Atmosphere lamp, lamp effect control method and device thereof and medium

Abstract

The invention relates to an atmosphere lamp, a lamp effect control method and device thereof and a medium. The method comprises the steps that music introduction information of target music is acquired; determining a target color set for generating light effect control information according to image information in the music introduction information; according to text information in the music introduction information, matching a target lamp effect template used for generating lamp effect control information from a lamp effect template library; and sleeving the target color set into the target lamp effect template to obtain lamp effect control information, and controlling the atmosphere lamp to play a corresponding lamp effect according to the lamp effect control information. According to the method, the image and text information of the music are efficiently fused, the overall feeling of the lamp effect and the music is accurately matched, the limited computing power of an embedded chip is adapted, smooth playing of the lamp effect is ensured, and high-cost-performance and high-quality atmosphere lighting experience is provided for a user.

Description

Technical Field

[0001] The present application relates to the field of lighting effect control technology, and in particular to an atmosphere lighting fixture and a lighting effect control method, device, and medium thereof. Background Art

[0002] In applications where voice-activated lighting effects are generated, traditional technologies typically extract rhythmic information from music to control lighting effects. For example, stage and automotive lighting systems, due to their advanced hardware, are capable of handling the complex processing of audio data. These systems can analyze drum beats in audio data in real time to generate lighting effects that match the rhythm of the music, creating a strong visual impact and immersive experience for the audience. However, these technical solutions are not fully applicable to ambient lighting in everyday home settings.

[0003] On the one hand, traditional technology tends to rely on melodic information when linking music to lighting effects. While this approach can convey the real-time feeling conveyed by the music, it has certain limitations. Melodic information can reflect the emotion and atmosphere of the music at a specific moment, but it may not accurately reflect the inherent overall feeling of the music itself, which is the effect the songwriter truly intended to convey. Therefore, when generating lighting effects, traditional technology often fails to fully reflect the overall style and emotion of the music, resulting in an inaccurate match between lighting effects and music, and failing to provide users with an optimal visual and auditory experience.

[0004] On the other hand, the atmosphere lamps of the present application are usually used in daily life and often appear in home scenes. In such scenarios, product economy is a key constraint. Due to product cost considerations, such atmosphere lamps usually use embedded chips to implement lighting effect control. The computing power of embedded chips is relatively limited, and complex traditional technical solutions cannot be directly applied. If a technical solution that requires real-time analysis of audio data is forcibly implanted in these lamps, it will result in a large amount of computing overhead, causing the lamps to freeze during the lighting effect playback process, affecting the user experience. In addition, atmosphere lamps are usually composed of a large number of lamp beads, and their embedded chips need to adapt to the requirements of high frame rates, generating a large amount of lamp bead brightness control data per second, which further limits their computing power. Therefore, the application of traditional technical solutions in home scenes is significantly limited, and they cannot fully realize their potential to enhance the atmosphere and enhance the user experience.

[0005] In summary, existing technologies face two major technical challenges when applied to ambient lighting in home settings: First, traditional technologies rely solely on melody information, failing to accurately reflect the overall feel of the music, resulting in an inaccurate match between lighting effects and music; second, the limited computing power of embedded chips prevents them from processing complex audio data, leading to choppy lighting effects. These issues limit the effectiveness of ambient lighting in home settings and hinder its full potential to enhance ambiance and user experience. Summary of the Invention

[0006] The primary purpose of the present application is to solve at least one of the above problems and to provide an ambient lighting fixture and a lighting effect control method, device, and medium thereof.

[0007] In order to meet the various objectives of this application, this application adopts the following technical solutions: A method for controlling lighting effects of an ambient lighting fixture provided to meet one of the purposes of this application includes the following steps: Obtain music introduction information of the target music; determining a target color set for generating lighting effect control information based on the image information in the music introduction information; According to the text information in the music introduction information, matching a target lighting effect template for generating the lighting effect control information from a lighting effect template library; The target color set is inserted into the target lighting effect template to obtain the lighting effect control information, and the atmosphere lighting fixture is controlled to play the corresponding lighting effect according to the lighting effect control information.

[0008] An ambient lighting fixture lighting effect control device is proposed to meet one of the objectives of this application, and includes: An information acquisition module configured to acquire music introduction information of a target music piece; a color matching determination module configured to determine a target color set for generating lighting effect control information based on image information in the music introduction information; a template matching module configured to match a target lighting effect template for generating the lighting effect control information from a lighting effect template library based on the text information in the music introduction information; The lighting effect control module is configured to insert the target color set into the target lighting effect template to obtain the lighting effect control information, and control the atmosphere lighting to play the corresponding lighting effect according to the lighting effect control information.

[0009] On the other hand, an atmosphere lighting fixture provided to meet one of the purposes of the present application includes a controller and at least one lighting fixture unit, the controller is communicatively connected to the lighting fixture unit, and the controller is used to execute the steps of the atmosphere lighting fixture lighting effect control method to control the lighting fixture unit to display lighting effects.

[0010] On the other hand, a computer-readable storage medium is provided to meet another purpose of the present application, which stores a computer program implemented according to the atmosphere lighting effect control method in the form of computer-readable instructions. When the computer program is called and executed by the computer, the steps included in the corresponding method are executed.

[0011] This application effectively addresses the challenges faced by ambient lighting in home settings through innovative technical solutions, demonstrating significant benefits and technical advantages. First, this application obtains music description information for the target music, including both image and text information, such as album cover, song title, lyrics, and genre description, comprehensively capturing the music's characteristics. This information collaboratively defines the target color set and target lighting effect template for the lighting effect, generating lighting effect control information that accurately matches and conveys the overall feel of the music, breaking through the limitations of traditional technologies and providing users with a personalized visual experience. Second, this application considers the limited computing power of embedded chips used in home ambient lighting and designs an efficient algorithm to avoid competing with the display refresh mechanism for computing power, ensuring smooth lighting effect playback, avoiding lag, and improving the user experience. Furthermore, this application strikes a balance between purpose, cost, and efficiency: providing a lighting effect control method that accurately reflects the musical experience, meeting home needs; avoiding complex solutions, reducing costs, and improving economic efficiency; and optimizing the algorithm to ensure efficiency and real-time performance, allowing smooth operation even with limited computing power, creating high-quality lighting products, enhancing market competitiveness, and providing users with a superior experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which: Figure 1 This is a schematic structural diagram of an exemplary atmosphere lighting device of the present application; Figure 2 This is a flow chart of a typical embodiment of the ambient lighting lighting effect control method of the present application; Figure 3 This is a principle block diagram of the lighting effect control device for the ambient lighting fixture of this application; Figure 4 This is a schematic diagram of the structure of a computer device used in this application. DETAILED DESCRIPTION

[0013] The atmosphere lighting of this application, such as Figure 1 As shown, it includes a controller 80 and lamp units 82 and 84. The controller 80 and the lamp units 82 and 84 can be directly connected by wire or wirelessly, as long as a communication connection can be achieved between the two.

[0014] The number of lamp units 82 and 84 is unlimited, limited only by the support capabilities of the controller 80. Lamp units 82 and 84 are responsible for controlling the numerous lamp beads within them to illuminate in an orderly manner, displaying the corresponding lighting effects, according to lighting effect control information sent by the controller 80. Lamp units 82 and 84 can be a single, minimalist lamp component that responds to the controller 80 as a whole.

[0015] In some embodiments, an ambient lighting fixture consisting of multiple such lighting units 82 and 84 connected to the same controller 80 can also be used as a lighting unit within a larger framework, and then communicated with the upper-level controller 80 within the larger framework to form the ambient lighting fixture of the present application. In other words, based on the architecture of the ambient lighting fixture of the present application, which includes the controller 80 and the lighting units, the lighting units therein can also be nested to form the ambient lighting fixture of the present application, as long as the upper and lower-level controllers 80 forming the nested relationship can reach a pre-agreed agreement.

[0016] In some embodiments, the ambient lighting fixture includes not only a control chip serving as the controller 80 , but also components configured as needed, such as a control panel, a communication component, a display screen, and an audio pickup unit.

[0017] The control chip can be implemented using various embedded chips, such as Bluetooth SoC (System on Chip), WiFi SoC, MCU (Micro Controller Unit), DSP (Digital Signal Processing), and other types of chips. The control chip usually includes a central processing unit and memory, and the memory and central processing unit are used to store and execute program instructions, respectively, to implement corresponding functions. The control panel usually provides one or more buttons for implementing on-off control of the controller 80, selecting various preset lighting effects, etc. The communication component is used to achieve wireless communication connection with each lighting unit 82, 84. The display screen can be used to display various control information so as to cooperate with the buttons in the control panel to support the implementation of human-computer interaction functions. The control panel and the display screen can also be integrated into the same touch screen.

[0018] In an embodiment including an audio pickup unit, the audio pickup unit is used to collect ambient audio data and transmit it to the controller 80 for processing. The controller 80 can perform audio pre-processing on the ambient audio data, detect human voice audio data therefrom, find the target music to which the human voice audio data belongs based on the human voice audio data, and then apply the ambient lighting effect control method of the present application to generate lighting effect control information based on the music introduction information of the target music. Based on the lighting effect control information, the controller 80 controls each lighting unit 82, 84 to play the specified lighting effect in a coordinated or synchronous manner.

[0019] In some embodiments, the controller 80 of the ambient lighting device of the present application can be implemented in a standalone computer device, as long as the computer device is equipped with a control chip that functions as the controller 80. When the controller 80 is implemented in a computer device, various resources inherent to the computer device can be shared to reduce overall implementation costs. The computer device referred to herein can be any terminal device for user use, such as a smartphone, personal computer, laptop computer, tablet computer, etc.

[0020] According to the product architecture and working principle of the above-mentioned atmosphere lighting fixture, the atmosphere lighting fixture lighting effect control method of the present application can be implemented as a computer program, stored in the storage medium of the controller 80 of the atmosphere lighting fixture of the present application, and called and run by the controller 80 from the storage medium to control the various lighting units 82, 84 connected to it for communication to play corresponding lighting effects.

[0021] See also Figure 2 In some embodiments, the ambient lighting lighting effect control method of the present application includes: Step S5100: Obtain music introduction information of the target music; Music description information is a multi-dimensional collection of information used to describe the target music track, including but not limited to image information and text information. Image information can be visual elements related to the target music track, such as album cover images, which often include colors and patterns that reflect the style, theme, or emotion of the music track. Text information can include any one or more of the following: song title, lyrics, genre description, and creative background. This textual content can provide a deeper understanding and experience of the music track.

[0022] In order to obtain the music introduction information of the target music, the present application can adopt a variety of specific implementation methods. For example, when the user is using the atmosphere lamp, an audio pickup unit can be used to collect audio data in the environment. The audio pickup unit can be a microphone, which can capture the music signal being played. Then, the collected audio data is analyzed by the controller to extract its audio features, and the target music to which the audio data belongs is identified from a pre-established music database on a local or cloud server based on the semantic features. In a further embodiment, the audio data can also be detected for human voices first, and when it is determined that there is human voice audio data, the target music is matched and determined from the music database based on its audio features. The music database is a collection that stores a large number of music and related information. It can identify the target music based on audio features, lyrics content or other identifiers. Once the target music is identified, the music introduction information corresponding to the target music can be obtained from the music database.

[0023] In another embodiment, the controller of the atmosphere lighting fixture is connected to music playback software that runs locally or is played on an external device connected to the controller. When playing the target music, the music playback software can send a music notification message to the controller. The controller responds to the music notification message and obtains the corresponding music introduction information from the music playback software through an interface call.

[0024] In another embodiment, the controller of the atmosphere lighting fixture can use its equipped camera unit to capture images corresponding to the graphic information on the external display interface, perform text and image recognition on these images, and determine the corresponding image information and text information as music introduction information.

[0025] In another embodiment, if the user already knows the target music to be played, he or she can directly select or input relevant information of the target music, such as the song title or artist name, through a user interface. The controller then retrieves the corresponding music introduction information from the music database based on the input information.

[0026] In other embodiments, when the target music is clearly identified, the music introduction information of the target music can also be obtained from an external database or the public network through the network, for example, the music introduction information of the target music can be obtained through the API interface of the music streaming platform to obtain the corresponding image information and text information.

[0027] Regardless of the method used to obtain song description information, the key is to ensure that the information obtained is accurate and complete, providing a sufficient basis for subsequent lighting effect generation. For example, for image information, it is necessary to be able to accurately read and interpret the color and pattern characteristics of the album cover image; for text information, it is necessary to be able to extract key content such as the emotional tone of the lyrics and the stylistic characteristics of the song description. This information will be directly used in the subsequent steps to determine the target color set and match the target lighting effect template, ensuring that the generated lighting effect accurately reflects the overall feeling of the target song.

[0028] The image information and text information in the music introduction information can be carried by independent information carriers or by the same carrier. For example, in one embodiment, the image information is carried by the album cover image, while the text information is carried by the song title text. In another embodiment, only the album cover image of the target music is retrieved from the music database or the public Internet. However, this album cover image carries both image information and text information. By applying mature image processing technology, the image information and text information in the album cover image can be separated, so that the image information and text information can be processed separately later.

[0029] Step S5200: Determine a target color set for generating lighting effect control information based on the image information in the music introduction information; Image information is a crucial component of music introductions, typically presented in the form of album cover art. These images, rich in colors and patterns, can reflect the style, theme, or emotion of the music. By analyzing this image information, we can extract color features that match the music's style, and then generate a target color set, providing the basis for subsequent lighting effect control.

[0030] In order to generate a target color set, various implementation methods may be used to utilize image information to obtain characteristic colors therein and construct the target color set.

[0031] In one embodiment, the number of colors in the original picture carrying the image information can be counted, the area ratio of each different color in the original picture can be counted, and then several colors with the largest area ratio can be selected as target colors to construct a target color set.

[0032] In another embodiment, inference can be performed using a pre-trained image feature color extraction model. This model is trained to understand the semantics of a given image and then constructs a target color set based on a predetermined number of feature colors. Based on this, the original image carrying the image information is fed into the image feature color extraction model to generate the corresponding target color set.

[0033] In some embodiments, the target color set determined above may be processed in more detail, either pre-processing or post-processing, such as removing black or gray colors, increasing the color difference between target colors, etc.

[0034] The target color set can also be adjusted based on different music styles and user needs. For example, in one embodiment, a preset classification model is first used to classify the target music based on the image information in the music introduction information to determine the music genre to which the target music belongs. The target color composition in the target color set is then adjusted based on the music genre. For example, for a gentle lyrical music, the target color set may preferably contain more soft tones, such as light blue or pink; while for a dynamic electronic music, the target color set may contain more vivid tones, such as bright yellow or orange.

[0035] It can be seen that through the flexible application of the above various implementation methods, personalized lighting effects can be generated for different types of target music, thereby enhancing the user's auditory and visual experience.

[0036] Step S5300: Matching a target lighting effect template for generating the lighting effect control information from a lighting effect template library according to the text information in the music introduction information; To achieve precise lighting effect control, this application pre-provides a lighting effect template library. This lighting effect template library contains a variety of different types of lighting effect templates, each corresponding to a specific lighting effect expression, and can provide the template content required for the lighting unit to generate lighting effect control information. These lighting effect templates cover a variety of lighting effect modes from simple to complex. For example, some templates can define the flashing frequency and intensity of the light to match the rhythmic music; some templates can define the color gradient speed and direction of the light to suit the lyrical or soft music style.

[0037] Each lighting effect template is described in detail through its description information set. The description information set provides descriptive information of the lighting effect template from multiple preset description dimensions. These dimensions may include but are not limited to the type of lighting effect (such as flashing, gradient, flow, etc.), applicable music style (such as rock, pop, classical, etc.), the speed of the lighting effect (fast, medium, slow), the color tendency of the lighting effect (warm tones, cool tones, colorful, etc.) and other features related to the expression of the lighting effect. For example, the description information set of a lighting effect template may indicate that it is suitable for fast-paced electronic music, the lighting effect type is fast flashing, the color tendency is colorful, and the speed is fast. In this way, each lighting effect template can be accurately defined and distinguished.

[0038] According to the text information in the music introduction information, the target lighting effect template for generating the lighting effect control information is matched from the lighting effect template library, which can be achieved by comparing the text information in the music introduction information with the description information set of each template in the lighting effect template library. For example, if the text information in the music introduction information contains semantics indicating that the music is a popular song with a brisk rhythm, then a lighting effect template with a description information set indicating that it is suitable for pop music and has a brisk rhythm can be matched from the lighting effect template library based on this semantics. In other embodiments, the matching relationship between the text information and the description information set can also be achieved through fuzzy matching or precise matching of keywords. Such matching methods can determine the target lighting effect template, but by performing semantic analysis on the text information and matching the target lighting effect template based on the semantics, the style and emotion of the music can be understood more accurately, thereby selecting the most appropriate lighting effect template.

[0039] To further improve the accuracy of the match, in other embodiments, the present application may also employ more complex matching algorithms. For example, keyword extraction and sentiment analysis may be performed on the textual information in the music introduction information, and then these analysis results may be comprehensively compared with the description information set of the lighting effect template. In addition, user preference settings may be introduced to adjust the matching results based on the user's personal preferences. For example, if the user prefers softer lighting effects, even if the music itself has a brisk rhythm, a relatively soft lighting effect template that still reflects the rhythm of the music can be selected.

[0040] Step S5400: insert the target color set into the target lighting effect template to obtain the lighting effect control information, and control the atmosphere lighting to play the corresponding lighting effect according to the lighting effect control information.

[0041] As previously mentioned, a target lighting effect template describes the lighting effect's presentation through its template content. This template content can define a target color set as an input parameter and, through a prescriptive format specification, define how this target color set controls the lighting units to produce the corresponding lighting effect. By applying the target color set to the target lighting effect template, the lighting effect control information is generated.

[0042] Specifically, a target lighting effect template is a preset lighting effect expression. Through its template content, it defines in detail how to use a target color set to control the lighting effect of a lighting unit. For example, a target lighting effect template might define specific expressions such as the flashing frequency, color gradient speed, and light flow direction. The implementation of these expressions depends on the input of the target color set. The target color set is embedded into the target lighting effect template as an input parameter to generate specific lighting effect control information.

[0043] For example, let's assume the target lighting effect template defines a "rhythmic flashing" pattern, which is suitable for rhythmic music. The template might specify that when the input target color set is red and blue, the lighting unit will flash alternately red and blue, with the flashing frequency synchronized with the music rhythm. In this case, after the target color set (red and blue) is applied to the target lighting effect template, the generated lighting effect control information will instruct the lighting unit to play the lighting effect according to the preset flashing pattern and frequency.

[0044] In another example, a target lighting effect template might define a "gradient flow" mode, suitable for lyrical or soft music. The template content might specify that the colors in the target color set should gradually flow across the lighting unit at a certain speed. For example, if the target color set is light blue and pink, the generated lighting effect control information will instruct the lighting unit to display these two colors in a soft gradient effect, creating a soothing atmosphere.

[0045] To ensure the accuracy and effectiveness of lighting effect control information, the target lighting effect template typically includes detailed, instructive formatting specifications. This text defines, in explicit instructions, how the target color set should be applied to the lighting effects of the lighting units. For example, the template content may specify parameters such as color switching time, brightness variation, and color blending methods. These parameters can be adjusted to suit different music styles and user needs to achieve the optimal lighting effect.

[0046] In actual applications, based on the matched target lighting effect template, the controller embeds the target color set into the template to generate specific lighting effect control information. The controller then sends this lighting effect control information to the lighting unit, which then plays the corresponding lighting effect according to the received lighting effect control information. The resulting lighting effects can accurately reflect the overall feeling of the target music and adapt to different musical styles and user preferences.

[0047] Through the above embodiments, the present application effectively solves the problems faced by ambient lighting and has significant beneficial effects and technical advantages, including but not limited to the following aspects: First of all, this application can capture the characteristics of the music more comprehensively by obtaining the music introduction information of the target music, including image information and text information. Image information can be visual elements such as album covers, while text information can be song titles, lyrics, genre descriptions, etc. These information work together to outline and collaboratively define the target color set and target lighting effect template for the lighting effects, and ultimately generate corresponding lighting effect control information for playing the lighting effects, so that this application can more accurately define the lighting effects that match the target music, thereby more accurately conveying the overall feeling that the target music wants to convey. This comprehensive information fusion method breaks through the limitations of traditional technology that relies solely on melody information, allowing lighting effects to reflect the style and emotion of the music as a whole, bringing users a richer and more personalized visual experience.

[0048] Secondly, this application specifically considers the hardware conditions of ambient lighting fixtures in home scenes. Since these lamps usually use embedded chips to implement lighting effect control, and the computing power of embedded chips is relatively limited, the technical solution of this application can adapt to such hardware conditions. Through efficient algorithm design, this application avoids competing with the display refresh mechanism of ambient lighting fixtures for the already limited computing power of embedded chips, and realizes the function of playing lighting effects according to target music without increasing excessive computing overhead. This not only ensures the smoothness of lighting effect playback, but also avoids the problem of jamming caused by insufficient computing power, thereby improving the user experience.

[0049] In addition, the present application has achieved a good balance in terms of purpose, cost, efficiency, etc. In terms of purpose, the present application provides a lighting effect control method that can accurately reflect the overall feeling of music, meeting the user's demand for atmosphere lighting in home scenes. In terms of cost, the present application avoids complex technical solutions, thereby reducing hardware requirements and costs, making the product more economical. In terms of efficiency, the present application ensures the high efficiency and real-time performance of lighting effect control by optimizing the algorithm, and can run smoothly even on embedded chips with limited computing power. This balanced effect enables the present application to obtain higher-quality lighting products, effectively solve specific technical problems in specific fields, not only improving the market competitiveness of the product, but also providing users with a better product experience.

[0050] Based on any embodiment of the method of the present application, obtaining music introduction information of the target music includes: Step S5110: collecting ambient audio data through the audio pickup unit, and determining whether the ambient audio data contains human voice audio data; Obtaining the music introduction information of the target music can be achieved through automatic recognition by the controller. The controller collects environmental audio data through the audio pickup unit and determines whether these data contain human voice audio data. When human voice audio data is contained, the controller further identifies and determines the target music and obtains its corresponding music introduction information.

[0051] The audio pickup unit can be a microphone or other device capable of capturing audio signals. These devices typically have a certain sensitivity and frequency response range, enabling them to effectively capture audio signals in the environment. The collected ambient audio data may contain a variety of sounds, such as background noise, human voices, and sounds from other electronic devices. Therefore, it is possible to further determine whether the ambient audio data contains human voice audio data to determine whether the target music piece includes vocal performances.

[0052] Considering that users frequently play songs sung by human voices, for this specific application, voice activity detection (VAD) can be performed on the ambient audio data first. When human voice activity is detected in the ambient audio data, it can be preliminarily confirmed that the ambient audio data contains human voice audio data.

[0053] Step S5120: When the human voice audio data exists, identify a target music that matches the environmental audio data from a music database; When the ambient audio data collected by the audio pickup unit is determined to contain human voice audio data, the controller can identify the target music to which the human voice audio data belongs from the music database. This can be achieved by comparing and matching the collected ambient audio data with the audio features of the music in the music database.

[0054] Specifically, the music database can be a collection that stores a large number of music pieces and related information, where each piece of music has unique audio features, including but not limited to audio fingerprints, melody patterns, rhythmic structures, etc. When the controller detects that the ambient audio data contains human voice audio data, it can use these audio features to identify the target music piece.

[0055] For example, audio fingerprints can be used as audio features. Audio fingerprint recognition technology generates a unique identifier (fingerprint) for the ambient audio data and matches it with the preset fingerprints of each song in a database, allowing for rapid and accurate identification of the target song. Audio fingerprint recognition technology offers high recognition accuracy and robustness against interference, enabling accurate identification of the target song in complex audio environments.

[0056] In addition to audio fingerprinting, a variety of other technical approaches can be employed to identify target music. For example, machine learning algorithms, such as convolutional neural networks (CNNs) in deep learning, can be used to train models on large amounts of music data, enabling them to identify the audio characteristics of different music pieces. When the collected ambient audio data is input into the trained model, the model will output the music information, such as the music ID, that best matches the ambient audio data, thereby identifying the target music piece.

[0057] Step S5130: Obtain music introduction information of the target music from the music database, wherein the music introduction information includes preset image information and text information corresponding to the target music, and the image information and text information are each separately represented on different information carriers, or are integrated with each other and represented on the same information carrier.

[0058] The music database not only stores the IDs of each song and its corresponding audio features, but also contains information about each song, including preset image and text information for the target song. The image and text information can be displayed separately on different information media or integrated into the same media.

[0059] In practical applications, image information and text information can be stored and represented in a variety of ways. For example, image information can be stored in the form of a digital image file, such as a JPEG or PNG format, while text information can be stored in the form of a text file or a database record. In some embodiments, image information and text information can also be integrated into a single information carrier, such as by including both image and text information in a multimedia file, or by embedding images and text in a web page using HTML format.

[0060] The process of obtaining music introduction information is automated and can be completed by controller from the music database.In case target music is identified, controller just can retrieve the music introduction information corresponding to this target music from the database.

[0061] This embodiment collects ambient audio data through an audio pickup unit and determines whether it contains human voice audio data, and then identifies the target music from the music database and obtains its music introduction information. This process realizes the automatic recognition and information acquisition of the target music, without the need for the user to manually input music information, thereby improving the convenience and efficiency of operation. At the same time, by using audio fingerprint recognition technology or machine learning algorithms and other means, the target music can be accurately identified in a complex audio environment, ensuring the accuracy and reliability of the recognition. In addition, by obtaining music introduction information containing image information and text information, a more comprehensive and rich basis is provided for the subsequent generation of lighting effects, so that the generated lighting effects can more accurately reflect the overall feeling of the target music, thereby enhancing the user's auditory and visual experience.

[0062] Based on any embodiment of the method of the present application, determining a target color set for generating lighting effect control information according to the image information in the music introduction information includes: Step S5210: compress the original image carrying the image information in the music introduction information to obtain a target-sized image carrying the image information; In this embodiment, the original image carrying the image information in the music introduction information is compressed to obtain a target specification image carrying the image information. This is the first step in determining the target color set. The purpose is to reduce the resolution and file size of the image through image compression technology, thereby reducing the computational complexity of subsequent processing while retaining the key color information in the image.

[0063] Image compression is a common image processing technique that aims to minimize the amount of image data while preserving the image's primary visual features. In this application, the original image may have a high resolution and a large file size, and directly performing color analysis on it may result in high computational overhead. Therefore, through image compression, the original image can be converted to a target-specification image with a lower resolution. This not only speeds up processing but also removes noise and details from the image to a certain extent, allowing color analysis to focus more on the image's primary color components.

[0064] In specific implementations, various image compression algorithms can be used, such as JPEG and PNG. These algorithms can significantly reduce image data size while maintaining image quality. For example, JPEG compression, through discrete cosine transform (DCT) and quantization, effectively removes redundant information from images while preserving their primary visual features. PNG compression, on the other hand, uses lossless compression technology to reduce image file size without sacrificing image quality.

[0065] In this application, the specific implementation of image compression can be selected based on actual needs. For example, if higher image quality is required, a lower compression ratio can be selected; if higher processing speed is required, a higher compression ratio can be selected. In addition, the appropriate compression algorithm and parameters can also be selected based on the intended use of the target image.

[0066] Step S5220: Count the occurrence frequencies of various colors in the pixel set of the target specification image, and determine the multiple colors with the highest occurrence frequencies to form a candidate color set; By performing color frequency statistics on the target image to determine the candidate color set, the pixel colors in the image can be analyzed based on the first color space, the frequency of occurrence of each color can be counted, and the colors with the highest occurrence frequency can be selected from them to form the candidate color set. These colors can generally represent the main color characteristics of the image, providing a basis for further color screening and lighting effect generation.

[0067] Specifically, the first color space refers to a mathematical model used to represent color. In this embodiment, the RGB color space is used as the first color space. In the RGB color space, each color is composed of three components: red, green, and blue. The value of each component typically ranges from 0 to 255. By analyzing each pixel in the target specification image, the frequency of occurrence of each color can be statistically calculated.

[0068] In practice, various methods can be used to count color frequencies. The recommended method is to use a color histogram. A color histogram is a statistical tool that divides the color space into multiple bins (or "buckets") and counts the number of pixels within each bin. For example, in the RGB color space, the value range of each color component can be divided into several small bins, and the number of pixels within each bin can be counted. This method can quickly determine the frequency of each color.

[0069] For example, suppose the target specification image is an album cover with dark blue and white as its main colors. By performing color frequency statistics on the image, it can be found that the number of dark blue and white pixels is much higher than that of other colors, so these two colors will be selected as part of the candidate color set.

[0070] In addition, to improve statistical accuracy, colors can be quantized. Color quantization is a technique that reduces the number of colors in a color space. By combining similar colors into a single representative color, the color counting process can be simplified and improved. For example, the colors in the RGB color space can be quantized into a limited set of colors, such as 256 colors, and the frequency of occurrence of these colors can then be counted.

[0071] The number of colors required for the candidate color set can be determined as needed. For example, 8, 16, or 32 colors can be selected to form the candidate color set. In a preferred implementation, the value is taken between 8 and 16, and the appropriate number is used to pursue the comprehensive effect of the lighting effect, so as to avoid the lighting effect appearing complicated due to too many colors, and also avoid the display being monotonous due to too few colors.

[0072] Step S5230: Detect whether each color in the candidate color set meets a preset color difference condition, and delete colors that do not meet the color difference condition to obtain the target color set.

[0073] By detecting whether each color in the candidate color set meets the preset color difference conditions in the second color space, the final target color set can be screened out. The purpose is to ensure that the selected colors can not only represent the main color characteristics of the image, but also have sufficient visual distinction, thereby providing high-quality color input for subsequent lighting effect control.

[0074] Specifically, the second color space is a color representation model that differs from the first color space (e.g., RGB), and is typically used to more accurately describe the visual properties of color. For example, in this embodiment, the HSV (hue, saturation, value) color space can be used as the second color space. This decomposes the visual properties of color into three independent components, making color processing more consistent with human visual perception.

[0075] To facilitate calculation, in this embodiment, the colors in the candidate color set are first converted to the second color space to facilitate more accurate color analysis and screening.

[0076] The preset color difference condition can be a threshold value set based on the visual properties of the color, which is used to determine the distinction between colors. For example, in the HSV color space, corresponding thresholds for saturation and brightness can be set to ensure that the selected color has sufficient vividness and brightness. For example, the saturation threshold can be set to 50% and the brightness threshold to 45%. Only when the saturation and brightness of the color meet these conditions will the color be considered to have sufficient visual impact and be retained.

[0077] In practice, each color in the candidate color set is normalized to convert it from the first color space to the second. Next, the saturation and brightness of each color are individually checked to see if they meet preset thresholds. If a color's saturation or brightness falls below the threshold, it is considered visually unsatisfactory and is removed from the candidate color set. Ultimately, the remaining colors constitute the target color set, which not only represents the primary color characteristics of the image but also exhibits good visual distinction.

[0078] To further optimize the target color set, additional processing can be performed on the filtered colors. For example, if the target color set contains too many colors, you can filter them based on frequency of occurrence or visual importance, retaining the most important ones. Conversely, if the number of colors is insufficient, you can use a generative model (such as an AI large model) to generate additional colors based on the existing colors and music description information to enrich the target color set.

[0079] This embodiment efficiently and accurately extracts a target color set from image information, demonstrating distinct advantages over other embodiments. First, using image compression technology to convert the original image to the target specification, it effectively reduces image resolution and file size, reducing the computational complexity of subsequent processing while preserving key color information, providing a more efficient data foundation for subsequent analysis. Second, color frequency statistics are performed in the first color space to select the most frequently occurring colors to form a candidate color set. This process, based on color frequency, ensures that the selected colors represent the primary visual features of the image, providing a representative color foundation for lighting effect generation. Finally, color difference condition detection is performed in the second color space to further select colors that meet specific visual effect requirements, ensuring that the target color set is not only representative but also visually distinct and expressive. This series of steps, combined to achieve a specific optimization solution, ensures that the final target color set more accurately reflects the core color characteristics of the image information while maintaining low system overhead. This provides high-quality color input for generating lighting effects that match the target music, thereby enhancing the overall expressiveness of the lighting effects and user experience.

[0080] Based on any embodiment of the method of the present application, after determining that a plurality of colors with the highest occurrence frequency constitute a candidate color set, the method includes: Step S6100: Based on each color component corresponding to each color defined in the first color space, identify a first target color in the candidate color set whose each color component is lower than a preset first component threshold, and delete the first target color from the candidate color set; As a way to optimize the candidate color set, by analyzing the color components based on the first color space (such as RGB), identifying and deleting colors whose color components are all below a preset threshold, colors that are too dark or close to black in the candidate color set can be removed, thereby improving the quality and visual effect of the final target color set.

[0081] Specifically, each color in the first color space is composed of multiple components. For example, in the RGB color space, each color is composed of three components: red (R), green (G), and blue (B). The value of each component typically ranges from 0 to 255. The preset first component threshold is a standard value used to determine the brightness of a color. If the value of each component of a color is lower than this preset first component threshold, the color is considered too dim or close to black and is generally not suitable for lighting effect control because it may not visually provide sufficient brightness or color saturation.

[0082] During implementation, a specific threshold can be set, such as setting the first component threshold to 30. This means that if the R, G, and B component values ​​of a color are all below 30, the color will be identified as the first target color and removed from the candidate color set. This processing method can effectively remove colors that are not visually obvious or may affect the overall lighting effect.

[0083] The first component threshold can be adjusted based on actual needs. For example, the first component threshold can be adjusted based on different application scenarios or user preferences. In scenes with high brightness requirements, the threshold can be set higher to ensure that the filtered colors have sufficient brightness; in scenes with high color subtlety requirements, the threshold can be appropriately lowered to preserve more color details.

[0084] Step S6200: Based on the color components, identify a second target color in the candidate color set whose absolute difference between any two color components is lower than a preset second component threshold, and delete the second target color from the candidate color set.

[0085] As another way to optimize the candidate color set, gray-toned colors are identified and deleted by detecting the differences between different color components of the same candidate color, thereby improving the color richness and visual effect of the target color set.

[0086] Specifically, based on the color components of a first color space (e.g., RGB), the differences between the R, G, and B component values ​​of each color in the candidate color set are analyzed. If the absolute difference between any two color components is below a preset second component threshold, the color is identified as gray, i.e., the second target color, and is removed from the candidate color set.

[0087] In the RGB color space, when the R, G, and B component values ​​of a color are similar, the color tends to be gray. For example, when the R, G, and B component values ​​are 128, 128, and 128 respectively, the color is neutral gray. In order to quantify the degree of this "closeness", this application sets a second component threshold. If the absolute difference between R and G, R and B, and G and B are all lower than the threshold, for example, set to 10, the color is considered gray. This processing method can effectively remove colors that visually lack color saturation to prevent them from having a negative impact on lighting effects.

[0088] The threshold setting for the second component can be adjusted based on actual needs. In some application scenarios, if a more vivid lighting effect is desired, the threshold can be set lower to strictly filter out non-gray colors; in some scenarios with strict color transition requirements, the threshold can be appropriately increased to retain more intermediate tones. Through this flexible threshold setting, this application can adapt to different lighting effect requirements and user preferences.

[0089] In practice, each color in the candidate color set is analyzed, and the absolute differences between its R, G, and B components are calculated. If all component differences for a color fall below the second component threshold, it is identified as the second target color and removed from the candidate color set. This process not only improves the color purity of the target color set but also ensures that the resulting lighting effect better reflects the overall feel of the target music while avoiding the visual monotony caused by excessive gray tones.

[0090] Through the above embodiments, the present application optimizes the candidate color set, enabling more precise selection of colors suitable for lighting effect control than other embodiments, significantly improving the quality and visual quality of the target color set. First, by analyzing the color components in the first color space, overly dim or near-black colors are identified and removed, effectively avoiding the potential visual issues these colors may cause in lighting effects. Furthermore, by flexibly adjusting the first component threshold, color brightness and saturation can be precisely controlled based on different application scenarios and user preferences. Then, by detecting differences between color components, grayscale colors are identified and removed, further enhancing the color richness and visual quality of the target color set. This processing approach not only improves the color purity of the target color set but also ensures that the resulting lighting effect better reflects the overall feel of the target music, while avoiding the visual monotony caused by excessive grayscale. Through these two optimization steps, this embodiment provides higher-quality color input for subsequent lighting effect control, thereby improving the overall expressiveness of the lighting effect and user experience.

[0091] Based on any embodiment of the method of the present application, detecting whether each color in the candidate color set meets a preset color difference condition, and deleting colors that do not meet the color difference condition to obtain the target color set includes: Step S5231: performing normalization processing on each candidate color in the candidate color set to convert each candidate color from a representation in the first color space to a representation in the second color space; By normalizing each candidate color in the candidate color set, we can efficiently and quickly convert these colors from a first color space (such as RGB) to a second color space (such as HSV). This conversion is necessary because different color spaces have their own advantages in describing the visual properties of color, and the second color space is generally more suitable for analyzing the visual effects of color.

[0092] During normalization, the values ​​of each color component can be normalized to a uniform range, typically 0 to 1. In this embodiment, through normalization, the color component values ​​in the RGB color space are converted from a range of 0 to 255 to a range of 0 to 1, and then converted to percentage values, thereby converting these colors to the HSV color space.

[0093] Through normalization, each color in the candidate color set is converted to the representation of the HSV color space. This conversion makes the subsequent color screening process more intuitive and effective because the HSV color space is closer to human visual perception of color.

[0094] Step S5232: Based on the representation of the second color space, detect and determine a third target color in the candidate color set whose saturation and / or brightness meet the corresponding preset color difference condition, retain the third target color in the candidate color set, and delete all other candidate colors; Once the second color space (such as HSV) is represented, the candidate color set can be further screened to identify a third target color that meets pre-defined color difference criteria. Specifically, this can be done by analyzing the color's saturation and / or brightness to ensure the selected color has sufficient visual impact and distinction, providing high-quality color input for subsequent lighting effect control.

[0095] Specifically, the HSV color space decomposes the visual attributes of color into three independent components: hue, saturation, and value. Hue indicates the type of color, saturation indicates the purity of the color, and value indicates the brightness of the color. In this step, the preset color difference conditions usually include thresholds for saturation and value. For example, in this embodiment, the saturation threshold can be set to 50% and the value threshold can be set to 45%. The setting of these thresholds is intended to screen out colors that are visually vivid and bright enough, while removing colors that are too dim or lack color saturation.

[0096] In practice, each color in the candidate color set is tested, and its saturation and brightness are determined one by one to see if they meet the preset threshold conditions. If the saturation or brightness of a color is lower than the set threshold, the color is considered to have poor visual effect and is removed from the candidate color set. Conversely, if the saturation and / or brightness of a color both meet or exceed the preset threshold, the color is retained and becomes the third target color. Ultimately, the retained third target colors constitute the target color set, which not only represents the main color characteristics of the image but also has good visual distinction and expressiveness.

[0097] Step S5233: Use the candidate color set containing only the third target color as the target color set, and convert the target colors in the target color set back into the representation of the first color space.

[0098] The third target color in the filtered candidate color set is used as the final target color set, and these colors are converted from the second color space (such as HSV) to the representation of the first color space (such as RGB). This ensures that the target color set not only meets the requirements of visual effects, but can also be used subsequently to construct lighting effect control information.

[0099] Specifically, the candidate color set has been screened for third target colors that meet preset color difference conditions. These colors have sufficient saturation and brightness in the HSV color space to provide good visual impact and distinction. However, for subsequent compatibility, these colors need to be converted back to the first color space, namely the RGB color space. The RGB color space is the standard color space used by most display devices and lighting control systems, so converting the target color set to RGB representation is necessary.

[0100] In practice, converting colors from the HSV color space to the RGB color space is a standard mathematical conversion process. Specifically, the hue, saturation, and value components of the HSV color space are first converted to their corresponding RGB component values. This conversion can be performed using known mathematical formulas or algorithms, ensuring that the colors retain their original visual properties during the conversion process.

[0101] For example, suppose a color in the HSV color space has a hue of 60 degrees, a saturation of 70%, and a lightness of 80%. Using the standard HSV to RGB conversion formula, the corresponding value of this color in the RGB color space can be calculated. This conversion ensures accurate color representation between different color spaces, allowing the target color set to be correctly applied by the lighting control system.

[0102] Furthermore, to further optimize the target color set, additional processing can be performed on the filtered colors. For example, if the target color set contains too many colors, filtering can be performed based on frequency of occurrence or visual importance, retaining the most important ones. Conversely, if the number of colors is insufficient, a generative model (such as an AI large model) can be used to generate additional colors based on the existing colors and music description information to enrich the target color set.

[0103] This embodiment, through refined color processing, efficiently selects a target color set from a candidate color set that meets visual effect requirements and converts it into a standard color space representation suitable for constructing lighting effect control information. First, by normalizing the candidate color set and converting it to a second color space (such as HSV), visual properties of colors, such as saturation and brightness, can be more intuitively and effectively analyzed. This conversion makes the color screening process more precise and effectively removes colors that lack vividness or brightness, thereby ensuring that the selected colors have sufficient visual impact and distinction. Second, by setting saturation and brightness thresholds in the HSV color space, the target color set can be further optimized to not only represent the primary color characteristics of the image but also adapt to different lighting effect requirements and user preferences. Finally, the filtered target color set is converted back to the first color space (such as RGB), ensuring that these colors can be recognized and applied by the subsequent lighting effect control process. This embodiment not only improves the quality of the target color set but also ensures its compatibility with existing lighting effect control systems. This provides high-quality color input for generating lighting effects that match the target music, enhancing the overall expressiveness of the lighting effects and the user experience.

[0104] Based on any embodiment of the method of the present application, after detecting whether each color in the candidate color set meets a preset color difference condition, and deleting the colors that do not meet the color difference condition to obtain the target color set, the method includes: Step S5240: Determine whether the number of colors in the target color set is zero. If it is zero, call a preset color matching generation model to generate a target color set that meets preset color matching conditions based on the image information and / or text information in the music introduction information. In order to ensure the effectiveness and practicality of the target color set, the number of colors in the target color set is judged. When the number of colors in the target color set is zero, it indicates that no color is obtained after the screening steps disclosed earlier in this application, and it is necessary to call the preset color matching generation model to generate a target color set that meets the preset color matching conditions based on the image information and / or text information in the music introduction information.

[0105] Specifically, a color generation model is an algorithmic or rule-based model that generates a set of colors based on input information. In this embodiment, the model uses either image information (such as the color characteristics of the album cover) or text information (such as lyrics, genre description, etc.) from the music description as input, or either of these two, to generate a target color set that matches the style of the target music. For example, if the text information indicates that the target music is a gentle, lyrical song, the color generation model might generate a target color set primarily composed of light blue or pink; if the image information indicates that the album cover is primarily composed of red and yellow, the model might generate a target color set containing these colors.

[0106] Color generation models can be implemented in a variety of ways. One approach is a rule-based system, in which a series of color matching rules are preset and appropriate rules are selected based on the input image and text information to generate a color set. Another approach is to use machine learning algorithms, such as generative adversarial networks (GANs) or variational autoencoders (VAEs) in deep learning, to learn to generate target color sets that match the style of the music by training on a large number of musical pieces and their corresponding color sets.

[0107] In practice, when the target color set is detected as empty, the color generation model is triggered. The model first analyzes the images and text in the music description, extracting key features such as the dominant colors in the image, the emotional tendencies in the text, and the genre description. Based on these features, it then generates a set of colors that meet pre-set color matching criteria. These colors not only match the style of the music but also provide a good visual effect.

[0108] Step S5250: When the number of colors in the target color set is not zero, continue to determine whether the number of colors in the target color set is lower than a preset lower threshold. If so, call a preset color matching generation model to generate a target color set that meets preset color matching conditions, using the target colors in the target color set as a reference and referring to the image information and / or text information in the music introduction information. When the color data in the target color set is non-zero, the system continues to determine whether the number of colors in the target color set is below a preset lower threshold, allowing for further optimization of the target color set to ensure it meets the preset lower threshold. Specifically, when the number of colors in the target color set is below the preset lower threshold but greater than 0, this indicates that the resulting number of colors is insufficient to meet the basic requirements of lighting effect control. At this point, a preset color matching generation model is called upon, using the existing colors in the target color set as a benchmark and referencing the image information and / or text information in the music introduction information to generate a target color set that meets the preset color matching conditions.

[0109] The color generation model's role in this step is to supplement the target color set to a preset lower threshold. Using the existing target colors as a reference, the model combines key features from the music description, such as the dominant colors in the image, the emotional tendencies in the text, and the genre description, to generate a new set of colors that aligns with the existing color style and the overall feel of the music. These newly generated colors are then added to the target color set to enrich its content and ensure a sufficient variety of color options for subsequent lighting effect control.

[0110] In practice, when the number of colors in the target color set is detected to be below a preset lower threshold, the color generation model first analyzes the existing target color set to extract its color features and style. Then, combining the images and text content in the song description information, it generates new colors using preset color matching rules or machine learning algorithms. For example, if the existing target color set is primarily warm-toned, and the song description information indicates that the target song is a vibrant pop song, the color generation model may generate some bright, warm colors, such as orange or yellow, to supplement the target color set.

[0111] Furthermore, when generating new colors, the color generation model ensures that they visually harmonize with existing colors and fit the overall style of the music. For example, if the text description in the music description indicates that the target music has a romantic sentiment, the model might generate colors with soft pink or purple tones to enhance the emotional expression of the target color set.

[0112] Step S5260: Determine whether the number of colors in the target color set exceeds a preset upper threshold. If so, retain the target colors with the highest frequency in the target color set according to the preset upper threshold, and delete the remaining target colors.

[0113] The number of colors in the target color set is continuously determined to ensure that it does not exceed a preset upper threshold. If the number of colors in the target color set exceeds the preset upper threshold, only the most frequently occurring target color is retained according to the preset rules, and the remaining target colors are deleted. This process further optimizes the number of target color sets to ensure that the lighting effect control requirements are met while not causing excessive visual complexity or confusion due to an excessive number of colors.

[0114] Specifically, the preset upper threshold is set based on the actual needs of lighting effect control to limit the maximum number of colors in the target color set. For example, processing too many colors can lead to performance degradation or poor visual effects. Setting a reasonable upper threshold can avoid these issues. When the number of colors in the target color set exceeds this threshold, the color set needs to be streamlined.

[0115] In actual operation, based on the frequency of occurrence of each target color obtained through statistics disclosed earlier in this application, the target colors are sorted from high to low in order of frequency of occurrence, and the colors with the highest frequency of occurrence are retained until a preset upper threshold is reached. Excess colors are deleted to ensure that the number of colors in the target color set does not exceed the upper threshold.

[0116] For example, suppose the preset upper threshold is 8, and the target color set, filtered in the previous step, contains 10 colors. Through counting and sorting, it is found that 8 colors appear frequently. These 8 colors will be retained, while the other 2 colors with lower frequency will be deleted. This processing method ensures that the target color set meets the processing capabilities and visual requirements of the ambient lighting fixture.

[0117] Furthermore, to further optimize the target color set, we can also consider the visual importance of the color and its compatibility with the musical style. For example, if a color, while not the most frequent, has a significant visual impact on the overall lighting effect or closely matches the musical style, we can adjust the retention strategy appropriately to ensure that this color is retained.

[0118] Through the above embodiment, the present application ensures that the target color set can meet the requirements of lighting effect control in terms of both quantity and quality, thereby achieving a balance between visual effects and system performance. First, when the target color set is empty, the color matching generation model is used to generate a color set that meets the preset conditions based on the music introduction information, avoiding the empty set problem caused by excessive color screening and ensuring the feasibility of lighting effect control. Secondly, the number of color sets is further optimized. When the number of colors is lower than the preset lower limit threshold, new colors that are consistent with the existing color style are generated to enrich the content of the color set and enhance the expressiveness of the lighting effect. Finally, by limiting the number of color sets to no more than the preset upper limit, visual confusion and system performance degradation caused by too many colors are avoided, ensuring the efficiency of lighting effect control and the coordination of visual effects. These steps work together to enable the target color set to not only accurately reflect the style of the music, but also provide high-quality visual effects, while adapting to the processing capabilities of the lighting effect control system, thereby improving the overall user experience.

[0119] Based on any embodiment of the method of the present application, according to the text information in the music introduction information, matching a target lighting effect template for generating the lighting effect control information from a lighting effect template library includes: Step S5310: Obtain a description information set of each lighting effect template in the lighting effect template library, where the description information set of each lighting effect template provides description information of the lighting effect template from multiple preset description dimensions. In this embodiment, for the lighting effect template library mentioned above in this application, the description information set of each lighting effect template provides detailed information about the lighting effect template from multiple preset description dimensions. These description dimensions may include, but are not limited to, the type of lighting effect (such as flashing, gradient, flow, etc.), the applicable music style (such as rock, pop, classical, etc.), the speed of the lighting effect (fast, medium, slow), the color tendency of the lighting effect (warm tones, cool tones, colorful, etc.), and other features related to the expression of the lighting effect. For example, the description information set of a lighting effect template may indicate that it is suitable for fast-paced electronic music, the lighting effect type is fast flashing, the color tendency is colorful, and the speed is fast.

[0120] The purpose of obtaining these description information sets is to provide a sufficient basis for subsequent lighting effect template matching. This detailed description information allows for a more accurate understanding of the characteristics and applicable scenarios of each lighting effect template, thereby supporting the selection of the most appropriate lighting effect template. Specifically, these description information sets are used to compare and match the text information in the music introduction information to determine which lighting effect templates best match the style and emotion of the target music.

[0121] In practice, a lighting effect template library can be a database that stores a large number of preset lighting effect templates, each of which includes a corresponding set of descriptive information. This information set can be generated through manual annotation or automatic extraction and stored in a structured format in the database. For example, each lighting effect template can be assigned one or more tags corresponding to different descriptive dimensions, such as "suitable for pop music" or "lighting effect type is gradient." In this way, the characteristics of each lighting effect template can be clearly described and distinguished.

[0122] Furthermore, to improve matching accuracy and efficiency, the information in the description set can be further refined and quantified. For example, the speed of a lighting effect can be quantified into a specific numerical range, and color tendencies can be quantified into specific color parameters. This quantification allows the description set to not only provide qualitative descriptions but also support quantitative analysis and comparison.

[0123] Step S5320: calling a preset matching instruction set and combining it with the text information in the music introduction information, the description information sets of each lighting effect template, and the target color set as matching prompt information, wherein the matching instruction set includes a first control instruction and a second control instruction that are executed successively, the first control instruction being used to instruct the lighting effect matching model to first determine a subset of lighting effect templates that semantically matches the text information in the music introduction information based on each description information set; the second control instruction being used to instruct the lighting effect matching model to score each lighting effect template in the lighting effect template subset from multiple description dimensions, and then fusing the scores to determine the total score of each lighting effect template, and selecting the lighting effect template with the highest total score as the target lighting effect template; In this step, by calling the preset matching instruction set, the text information in the music introduction information, the description information set of each lighting effect template in the lighting effect template library, and the target color set are combined into matching prompt information, and then the target lighting effect template that matches the target music is determined through the lighting effect matching model. The purpose is to accurately select the lighting effect template that best suits the current music through multi-dimensional analysis and scoring.

[0124] Specifically, the matching instruction set consists of two control instructions that are executed sequentially. The first control instruction instructs the lighting effect matching model to determine a subset of lighting effect templates that semantically match the textual information in the song description, based on the description information set of each lighting effect template. This process primarily relies on semantic analysis of the textual information, comparing key information in the song description (such as genre, emotion, and lyrics) with the applicable scenarios and style characteristics of the lighting effect template description to select a subset of lighting effect templates that are initially matched.

[0125] The second control instruction further refines the scoring of the selected subset of lighting effect templates. The lighting effect matching model scores each lighting effect template from multiple descriptive dimensions, such as lighting effect type dimension, effect performance dimension, atmosphere performance dimension, visual impact performance dimension, and other preset dimensions. The scoring results of these dimensions are then fused using the mean or weighted mean to determine the total score of each lighting effect template. Finally, the lighting effect template with the highest total score is selected as the target lighting effect template. This multi-dimensional scoring mechanism can comprehensively consider all aspects of the lighting effect template to ensure that the selected template not only matches the music in style, but also achieves the best visual effect. Through comprehensive scoring, these factors can be balanced to select the most suitable target lighting effect template.

[0126] In actual operation, a matching instruction set is prepared in advance, which includes placeholders for inserting text information, description information set and target color set. By replacing the placeholders, this information is merged into the same data structure to become matching prompt information.

[0127] In this embodiment, a large language model that has been fine-tuned and trained in advance is used as a lighting effect matching model, and matching prompt information can be output to the lighting effect matching model so that the model can determine the target lighting effect template based on the matching prompt information.

[0128] Step S5330: input the matching prompt information into the lighting effect matching model to obtain the target lighting effect template determined by the lighting effect matching model.

[0129] The matching hint information generated in the previous step is fed into the lighting effect matching model. The model processes the first and second control instructions in the matching hint information to determine the target lighting effect template that matches the target music track. The model comprehensively analyzes the music description, the lighting effect template description, and the target color set to accurately select the lighting effect template that best matches the current music track.

[0130] Specifically, the matching prompt information includes the text from the song description, the lighting effect template description, and the target color set. This information is integrated into a unified data structure for processing by the lighting effect matching model. The lighting effect matching model is a large, pre-trained language model that understands and processes natural language text and performs complex matching and scoring operations based on the input information.

[0131] During processing, the lighting effect matching model first determines, based on the first control instruction and the description information set of each lighting effect template, a subset of lighting effect templates that semantically matches the textual information in the song description. By comparing key information in the song description (such as genre, emotion, and lyrics) with the applicable scenarios and stylistic features of the lighting effect template description, a subset of lighting effect templates with preliminary matches is selected. For example, if the song description indicates a pop song with a lively beat, the matching model will prioritize lighting effect templates suitable for pop music and featuring a lively rhythm.

[0132] The lighting effect matching model then scores each lighting effect template in the selected subset based on multiple descriptive dimensions, according to the second control instruction. The score for each dimension can be determined based on preset rules or through the model's internal learning mechanism. The model then uses a mean or weighted mean to combine the scores from these dimensions to determine the overall score for each lighting effect template. Ultimately, the lighting effect template with the highest overall score is selected as the target lighting effect template. This multi-dimensional scoring mechanism comprehensively considers all aspects of the lighting effect template, ensuring that the selected template not only matches the music stylistically but also achieves optimal visual performance.

[0133] In practice, the format and content of the matching prompt information must match the input requirements of the lighting effect matching model. For example, the matching prompt information can be a JSON object containing multiple fields, where each field corresponds to a different information type (such as text information, description information set, target color set, etc.). After receiving the matching prompt information, the lighting effect matching model processes it according to preset instructions and rules and outputs the final selected target lighting effect template.

[0134] This embodiment significantly improves the matching accuracy and visual expressiveness of lighting effects with target music through a sophisticated lighting effect template matching process. First, by obtaining a multi-dimensional description information set for each template in the lighting effect template library, a detailed basis is provided for subsequent matching, enabling the characteristics of the lighting effect templates to be clearly described and distinguished. Next, using a preset matching instruction set, the music introduction information, description information set, and target color set are integrated into matching prompts. Through semantic analysis and a multi-dimensional scoring mechanism, a subset of lighting effect templates that best matches the style and emotion of the music is precisely selected. The target lighting effect template with the highest overall score is then determined from this subset. This matching approach, which comprehensively considers text semantics, visual effects, and musical style, not only ensures a high degree of consistency between the lighting effect and the music, but also balances multiple visual and musical factors through quantitative scoring, providing users with a high-quality, personalized lighting effect experience. Furthermore, the use of a finely tuned large language model as the lighting effect matching model further enhances the intelligence and accuracy of the matching process, making the entire lighting effect control process more efficient and precise.

[0135] See also Figure 3 , an atmosphere lighting fixture lighting effect control device provided to meet one of the purposes of the present application is a functional embodiment of the atmosphere lighting fixture lighting effect control method of the present application, the device includes an information acquisition module 5100, a color matching determination module 5200, a template matching module 5300, and a lighting effect control module 5400, wherein the information acquisition module 5100 is configured to obtain music introduction information of the target music; the color matching determination module 5200 is configured to determine the target color set for generating the lighting effect control information based on the image information in the music introduction information; the template matching module 5300 is configured to match the target lighting effect template for generating the lighting effect control information from the lighting effect template library based on the text information in the music introduction information; the lighting effect control module 5400 is configured to insert the target color set into the target lighting effect template to obtain the lighting effect control information, and control the atmosphere lighting fixture to play the corresponding lighting effect according to the lighting effect control information.

[0136] Based on any embodiment of the device of the present application, the information acquisition module 5100 includes: an audio pickup module, configured to collect environmental audio data through an audio pickup unit, and determine whether the environmental audio data contains human voice audio data; a target recognition module, configured to identify the target music matching the environmental audio data from the music database when the human voice audio data exists; an information retrieval module, configured to obtain music introduction information of the target music from the music database, the music introduction information includes preset image information and text information corresponding to the target music, and the image information and text information are each separately represented on different information carriers, or are integrated with each other and represented on the same information carrier.

[0137] Based on any embodiment of the device of the present application, the color matching determination module 5200 includes: an image compression module, which is configured to perform image compression on the original image carrying the image information in the music introduction information to obtain a target specification image carrying the image information; a statistical color selection module, which is configured to count the occurrence frequency of each color in the pixel set of the target specification image, and determine that the multiple colors with the highest occurrence frequency constitute a candidate color set; a color optimization module, which is configured to detect whether each color in the candidate color set meets a preset color difference condition, and delete the colors that do not meet the color difference condition to obtain the target color set.

[0138] On the basis of any embodiment of the device of the present application, the statistical color selection module includes: a dark color filtering module, which is configured to identify, based on the respective color components corresponding to each color defined by the first color space, a first target color in the candidate color set in which each color component is lower than a preset first component threshold, and delete the first target color from the candidate color set; a grayscale filtering module, which is configured to identify, based on the respective color components, a second target color in the candidate color set in which the absolute difference between each two color components is lower than a preset second component threshold, and delete the second target color from the candidate color set.

[0139] Based on any embodiment of the device of the present application, the color optimization module includes: a space conversion module, which is configured to perform normalization processing on each candidate color in the candidate color set to convert each candidate color from the representation of the first color space to the representation of the second color space; a bright color selection module, which is configured to detect and determine the third target color in the candidate color set based on the representation of the second color space, whose saturation and / or brightness meets its corresponding preset color difference condition, retain the third target color in the candidate color set, and delete all other candidate colors; a space restoration module, which is configured to use the candidate color set containing only the third target color as the target color set, and convert and restore the target colors in the target color set to the representation of the first color space.

[0140] On the basis of any embodiment of the device of the present application, after the color optimization module, it includes: a color-deficient generation module, which is configured to determine whether the number of colors in the target color set is zero. When it is zero, it calls a preset color matching generation model to generate a target color set that meets the preset color matching conditions according to the image information and / or text information in the music introduction information; a color-deficient supplement module, which is configured to continue to determine whether the number of colors in the target color set is lower than a preset lower limit threshold when the number of colors in the target color set is not zero. When it is lower, it calls a preset color matching generation model to use the target colors in the target color set as a benchmark and refer to the image information and / or text information in the music introduction information to generate a target color set that meets the preset color matching conditions; a residual color filtering module, which is configured to determine whether the number of colors in the target color set exceeds a preset upper limit threshold. When it exceeds, it retains multiple target colors with the highest frequency in the target color set according to the preset upper limit threshold and deletes other redundant target colors.

[0141] Based on any embodiment of the device of the present application, the template matching module 5300 includes: a description acquisition module, configured to obtain a description information set of each lighting effect template in a lighting effect template library, wherein the description information set of each lighting effect template provides description information of the lighting effect template from multiple preset description dimensions; a prompt construction module, configured to call a preset matching instruction set, and combine it with the text information in the music introduction information, the description information set of each lighting effect template, and the target color set to form matching prompt information, wherein the matching instruction set includes a first control instruction and a second control instruction that are executed successively, the first control instruction being used to instruct the lighting effect matching model to first determine, based on each description information set, a subset of lighting effect templates that semantically matches the text information in the music introduction information; the second control instruction being used to instruct the lighting effect matching model to score each lighting effect template in the lighting effect template subset from multiple description dimensions, and then fuse them to determine the total score of each lighting effect template, and select the lighting effect template with the highest total score as the target lighting effect template; and a target determination module being configured to input the matching prompt information into the lighting effect matching model to obtain the target lighting effect template determined by the lighting effect matching model.

[0142] In order to solve the above technical problems, the embodiment of the present application also provides a computer device. Figure 4 As shown, a schematic diagram of the internal structure of a computer device. The computer device includes a processor, a computer-readable storage medium, a memory, and a network interface connected via a system bus. Among them, the computer-readable storage medium of the computer device stores an operating system, a database, and computer-readable instructions, and the database may store a control information sequence, and when the computer-readable instructions are executed by the processor, the processor may implement a method for controlling the lighting effects of an atmosphere lamp. The processor of the computer device is used to provide computing and control capabilities to support the operation of the entire computer device. The memory of the computer device may store computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor may execute the method for controlling the lighting effects of an atmosphere lamp of the present application. The network interface of the computer device is used to connect and communicate with a terminal. Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0143] In this embodiment, the processor is used to execute Figure 3The memory stores the program code and various data required to execute the specific functions of each module and its submodule. The network interface is used to transmit data between user terminals or servers. The memory in this embodiment stores the program code and data required to execute all modules / submodules in the ambient lighting lighting effect control device of this application. The server can call the server's program code and data to execute the functions of all submodules.

[0144] The present application also provides a storage medium storing computer-readable instructions. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the ambient lighting lighting effect control method of any embodiment of the present application.

[0145] Those skilled in the art will appreciate that all or part of the processes in the above-described embodiments of the present application can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes in the above-described embodiments of the method. The aforementioned storage medium can be a computer-readable storage medium such as a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0146] Those skilled in the art will understand that the various operations, methods, steps, measures, and schemes in the processes discussed in this application may be interchanged, changed, combined, or deleted. Furthermore, other steps, measures, and schemes in the various operations, methods, and processes discussed in this application may also be interchanged, changed, rearranged, decomposed, combined, or deleted. Furthermore, the steps, measures, and schemes in the various operations, methods, and processes in the prior art that are open source and disclosed in this application may also be interchanged, changed, rearranged, decomposed, combined, or deleted.

[0147] The above description is only part of the implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for controlling lighting effects of an ambient lighting fixture, characterized in that: include: Obtain music introduction information of the target music; determining a target color set for generating lighting effect control information based on the image information in the music introduction information; According to the text information in the music introduction information, matching a target lighting effect template for generating the lighting effect control information from a lighting effect template library; The target color set is inserted into the target lighting effect template to obtain the lighting effect control information, and the atmosphere lighting fixture is controlled to play the corresponding lighting effect according to the lighting effect control information.

2. The method for controlling lighting effects of ambient lighting according to claim 1, wherein: Get the target song's introduction information, including: Collecting ambient audio data through an audio pickup unit, and determining whether the ambient audio data contains human voice audio data; When the human voice audio data exists, identifying a target music that matches the environmental audio data from a music database; The music introduction information of the target music is obtained from the music database, wherein the music introduction information includes preset image information and text information corresponding to the target music, and the image information and text information are each represented separately on different information carriers, or are integrated with each other and represented on the same information carrier.

3. The method for controlling lighting effects of ambient lighting according to claim 1, wherein: Determining a target color set for generating lighting effect control information based on image information in the music introduction information includes: performing image compression on the original image carrying the image information in the music introduction information to obtain an image of target specifications carrying the image information; Counting the frequency of occurrence of each color in the pixel set of the target specification image, and determining the multiple colors with the highest frequency of occurrence to form a candidate color set; It is detected whether each color in the candidate color set meets a preset color difference condition, and the colors that do not meet the color difference condition are deleted to obtain the target color set.

4. The method for controlling lighting effects of ambient lighting according to claim 3, wherein: After determining the multiple colors with the highest frequency of occurrence to form a candidate color set, including: identifying, based on each color component corresponding to each color defined in the first color space, a first target color in the candidate color set whose each color component is lower than a preset first component threshold, and deleting the first target color from the candidate color set; Based on the color components, a second target color in the candidate color set whose absolute difference between any two color components is lower than a preset second component threshold is identified, and the second target color is deleted from the candidate color set.

5. The method for controlling lighting effects of ambient lighting according to claim 3, wherein: Detecting whether each color in the candidate color set meets a preset color difference condition, and deleting colors that do not meet the color difference condition to obtain the target color set, including: performing a normalization process on each candidate color in the candidate color set to convert each candidate color from a representation in a first color space to a representation in a second color space; Based on the representation of the second color space, detecting and determining a third target color in the candidate color set whose saturation and / or brightness satisfies a corresponding preset color difference condition, retaining the third target color in the candidate color set, and deleting all other candidate colors; The candidate color set containing only the third target color is used as the target color set, and the target colors in the target color set are converted and restored to representations in the first color space.

6. The method for controlling lighting effects of ambient lighting according to claim 3, wherein: After detecting whether each color in the candidate color set meets a preset color difference condition and deleting colors that do not meet the color difference condition to obtain the target color set, the method includes: determining whether the number of colors in the target color set is zero, and if so, calling a preset color matching generation model to generate a target color set that meets preset color matching conditions based on the image information and / or text information in the music introduction information; When the number of colors in the target color set is not zero, further determining whether the number of colors in the target color set is lower than a preset lower threshold, and if so, calling a preset color matching generation model to generate a target color set that meets a preset color matching condition, taking the target colors in the target color set as a benchmark and referring to the image information and / or text information in the music introduction information; Determine whether the number of colors in the target color set exceeds a preset upper threshold. If so, retain the target colors with the highest frequency in the target color set according to the preset upper threshold and delete other redundant target colors.

7. The method for controlling lighting effects of ambient lighting according to any one of claims 1 to 6, wherein: According to the text information in the music introduction information, a target lighting effect template for generating the lighting effect control information is matched from a lighting effect template library, including: Obtaining a description information set of each lighting effect template in the lighting effect template library, wherein the description information set of each lighting effect template provides description information of the lighting effect template from multiple preset description dimensions; A preset matching instruction set is called and combined with the text information in the music introduction information, the description information sets of each lighting effect template, and the target color set to form matching prompt information, wherein the matching instruction set includes a first control instruction and a second control instruction that are executed successively, the first control instruction being used to instruct the lighting effect matching model to first determine, based on each description information set, a subset of lighting effect templates that semantically matches the text information in the music introduction information; the second control instruction being used to instruct the lighting effect matching model to score each lighting effect template in the lighting effect template subset based on multiple description dimensions, and then to fuse and determine the total score of each lighting effect template, and select the lighting effect template with the highest total score as the target lighting effect template; The matching prompt information is input into the lighting effect matching model to obtain the target lighting effect template determined by the lighting effect matching model.

8. A lighting effect control device for an ambient lighting fixture, characterized in that: include: An information acquisition module configured to acquire music introduction information of a target music piece; a color matching determination module configured to determine a target color set for generating lighting effect control information based on image information in the music introduction information; a template matching module configured to match a target lighting effect template for generating the lighting effect control information from a lighting effect template library based on the text information in the music introduction information; The lighting effect control module is configured to insert the target color set into the target lighting effect template to obtain the lighting effect control information, and control the atmosphere lighting to play the corresponding lighting effect according to the lighting effect control information.

9. An ambient lighting fixture, comprising a controller and at least one lighting fixture unit, wherein the controller is in communication with the lighting fixture unit, wherein: The controller is used to execute the steps of the ambient lighting lighting effect control method according to any one of claims 1 to 7 to control the lighting unit to display the lighting effect.

10. A computer-readable storage medium, characterized in that It stores a computer program implemented according to the method described in any one of claims 1 to 7 in the form of computer-readable instructions, and when the computer program is called and executed by a computer, the steps included in the corresponding method are executed.

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