, thereby controlling the light screen to play the corresponding lighting effects.

[0046] Any model in this application can be deployed on a cloud server, a terminal device, or the controller of the light screen device in this application, as long as the computing power of the deployed end is sufficient to meet the requirements for running the light effect generation model.

[0047] Please refer to Figure 3. A lighting effect display method of this application, in its typical embodiment, includes the following steps:

[0048] Step S1100: Generate a corresponding light effect image based on the light effect generation text, determine the target position corresponding to the original position of the color value of each pixel in the light effect image on the color wheel, and reset the color value of the pixel according to the target color value of the target position of each pixel.

[0049] The lighting effect generation text is descriptive text generated for displaying the desired lighting effects on the lighting screen device. Users provide the corresponding lighting effect generation text based on their own lighting effect requirements. This can be provided by the user directly inputting the lighting effect generation text in natural language via an input method, or by the user inputting the text via voice, which is then converted into the corresponding lighting effect generation text.

[0050] In one embodiment, a preset prompt template based on few-shot learning is invoked. The prompt template includes a task description, examples, and text to be embedded for generating lighting effects. Those skilled in the art can flexibly modify the prompt template with reference to the following disclosure. An exemplary prompt template is provided: The task description in the prompt template is: "Determine whether the user wants 'abstract style' or 'concrete style' by specifying the structure and providing some examples."

[0051] 1.Judge based on keywords in the text.

[0052] 2.Give the final result directly without any explanation.”

[0053] Example: <examples>{'input': 'Switch to a party light atmosphere.', 'output': 'Abstract style'},{'input': 'Set the light for a movie night ambiance.', 'output': 'Abstract style'},{'input': 'Turn on the soothing lighting suitable for resting.', 'output': 'Abstract style'},{'input': 'Generate a jumping frog pattern light effect.', 'output': 'Representational style'},{'input': 'Design an approaching train light effect.', 'output': 'Representational style'},{'input': 'Make a floating sea turtle pattern light effect.', 'output': 'Representational style'}< / examples> "

[0054] The text to be generated for the lighting effect to be embedded: <input> $query_input$

[0055] The light effect generation text is embedded into the prompt template to obtain the corresponding prompt text. The prompt text is then input into the large language model to obtain the light effect content style of the light effect generation text determined by the large language model.

[0056] In addition, a preset prompt template based on few-shot learning is invoked. This prompt template includes a task description, examples, and the text to be embedded for generating the lighting effect. Those skilled in the art can flexibly adapt the prompt template with reference to the following disclosure. An exemplary prompt template is provided: The task description in the prompt template reads: "Determine whether the user wants a sport image or a static image by specifying the structure and providing some examples."

[0057] 1.Judge based on the importance of keywords in the text.

[0058] 2.Give the final result directly without any explanation.”

[0059] Example: <examples> {'input': 'Switch to a party light atmosphere.', 'output': 'Static motion type'},{'input': 'Set the light for a movie night ambiance.', 'output': 'Static motion type'},{'input': 'Turn on the soothing lighting suitable for resting.', 'output': 'Static motion type'},{'input': 'Generate a jumping frog pattern light effect.', 'output': 'Dynamic motion type'},{'input': 'Design an approaching train light effect.', 'output': 'Dynamic motion type'},{'input': 'Make a floating sea turtle pattern light effect.', 'output': 'Dynamic motion type'}< / examples> "

[0060] The text to be generated for the lighting effect to be embedded: <input> $query_input$

[0061] The light effect generation text is embedded into the prompt template to obtain the corresponding prompt text. The prompt text is then input into the large language model to obtain the light effect motion type of the light effect generation text determined by the large language model.

[0062] If the lighting effect motion type is a static motion type, in one embodiment, an open-source text-based image generation model can be used to generate corresponding images as lighting effect images based on the keyword set. The image format of the lighting effect image can be PNG or JPG. The model can be any one of the following: DELL E series model, ERNIE-ViLG series model, Midjourney, Stable Diffusion, eDiff-I, ModelScope, AltDiffusion, layerDiffusion, etc. Those skilled in the art can choose one to implement as needed.

[0063] If the light effect motion type is a dynamic motion type, in one embodiment, an open-source model that generates multiple image frames based on text can be used to generate an image consisting of multiple corresponding image frames according to the keyword set as the light effect image. The image format of the light effect image can be any of the video formats such as GIF or MP4. The model can be any of AnimateDiff, Gen-2, Stable Video Diffusion, Emu Video, etc., based on Stable Diffusion. Those skilled in the art can choose one to implement as needed.

[0064] In a further embodiment, if the generated lighting effect image contains a background, an open-source pre-trained image semantic segmentation model is used to determine the content belonging to the background in the lighting effect image, and the color value of each pixel in it is set to the color value corresponding to black (R: 0, G: 0, B: 0), so that the corresponding light-emitting unit does not need to emit light when the background is displayed on the light screen device. The image semantic segmentation model can be Mask R-CNN, U-Net, DeepLabv3, etc.

[0065] Determine the target position corresponding to the original position of the color value of each pixel in the lighting effect image on the color wheel. Taking the color value of a single pixel as an example, the target position can be the color value of the pixel in the corresponding color wheel, with the corresponding S value being the S value of the original position * (1 + a%), where a ∈ (0,1], and / or the corresponding H value being the H value of the original position * (1 + b%), where b ∈ (0,1]. The corresponding positions, a and b, can be set as needed based on the information disclosed here.

[0066] Step S1200: Determine multiple main color values ​​in the lighting effect image whose total number of pixels meets preset conditions, and reset the color value of each pixel according to the main color value closest to its color value.

[0067] For each different color value in the lighting effect image, the number of pixels displaying the same color value is determined as the total number of pixels for that color value. Based on the total number of pixels from high to low, all different color values ​​are sorted, and the top N color values ​​are selected as individual main color values. The number N can be set as needed.

[0068] For each pixel, the Euclidean distance between the pixel's color value and each major color value is calculated as the distance value. For example, if the pixel's color value is R: 246, B: 3, G: 255, and a major color value is R: 255, B: 255, G: 255, the corresponding Euclidean distance is 252.08. Then, the major color value with the lowest distance value is selected, and the pixel's color value is replaced with that major color value.

[0069] Step S1300: Determine the difference color value that satisfies the preset condition with the average hue value of the lighting effect image, and reset the color value of the pixel points belonging to the predetermined color value in the main content of the lighting effect image according to the difference color value.

[0070] The main content of the lighting effect image is obtained. Specifically, the main content of the lighting effect image is usually the foreground content. Therefore, after constructing the lighting effect image, an open-source pre-trained foreground recognition model can be used to determine the foreground content. When the background of the lighting effect image is transparent, the content with non-zero transparency can be directly identified as the main content. The foreground recognition model can be Mask R-CNN, U-Net, DeepLabv3, etc. The color value of each pixel in the main content of the current lighting effect image is traversed to determine whether the display effect of the color value is close to black. Specifically, the Euclidean distance between the color value and the color value corresponding to black can be calculated. When the Euclidean distance is less than or equal to a preset threshold, the color value is considered to be close to the color value corresponding to black and belongs to the predetermined color value. Then, based on the hue value corresponding to the color value of each pixel in the lighting effect image, the average hue value is calculated. A contrasting color effect, defined in color art, is determined that corresponds to the average hue value. The color values ​​of the pixels belonging to the predetermined color value are then replaced with the corresponding RGB difference color value. Those skilled in the art can further set the difference color value as needed, as disclosed herein.

[0071] Step S1400: Reconstruct the lighting effect image into a target lighting effect image corresponding to the target resolution, and control the light screen device to play the corresponding lighting effect according to the target lighting effect image, so as to display the target lighting effect image through the light screen device.

[0072] When the resolution of the lighting effect image does not match the resolution of the light screen device, the lighting effect image can be converted into an image corresponding to the resolution of the light screen device. Those skilled in the art can flexibly adapt this method. Then, matching lighting effect control data is generated based on the converted lighting effect image, and the light screen device is controlled to play the corresponding lighting effect based on the lighting effect control data. The specific implementation of this step will be further revealed in subsequent embodiments, and will not be described in detail here.

[0073] As can be seen from the above embodiments, this application has many advantages, including but not limited to:

[0074] First, this application generates a corresponding lighting effect image by parsing the lighting effect generation text, determines the target position corresponding to the original position of the color value of each pixel on the color wheel, and resets the color value of the pixel according to the target color value of the target position corresponding to the pixel. It can be seen that the color values ​​of all pixels in the generated lighting effect image can be appropriately transformed as needed, so as to obtain a color change that is more in line with expectations.

[0075] Secondly, determine multiple primary color values ​​in the lighting effect image that satisfy the preset conditions for the total number of pixels. Then, reset the color value of each pixel based on the primary color value closest to its color value. As can be seen, this optimizes the color distribution of the lighting effect image and reasonably reduces the richness of the color distribution, thereby improving the naturalness of the overall visual effect.

[0076] Furthermore, the difference color value between the average hue value of the lighting effect image and the preset condition is determined. Based on the difference color value, the color value of the pixels in the main content of the lighting effect image that belong to the preset color value is reset. It can be seen that the color in the lighting effect image that belongs to the preset color can be replaced with a color that is visually different from it, thereby making the lighting effect image that may have appeared monotonous or dim more vivid and interesting.

[0077] Finally, the lighting effect image is reconstructed into a target lighting effect image corresponding to the target resolution. Based on the target lighting effect image, the lighting screen device is controlled to play the corresponding lighting effect, so as to display the target lighting effect image through the lighting screen device and provide users with a high-quality lighting effect visual experience that matches the lighting screen device.

[0078] Referring to Figure 4, in a further embodiment, step S1100, determining the target position corresponding to the original position of the color value of each pixel in the light effect image on the color wheel, and resetting the color value of the pixel according to the target color value of the target position, includes the following steps:

[0079] Step S1110: For each pixel in the lighting effect image, determine the region within the color wheel to which the original position of the pixel's color value belongs on the color wheel;

[0080] The color value of a pixel in the lighting effect image can be an RGB value or an HSV value. If the color value of a pixel is an RGB value, then the RGB value of the pixel is converted into the corresponding HSV value.

[0081] For each pixel in the lighting effect image, in the HSV three-dimensional coordinate system, the color value of the pixel represented by HSV can be located on the corresponding color wheel to the two-dimensional coordinates of the HSV value (the H value and the S value in the HSV value), which serve as the original position of the pixel on the color wheel. The color wheel is a circular two-dimensional plane that is perpendicular to the V axis in the HSV three-dimensional coordinate system and corresponds to the V value in the HSV value. The V value is constant in the circular two-dimensional plane. The range of the V value, the S value is [0,1], and the range of the H value is [0,360].

[0082] For any V value in the HSV three-dimensional coordinate system corresponding to the same hue ring size, the hue ring can be divided using the same region division method. Taking a single hue ring as an example, in one embodiment, the hue ring is divided into N sectors of equal size (the central angle of each sector is N / 360°), and M concentric circles of different sizes are also divided (the center of each concentric circle is the center of the hue ring; the diameter of the i-th concentric circle is i / M of the diameter of the hue ring, where i is an integer and i∈(0,M]). Thus, the hue ring is obtained. There are N*M ring-shaped regions, each of which is a closed space composed of the minimum number of edges. N and M can be set as needed. In a recommended embodiment, the LED density in the light screen device is determined based on the light source location distribution information. N and M are then set accordingly. It is easy to understand that the higher the LED density, the larger N*M can be. For example, the LED density of a curtain light is smaller than that of a pixel light; therefore, the N*M corresponding to a pixel light is set larger than that corresponding to a curtain light. Those skilled in the art can further set the specific values ​​of N and M as needed based on this disclosure, so that the subsequent image as a whole contains multiple target color values, resulting in a richer visual effect. As an example, with N=6 and M=3, the ring-shaped regions obtained by dividing the hue ring are shown in Figure 5, including 6 ring-shaped regions 100, 6 ring-shaped regions 101, and 6 ring-shaped regions 102 of the same size, totaling 3*6, or 18 ring-shaped regions. Regions. It's easy to understand that the two-dimensional coordinate range corresponding to each region within the hue ring can be determined, and those skilled in the art can flexibly adapt this to their needs. For example, as shown in Figure 5, the two-dimensional coordinate range corresponding to region 100 is H∈[0, 45], S∈[0, 1 / 3]; the two-dimensional coordinate range corresponding to region 101 is H∈[315, 360], S∈[1 / 3, 2 / 3]; and the two-dimensional coordinate range corresponding to region 102 is H∈[270, 315], S∈[2 / 3, 1]. Therefore, the two-dimensional coordinate range of a single region within the corresponding hue ring to which the pixel belongs can be determined, thus confirming that the original position of the pixel belongs to that region.

[0083] In other embodiments, the region division method can be any one or any combination of multiple sectors, multiple concentric circles, multiple rectangles, etc., of the color wheel.

[0084] Step S1120: Determine the target color value of the target position in the inner ring region that is at a distance from the original position that meets the preset conditions, and use it to replace the color value of the pixel.

[0085] Furthermore, in one embodiment, if the region within the color wheel to which the original position of the pixel's color value belongs is a sector within the corresponding color wheel, such as region 100 shown in Figure 5, then the distance from the original position is considered to be the distance from the original position to the center of the color wheel, and this is regarded as meeting a preset condition. The center of the circle is taken as the target position, and the color value represented by HSV corresponding to the center is converted to a color value represented by RGB as the target color value. The color value of the pixel is then replaced with the target color value. The region within the color wheel to which the original position of the pixel's color value belongs is a non-fan-shaped region within the corresponding color wheel, such as region 101 or region 102 shown in Figure 5. The distance from the original position is considered to be the distance from the original position to the midpoint of the longest arc edge in the annular region, which satisfies the preset condition. The midpoint is taken as the target position, and the color value corresponding to the midpoint, represented in HSV, is converted to a color value represented in RGB as the target color value. The color value of the pixel is then replaced with the target color value.

[0086] In other embodiments, the target location within the ring region that meets a preset condition in terms of distance from the original location can be any single location within the ring region that meets the condition, provided that the distance from the original location is a preset length and the corresponding S value is greater than the S value of the original location. Alternatively, the location within the ring region that is furthest from the original location and has a corresponding S value greater than the S value of the original location can be considered as meeting the preset condition, and the location corresponding to this condition can be taken as the target location. This appropriately increases the color purity of the pixels, thereby enhancing the corresponding colors and making them appear more vibrant.

[0087] In this embodiment, by determining the target color value of the target position in the color wheel that is a distance from the original position to the target position that meets the preset conditions based on the color value of each pixel in the light effect image, the target color value is used to replace the color value of the corresponding pixel. It can be seen that the color values ​​of all pixels in the light effect image can be appropriately changed as needed, so as to obtain a color change that is more in line with expectations.

[0088] Referring to Figure 6, in a further embodiment, step S1200, determining multiple primary color values ​​in the lighting effect image whose total number of pixels meets preset conditions, and resetting the color value of each pixel based on the primary color value closest to its color value, includes the following steps:

[0089] Step S1210: Determine the total number of pixels for each color value in the lighting effect image, and select the color values ​​whose total number of pixels meets the preset conditions as the main color values;

[0090] For each different color value in the lighting effect image, the number of pixels displaying the same color value is determined as the total number of pixels for that color value. Based on the total number of pixels, all different color values ​​are sorted from highest to lowest, and the top N color values ​​are selected as individual main color values. N can be set as needed. In a recommended embodiment, the LED density in the lighting screen device is determined based on the light source location distribution information. N is set accordingly based on the LED density. It is easy to understand that the higher the LED density, the larger the corresponding N. For example, the LED density of a curtain light is smaller than that of a pixel light. Therefore, the N corresponding to a pixel light is set larger than the N corresponding to a curtain light. Those skilled in the art can further set N as needed based on this disclosure, so that the subsequent image as a whole contains multiple main color values, resulting in a richer visual effect.

[0091] Step S1220: For each pixel, calculate the distance between the pixel's color value and each primary color value, and select the primary color value with the lowest distance value to replace the pixel's color value.

[0092] For each pixel, the Euclidean distance between the pixel's color value and each major color value is calculated as the distance value. For example, if the pixel's color value is R: 246, B: 3, G: 255, and a major color value is R: 255, B: 255, G: 255, the corresponding Euclidean distance is 252.08. Then, the major color value with the lowest distance value is selected, and the pixel's color value is replaced with that major color value.

[0093] In this embodiment, by determining the dominant color value whose total number of pixels in the lighting effect image meets preset conditions, the nearest dominant color corresponding to the color value of each pixel in the lighting effect image is determined and used to replace the color value of the corresponding pixel. It can be seen that this achieves appropriate normalization of the colors in the lighting effect image, thereby reducing color complexity and improving the clarity of the display effect. It also avoids the indistinct color transitions caused by a large number of noise-related colors in the image, making the lighting effect image look more natural.

[0094] Referring to Figure 7, in a further embodiment, step S1300, determining the difference color value that satisfies the preset condition with the average hue value of the lighting effect image, and resetting the color value of the pixels belonging to the predetermined color value in the main content of the lighting effect image according to the difference color value, includes the following steps:

[0095] Step S1310: Determine the color value of the pixel points belonging to the predetermined color value in the main content of the lighting effect image;

[0096] Typically, the main content of a lighting effect image is its foreground content. Therefore, after constructing the lighting effect image, in one embodiment, an open-source pre-trained foreground recognition model can be used to determine the foreground content. When the background of the lighting effect image is transparent, the content with non-zero transparency can be directly identified as the main content. The foreground recognition model can be Mask R-CNN, U-Net, DeepLabv3, etc.

[0097] In another embodiment, when the lighting effect image contains multiple entity objects and the main content is one or more of these entity objects, an open-source pre-trained object detection model can be used to detect all entity objects in the lighting effect image, thereby determining the main content among these entity objects. The object detection model can be SSD, YOLO series, R-CNN family, RetinaNet, CornerNet, etc.

[0098] Traverse the color value of each pixel in the main content of the current lighting effect image, and confirm whether the display effect of the color value is close to black. Specifically, this can be done by calculating the Euclidean distance between the color value and the color value corresponding to black. When the Euclidean distance is less than or equal to a preset threshold, it is confirmed that the color value is close to the color value corresponding to black and belongs to the predetermined color value.

[0099] Step S1320: Calculate the average hue value based on the hue value corresponding to the color value of each pixel in the lighting effect image;

[0100] Taking the RGB color value of a single pixel as an example, the hue value corresponding to that color value is calculated. An example formula is shown below:

[0101] The R, G, and B channel values ​​of the color value of this pixel are normalized respectively (e.g., each value is divided by 255).

[0102]

[0103]

[0104] Where: H is the hue value corresponding to the color value of this pixel.

[0105] The average hue value is obtained by summing the hue values ​​of all pixels in the lighting effect image and then dividing by the number of pixels.

[0106] Step S1330: Determine the difference color value in the difference color range that satisfies the preset condition with the average hue value, and use it to replace the color value of the pixel that belongs to the predetermined color value;

[0107] The color effect corresponding to the difference color range and the color effect corresponding to the average hue value constitute a contrasting color effect as defined in color art. Therefore, a hue value range differing from the average hue value by 120 to 180 can be determined as the difference color range to ensure that the contrasting color effect can be formed. Those skilled in the art can flexibly set the difference color range as needed. Then, a color value represented by HSV is randomly selected from the difference color range as the difference color value, and the HSV color value is converted to an RGB color value as needed. The color values ​​of the pixels belonging to the predetermined color value are then replaced with the difference color value.

[0108] In this embodiment, a difference color value that meets a preset condition is determined based on the average hue value corresponding to the lighting effect image, and this difference color value is used to replace the color value of pixels in the lighting effect image that belong to the predetermined color value. It can be seen that colors belonging to the preset color in the lighting effect image can be replaced with colors that are visually distinct from them, thereby making the originally monotonous or dim lighting effect image more vivid and interesting.

[0109] Please refer to Figure 8. In a further embodiment, step S1100, generating a corresponding lighting effect image based on the lighting effect generation text, includes the following steps:

[0110] Step S1101: Determine the motion type of the lighting effect based on the generated text, and extract the keyword set from the generated text;

[0111] Step S1102: Generate a lighting effect image based on the keyword set and the lighting effect motion type.

[0112] Please refer to Figure 9. In a further embodiment, step S1100, generating a corresponding lighting effect image based on the lighting effect generation text, includes the following steps:

[0113] Step S1103: Determine the style of the lighting effect content and the type of lighting effect movement based on the generated text of the lighting effect, and extract the set of keywords from the generated text of the lighting effect;

[0114] In one embodiment, a style recognition model can be pre-implemented, trained to a convergent state, and learned to determine the style of the lighting effect content in the text generating the lighting effect. Additionally, a motion recognition model can be pre-implemented, trained to a convergent state, and learned to determine the motion type of the lighting effect in the text generating the lighting effect. Using the text generating the lighting effect as input, the style recognition model extracts deep semantic information from the text generating the lighting effect through its text semantic representation layer, and accordingly derives a style feature vector representing this deep semantic information. This style feature vector characterizes the style-related semantic features in the text generating the lighting effect. Then, the classification layer in the style recognition model maps the style feature vector to binary style categories, and accordingly derives the classification probabilities of abstract and concrete styles within the binary style categories. The style category with the highest classification probability is identified as the lighting effect content style of the text generating the lighting effect. A motion recognition model is used to take the text generated by the lighting effect as input. The text semantic representation layer in the motion recognition model extracts the deep semantic information of the text generated by the lighting effect and obtains the motion feature vector that represents the deep semantic information in a vectorized form. The motion feature vector represents the semantic feature information related to the motion state in the text generated by the lighting effect. Then, the classification layer in the motion recognition model maps the motion feature vector to a binary motion category and obtains the classification probability of static motion type and dynamic motion type in the binary motion category. The style category with the highest classification probability is identified as the lighting effect content style of the text generated by the lighting effect.

[0115] The text representation layer in the style recognition model can be a deep learning model suitable for text semantic representation in the NLP field, such as RoBERTa, Transformer Encoder, MPNet, BiLSTM, GPT, etc. The classification layer in the style recognition model can be a fully connected layer, MLP, etc., which can be selected and implemented as needed by those skilled in the art. Similarly, the text representation layer in the motion recognition model can be a deep learning model suitable for text semantic representation in the NLP field, such as RoBERTa, Transformer Encoder, MPNet, BiLSTM, GPT, etc., and the classification layer in the motion recognition model can be a fully connected layer, MLP, etc., which can be selected and implemented as needed by those skilled in the art. The specific training process of the style recognition model and the motion recognition model can be flexibly adapted and implemented by those skilled in the art based on the reasoning process disclosed herein.

[0116] The keyword set in the generated text for the lighting effect includes all keywords describing the visual characteristics of the corresponding lighting effect. Specifically, to extract the keyword set from the generated text, the generated text is first formatted, including converting uppercase to lowercase, removing punctuation, and removing stop words, or any one or more of these methods. Then, the formatted generated text is segmented to obtain a corresponding segmentation sequence. The segmentation algorithm can be Jieba segmentation, n-gram segmentation, WordPiece segmentation, or CRF segmentation. In one embodiment, each segment in the segmentation sequence is matched with keywords in a preset dictionary. If a keyword matching the segment exists in the dictionary, the segment is confirmed as a keyword; otherwise, it is confirmed as not a keyword. Thus, all word units belonging to keywords in the segmentation sequence constitute the keyword set. The dictionary contains multiple keywords related to the description of lighting effects. Furthermore, a text set can be constructed by pre-collecting multiple lighting effect-generated texts. The importance of each word in the text set is determined using the TF-IDF algorithm. Words with importance exceeding a preset threshold are designated as keywords, thus forming the dictionary from all keywords. The preset threshold can be set as needed. The matching can be based on Elasticsearch for exact matching and / or on deep learning for semantic matching. In another embodiment, a vocabulary classification model, such as a Support Vector Machine (SVM) or Random Forest, can be pre-trained. After the model converges, it learns the probability that each word in the input text belongs to a keyword. Therefore, the vocabulary classification model uses the segmented sequence as input to determine the probability that each word in the segmented sequence belongs to a keyword. Words with probabilities exceeding a preset threshold are identified as keywords, and all keywords are combined to form a keyword set. The preset threshold can be set as needed. The specific training process of the vocabulary classification model can be flexibly implemented by those skilled in the art based on the reasoning process disclosed herein.

[0117] Step S1104: When the style of the lighting effect content belongs to the target style, match the keyword set and the lighting effect motion type of the lighting effect image from the lighting effect library;

[0118] The lighting effect library contains multiple pre-set lighting effect images with abstract style content, as well as image formats and lighting effect description text for each image. The image formats include video formats such as GIF, JPG, PNG, and MP4. As an example, a user can manually anticipate their need for abstract style lighting effects, set corresponding lighting effect generation text, and then use the lighting effect image generation method of this application to generate multiple corresponding lighting effect images based on these generation texts. Then, a manual selection process is used to identify the lighting effect images with better visual effects, and the visual characteristics of each image are described to form corresponding lighting effect description text. These images are then stored in the lighting effect library along with their image formats and description texts for later retrieval. Alternatively, users can manually define and directly construct lighting effect images with abstract style content, describe the visual characteristics of each image, and form corresponding lighting effect description texts. These images are then stored in the lighting effect library along with their description texts and image formats.

[0119] The target style is an abstract style. Therefore, when the lighting effect content style is abstract, it means that the lighting effect content style belongs to the target style. In this case, if the lighting effect motion type is static motion, all lighting effect images in JPG or PNG format are retrieved from the lighting effect library. Then, an open-source deep learning model suitable for text semantic representation in the NLP field is used to determine the vectorized representation of the semantics of the keyword set. This deep learning model also determines the vectorized representation of the semantics of each lighting effect description text in the lighting effect library. A vector similarity algorithm is used to calculate the similarity between the vectorized representation of the keyword set's semantics and the vectorized representation of the semantics of each lighting effect description text. The lighting effect image with the highest similarity exceeding a preset threshold is selected, confirming that this lighting effect image is similar to the keyword set and the lighting effect motion. The preset threshold can be set as needed to match the motion type. If the motion type of the light effect is dynamic, all light effect images in GIF or MP4 format are obtained from the light effect library. Then, an open-source deep learning model suitable for text semantic representation in the NLP field is used to determine the vectorized representation of the semantics of the keyword set. The deep learning model also determines the vectorized representation of the semantics of each light effect description text in the light effect library. The similarity between the vectorized representation of the semantics of the keyword set and the vectorized representation of the semantics of each light effect description text is calculated using a vector similarity algorithm. The light effect image with the highest similarity and exceeding the preset threshold is selected to confirm that the light effect image matches the keyword set and the motion type of the light effect. The preset threshold can be set as needed.

[0120] Step S1105: When no lighting effect image is matched from the lighting effect library, generate a lighting effect image based on the keyword set and the lighting effect motion type;

[0121] When none of the lighting effect images in the lighting effect library match the keyword set and the lighting effect motion type, indicating that no lighting effect image was found in the lighting effect library, in one embodiment, if the lighting effect motion type is a static motion type, an open-source deep learning model suitable for text semantic representation in the NLP field is used to determine the text semantic representation of the keyword set. A Gaussian noise matrix image is constructed using a random function as a random noise image. This random noise image and the text semantic representation constitute the initial input data. A preset image generation model is used with the initial input data as input to iteratively optimize the random noise image in the initial input data to obtain the corresponding target latent features. The target latent features are then decoded to reconstruct the lighting effect image. The image format of this lighting effect image can be PNG or JPG. The image generation model is pre-trained to a convergent state, learning the ability to generate corresponding images based on the input text. Stable Diffusion can be selected as the model type.

[0122] In one embodiment, if the light effect motion type is a dynamic motion type, an open-source model based on text to generate multiple image frames can be used to generate image files of multiple corresponding image frames as light effect images according to the keyword set. The image format of the image file composed of the multiple image frames can be any one of video formats such as GIF or MP4. The model can be any one of AnimateDiff, Gen-2, Stable Video Diffusion, Emu Video, etc., based on Stable Diffusion. Those skilled in the art can choose one to implement as needed.

[0123] In this embodiment, firstly, by parsing the generated text of the lighting effect, the style and motion type of the lighting effect content are determined, and the keyword set in the generated text is extracted. This refines the user's specific personalized requirements for the lighting effect content style and motion type, achieving a high degree of consistency with user expectations. Secondly, for cases where the lighting effect content style belongs to the target style, lighting effect images matching the keyword set and motion type are directly generated from the lighting effect library. Considering the uncertainty in the quality of lighting effect images generated for the target style, images that accurately match the user's needs are directly used from the existing lighting effect library. These images are usually pre-designed and optimized, ensuring a certain level of visual appeal and artistic merit, avoiding the possibility of poor image quality due to instant generation, and significantly reducing user confusion and time consumption during the selection process, thus improving the user experience. Thirdly, for cases where no matching lighting effect image is found from the lighting effect library, corresponding lighting effect images are generated based on the keyword set and motion type. This allows for the generation of lighting effect images that meet the user's actual needs based on clearly defined user requirements.

[0124] In a further embodiment, step S1103, determining the style of the lighting effect content and the type of lighting effect movement based on the text generated by the lighting effect, includes the following steps:

[0125] Step S11031: Use a large language model to extract the description of the lighting effects from the generated text;

[0126] The large language model described is suitable for text processing in the field of NLP. It is pre-trained to convergence using an extremely large corpus, acquires the ability to generate human language, and possesses a certain degree of accurate text semantic understanding and logical reasoning ability. The large language model can be selected from OpenAI, Falcon, Chinchilla, PaLM, LLaMA 2, text-embedding-ada-002, etc., which can be chosen by those skilled in the art as needed.

[0127] A preset prompt template is invoked. The prompt template includes a task description and the text to be embedded for generating the lighting effect. Those skilled in the art can refer to the following disclosure to flexibly modify the prompt template. An exemplary prompt template is provided: The task description in the prompt template is: "Filter out numbers and indicative verbs in the following text for generating the lighting effect, and retain the nouns, verbs, and adjectives corresponding to the descriptions of visually perceptible objects, the visual characteristics of the required lighting effect, and the observable human behaviors in the text for generating the lighting effect, thereby deriving the lighting effect description as the final result, which requires no explanation." The text to be embedded for generating the lighting effect is: " <input> $query_input$.

[0128] The generated text of the lighting effect is embedded into the prompt template to obtain the corresponding prompt text. The prompt text is then input into the large language model to obtain the lighting effect description content in the generated text of the lighting effect determined by the large language model.

[0129] Step S11032: Determine the lighting effect content style and lighting effect movement type corresponding to the lighting effect generation text based on the lighting effect description.

[0130] The first prompt template based on Few-shot learning is invoked. The first prompt template includes a task description, an example, and a description of the lighting effect to be embedded. Those skilled in the art can flexibly modify the first prompt template with reference to the following disclosure. An exemplary example of the first prompt template is as follows: The task description in the first prompt template is: "Determine whether the user wants an 'abstract style' or a 'concrete style' by specifying the structure and providing some examples."

[0131] 1. Determine based on keywords.

[0132] 2. Directly give the final result without any explanation.

[0133] Example: "<example>{"input": "Relaxing and pleasant lighting effects", "output": "Abstract style"},{"input": "Complex and beautiful", "output": "Abstract style"},{"input": "Surprising lighting colors", "output": "Abstract style"},{"input": "Comfortable ambient light", "output": "Abstract style"}, {"input": "Approaching train lighting effects", "output": "Figurative style"},{"input": "Lighting effects with floating turtle patterns", "output": "Figurative style"},{"input": "Lighting effects with strong rhythm", "output": "Figurative style"}]< / example>"

[0134] The content of the lighting effect description to be embedded: "<input>$The input content to be judged$< / input>"

[0135] Embed the content of the lighting effect description into the first prompt template to obtain the corresponding prompt text, and input the prompt text into the large language model to obtain the style of the lighting effect content of the lighting effect generation text determined by the large language model.

[0136] In addition, call a preset second prompt template based on Few-shot learning. The second prompt template includes a task description, examples, and the content of the lighting effect description to be embedded. Those skilled in the art can refer to the following disclosure to flexibly set the second prompt template. A demonstrative example of the second prompt template: The task description in the second prompt template: "Judge whether the user wants'static motion type' or 'dynamic motion type' by specifying the structure and providing some examples.

[0137] 1. Judge according to the keywords.

[0138] 2. Directly give the final result without any explanation.

[0139] Example: "<example>{"input": "Relaxing and pleasant lighting effects", "output": "Static motion type"},{"input": "Complex and beautiful", "output": "Static motion type"},{"input": "Surprising lighting colors", "output": "Static motion type"},{"input": "Comfortable ambient light", "output": "Static motion type"}, {"input": "Approaching train lighting effects", "output": "Dynamic motion type"},{"input": "Floating turtle pattern lighting effects", "output": "Dynamic motion type"},{"input": "Strongly rhythmic lighting effects", "output": "Dynamic motion type"}]< / example>"

[0140] The content description of the lighting effect to be embedded: "<input>$The input content to be judged$< / input>"

[0141] Embed the content description of the lighting effect into the second prompt template to obtain the corresponding prompt text, and input the prompt text into the large language model to obtain the lighting effect motion type of the lighting effect generation text determined by the large language model.

[0142] In this embodiment, by using the large language model to extract the content description of the lighting effect in the lighting effect generation text, accordingly, the lighting effect content style and lighting effect motion type corresponding to the lighting effect generation text are determined, which can exclude the redundant information in the lighting effect generation text that is irrelevant to confirming its lighting effect content style and lighting effect motion type, so as to ensure the accuracy and reliability of the determined lighting effect content style and lighting effect motion type.

[0143] In a further embodiment, before determining the lighting effect content style and lighting effect motion type according to the lighting effect generation text in step S1103, the following steps are included:

[0144] Step S1106: Obtain the description text provided by the user, confirm whether there is an intention to generate a lighting effect in the description text, and when there is, use the description text as the lighting effect generation text;

[0145] To display the desired lighting effects on the light screen device, the user can provide corresponding descriptive text. However, given that the user's description of the lighting effect generation intention may not be clear enough, i.e., the description text may not contain the intention to generate the lighting effect, thus preventing the subsequent generation of the corresponding lighting effect image, a preset intention recognition model is first invoked on the description text. The intention recognition model has been pre-trained to a convergent state and has learned the ability to recognize whether the input text contains the intention to generate the lighting effect. Since the training process of the intention recognition model is known in the art, those skilled in the art can flexibly and adapt the training of the intention recognition model according to the forward reasoning process of the intention recognition model disclosed later, so that the intention recognition model trained to convergence has the aforementioned ability. In one embodiment, the intent recognition model is implemented using BERT. A word segmentation algorithm is used to segment the descriptive text, obtaining a word segmentation sequence. A [CLS] identifier is added at the beginning of the word segmentation sequence, and a [SEP] identifier is added at the end. The word segmentation sequence is then input into the intent recognition model. The WordPiece embedding layer in the intent recognition model determines the input embedding vector for each identifier and word in the word segmentation sequence. This input embedding vector is then input into a multi-layered stacked Transformer encoder to obtain the text feature vector for each identifier and word in the word segmentation sequence output by the last Transformer encoder layer. A feedforward neural network layer performs a linear transformation on the text feature vector with the [CLS] identifier, and then a Softmax layer derives a binary probability distribution. This binary probability distribution includes the probability of a first category and the probability of a second category. The first category represents the input text's intent to generate lighting effects, and the second category represents the input text's intent not to generate lighting effects. The category corresponding to the highest probability in the binary probability distribution is determined. When this category is the first category, it indicates that the descriptive text has the intent to generate lighting effects, and in this case, the descriptive text is used as the text intended to generate lighting effects.

[0146] Step S1107: When there is no intention to generate lighting effects, send multiple preset lighting effect images and their effect descriptions from the lighting effect library to the user;

[0147] When the category with the highest probability in the binary probability distribution is the second category, it means that the description text does not intend to generate lighting effects. At this time, multiple preset lighting effect images are obtained from the lighting effect library, and the lighting effect description text of each lighting effect image is obtained. These lighting effect images and their lighting effect description texts are sent to the user. The multiple lighting effect images can be lighting effect images that are judged by the user to have a relatively high visual aesthetics in the lighting effect library, or lighting effect images can be randomly selected from all lighting effect images in the lighting effect library. The specific number of these lighting effect images can be set as needed.

[0148] Step S1108: In response to the selection event of any one of the multiple lighting effect images, recall the lighting effect image in the lighting effect library that matches the target lighting effect image.

[0149] In a recommended embodiment, a pre-constructed lighting effect playback interface is provided to the user. For the multiple lighting effect images, the user can preview any one of them in this interface. The interface displays a description of the lighting effect of the previewed image and loads and plays a video of the corresponding lighting effect displayed on the lighting screen device. This allows the user to intuitively understand the visual effect of the image on the screen and to review the description, thus enhancing their comprehension of the visual effect. The lighting effect playback interface can be flexibly implemented by those skilled in the art. Furthermore, for each lighting effect image in the lighting effect library, those skilled in the art can pre-record a video of the image displaying its corresponding lighting effect on the lighting screen device and store these videos associated with the lighting effect images in the lighting effect library for later retrieval. Thus, the user can preview any of the multiple lighting effect images, select any one as needed, and then use the selected image as the target lighting effect image on the lighting effect playback interface. In response to the selection event, the system retrieves the lighting effect image corresponding to the target lighting effect image from the lighting effect library.

[0150] In this embodiment, by clearly identifying whether the user-provided descriptive text indicates an intention to generate lighting effects, descriptive text with such an intention is used as the generated lighting effect text. This avoids using descriptive text without such an intention to generate lighting effects, which could lead to poor generation results or failure, wasting user waiting time and / or reducing user experience. Furthermore, when the descriptive text lacks an intention to generate lighting effects, multiple lighting effect images and their descriptions are provided to the user. The system then retrieves the target lighting effect image from the user's selection and recalls the corresponding image from the lighting effect library. This user-friendly design allows for timely selection of readily available lighting effect images when the user's current intention to generate lighting effects is not accurate enough, significantly reducing the latency in determining the lighting effect image. This enables users to quickly see the visual effect of the desired lighting effect displayed on the lighting screen device, improving user experience.

[0151] In a further embodiment, step S1103, extracting the keyword set from the generated text of the lighting effect, includes the following steps:

[0152] Step S11033: Embed the generated text of the lighting effect into a preset prompt template to obtain the prompt text, and use the prompt text to guide the large language model to determine the set of keywords in the generated text of the lighting effect;

[0153] A preset prompt template is invoked. The prompt template includes a task description and the text to be embedded for generating the lighting effect. Those skilled in the art can refer to the following disclosure to flexibly modify the prompt template. An example prompt template is provided: The task description in the prompt template is: "Extract all keywords in the text to generate the lighting effect according to the following rules, and determine the importance of each keyword relative to other keywords."

[0154] 1. Each keyword should contain at most one noun to ensure indirectness and focus.

[0155] 2. If the keyword contains a noun, an article should be added before the noun to help clarify the reference and enhance the naturalness of the language.

[0156] 3. Prioritize the use of proper nouns (such as landmarks and specific names) as keywords, as they are unique and easily recognizable.

[0157] 4. Each keyword should contain a maximum of one adjective to maintain the accuracy of the description without overcomplicating it.

[0158] 5. Based on the importance of each keyword in the generated text for the lighting effect, all keywords are sorted to ensure that more important keywords are ranked first and given priority when used to generate the lighting effect image.

[0159] 6. Prioritize using nouns describing real objects (excluding objects like lighting equipment) as keywords to ensure that subsequent generation of practical and relevant lighting effect images is used,” the lighting effect generation text to be embedded: <input> $query_input$.

[0160] Step S11034: Using the large language model, determine each keyword and its importance in the light effect generation text based on the prompt text, and arrange the keywords in order of importance to construct a keyword set.

[0161] The prompt text is input into a large language model to obtain all the keywords in the light effect generation text determined by the large language model, as well as the importance of each keyword relative to other keywords. Then, all keywords are sorted in descending order of importance, and the sorted keywords constitute the keyword set in the light effect generation text.

[0162] In this embodiment, a large language model guided by prompt text is used to determine all keywords in the light effect generation text, as well as the importance of each keyword relative to other keywords. Then, the keywords are arranged in order of importance to construct the keyword set in the light effect generation text. It can be seen that the large language model guided by prompt text, which is highly interpretable and editable, can quickly and accurately extract the required keyword set. Moreover, it can ensure that the keywords with relatively high importance in the keyword set are ranked higher, so that they are given priority when generating light effect images. This ensures the generation of practical and relevant light effect images, meets user needs, and improves user experience.

[0163] In a further embodiment, step S1105, when no lighting effect image is matched from the lighting effect library, generates a lighting effect image based on the keyword set and the lighting effect motion type, including the following steps:

[0164] Step S11051: When the light effect motion type belongs to the static motion type, the text encoding module in the preset image-text matching model is used to determine the text semantic representation of the keyword set, and it is combined with the random noise image to obtain the initial input data.

[0165] The image-text matching model is a CLIP model that has been pre-trained to a convergent state. It learns to determine the vector representations of the input image and text that are respectively in the same semantic space, and determines the similarity between the image and the text based on the similarity between these two vector representations.

[0166] Therefore, the text encoding module in the image-text matching model can be used as input to extract the deep semantic information of the keyword set and derive a vectorized text semantic representation of this deep semantic information. Furthermore, an image of a Gaussian noise matrix is ​​constructed using a random function as a random noise image. Combining the text semantic representation and the random noise image, the initial input data is obtained.

[0167] Step S11052: Iteratively optimize the random noise image in the initial input data using the image optimization module in the preset image generation model to obtain the target hidden features;

[0168] The image generation model employs Stable Diffusion, which is pre-trained to convergence and learns the ability to generate corresponding images based on input text.

[0169] The image generation model employs an image optimization module that iteratively optimizes the image. During this process, the U-Net network continuously optimizes the generation process, predicting noise in the random noise image from the initial input data, and simultaneously injecting textual semantic information based on the textual semantic representation in the initial input data. Furthermore, the Schedule algorithm optimizes the noise predicted by U-Net at each iteration. This optimization includes dynamically adjusting the predicted noise and controlling its intensity, thereby coordinating the progress of the generation process. Finally, when the U-Net has iterated a certain number of times, such as 50 or 100 times, the pure noise in the random noise image is removed. The image semantic information of this image is then matched with the textual semantic representation, thus deriving the corresponding image in the latent space as the target latent feature.

[0170] Step S11053: The image decoder in the image generation model reconstructs the lighting effect image from the target's hidden features.

[0171] The image encoder is a VAE (Variational Auto-Encoder). This image encoder converts the target's latent features from the latent space into the original pixel space, generating a corresponding image as the lighting effect image, in PNG or JPG format.

[0172] This embodiment discloses the process of generating a corresponding light effect image based on the keyword set of the light effect generating text when the light effect motion type of the light effect generating text is a static motion type. This ensures that the light effect image is closely related to the keyword set, meets user needs, and improves user experience.

[0173] In a further embodiment, step S1105, when no lighting effect image is matched from the lighting effect library, generates a lighting effect image based on the keyword set and the lighting effect motion type, including the following steps:

[0174] Step S11054: When the lighting effect motion type belongs to the dynamic motion type, a preset multi-image frame generation model is used to generate multiple image frames according to the keyword set;

[0175] The light effect motion type is a dynamic motion type, which can be generated by an open-source text-based multi-image-frame generation model based on the keyword set. The image format of the light effect image can be any video format such as GIF or MP4. The model can be any one of AnimateDiff, Gen-2, Stable Video Diffusion, Emu Video, etc., based on Stable Diffusion. Those skilled in the art can choose one to implement as needed.

[0176] Step S11055: The lighting effect image is composed of the multiple image frames.

[0177] By constructing the lighting effect image from the multiple consecutive image frames, it is easy to understand that when the corresponding lighting effect is played based on the lighting effect image, the corresponding dynamic effect can be presented.

[0178] In this embodiment, when the light effect motion type is dynamic, a multi-image frame generation model is used to generate multiple image frames based on a keyword set to form a light effect image, which can serve the need to play dynamic light effects on the light screen device and meet the personalized visual experience.

[0179] Please refer to Figure 10. In a further embodiment, after step S1100, which generates the corresponding lighting effect image based on the lighting effect generation text, the following steps are included:

[0180] Step S2100: Determine whether the transparency of each pixel in the lighting effect image meets the preset conditions;

[0181] The transparency of each pixel in the lighting effect image is obtained, and the transparency is usually represented by the value of the alpha channel. If the transparency of a pixel is 0, it means that the display effect of the pixel is completely transparent from a visual perspective, thus confirming that the pixel meets the preset condition; if the transparency of a pixel is greater than 0, it means that the display effect of the pixel is not completely transparent from a visual perspective and has a certain color expression, thus determining that the pixel does not meet the preset condition.

[0182] Step S2110: When the transparency of a pixel meets the preset conditions, reset the color value of the pixel with the preset color value.

[0183] When the transparency of a pixel meets the preset conditions, the color value of that pixel is set to the preset color value. The preset color value is recommended to be the color value corresponding to black (R: 0, G: 0, B: 0). It can also be set by those skilled in the art as needed. For example, in a bright environment, it may be necessary to select a darker color value to enhance the visibility of the image; while in a darker environment, it may be necessary to select a lighter color value to avoid excessive visual fatigue.

[0184] In this embodiment, by identifying the pixels in the lighting effect image whose transparency meets the preset conditions, and resetting the color values ​​of these pixels to the preset color values, it is possible to ensure that the lighting effect corresponding to the lighting effect image can be played accurately in the future, and to a certain extent, control the contrast of the lighting effect image.

[0185] In a further embodiment, step S1400, reconstructing the lighting effect image into a target lighting effect image corresponding to the target resolution, and controlling the light screen device to play the corresponding lighting effect according to the target lighting effect image, includes the following steps:

[0186] Step S1410: Determine whether the resolution of the lighting effect image meets the preset conditions based on the light source position distribution information of the light screen device. If it does, reconstruct the lighting effect image into a target lighting effect image that matches the light source position distribution information.

[0187] Step S1420: Generate lighting effect control data matching the lighting screen device based on the target lighting effect image;

[0188] When the target lighting effect image is in any video format such as GIF or MP4, each image frame in the target lighting effect image can be extracted and converted into corresponding lighting effect control data, which is then transmitted to the lighting screen device to control the lighting screen device to play the corresponding lighting effect. When the target lighting effect image is in PNG or JPG format, the target lighting effect image can be directly converted into corresponding lighting effect control data and transmitted to the lighting screen device to control the lighting screen device to play the corresponding lighting effect.

[0189] Since the resolution of the target lighting effect image is completely consistent with the display area / resolution of the light screen device, in this case, the resolution of the target lighting effect image corresponds one-to-one with the light-emitting units in the display area. The control data of the corresponding light-emitting unit can be directly generated according to the color of each pixel in the target lighting effect image. Thus, lighting effect control data is generated between the target lighting effect image and the display area in a one-to-one partition mapping relationship.

[0190] Step S1430: Control the light screen device to play the corresponding light effects according to the light effect control data.

[0191] If the target lighting effect image is in any video format such as GIF or MP4, and multiple lighting effect control data are generated accordingly, the controller can trigger the transmission of lighting effect control data to the light screen device at intervals according to a preset playback time slot or the frame rate of the target lighting effect image, thereby transmitting the lighting effect control data corresponding to each image frame in the target lighting effect image to the light screen device in turn. If the target lighting effect image is in PNG or JPG format, the corresponding lighting effect control data can be directly transmitted to the light screen device.

[0192] When the light screen device receives lighting effect control data, it transmits it to each of the light-emitting units according to the data communication protocol it follows with each light-emitting unit, such as a serial communication protocol. Each light-emitting unit, upon receiving the lighting effect control data, extracts or intercepts the control data corresponding to its own function, controls its own light-emitting element to emit the corresponding light, and forwards the lighting effect control data to other light-emitting units that have not yet received it. Each light-emitting unit receives, parses, responds with light emission, and forwards the lighting effect control data according to its inherent business logic. The entire light screen device can then present the visual effect of the target lighting effect image corresponding to the lighting effect control data.

[0193] It's easy to understand that when a target lighting effect image contains multiple image frames, the corresponding lighting effects of each image frame are presented in turn on the display screen of the lighting device, forming a constantly changing overall lighting effect. Since these image frames originate from the same set of keywords, i.e., the same theme, they can usually present a thematic overall lighting effect on the lighting screen device. It's easy to understand that such an overall lighting effect has a consistent and dynamic style, creating a more immersive experience.

[0194] This embodiment discloses the process of playing the lighting effect corresponding to the target lighting effect image on the light screen device, ensuring the accuracy and reliability of the lighting effect playback, presenting the lighting effect required by the user, and protecting the user experience.

[0195] Referring to Figure 11, in a further embodiment, step S1400, reconstructing the lighting effect image into a target lighting effect image corresponding to the target resolution, includes the following steps:

[0196] Step S1401: Divide the lighting effect image into multiple regions corresponding to the target resolution;

[0197] The lighting effect image is divided into multiple regions, each region's size corresponding to a single pixel at the target resolution. Specifically, the size of each region can be determined by dividing the width and height of the lighting effect image by the width and height of the target resolution, respectively. The target resolution can be determined based on the resolution of the lighting screen device; it is sufficient to ensure that the target resolution matches the resolution of the lighting effect device. For example, the target resolution can be set to be the same as the resolution of the lighting screen device, or it can be set to 1 / N of the resolution of the lighting screen device, where N can be set as needed.

[0198] Step S1402: For each region, select the color value with the highest total number of pixels in that region as the core color value for that region;

[0199] For each region, downsampling is performed on that region. Specifically, maximum pooling is performed on the color values ​​of all pixels in that region to obtain the region with the highest total number of pixels, i.e., the region with the most pixels displaying the same color value. The corresponding color value is then used as the core color value for that region.

[0200] Step S1403: Reconstruct the target lighting effect image corresponding to the target resolution based on the core color value of each region.

[0201] By iterating through each region, the core color value of that region is used as the color value of the pixel in the target lighting effect image corresponding to the target resolution. Thus, the color values ​​of all pixels in the target lighting effect image are obtained, thereby deriving the target lighting effect image.

[0202] This embodiment discloses the process of constructing a target lighting effect image corresponding to the target resolution based on the lighting effect image, which can appropriately adjust the lighting effect image so that the corresponding target lighting effect image can be correctly and completely displayed on the lighting screen device.

[0203] Please refer to Figure 12. A lighting effect display device provided to meet one of the purposes of this application is a functional embodiment of the lighting effect display method of this application. On another aspect, this lighting effect display device, provided to meet one of the purposes of this application, includes a first color reset module 1100, a second color reset module 1200, a third color reset module 1300, and a lighting effect playback module 1400. The first color reset module 1100 is used to generate a corresponding lighting effect image based on the lighting effect generation text, determine the target position corresponding to the original position of the color value of each pixel in the lighting effect image on the color wheel, and reset the color of each pixel according to the target color value corresponding to the target position. The light effect image is configured with a color value; a second color reset module 1200, which determines multiple primary color values ​​that satisfy preset conditions for the total number of pixels in the light effect image, and resets the color value of each pixel based on the primary color value closest to its color value; a third color reset module 1300, which determines the difference color value that satisfies preset conditions with the average hue value of the light effect image, and resets the color value of pixels belonging to a predetermined color value in the main content of the light effect image based on the difference color value; and a light effect playback module 1400, which reconstructs the light effect image into a target light effect image corresponding to the target resolution, and controls the light screen device to play the corresponding light effect based on the target light effect image, so as to display the target light effect image through the light screen device.

[0204] In some embodiments, referring to FIG13, the lighting effect display device further includes a text parsing module 1500, an image matching module 1600, an image generation module 1700, and a lighting effect playback module 1400. The text parsing module 1500 is used to determine the lighting effect content style and lighting effect movement type based on the lighting effect generated text, and extract a set of keywords from the lighting effect generated text. The image matching module 1600 is used to match the lighting effect image with the keyword set and the lighting effect movement type from the lighting effect library when the lighting effect content style belongs to the target style. The image generation module 1700 is used to generate a lighting effect image based on the keyword set and the lighting effect movement type when no lighting effect image is matched from the lighting effect library. The lighting effect playback module 1400 is used to control the lighting screen device to play the corresponding lighting effect based on the lighting effect image, so as to display the lighting effect image through the lighting screen device.

[0205] To address the aforementioned technical problems, this application also provides a computer device. Figure 14 shows a schematic diagram of the internal structure of the computer device. The computer device includes a processor, a computer-readable storage medium, a memory, and a network interface connected via a system bus. The computer-readable storage medium stores an operating system, a database, and computer-readable instructions. The database may store a sequence of control information. When the computer-readable instructions are executed by the processor, the processor can implement a lighting effect display method. The processor of the computer device provides 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 lighting effect display method of this application. The network interface of the computer device is used for communication with a terminal. Those skilled in the art will understand that the structure shown in Figure 14 is merely a block diagram of a portion of the structure related to the solution of this application and does not constitute a limitation on the computer device to which the solution of this application is applied. A specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0206] In this embodiment, the processor executes the specific functions of each module and its sub-modules shown in Figures 12-13, and the memory stores the program code and various types of data required to execute the aforementioned modules or sub-modules. The network interface is used for data transmission between the user terminal and the server. In this embodiment, the memory stores the program code and data required to execute all modules / sub-modules in the lighting effect display device of this application, and the server can call the server's program code and data to execute the functions of all sub-modules.

[0207] This application also provides a storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the lighting effect display method of any embodiment of this application.

[0208] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

Claims

1. A method for displaying lighting effects, characterized in that, Includes the following steps: Generate a corresponding lighting effect image based on the lighting effect text, determine the target position corresponding to the original position of the color value of each pixel in the lighting effect image on the color wheel, and reset the color value of each pixel according to the target color value of the target position corresponding to the target position. Determine multiple primary color values ​​in the lighting effect image that satisfy preset conditions for the total number of pixels, and reset the color value of each pixel based on the primary color value closest to its color value. Determine the difference color value that satisfies the preset condition with the average hue value of the lighting effect image, and reset the color value of the pixel points belonging to the predetermined color value in the main content of the lighting effect image according to the difference color value; The lighting effect image is reconstructed into a target lighting effect image corresponding to the target resolution. The corresponding lighting effect is then played by the light screen device based on the target lighting effect image, so as to display the target lighting effect image through the light screen device.

2. The lighting effect display method according to claim 1, characterized in that, Determine the target position corresponding to the original position of the color value of each pixel in the lighting effect image on the color wheel, and reset the color value of each pixel according to the target color value of the target position, including the following steps: For each pixel in the lighting effect image, determine the region within the color wheel to which the original position of the pixel's color value belongs on the color wheel; The target color value of the target position in the inner region of the ring, which is at a distance from the original position that meets a preset condition, is determined and used to replace the color value of the pixel.

3. The lighting effect display method according to claim 1, characterized in that, Determine multiple primary color values ​​in the lighting effect image whose total number of pixels meets preset conditions, and reset the color value of each pixel based on the primary color value closest to its current color value. This includes the following steps: Determine the total number of pixels for each color value in the lighting effect image, and select the color values ​​whose total number of pixels meets the preset conditions as the main color values; For each pixel, calculate the distance between the pixel's color value and each primary color value, and select the primary color value with the lowest distance value to replace the pixel's color value.

4. The lighting effect display method according to claim 1, characterized in that, Determine the color difference value that satisfies a preset condition with the average hue value of the lighting effect image, and reset the color value of the pixels belonging to the predetermined color value in the main content of the lighting effect image according to the color difference value, including the following steps: Determine the color value of the pixels in the main content of the lighting effect image that belong to a predetermined color value; The average hue value is calculated based on the hue value corresponding to the color value of each pixel in the lighting effect image; Determine the difference color value within the difference color range that satisfies the preset condition with the average hue value, and use it to replace the color value of the pixel that belongs to the predetermined color value.

5. The lighting effect display method according to claim 1, characterized in that, After generating the corresponding lighting effect image based on the lighting effect text, the following steps are included: Determine whether the transparency of each pixel in the lighting effect image meets a preset condition; When the transparency of a pixel meets the preset conditions, the color value of that pixel is reset with the preset color value.

6. The lighting effect display method according to claim 1, characterized in that, Reconstructing the lighting effect image into a target lighting effect image corresponding to the target resolution includes the following steps: The lighting effect image is divided into multiple regions corresponding to the target resolution; For each region, the color value with the highest total number of pixels in that region is selected as the core color value for that region; The target lighting effect image corresponding to the target resolution is reconstructed based on the core color value of each region.

7. The lighting effect display method according to claim 1, characterized in that, Generate corresponding lighting effect images based on the lighting effect text, including the following steps: The type of light effect motion is determined based on the generated text of the light effect, and the set of keywords in the generated text of the light effect is extracted; A lighting effect image is generated based on the keyword set and the lighting effect motion type.

8. The lighting effect display method according to claim 1, characterized in that, Generate corresponding lighting effect images based on the lighting effect text, including the following steps: The style and motion type of the lighting effect content are determined based on the generated text, and the set of keywords in the generated text is extracted. When the style of the lighting effect content belongs to the target style, the lighting effect image of the keyword set and the lighting effect motion type is matched from the lighting effect library; When no lighting effect image is matched from the lighting effect library, a lighting effect image is generated based on the keyword set and the lighting effect motion type.

9. The lighting effect display method according to claim 8, characterized in that, The lighting effect content style and motion type are determined based on the generated text, including the following steps: A large language model is used to extract the description of the lighting effects from the generated text. Based on the description of the lighting effect, determine the lighting effect content style and lighting effect movement type corresponding to the generated text.

10. The lighting effect display method according to claim 8, characterized in that, Before determining the style and motion type of the lighting effects based on the generated text, the following steps are included: Obtain the description text provided by the user, confirm whether the description text contains the intention to generate lighting effects, and if so, use the description text as the text to generate lighting effects; When there is no intention to generate lighting effects, multiple preset lighting effect images and their effect descriptions from the lighting effect library are sent to the user. In response to the selection event of any one of the multiple lighting effect images, recall the lighting effect image in the lighting effect library that matches the target lighting effect image.

11. The lighting effect display method according to claim 7 or 8, characterized in that, Extracting the keyword set from the generated text of the lighting effect includes the following steps: The lighting effect generated text is embedded into a preset prompt template to obtain the prompt text. This prompt text is then used to guide the large language model to determine the set of keywords in the lighting effect generated text. The large language model is used to determine the keywords and their importance in the generated text of the lighting effect based on the prompt text, and the keywords are arranged in order of importance to construct a keyword set.

12. The lighting effect display method according to claim 7 or 8, characterized in that, Based on the keyword set and the lighting effect motion type, a lighting effect image is generated, including the following steps: When the light effect motion type is a static motion type, the text encoding module in the preset image-text matching model is used to determine the text semantic representation of the keyword set, and it is combined with the random noise image to obtain the initial input data; The image optimization module in the preset image generation model is used to iteratively optimize the random noise image in the initial input data to obtain the target hidden features; The image decoder in the image generation model reconstructs the lighting effect image from the target's hidden features.

13. The lighting effect display method according to claim 7 or 8, characterized in that, Based on the keyword set and the lighting effect motion type, a lighting effect image is generated, including the following steps: When the lighting effect motion type is a dynamic motion type, a preset multi-image frame generation model is used to generate multiple image frames based on the keyword set. The lighting effect image is composed of the multiple image frames.

14. The lighting effect display method according to claim 8, characterized in that, The process of reconstructing the lighting effect image into a target lighting effect image corresponding to the target resolution, and controlling the lighting screen device to play the corresponding lighting effect based on the target lighting effect image, includes the following steps: Based on the light source position distribution information of the light screen device, determine whether the resolution of the light effect image meets the preset conditions. If it does, reconstruct the light effect image into a target light effect image that matches the light source position distribution information. Generate lighting effect control data matching the lighting screen device based on the target lighting effect image; The lighting effect control data is used to control the lighting screen device to play the corresponding lighting effects.

15. A lighting effect display device, characterized in that, include: The first color reset module is used to generate a corresponding light effect image based on the light effect generation text, determine the target position corresponding to the original position of the color value of each pixel in the light effect image on the color wheel, and reset the color value of the pixel according to the target color value of the target position corresponding to the target position of each pixel. The second color reset module is used to determine multiple main color values ​​in the lighting effect image where the total number of pixels meets preset conditions, and reset the color value of each pixel according to the main color value closest to the color value of each pixel. The third color reset module is used to determine the difference color value that meets the preset condition with the average hue value of the light effect image, and reset the color value of the pixel points belonging to the predetermined color value in the main content of the light effect image according to the difference color value. The lighting effect playback module is used to reconstruct the lighting effect image into a target lighting effect image corresponding to the target resolution, and control the lighting screen device to play the corresponding lighting effect according to the target lighting effect image, so as to display the target lighting effect image through the lighting screen device.

16. The lighting effect display device according to claim 15, characterized in that, include: The text parsing module is used to determine the style and motion type of the lighting effect content based on the generated text, and to extract the set of keywords from the generated text. The image matching module is used to match the keyword set and the light effect motion type of the light effect image from the light effect library when the light effect content style belongs to the target style; An image generation module is used to generate a lighting effect image based on the keyword set and the lighting effect motion type when no lighting effect image is matched from the lighting effect library. The lighting effect playback module is used to control the lighting screen device to play corresponding lighting effects according to the lighting effect image, so as to display the lighting effect image through the lighting screen device.

17. A computer device comprising a central processing unit and a memory, characterized in that, The central processing unit is used to invoke and run a computer program stored in the memory to perform the steps of the method as described in any one of claims 1 to 14.

18. A computer-readable storage medium, characterized in that, It stores, in the form of computer-readable instructions, a computer program implemented according to any one of claims 1 to 14, which, when invoked by a computer, executes the steps included in the corresponding method.

Images