CN115315038A - Method and device for adjusting color temperature and color rendering of LED device - Google Patents
Method and device for adjusting color temperature and color rendering of LED device Download PDFInfo
- Publication number
- CN115315038A CN115315038A CN202211230750.9A CN202211230750A CN115315038A CN 115315038 A CN115315038 A CN 115315038A CN 202211230750 A CN202211230750 A CN 202211230750A CN 115315038 A CN115315038 A CN 115315038A
- Authority
- CN
- China
- Prior art keywords
- parameter
- color temperature
- color
- led device
- instruction
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
- H05B—ELECTRIC HEATING; ELECTRIC LIGHT SOURCES NOT OTHERWISE PROVIDED FOR; CIRCUIT ARRANGEMENTS FOR ELECTRIC LIGHT SOURCES, IN GENERAL
- H05B45/00—Circuit arrangements for operating light-emitting diodes [LED]
- H05B45/10—Controlling the intensity of the light
-
- H—ELECTRICITY
- H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
- H05B—ELECTRIC HEATING; ELECTRIC LIGHT SOURCES NOT OTHERWISE PROVIDED FOR; CIRCUIT ARRANGEMENTS FOR ELECTRIC LIGHT SOURCES, IN GENERAL
- H05B45/00—Circuit arrangements for operating light-emitting diodes [LED]
- H05B45/20—Controlling the colour of the light
-
- H—ELECTRICITY
- H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
- H05B—ELECTRIC HEATING; ELECTRIC LIGHT SOURCES NOT OTHERWISE PROVIDED FOR; CIRCUIT ARRANGEMENTS FOR ELECTRIC LIGHT SOURCES, IN GENERAL
- H05B47/00—Circuit arrangements for operating light sources in general, i.e. where the type of light source is not relevant
- H05B47/10—Controlling the light source
- H05B47/165—Controlling the light source following a pre-assigned programmed sequence; Logic control [LC]
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B20/00—Energy efficient lighting technologies, e.g. halogen lamps or gas discharge lamps
- Y02B20/40—Control techniques providing energy savings, e.g. smart controller or presence detection
Abstract
The application provides a method and a device for adjusting color temperature and color rendering of an LED device, a computer readable medium and electronic equipment. The method for adjusting the color temperature and the color rendering of the LED device comprises the following steps: taking a historical instruction and a label parameter corresponding to the historical instruction as training data, training a preset semantic analysis model based on the training data, performing semantic analysis on an adjusting instruction based on the trained semantic analysis model, determining a color temperature parameter and a color development parameter corresponding to the adjusting instruction, and determining a control parameter corresponding to the color temperature parameter and the color development parameter based on configuration information of an LED device; and finally, generating a control instruction corresponding to the control parameter so as to send the control instruction to the LED device through a driving circuit. According to the technical scheme, the light emitting condition of the LED device can be controlled by directly identifying the semantic information of the user, and the light emitting control efficiency of the LED light source is improved.
Description
Technical Field
The application relates to the technical field of computers, in particular to a method and a device for adjusting color temperature and color rendering of an LED device, a computer readable medium and electronic equipment.
Background
In the process of controlling the light source device, manual control is required to be performed through a remote controller or other control devices, the requirement on hardware is high in the mode, for example, the working state of the light source is controlled by manually contacting the control device, and particularly under some special requirements, the requirement of a user cannot be met frequently, so that the problem of low light source control efficiency is caused.
Disclosure of Invention
The application provides a method and a device for adjusting color temperature and color rendering of an LED device, a computer readable medium and electronic equipment, so that light source control efficiency can be improved at least to a certain extent.
Other features and advantages of the present application will be apparent from the following detailed description, or may be learned by practice of the application.
According to an aspect of the present application, there is provided a method of adjusting color temperature and color rendering of an LED device, including: acquiring an adjusting instruction of the LED device; acquiring a historical instruction and a label parameter corresponding to the historical instruction as training data, and training a preset semantic analysis model based on the training data; wherein the label parameters comprise a color temperature label and a color development label; performing semantic analysis on the adjusting instruction based on a semantic analysis model obtained by training, and determining a corresponding color temperature parameter and a corresponding color development parameter in the adjusting instruction; determining control parameters corresponding to the color temperature parameter and the color rendering parameter based on configuration information of the LED device; and generating a control instruction corresponding to the control parameter, and sending the control instruction to the LED device through a driving circuit.
In this application, based on the foregoing scheme, the obtaining of the historical instruction and the tag parameter corresponding thereto as training data, training a preset semantic analysis model based on the training data, includes: acquiring a historical instruction and a label parameter corresponding to the historical instruction as training data, and constructing a semantic analysis model based on a convolutional neural network, wherein the semantic analysis model comprises the following steps: a convolutional layer, a pooling layer, and a full link layer; inputting the training data into the semantic analysis model, and outputting a recognition result; and comparing the recognition result with the label parameters to determine a training loss so as to update the semantic analysis model based on the training loss.
In this application, based on the foregoing solution, the determining, based on configuration information of an LED device, a control parameter corresponding to the color temperature parameter and the color rendering parameter includes: acquiring configuration information of the LED device, wherein the configuration information comprises combination information, arrangement information and power information of light-emitting components; and determining control parameters corresponding to the LED device based on the combination information, the arrangement information and the power information of the light-emitting components, the color temperature parameter and the color rendering parameter.
In this application, based on the foregoing solution, determining the control parameters corresponding to the LED device based on the combination information, the arrangement information, and the power information of the light emitting components, the color temperature parameter, and the color rendering parameter includes: determining the number and identification of target light emitting components in the light emitting components based on the combination information of the light emitting components and the color temperature parameter; determining the working power of the target light-emitting component based on the number, the identification and the color development parameter of the target light-emitting component; taking the number, identification and the operating power of the target light emitting assembly as the control parameters.
In this application, based on the foregoing scheme, the color temperature parameter includes a color temperature level, and the color rendering parameter includes a color rendering level.
In this application, based on the foregoing scheme, after the generating a control instruction corresponding to the control parameter and sending the control instruction to the LED lamp through the driving circuit, the method further includes: detecting real-time color temperature parameters and real-time color rendering parameters corresponding to the LED devices; comparing the real-time color temperature parameter and the real-time color rendering parameter with the color temperature parameter and the color rendering parameter respectively, and determining a first difference parameter and a second difference parameter which correspond to the color temperature parameter and the color rendering parameter respectively; and judging whether the LED device needs to be readjusted or not based on the first difference parameter and the second difference parameter.
In this application, based on the foregoing scheme, comparing the real-time color temperature parameter and the real-time color rendering parameter with the color temperature parameter and the color rendering parameter, respectively, and determining a first difference parameter and a second difference parameter corresponding to the two parameters, respectively, includes: determining the first difference parameter based on a difference between the real-time color temperature parameter and the color temperature parameter; determining the second difference parameter based on a difference between the real-time rendering parameter and the rendering parameter.
According to an aspect of the present application, there is provided an apparatus for adjusting color temperature and color rendering of an LED apparatus, comprising:
the acquisition unit is used for acquiring an adjusting instruction of the LED device;
the training unit is used for acquiring the historical instruction and the label parameters corresponding to the historical instruction as training data and training a preset semantic analysis model based on the training data; wherein the label parameters comprise a color temperature label and a color development label;
the analysis unit is used for carrying out semantic analysis on the adjusting instruction based on a semantic analysis model obtained by training and determining a corresponding color temperature parameter and a corresponding color development parameter in the adjusting instruction;
the parameter unit is used for determining control parameters corresponding to the color temperature parameters and the color rendering parameters based on configuration information of the LED device;
and the control unit is used for generating a control instruction corresponding to the control parameter and sending the control instruction to the LED device through the driving circuit.
In this application, based on the foregoing scheme, the obtaining of the historical command and the corresponding tag parameter thereof as training data, training a preset semantic analysis model based on the training data, includes: acquiring a history instruction and a label parameter corresponding to the history instruction as training data, and constructing a semantic analysis model based on a convolutional neural network, wherein the semantic analysis model comprises the following steps: a convolutional layer, a pooling layer, and a full link layer; inputting the training data into the semantic analysis model, and outputting a recognition result; comparing the recognition result with the label parameter to determine a training loss, so as to update the semantic analysis model based on the training loss.
In this application, based on the foregoing scheme, the determining, based on configuration information of the LED device, a control parameter corresponding to the color temperature parameter and the color rendering parameter includes: acquiring configuration information of the LED device, wherein the configuration information comprises combination information, arrangement information and power information of light-emitting components; and determining control parameters corresponding to the LED device based on the combination information, the arrangement information and the power information of the light-emitting components, the color temperature parameter and the color rendering parameter.
In this application, based on the foregoing solution, determining the control parameters corresponding to the LED device based on the combination information, the arrangement information, and the power information of the light emitting components, the color temperature parameter, and the color rendering parameter includes: determining the number and identification of target light emitting components in the light emitting components based on the combination information of the light emitting components and the color temperature parameter; determining the working power of the target light-emitting component based on the number, the identification and the color development parameters of the target light-emitting component; taking the number, identification and the operating power of the target light emitting assembly as the control parameters.
In this application, based on the foregoing scheme, the color temperature parameter includes a color temperature level, and the color rendering parameter includes a color rendering level.
In this application, based on the foregoing solution, the device for adjusting color temperature and color rendering of an LED device further includes: detecting real-time color temperature parameters and real-time color development parameters corresponding to the LED devices; comparing the real-time color temperature parameter and the real-time color rendering parameter with the color temperature parameter and the color rendering parameter respectively, and determining a first difference parameter and a second difference parameter which correspond to the color temperature parameter and the color rendering parameter respectively; and judging whether the LED device needs to be readjusted or not based on the first difference parameter and the second difference parameter.
In this application, based on the foregoing scheme, comparing the real-time color temperature parameter and the real-time color rendering parameter with the color temperature parameter and the color rendering parameter, respectively, and determining a first difference parameter and a second difference parameter corresponding to the two parameters, respectively, includes: determining the first difference parameter based on a difference between the real-time color temperature parameter and the color temperature parameter; determining the second difference parameter based on a difference between the real-time rendering parameter and the rendering parameter.
According to an aspect of the present application, a computer-readable medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, is adapted to carry out the method of adjusting the color temperature and the color rendering of an LED arrangement as described above.
According to an aspect of the present application, there is provided an electronic device including: one or more processors; a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method of adjusting the color temperature and color rendering of an LED device as described above.
According to an aspect of the application, a computer program product or computer program is provided, comprising computer instructions, the computer instructions being stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the method for adjusting the color temperature and the color rendering of the LED device provided in the above various alternative implementations.
In the technical scheme provided by the application, a historical instruction and a label parameter corresponding to the historical instruction are used as training data, a preset semantic analysis model is trained on the basis of the training data, then semantic analysis is carried out on an adjusting instruction on the basis of the semantic analysis model obtained through training, a color temperature parameter and a color development parameter corresponding to the adjusting instruction are determined, and a control parameter corresponding to the color temperature parameter and the color development parameter is determined on the basis of configuration information of an LED device; and finally, generating a control instruction corresponding to the control parameter so as to send the control instruction to the LED device through a driving circuit. According to the technical scheme, the light emitting condition of the LED device can be controlled by directly identifying the semantic information of the user, and the light emitting control efficiency of the LED light source is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. It is obvious that the drawings in the following description are only some embodiments of the application, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
Fig. 1 schematically shows a flow chart of a method of adjusting the color temperature and color rendering of an LED arrangement according to an embodiment of the application.
Fig. 2 schematically shows a flow chart for determining a control parameter according to an embodiment of the application.
Fig. 3 schematically shows a schematic diagram of an arrangement for adjusting the color temperature and color rendering of an LED arrangement according to an embodiment of the application.
FIG. 4 illustrates a schematic structural diagram of a computer system suitable for use to implement the electronic device of the embodiments of the subject application.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the subject matter of the present application can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the application.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The flowcharts shown in the figures are illustrative only and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
The implementation details of the technical solution of the embodiment of the present application are set forth in detail below:
fig. 1 shows a flow chart of a method of adjusting the color temperature and color rendering of an LED arrangement according to an embodiment of the application. Referring to fig. 1, the method for adjusting the color temperature and color rendering of the LED device at least includes steps S110 to S150, which are described in detail as follows:
in step S110, an adjustment instruction of the LED device is acquired.
In one embodiment of the application, a user sends an adjusting instruction in the case that the light and the lighting condition of the LED light source or the device need to be adjusted. The adjusting instruction can be information such as voice, text and the like. For example, the light source is controlled by voice, and the light emission level information of the light source is selected in a mobile phone terminal or a remote controller to control the light emission of the LED device.
In step S120, acquiring a history instruction and a tag parameter corresponding to the history instruction as training data, and training a preset semantic analysis model based on the training data; the label parameters comprise a color temperature label and a color development label.
In an embodiment of the present application, by obtaining a history instruction and a tag parameter corresponding to the history instruction, and using the information as training data, the tag parameter in the embodiment includes a color temperature tag and a color rendering tag. Wherein, the color temperature label represents words or data related to color temperature in the instruction, such as primary color temperature, secondary color temperature, cold light and warm light; and the text in the color development label instruction is related to the color development degree, such as the color development index, the color development degree and the like.
A semantic analysis model is constructed based on a convolutional neural network, and specifically, the semantic analysis model in this embodiment includes a multilayer structure: the method comprises the following steps of convolutional layer, pooling and full-link layer, wherein the convolutional layer has the function of carrying out feature extraction on input data, the convolutional layer internally comprises a plurality of convolutional kernels, and each element forming the convolutional kernels corresponds to a weight coefficient and a deviation value; after the feature extraction is carried out on the convolutional layer, the output feature graph is transmitted to a pooling layer for feature selection and information filtering, the pooling layer comprises a preset pooling function, and the function of the pooling function is to replace the result of a single point in the feature graph with feature graph statistics of an adjacent area; the fully-connected layer is located at the last part of the hidden layer of the convolutional neural network and only signals are transmitted to other fully-connected layers.
In the training process, training data is input into a semantic analysis model, a recognition result is output, and then the recognition result is based on the recognition result
And label parameters
Comparing, calculating the training loss
Comprises the following steps:
wherein i represents a numberAccording to the dimensions, the total k dimensions of the data are provided, each dimension is used for representing the depth of semantic recognition,
and
respectively representing the identification result and the label parameter corresponding to each dimension. After the training loss is obtained through calculation, parameter memorability in the semantic analysis model is adjusted and updated based on the training loss, and in such a way, circulation is carried out, so that a final semantic analysis model is obtained, and accurate control information is obtained through the semantic analysis model.
In step S130, based on the trained semantic analysis model, performing semantic analysis on the adjustment instruction, and determining a color temperature parameter and a color rendering parameter corresponding to the adjustment instruction.
In an embodiment of the application, after the semantic analysis model is obtained through training, the semantic analysis is performed on the adjustment instruction through the model, and then the color temperature parameter and the color development parameter are determined.
Specifically, in the operation process of the semantic analysis model, an adjustment instruction is input, the adjustment instruction can be in an audio form or a text form, and then the color temperature parameter and the color development parameter corresponding to the adjustment instruction are output through the semantic analysis model.
In step S140, control parameters corresponding to the color temperature parameter and the color rendering parameter are determined based on configuration information of the LED device.
In one embodiment of the application, after the color temperature parameter and the color rendering parameter are obtained, the corresponding control parameter is determined based on the configuration information of the LED device.
In an embodiment of the application, the process of determining the control parameters corresponding to the color temperature parameter and the color rendering parameter based on the configuration information of the LED device in step S130 includes:
acquiring configuration information of the LED device, wherein the configuration information comprises combination information, arrangement information and power information of light-emitting components;
and determining control parameters corresponding to the LED device based on the combination information, the arrangement information and the power information of the light-emitting components, the color temperature parameter and the color rendering parameter.
In an embodiment of the present application, the configuration information of the LED device includes combination information, arrangement information, and power information of the light emitting elements. Specifically, the combination information of the light emitting components may be how many light emitting components are included in the LED device, the light emitting colors of the respective components, and the like; the arrangement information includes position information of the light emitting assembly in the LED device, and the power information includes power of the light emitting assembly at the time of actual operation. According to the scheme, the control parameters corresponding to the LED device are determined by combining the color temperature parameters and the color rendering parameters input by the user.
It should be noted that, in the present embodiment, the color temperature parameter includes a color temperature level, and the color rendering parameter includes a color rendering level, such as a primary color temperature, a secondary color rendering, and so on, so as to accurately measure the color temperature and the color rendering condition when the light source emits light through the level information.
In an embodiment of the application, as shown in fig. 2, the determining the control parameters corresponding to the LED device based on the combination information, the arrangement information, and the power information of the light emitting components, the color temperature parameter, and the color rendering parameter in the above process includes:
s210, determining the number and the identification of target light-emitting components in the light-emitting components based on the combination information of the light-emitting components and the color temperature parameter;
s220, determining the working power of the target light-emitting assembly based on the number, the identification and the color development parameters of the target light-emitting assembly;
and S230, taking the number, the identification and the working power of the target light-emitting components as the control parameters.
Specifically, the number and identification of target light emitting components among the light emitting components are first determined based on the combination information of the light emitting components and the color temperature parameter. Illustratively, when the color temperature parameter is first-level warm light, the target light-emitting assembly is a warm light assembly in the light-emitting assemblies, that is, light source assemblies such as red and yellow, and meanwhile, based on the warm light level and a preset light source correspondence, the light-emitting quantity is determined, that is, the quantity of the target light-emitting assembly is finally obtained, and the identifier of the light source assembly needing to emit light is determined.
Determining the working power of the target light-emitting component based on the number, the identification and the color development parameters of the target light-emitting component. For example, when the color rendering parameter is a secondary color rendering parameter, the working power corresponding to the target light emitting assembly of each identifier is determined based on a preset color rendering relationship and the number of the target light emitting assemblies, and then the number of the target light emitting assemblies, the identifiers, and the working power are used as the control parameters.
In step S150, a control command corresponding to the control parameter is generated and sent to the LED device through the driving circuit.
In one embodiment of the present application, after acquiring the control parameters, the control instruction is determined based on the control parameters, for example, the light source assemblies identified as "aa", "bb", "ss" in the LED device emit light, and wherein the brightness of the light source assemblies "aa", "bb" is of one level and the brightness of the light source assembly "ss" is of two levels.
In an embodiment of the present application, after the step S150 generates a control instruction corresponding to the control parameter and sends the control instruction to the LED lamp through the driving circuit, the method further includes:
detecting real-time color temperature parameters and real-time color development parameters corresponding to the LED devices;
comparing the real-time color temperature parameter and the real-time color rendering parameter with the color temperature parameter and the color rendering parameter respectively, and determining a first difference parameter and a second difference parameter which respectively correspond to the color temperature parameter and the color rendering parameter;
and judging whether the LED device needs to be readjusted or not based on the first difference parameter and the second difference parameter.
In the process, the real-time color temperature parameter and the real-time color rendering parameter corresponding to the LED device are compared, and the first difference parameter and the second difference parameter respectively corresponding to the LED device are determined, so that the difference between the light emitting condition of the LED device and the actual instruction is detected through the parameters, and whether the LED device needs to be readjusted or not is judged.
In an embodiment of the application, the comparing the real-time color temperature parameter and the real-time color rendering parameter with the color temperature parameter and the color rendering parameter respectively in the above process, and determining a first difference parameter and a second difference parameter corresponding to the real-time color temperature parameter and the real-time color rendering parameter respectively includes:
determining the first difference parameter based on a difference between the real-time color temperature parameter and the color temperature parameter;
determining the second difference parameter based on a difference between the real-time rendering parameter and the rendering parameter.
In an embodiment of the present application, the real-time color temperature parameter is based on
And the color temperature parameter
The difference between them, determining the first difference parameter
Comprises the following steps:
based on the real-time color rendering parameters
And the color development parameter
The difference between them, determining the second difference parameter
Comprises the following steps:
in an embodiment of the present application, after obtaining a first difference parameter and a second difference parameter by calculation, based on the first difference parameter and the second difference parameter, and by weighting the first difference parameter and the second difference parameter, the calibration parameter obtained by calculation is:
wherein the content of the first and second substances,
for representing a preset difference factor. The above-mentioned mode obtains calibration parameter through first difference parameter and the calculation of second difference parameter, later compares calibration parameter and preset calibration threshold value, if calibration parameter is greater than or equal to the calibration threshold value, then need readjust the LED device to guarantee that the light that the LED device distributed can be unanimous with the light illumination degree that adjustment command corresponds, and then improve the accuracy nature and the degree of automation of light source show greatly.
In the technical solutions provided by some embodiments of the present application, a historical instruction and a tag parameter corresponding to the historical instruction are used as training data, a preset semantic analysis model is trained based on the training data, then semantic analysis is performed on an adjustment instruction based on the semantic analysis model obtained by training, a color temperature parameter and a color development parameter corresponding to the adjustment instruction are determined, and a control parameter corresponding to the color temperature parameter and the color development parameter is determined based on configuration information of an LED device; and finally, generating a control instruction corresponding to the control parameter so as to send the control instruction to the LED device through a driving circuit. According to the technical scheme of the embodiment of the application, the light emitting condition of the LED device can be controlled by directly identifying the semantic information of the user, and the light emitting control efficiency of the LED light source is improved.
Embodiments of the device of the present application are described below, which can be used to perform the methods of adjusting the color temperature and color rendering of the LED device in the above-described embodiments of the present application. It will be appreciated that the apparatus may be a computer program (comprising program code) running on a computer device, for example an application software; the apparatus may be used to perform the corresponding steps in the methods provided by the embodiments of the present application. For details that are not disclosed in the embodiments of the device of the present application, please refer to the embodiments of the method for adjusting the color temperature and the color rendering of the LED device described above in the present application.
Fig. 3 shows a block diagram of an apparatus for adjusting color temperature and color rendering of an LED arrangement according to an embodiment of the present application.
Referring to fig. 3, an apparatus for adjusting color temperature and color rendering of an LED apparatus according to an embodiment of the present application includes:
an obtaining unit 310, configured to obtain an adjustment instruction of the LED device;
the training unit 320 is configured to acquire a historical instruction and a tag parameter corresponding to the historical instruction as training data, and train a preset semantic analysis model based on the training data; the label parameters comprise a color temperature label and a color development label;
the analysis unit 330 is configured to perform semantic analysis on the adjustment instruction based on the trained semantic analysis model, and determine a color temperature parameter and a color development parameter corresponding to the adjustment instruction;
a parameter unit 340, configured to determine, based on configuration information of the LED device, a control parameter corresponding to the color temperature parameter and the color rendering parameter;
and a control unit 350, configured to generate a control instruction corresponding to the control parameter, and send the control instruction to the LED device through the driving circuit.
In some embodiments of the present application, based on the foregoing scheme, the obtaining of the historical instruction and the tag parameter corresponding to the historical instruction is used as training data, and training a preset semantic analysis model based on the training data includes: acquiring a historical instruction and a label parameter corresponding to the historical instruction as training data, and constructing a semantic analysis model based on a convolutional neural network, wherein the semantic analysis model comprises the following steps: a convolutional layer, a pooling layer, and a full link layer; inputting the training data into the semantic analysis model, and outputting a recognition result; comparing the recognition result with the label parameter to determine a training loss, so as to update the semantic analysis model based on the training loss.
In some embodiments of the application, based on the foregoing solution, the determining, based on configuration information of the LED device, a control parameter corresponding to the color temperature parameter and the color rendering parameter includes: acquiring configuration information of the LED device, wherein the configuration information comprises combination information, arrangement information and power information of light-emitting components; and determining control parameters corresponding to the LED device based on the combination information, the arrangement information and the power information of the light-emitting components, the color temperature parameter and the color rendering parameter.
In some embodiments of the present application, based on the foregoing solution, the determining the control parameter corresponding to the LED device based on the combination information, the arrangement information, and the power information of the light emitting components, and the color temperature parameter and the color rendering parameter includes: determining the number and identification of target light-emitting components in the light-emitting components based on the combination information of the light-emitting components and the color temperature parameter; determining the working power of the target light-emitting component based on the number, the identification and the color development parameter of the target light-emitting component; taking the number, identification and the operating power of the target light emitting assembly as the control parameters.
In some embodiments of the present application, the color temperature parameter includes a color temperature level, and the color rendering parameter includes a color rendering level.
In some embodiments of the present application, based on the foregoing solution, the apparatus for adjusting color temperature and color rendering of an LED apparatus further includes: detecting real-time color temperature parameters and real-time color development parameters corresponding to the LED devices; comparing the real-time color temperature parameter and the real-time color rendering parameter with the color temperature parameter and the color rendering parameter respectively, and determining a first difference parameter and a second difference parameter which respectively correspond to the color temperature parameter and the color rendering parameter; and judging whether the LED device needs to be readjusted or not based on the first difference parameter and the second difference parameter.
In some embodiments of the present application, based on the foregoing solution, the comparing the real-time color temperature parameter and the real-time color rendering parameter with the color temperature parameter and the color rendering parameter respectively, and determining a first difference parameter and a second difference parameter corresponding to the real-time color temperature parameter and the real-time color rendering parameter respectively includes: determining the first difference parameter based on a difference between the real-time color temperature parameter and the color temperature parameter; determining the second difference parameter based on a difference between the real-time rendering parameter and the rendering parameter.
In the technical solutions provided by some embodiments of the present application, a historical instruction and a tag parameter corresponding to the historical instruction are used as training data, a preset semantic analysis model is trained based on the training data, then semantic analysis is performed on an adjustment instruction based on the semantic analysis model obtained by training, a color temperature parameter and a color development parameter corresponding to the adjustment instruction are determined, and a control parameter corresponding to the color temperature parameter and the color development parameter is determined based on configuration information of an LED device; and finally, generating a control instruction corresponding to the control parameter so as to send the control instruction to the LED device through a driving circuit. According to the technical scheme, the light emitting condition of the LED device can be controlled by directly identifying the semantic information of the user, and the light emitting control efficiency of the LED light source is improved.
FIG. 4 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application.
It should be noted that the computer system 400 of the electronic device shown in fig. 4 is only an example, and should not bring any limitation to the functions and the scope of the application of the embodiments.
As shown in fig. 4, the computer system 400 includes a Central Processing Unit (CPU) 401, which can perform various appropriate actions and processes, such as executing the methods described in the above embodiments, according to a program stored in a Read-Only Memory (ROM) 402 or a program loaded from a storage section 408 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data necessary for system operation are also stored. The CPU 401, ROM 402, and RAM 403 are connected to each other via a bus 404. An Input/Output (I/O) interface 405 is also connected to the bus 404.
The following components are connected to the I/O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output section 407 including a Display device such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and a speaker; a storage section 408 including a hard disk and the like; and a communication section 409 including a Network interface card such as a LAN (Local Area Network) card, a modem, or the like. The communication section 409 performs communication processing via a network such as the internet. A drive 410 is also connected to the I/O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 410 as necessary, so that a computer program read out therefrom is mounted into the storage section 408 as necessary.
In particular, according to embodiments of the application, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 409, and/or installed from the removable medium 411. The computer program executes various functions defined in the system of the present application when executed by a Central Processing Unit (CPU) 401.
It should be noted that the computer readable media shown in the embodiments of the present application may be computer readable signal media or computer readable storage media or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM), a flash Memory, an optical fiber, a portable Compact Disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer-readable signal medium may include a propagated data signal with a computer program embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves.
According to an aspect of the application, a computer program product or computer program is provided, comprising computer instructions, the computer instructions being stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method provided in the above-mentioned various alternative implementation modes.
As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiment; or may be separate and not incorporated into the electronic device. The computer readable medium carries one or more programs, which when executed by one of the electronic devices, cause the electronic device to implement the method described in the above embodiments.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the application. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains.
It will be understood that the present application is not limited to the precise arrangements that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (10)
1. A method of adjusting color temperature and color rendering of an LED device, comprising:
acquiring an adjusting instruction of the LED device;
acquiring a historical instruction and a label parameter corresponding to the historical instruction as training data, and training a preset semantic analysis model based on the training data; the label parameters comprise a color temperature label and a color development label;
performing semantic analysis on the adjusting instruction based on a semantic analysis model obtained by training, and determining a color temperature parameter and a color development parameter corresponding to the adjusting instruction;
determining control parameters corresponding to the color temperature parameter and the color rendering parameter based on configuration information of the LED device;
and generating a control instruction corresponding to the control parameter, and sending the control instruction to the LED device through a driving circuit.
2. The method according to claim 1, wherein the step of obtaining a historical command and a corresponding label parameter thereof as training data, and training a preset semantic analysis model based on the training data comprises:
acquiring a history instruction and a label parameter corresponding to the history instruction as training data, and constructing a semantic analysis model based on a convolutional neural network, wherein the semantic analysis model comprises the following steps: convolutional layers, pooling, and full-link layers;
inputting the training data into the semantic analysis model, and outputting a recognition result;
comparing the recognition result with the label parameter to determine a training loss, so as to update the semantic analysis model based on the training loss.
3. The method of claim 2, wherein determining the control parameters corresponding to the color temperature parameter and the color rendering parameter based on configuration information of the LED device comprises:
acquiring configuration information of the LED device, wherein the configuration information comprises combination information, arrangement information and power information of light-emitting components;
and determining control parameters corresponding to the LED device based on the combination information, the arrangement information and the power information of the light-emitting components, the color temperature parameter and the color rendering parameter.
4. The method of claim 3, wherein determining the corresponding control parameters of the LED device based on the combination information, the arrangement information, and the power information of the light emitting components, and the color temperature parameter and the color rendering parameter comprises:
determining the number and identification of target light-emitting components in the light-emitting components based on the combination information of the light-emitting components and the color temperature parameter;
determining the working power of the target light-emitting component based on the number, the identification and the color development parameter of the target light-emitting component;
taking the number, identification and the operating power of the target light emitting assembly as the control parameters.
5. The method of claim 1, wherein the color temperature parameter comprises a color temperature level and the color rendering parameter comprises a color rendering level.
6. The method of claim 1, wherein after generating a control command corresponding to the control parameter and sending the control command to the LED device through the driving circuit, the method further comprises:
detecting real-time color temperature parameters and real-time color development parameters corresponding to the LED devices;
comparing the real-time color temperature parameter and the real-time color rendering parameter with the color temperature parameter and the color rendering parameter respectively, and determining a first difference parameter and a second difference parameter which correspond to the color temperature parameter and the color rendering parameter respectively;
and judging whether the LED device needs to be readjusted or not based on the first difference parameter and the second difference parameter.
7. The method of claim 6, wherein comparing the real-time color temperature parameter and the real-time color rendering parameter with the color temperature parameter and the color rendering parameter, respectively, and determining a first difference parameter and a second difference parameter corresponding to the color temperature parameter and the color rendering parameter, respectively, comprises:
determining the first difference parameter based on a difference between the real-time color temperature parameter and the color temperature parameter;
determining the second difference parameter based on a difference between the real-time rendering parameter and the rendering parameter.
8. An apparatus for adjusting color temperature and color rendering of an LED device, comprising:
the acquisition unit is used for acquiring an adjusting instruction of the LED device;
the training unit is used for acquiring a historical instruction and a label parameter corresponding to the historical instruction as training data and training a preset semantic analysis model based on the training data; wherein the label parameters comprise a color temperature label and a color development label;
the analysis unit is used for carrying out semantic analysis on the adjusting instruction based on a semantic analysis model obtained by training and determining a corresponding color temperature parameter and a corresponding color development parameter in the adjusting instruction;
the parameter unit is used for determining control parameters corresponding to the color temperature parameters and the color rendering parameters based on configuration information of the LED device;
and the control unit is used for generating a control instruction corresponding to the control parameter and sending the control instruction to the LED device through the driving circuit.
9. A computer-readable medium, on which a computer program is stored which, when being executed by a processor, carries out the method of adjusting the color temperature and the color rendering of an LED arrangement according to any one of claims 1 to 7.
10. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method of adjusting color temperature and color rendering of an LED arrangement of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211230750.9A CN115315038B (en) | 2022-10-10 | 2022-10-10 | Method and device for adjusting color temperature and color rendering of LED device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211230750.9A CN115315038B (en) | 2022-10-10 | 2022-10-10 | Method and device for adjusting color temperature and color rendering of LED device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115315038A true CN115315038A (en) | 2022-11-08 |
| CN115315038B CN115315038B (en) | 2023-06-23 |
Family
ID=83867027
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211230750.9A Active CN115315038B (en) | 2022-10-10 | 2022-10-10 | Method and device for adjusting color temperature and color rendering of LED device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115315038B (en) |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106851927A (en) * | 2017-04-19 | 2017-06-13 | 慈溪锐恩电子科技有限公司 | A kind of multichannel light modulation toning LED drive circuit of speech recognition |
| CN108738215A (en) * | 2018-06-05 | 2018-11-02 | 信利光电股份有限公司 | A kind of automatic adjustment desk lamp technical parameter method, apparatus and desk lamp |
| US20180366086A1 (en) * | 2017-06-19 | 2018-12-20 | Guangdong Oppo Mobile Telecommunications Corp., Lt D. | Method and device for adjusting color temperature of screen, and electronic device |
| CN109890106A (en) * | 2018-11-02 | 2019-06-14 | 中国计量大学 | Hotel's individualized intelligent lighting device, System and method for based on user identity automatic identification |
| CN110108008A (en) * | 2019-05-20 | 2019-08-09 | 珠海格力电器股份有限公司 | Control method, device and the air-conditioning of voice air conditioner light |
| CN111862974A (en) * | 2020-07-15 | 2020-10-30 | 广州三星通信技术研究有限公司 | Control method of intelligent equipment and intelligent equipment |
| US20210029789A1 (en) * | 2018-10-05 | 2021-01-28 | Ledvance Llc | Predictive smart light control |
| CN112612992A (en) * | 2020-12-24 | 2021-04-06 | 东莞锐视光电科技有限公司 | Color temperature optimization method and device, terminal equipment and storage medium |
| CN113347768A (en) * | 2021-06-04 | 2021-09-03 | 深圳市欧瑞博科技股份有限公司 | Intelligent light regulation and control method and device, electronic equipment and storage medium |
| CN114205949A (en) * | 2022-02-17 | 2022-03-18 | 东莞锐视光电科技有限公司 | Method and system for controlling multiple LED light sources based on light source controller |
| CN114245514A (en) * | 2021-12-15 | 2022-03-25 | 广州中大中鸣科技有限公司 | Self-adaptive color temperature adjusting method and device, electronic equipment and storage medium |
| US20220139096A1 (en) * | 2021-03-10 | 2022-05-05 | Beijing Baidu Netcom Science Technology Co., Ltd. | Character recognition method, model training method, related apparatus and electronic device |
| US20220141931A1 (en) * | 2020-10-30 | 2022-05-05 | Savant Technologies Llc | System for Controlling Lamp, Circadian Lamp and Holiday Lamp |
-
2022
- 2022-10-10 CN CN202211230750.9A patent/CN115315038B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106851927A (en) * | 2017-04-19 | 2017-06-13 | 慈溪锐恩电子科技有限公司 | A kind of multichannel light modulation toning LED drive circuit of speech recognition |
| US20180366086A1 (en) * | 2017-06-19 | 2018-12-20 | Guangdong Oppo Mobile Telecommunications Corp., Lt D. | Method and device for adjusting color temperature of screen, and electronic device |
| CN108738215A (en) * | 2018-06-05 | 2018-11-02 | 信利光电股份有限公司 | A kind of automatic adjustment desk lamp technical parameter method, apparatus and desk lamp |
| US20210029789A1 (en) * | 2018-10-05 | 2021-01-28 | Ledvance Llc | Predictive smart light control |
| CN109890106A (en) * | 2018-11-02 | 2019-06-14 | 中国计量大学 | Hotel's individualized intelligent lighting device, System and method for based on user identity automatic identification |
| CN110108008A (en) * | 2019-05-20 | 2019-08-09 | 珠海格力电器股份有限公司 | Control method, device and the air-conditioning of voice air conditioner light |
| CN111862974A (en) * | 2020-07-15 | 2020-10-30 | 广州三星通信技术研究有限公司 | Control method of intelligent equipment and intelligent equipment |
| US20220141931A1 (en) * | 2020-10-30 | 2022-05-05 | Savant Technologies Llc | System for Controlling Lamp, Circadian Lamp and Holiday Lamp |
| CN112612992A (en) * | 2020-12-24 | 2021-04-06 | 东莞锐视光电科技有限公司 | Color temperature optimization method and device, terminal equipment and storage medium |
| US20220139096A1 (en) * | 2021-03-10 | 2022-05-05 | Beijing Baidu Netcom Science Technology Co., Ltd. | Character recognition method, model training method, related apparatus and electronic device |
| CN113347768A (en) * | 2021-06-04 | 2021-09-03 | 深圳市欧瑞博科技股份有限公司 | Intelligent light regulation and control method and device, electronic equipment and storage medium |
| CN115023004A (en) * | 2021-06-04 | 2022-09-06 | 深圳市欧瑞博科技股份有限公司 | Intelligent light regulation and control method and device |
| CN114245514A (en) * | 2021-12-15 | 2022-03-25 | 广州中大中鸣科技有限公司 | Self-adaptive color temperature adjusting method and device, electronic equipment and storage medium |
| CN114205949A (en) * | 2022-02-17 | 2022-03-18 | 东莞锐视光电科技有限公司 | Method and system for controlling multiple LED light sources based on light source controller |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115315038B (en) | 2023-06-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107766940B (en) | Method and apparatus for generating a model | |
| CN110766142A (en) | Model generation method and device | |
| US11580299B2 (en) | Corpus cleaning method and corpus entry system | |
| CN112749081B (en) | User interface testing method and related device | |
| CN113327136B (en) | Attribution analysis method, attribution analysis device, electronic equipment and storage medium | |
| CN107909638A (en) | Rendering intent, medium, system and the electronic equipment of dummy object | |
| CN111695594A (en) | Image category identification method and device, computer equipment and medium | |
| Kwasniewska et al. | Deep learning optimization for edge devices: Analysis of training quantization parameters | |
| CN113435582A (en) | Text processing method based on sentence vector pre-training model and related equipment | |
| CN114676279A (en) | Image retrieval method, device, equipment and computer readable storage medium | |
| CN112269875B (en) | Text classification method, device, electronic equipment and storage medium | |
| CN115315038B (en) | Method and device for adjusting color temperature and color rendering of LED device | |
| CN116108276A (en) | Information recommendation method and device based on artificial intelligence and related equipment | |
| WO2022252694A1 (en) | Neural network optimization method and apparatus | |
| CN112233194B (en) | Medical picture optimization method, device, equipment and computer readable storage medium | |
| CN115470900A (en) | Pruning method, device and equipment of neural network model | |
| WO2022086728A1 (en) | Multi-task learning via gradient split for rich human analysis | |
| CN116685030B (en) | Light source state control method, controller, computer readable medium and electronic device | |
| CN115835453B (en) | Method, device, medium and electronic equipment for adjusting light parameters of light source | |
| WO2024002026A1 (en) | Energy-consumption optimization method, system and apparatus, and storage medium | |
| US20220391732A1 (en) | Continuous optimization of human-algorithm collaboration performance | |
| US20230229736A1 (en) | Embedding optimization for a machine learning model | |
| CN117132303A (en) | Price prediction method and system based on artificial intelligence and big data | |
| CN117972515A (en) | Coal mine subsystem classification method and device based on information system architecture model | |
| CN118043826A (en) | Prediction model creation method, prediction model creation device, prediction model creation program, and prediction program |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |