Brightness adjustment method and device, storage medium and electronic device

Abstract

The application discloses a brightness adjusting method and device, a storage medium and an electronic device, and relates to the technical field of refrigerators. The method comprises the following steps: when a target object is detected by an infrared sensor of a refrigerator, an image acquisition device on the refrigerator is used to acquire an image of a target area where the refrigerator is located, and a target picture is obtained; a first brightness detection algorithm is used to determine a first brightness corresponding to the target picture, and a second brightness detection algorithm is used to determine a second brightness corresponding to the target picture; the environment brightness of the target area is determined according to the first brightness and the second brightness, and the brightness of a display of the refrigerator is adjusted according to the environment brightness. By using the technical scheme, the problem that the brightness of the display of the refrigerator cannot be automatically adjusted when the refrigerator does not have a photosensitive element is solved.

Description

Technical Field

[0001] This invention relates to the field of communications, and more specifically, to a brightness adjustment method and apparatus, a storage medium, and an electronic device. Background Technology

[0002] With the advancement of science and technology and the development of artificial intelligence, intelligent algorithms are increasingly being applied to daily life. Especially for refrigerators, as one of the most frequently used household appliances, the development of their intelligence is crucial. The key issue of intelligence lies in providing convenience for daily life and how to make refrigerators intelligent.

[0003] Current technology uses human body sensors to control the smart screen on and off of refrigerators. When someone approaches the refrigerator, the infrared sensor detects the person and controls the smart screen to light up; when the person leaves, the screen turns off. Therefore, automatically adjusting the brightness of the smart screen when it's on becomes crucial. Newly manufactured refrigerators, equipped with photosensors, can determine the ambient brightness through hardware. However, refrigerators that are manufactured without photosensors cannot determine the ambient brightness and thus cannot automatically adjust the screen's brightness.

[0004] Regarding the issue that refrigerators without photosensitive elements cannot automatically adjust the brightness of their displays, no effective solution has yet been proposed.

[0005] Therefore, it is necessary to improve the relevant technology to overcome the aforementioned defects. Summary of the Invention

[0006] This invention provides a brightness adjustment method and apparatus, a storage medium and an electronic device, to at least solve the problem that refrigerators without photosensitive elements cannot automatically adjust the brightness of the refrigerator's display.

[0007] According to one aspect of the present invention, a brightness adjustment method is provided, wherein when a target object is detected by an infrared sensor of a refrigerator, an image acquisition device on the refrigerator is used to acquire an image of the target area where the refrigerator is located to obtain a target image; a first brightness of the target image is determined by a first brightness detection algorithm, and a second brightness of the target image is determined by a second brightness detection algorithm; the ambient brightness of the target area is determined based on the first brightness and the second brightness, and the brightness of the refrigerator's display is adjusted based on the ambient brightness.

[0008] Further, determining the first brightness of the target image using a first brightness detection algorithm includes: weighted summation of the pixel values ​​of each pixel in the RGB channel of the target image to obtain the grayscale value of each pixel; weighted summation of the grayscale values ​​of all pixels in the target image to obtain the grayscale value of the target image; and determining the brightness of the target image based on the correspondence between the grayscale value and the brightness of the target image.

[0009] Further, determining the second brightness of the target image using a second brightness detection algorithm includes: determining a brightness detection model from multiple neural network models of the refrigerator, wherein the brightness detection model is a model trained with multiple sets of data, each set of data including: a sample image, the brightness of the sample image; sending the target image to the brightness detection model to obtain the second brightness of the target image.

[0010] Further, determining the ambient brightness of the target area based on the first brightness and the second brightness includes: determining a first weight value for the first brightness and a second weight value for the second brightness; and determining the sum of the product of the first brightness and the first weight value and the product of the second brightness and the second weight value as the ambient brightness of the target area.

[0011] Further, adjusting the brightness of the refrigerator display according to the ambient brightness includes: determining the target brightness of the refrigerator display according to the ambient brightness; and adjusting the brightness of the refrigerator display to the target brightness.

[0012] Further, determining the target brightness of the refrigerator's display based on the ambient brightness includes: determining a preset brightness range in which the ambient brightness is located, and determining the preset brightness corresponding to the preset brightness range as the target brightness; or determining the target brightness of the refrigerator's display based on the correspondence between the ambient brightness and the brightness of the refrigerator's display.

[0013] Furthermore, after adjusting the brightness of the refrigerator's display to the target brightness, the method further includes: when a target object is detected touching the refrigerator's display brightness control component, determining a third brightness determined by the display brightness control component; adjusting target parameters according to the third brightness and the ambient brightness; wherein the target parameters include: a first weight value and a second weight value.

[0014] According to another aspect of the present invention, a brightness adjustment device is also provided, comprising: an acquisition module, configured to acquire an image of the target area where the refrigerator is located by means of an image acquisition device on the refrigerator when a target object is detected by an infrared sensor of the refrigerator, thereby obtaining a target image; a determination module, configured to determine a first brightness of the target image by means of a first brightness detection algorithm, and a second brightness of the target image by means of a second brightness detection algorithm; and an adjustment module, configured to determine the ambient brightness of the target area based on the first brightness and the second brightness, and adjust the brightness of the refrigerator's display based on the ambient brightness.

[0015] According to another aspect of the present invention, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer program, wherein the computer program is configured to execute the above-described brightness adjustment method when running.

[0016] According to another aspect of the present invention, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the brightness adjustment method described above through the computer program.

[0017] This invention, when a target object is detected by the refrigerator's infrared sensor, captures an image of the target area using an image acquisition device on the refrigerator, obtaining a target image. A first brightness detection algorithm is then used to determine the first brightness of the target image, and a second brightness detection algorithm is used to determine the second brightness. Based on the first and second brightness levels, the ambient brightness of the target area is determined, and the brightness of the refrigerator's display is adjusted accordingly. This technical solution solves the problem that refrigerators without photosensitive elements cannot automatically adjust the brightness of their displays. It allows for the acquisition of images of the refrigerator's area, determination of the area's brightness from the images, and automatic adjustment of the refrigerator's display brightness, thus improving the user experience. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with the description thereof, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0019] Figure 1 This is a hardware structure block diagram of a computer terminal for the brightness adjustment method according to an embodiment of the present invention;

[0020] Figure 2 This is a flowchart (a) of a brightness adjustment method according to an embodiment of the present invention;

[0021] Figure 3This is a flowchart (II) of a brightness adjustment method according to an embodiment of the present invention;

[0022] Figure 4 This is a flowchart of the brightness detection algorithm according to an embodiment of the present invention;

[0023] Figure 5 This is a structural diagram of a neural network model according to an embodiment of the present invention;

[0024] Figure 6 This is a structural block diagram of a brightness adjustment device according to an embodiment of the present invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] The methods and embodiments provided in this application can be executed on a computer terminal or similar computing device. Taking running on a computer terminal as an example, Figure 1 This is a hardware structure block diagram of a computer terminal for the brightness adjustment method according to an embodiment of the present invention. Figure 1 As shown, a computer terminal may include one or more ( Figure 1Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor unit (MPU) or a programmable logic device (PLD)) and a memory 104 for storing data are also shown. In one exemplary embodiment, the computer terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the computer terminal described above. For example, the computer terminal may also include components that are more complex than those described above. Figure 1 The more or fewer components shown, or having the same Figure 1 Equivalent functions or ratios shown Figure 1 The functions shown have more different configurations.

[0028] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the brightness adjustment method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to a computer terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0029] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider for the computer terminal. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0030] To address the aforementioned problems, this embodiment provides a brightness adjustment method. Figure 2 This is a flowchart (I) of a brightness adjustment method according to an embodiment of the present invention, which includes the following steps:

[0031] Step S202: When the target object is detected by the infrared sensor of the refrigerator, the target area where the refrigerator is located is captured by the image acquisition device on the refrigerator to obtain a target image;

[0032] In one exemplary embodiment, the image acquisition device includes, but is not limited to, a camera. After the refrigerator's infrared sensor detects that a user is approaching the refrigerator, the camera on the refrigerator will acquire a target image of the area where the refrigerator is located.

[0033] Step S204: Determine the first brightness of the target image using a first brightness detection algorithm, and determine the second brightness of the target image using a second brightness detection algorithm;

[0034] It should be noted that the first brightness detection algorithm is a non-neural network algorithm, while the second brightness detection algorithm is a neural network algorithm.

[0035] It should be noted that since the brightness of the image is determined differently by different methods, in order to more accurately determine the brightness of the area where the refrigerator is located from the image, two different algorithms can be used to determine the brightness of the image separately, and then the brightness determined by the two methods can be used together to determine the ambient brightness of the area where the refrigerator is located.

[0036] It should be noted that the unit of brightness is candela per square meter. For example, the first brightness is 200 candela per square meter.

[0037] Step S206: Determine the ambient brightness of the target area based on the first brightness and the second brightness, and adjust the brightness of the refrigerator's display based on the ambient brightness.

[0038] In the above steps, when the target object is detected by the refrigerator's infrared sensor, an image acquisition device on the refrigerator acquires an image of the target area where the refrigerator is located, obtaining a target image. A first brightness detection algorithm is then used to determine the first brightness of the target image, and a second brightness detection algorithm is used to determine the second brightness. Based on the first and second brightness levels, the ambient brightness of the target area is determined, and the brightness of the refrigerator's display is adjusted accordingly. This technical solution solves the problem that refrigerators without photosensitive elements cannot automatically adjust the brightness of their displays. It allows for the acquisition of images of the area where the refrigerator is located, the determination of the area's brightness based on the images, and the automatic adjustment of the refrigerator's display brightness, thus improving the user experience.

[0039] In an optional embodiment, if the target object is detected by the refrigerator's infrared sensor, multiple images can be captured within 1 second by the image acquisition device on the refrigerator, and the ambient brightness of the area where the refrigerator is located can be determined by the multiple images.

[0040] In an exemplary embodiment, the first brightness of the target image is determined by the first brightness detection algorithm, which can be achieved by: weighted summing of the pixel values ​​of each pixel in the RGB channel of the target image to obtain the grayscale value of each pixel; weighted summing of the grayscale values ​​of all pixels in the target image to obtain the grayscale value of the target image; and determining the brightness of the target image based on the correspondence between the grayscale value and the brightness of the target image.

[0041] It's important to note that an image is composed of multiple pixels, each with three channels: the R channel, the G channel, and the B channel. Each pixel has a corresponding pixel value across these three channels, ranging from 0 to 255. The weighted sum of these RGB channel values ​​for each pixel is then used to determine its grayscale value. For example, image A has 9 pixels. Pixel A has a value of 100 in the R channel, 150 in the G channel, and 200 in the B channel. Assuming we use the average value, the grayscale value of pixel A is (100 + 150 + 200) / 3 = 150.

[0042] Furthermore, the grayscale values ​​of all pixels in the image are weighted and summed to obtain the grayscale value of the image. For image A, the grayscale values ​​of the 9 pixels in image A are weighted and summed, and the result of the weighted sum is determined as the grayscale value of image A. Finally, the brightness of image A is determined by the correspondence between the image grayscale value and the ambient brightness.

[0043] Optionally, the second brightness of the target image can be determined by the second brightness detection algorithm in the following way: a brightness detection model is determined from multiple neural network models of the refrigerator, wherein the brightness detection model is a model trained by multiple sets of data, each set of data including: a sample image and the brightness of the sample image; the target image is sent to the brightness detection model to obtain the second brightness corresponding to the target image.

[0044] In other words, a brightness detection module can be pre-trained. Specifically, multiple sample images and the brightness of the environment corresponding to each sample image can be input into the neural network model for training, allowing the neural network model to determine the brightness of the environment based on the images. That is, the second brightness of the environment where the refrigerator is located is determined by the neural network model.

[0045] In an exemplary embodiment, determining the ambient brightness of the target area based on the first brightness and the second brightness can be achieved by: determining a first weight value for the first brightness and a second weight value for the second brightness; and determining the ambient brightness of the target area by summing the product of the first brightness and the first weight value and the product of the second brightness and the second weight value. That is, after determining the first brightness of the target area using a first brightness detection algorithm and the second brightness of the target area using a second brightness detection algorithm, the final ambient brightness of the target area needs to be determined by combining the first brightness, the second brightness, and their respective weight values. It should be noted that the sum of the first weight value and the second weight value can be 1.

[0046] Assuming the target area brightness determined by the first brightness detection algorithm is 200, and the target area brightness determined by the second brightness detection algorithm is 220, with their respective weight values ​​of 0.4 and 0.6, then the final target area brightness is 200*0.4 + 220*0.6 = 212.

[0047] In one exemplary embodiment, adjusting the brightness of the refrigerator display based on ambient brightness can be achieved by: determining a target brightness for the refrigerator display based on the ambient brightness; and adjusting the brightness of the refrigerator display to the target brightness.

[0048] In an exemplary embodiment, the target brightness of the refrigerator's display can be determined based on the ambient brightness in the following ways: determining a preset brightness range in which the ambient brightness is located, and setting the preset brightness corresponding to the preset brightness range as the target brightness; or determining the target brightness of the refrigerator's display based on the correspondence between the ambient brightness and the brightness of the refrigerator's display.

[0049] Assuming the refrigerator's display brightness is determined by brightness levels (e.g., 0-10), with different levels corresponding to different brightness levels, multiple brightness ranges can be preset, each corresponding to a brightness level on the refrigerator. For example, if the ambient brightness of the target area is 200 candela per square meter, and the refrigerator's display brightness is represented by levels, such as 0-10, and 200 candela falls within the fifth preset range, which corresponds to the fifth brightness level on the refrigerator's display, then the refrigerator's display brightness can be adjusted to the level corresponding to that fifth brightness level.

[0050] Assuming the brightness of the refrigerator's display is determined by a brightness value (e.g., 0-100), a functional relationship can be established between the ambient brightness and the display's brightness value. This function is then used to calculate the display's brightness value.

[0051] In an optional embodiment, after adjusting the brightness of the refrigerator's display to the target brightness, if a target object is detected touching the refrigerator's display brightness control component, a third brightness determined by the display brightness control component is determined for the target object; and target parameters are adjusted according to the third brightness and the ambient brightness; wherein the target parameters include: a first weight value and a second weight value.

[0052] Understandably, if the user adjusts the monitor's brightness after it has been automatically determined, it means the automatically determined brightness does not meet the user's needs. Therefore, the target parameter needs to be adjusted based on the user's manual adjustment and the ambient brightness determined from the image. For example, if the user's manually adjusted third brightness is greater than the target brightness, the target parameter is adjusted to make the ambient brightness closer to the third brightness. Then, the adjusted target parameter is used to determine the ambient brightness of the refrigerator's location the next time the monitor's brightness is automatically adjusted.

[0053] Obviously, the embodiments described above are merely some embodiments of the present invention, and not all embodiments. To better understand the above brightness adjustment method, the process is described below with reference to embodiments, but this is not intended to limit the technical solutions of the embodiments of the present invention. Specifically:

[0054] In an optional embodiment, Figure 3 This is a flowchart (II) of the brightness adjustment method according to an embodiment of the present invention, specifically:

[0055] Step S1: Capture images using a camera (equivalent to the image acquisition device in the above embodiment);

[0056] Step S2: Determine the first brightness of the image using a traditional brightness detection algorithm (equivalent to the first brightness detection algorithm in the above embodiment), and determine the second brightness of the image using a deep learning algorithm (equivalent to the second brightness detection algorithm in the above embodiment);

[0057] Step S3: Weighted fusion of the first brightness and the second brightness;

[0058] Step S4: Output the brightness of the environment (equivalent to the second brightness in the above embodiment);

[0059] Step S5: Adjust the brightness of the refrigerator's smart screen (equivalent to the display in the above embodiment) based on the ambient brightness.

[0060] Through the above steps, the ambient light intensity is detected by using real-time images captured by the camera on the refrigerator's smart display screen. Then, the brightness of the smart screen is adjusted according to the detected results, achieving adaptive brightness adjustment of the smart screen.

[0061] It should be noted that this embodiment achieves ambient light intensity detection by combining a brightness detection algorithm and a deep learning algorithm. Specifically, Figure 4 This is a flowchart of the brightness detection algorithm according to an embodiment of the present invention, specifically:

[0062] Step S1: Obtain the RGB image:

[0063] Step S2: Convert the RGB image to a grayscale image;

[0064] Specifically, the pixel values ​​of each pixel in the R, G, and B channels are weighted and summed to obtain a grayscale image.

[0065] Step S3: Calculate the average pixel value of each pixel in the grayscale image (equivalent to the pixel value of the image above);

[0066] Step S4: Compare the average value with a threshold;

[0067] Specifically, the brightness of the image corresponding to the average value is determined based on the correspondence between the average value and the brightness.

[0068] Step S5: Output the brightness of the image.

[0069] Figure 5 This is a structural diagram of a neural network model according to an embodiment of the present invention, specifically, as shown below. Figure 5 As shown, the neural network model uses the MobileNet V2 network, which can improve the accuracy of brightness detection.

[0070] Furthermore, the above-mentioned technical solution of the present invention solves the problem that the smart screen of the refrigerator cannot automatically adjust its brightness when there is no photosensitive element. It uses real-time images captured by the camera on the refrigerator screen and image algorithms to detect the brightness of the ambient light. The brightness of the smart screen of the refrigerator is automatically adjusted according to the brightness of the ambient light, thereby achieving the effect of adaptive brightness adjustment of the smart screen of the refrigerator.

[0071] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0072] This embodiment also provides a brightness adjustment device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0073] Figure 6 This is a structural block diagram of a brightness adjustment device according to an embodiment of the present invention, the device comprising:

[0074] The acquisition module 62, when a target object is detected by the infrared sensor of the refrigerator, acquires an image of the target area where the refrigerator is located through the image acquisition device on the refrigerator, and obtains a target image.

[0075] The determining module 64 is used to determine the first brightness of the target image through a first brightness detection algorithm, and to determine the second brightness of the target image through a second brightness detection algorithm;

[0076] The adjustment module 66 is used to determine the ambient brightness of the target area based on the first brightness and the second brightness, and to adjust the brightness of the refrigerator's display based on the ambient brightness.

[0077] With the aforementioned device, when a target object is detected by the refrigerator's infrared sensor, an image acquisition device on the refrigerator captures an image of the target area, obtaining a target image. A first brightness detection algorithm is then used to determine the first brightness of the target image, and a second brightness detection algorithm is used to determine the second brightness. Based on the first and second brightness levels, the ambient brightness of the target area is determined, and the brightness of the refrigerator's display is adjusted accordingly. This technical solution solves the problem that refrigerators without photosensitive elements cannot automatically adjust the brightness of their displays. It allows for the acquisition of images of the refrigerator's area, determination of the area's brightness based on the images, and automatic adjustment of the refrigerator's display brightness, thus improving the user experience.

[0078] In an optional embodiment, if the target object is detected by the refrigerator's infrared sensor, multiple images can be captured within 1 second by the image acquisition device on the refrigerator, and the ambient brightness of the area where the refrigerator is located can be determined by the multiple images.

[0079] In an exemplary embodiment, the determining module 64 is further configured to perform a weighted summation of the pixel values ​​of each pixel in the RGB channel of the target image to obtain the grayscale value of each pixel; perform a weighted summation of the grayscale values ​​of all pixels in the target image to obtain the grayscale value of the target image; and determine the brightness of the target image according to the correspondence between the grayscale value and the brightness of the target image.

[0080] It's important to note that an image is composed of multiple pixels, each with three channels: the R channel, the G channel, and the B channel. Each pixel has a corresponding pixel value across these three channels, ranging from 0 to 255. The weighted sum of these RGB channel values ​​for each pixel is then used to determine its grayscale value. For example, image A has 9 pixels. Pixel A has a value of 100 in the R channel, 150 in the G channel, and 200 in the B channel. Assuming we use the average value, the grayscale value of pixel A is (100 + 150 + 200) / 3 = 150.

[0081] Furthermore, the grayscale values ​​of all pixels in the image are weighted and summed to obtain the grayscale value of the image. For image A, the grayscale values ​​of the 9 pixels in image A are weighted and summed, and the result of the weighted sum is determined as the grayscale value of image A. Finally, the brightness of image A is determined by the correspondence between the image grayscale value and the ambient brightness.

[0082] Optionally, the determining module 64 is further configured to determine a brightness detection model from multiple neural network models of the refrigerator, wherein the brightness detection model is a model trained by multiple sets of data, each set of data including: a sample image, the brightness of the sample image; and send the target image to the brightness detection model to obtain a second brightness corresponding to the target image.

[0083] In other words, a brightness detection module can be pre-trained. Specifically, multiple sample images and the brightness of the environment corresponding to each sample image can be input into the neural network model for training, allowing the neural network model to determine the brightness of the environment based on the images. That is, the second brightness of the environment where the refrigerator is located is determined by the neural network model.

[0084] In an exemplary embodiment, the adjustment module 66 is further configured to determine a first weight value for the first brightness and a second weight value for the second brightness; and to determine the target brightness of the target area by summing the product of the first brightness and the first weight value and the product of the second brightness and the second weight value. That is, after determining the first brightness of the target area using a first brightness detection algorithm and the second brightness of the target area using a second brightness detection algorithm, the final ambient brightness of the target area needs to be determined by combining the first brightness, the second brightness, and their respective weight values. It should be noted that the sum of the first weight value and the second weight value can be 1.

[0085] Assuming the target area brightness determined by the first brightness detection algorithm is 200, and the target area brightness determined by the second brightness detection algorithm is 220, with their respective weight values ​​of 0.4 and 0.6, then the final determined ambient brightness of the target area is 200*0.4 + 220*0.6 = 212.

[0086] In an exemplary embodiment, the adjustment module 66 is further configured to determine the target brightness of the refrigerator's display based on the ambient brightness; and adjust the brightness of the refrigerator's display to the target brightness.

[0087] In an exemplary embodiment, the target brightness of the refrigerator's display can be determined based on the ambient brightness in the following ways: determining a preset brightness range in which the ambient brightness is located, and setting the preset brightness corresponding to the preset brightness range as the target brightness; or determining the target brightness of the refrigerator's display based on the correspondence between the ambient brightness and the brightness of the refrigerator's display.

[0088] Assuming the refrigerator's display brightness is determined by brightness levels (e.g., 0-10), with different levels corresponding to different brightness levels, multiple brightness ranges can be preset, each corresponding to a brightness level on the refrigerator. For example, if the ambient brightness of the target area is 200 candela per square meter, and the refrigerator's display brightness is represented by levels, such as 0-10, and 200 candela falls within the fifth preset range, which corresponds to the fifth brightness level on the refrigerator's display, then the refrigerator's display brightness can be adjusted to the level corresponding to that fifth brightness level.

[0089] Assuming the brightness of the refrigerator's display is determined by a brightness value (e.g., 0-100), a functional relationship can be established between the ambient brightness and the display's brightness value. This function is then used to calculate the display's brightness value.

[0090] In an optional embodiment, the adjustment module 66 is further configured to, upon detecting that a target object touches the display brightness control component of the refrigerator, determine a third brightness of the target object as determined by the display brightness control component; and adjust target parameters according to the third brightness and the ambient brightness; wherein the target parameters include: a first weight value and a second weight value.

[0091] Understandably, if the user adjusts the monitor's brightness after it has been automatically determined, it means the automatically determined brightness does not meet the user's needs. Therefore, the target parameter needs to be adjusted based on the user's manual adjustment and the ambient brightness determined from the image. For example, if the user's manually adjusted third brightness is greater than the target brightness, the target parameter is adjusted to make the ambient brightness closer to the third brightness. Then, the adjusted target parameter is used to determine the ambient brightness of the refrigerator's location the next time the monitor's brightness is automatically adjusted.

[0092] Embodiments of the present invention also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to perform the steps in any of the above method embodiments when executed.

[0093] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0094] S1, when the target object is detected by the infrared sensor of the refrigerator, the target area where the refrigerator is located is captured by the image acquisition device on the refrigerator to obtain a target image;

[0095] S2, determine the first brightness of the target image using a first brightness detection algorithm, and determine the second brightness of the target image using a second brightness detection algorithm;

[0096] S3, determine the ambient brightness of the target area based on the first brightness and the second brightness, and adjust the brightness of the refrigerator's display based on the ambient brightness.

[0097] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0098] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0099] Embodiments of the present invention also provide an electronic device including a memory and a processor, the memory storing a computer program and the processor being configured to run the computer program to perform the steps in any of the above method embodiments.

[0100] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0101] S1, when the target object is detected by the infrared sensor of the refrigerator, the target area where the refrigerator is located is captured by the image acquisition device on the refrigerator to obtain a target image;

[0102] S2, determine the first brightness of the target image using a first brightness detection algorithm, and determine the second brightness of the target image using a second brightness detection algorithm;

[0103] S3, determine the ambient brightness of the target area based on the first brightness and the second brightness, and adjust the brightness of the refrigerator's display based on the ambient brightness.

[0104] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0105] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0106] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0107] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A brightness adjustment method, characterized in that, include: When a target object is detected by the infrared sensor of the refrigerator, an image acquisition device on the refrigerator is used to acquire an image of the target area where the refrigerator is located, thereby obtaining a target image; The first brightness of the target image is determined by a first brightness detection algorithm, and the second brightness of the target image is determined by a second brightness detection algorithm. The ambient brightness of the target area is determined based on the first brightness and the second brightness, and the brightness of the refrigerator's display is adjusted based on the ambient brightness. The first brightness detection algorithm is an algorithm that uses the pixel value of each pixel in the RGB channel to detect the brightness of the image; the second brightness detection algorithm is an algorithm that uses a deep learning algorithm to detect the brightness of the image.

2. The method according to claim 1, characterized in that, Determining the first brightness of the target image using a first brightness detection algorithm includes: The grayscale value of each pixel in the target image is obtained by weighted summing of the pixel values ​​in the RGB channels. The grayscale values ​​of all pixels in the target image are weighted and summed to obtain the grayscale value of the target image. The brightness of the target image is determined based on the correspondence between the grayscale value and the brightness of the target image.

3. The method according to claim 1, characterized in that, Determining the second brightness of the target image using a second brightness detection algorithm includes: A brightness detection model is determined from multiple neural network models of the refrigerator, wherein the brightness detection model is a model trained by multiple sets of data, each set of data including: a sample image, and the brightness of the sample image; The target image is sent to the brightness detection model to obtain the second brightness of the target image.

4. The method according to claim 1, characterized in that, Determining the ambient brightness of the target area based on the first brightness and the second brightness includes: Determine a first weight value for the first brightness and a second weight value for the second brightness; The sum of the product of the first brightness and the first weight value and the product of the second brightness and the second weight value is determined as the ambient brightness of the target area.

5. The method according to claim 4, characterized in that, Adjusting the brightness of the refrigerator's display based on the ambient brightness includes: The target brightness of the refrigerator's display is determined based on the ambient brightness. Adjust the brightness of the refrigerator's display to the target brightness.

6. The method according to claim 5, characterized in that, Determining the target brightness of the refrigerator's display based on the ambient brightness includes: Determine the preset brightness range within which the ambient brightness falls, and set the preset brightness corresponding to the preset brightness range as the target brightness; or The target brightness of the refrigerator's display is determined based on the correspondence between the ambient brightness and the brightness of the refrigerator's display.

7. The method according to claim 5, characterized in that, After adjusting the brightness of the refrigerator's display to the target brightness, the method further includes: If it is detected that a target object touches the display brightness control component of the refrigerator, determine the third brightness adjusted by the target object through the display brightness control component; The target parameters are adjusted based on the third brightness and the ambient brightness; wherein the target parameters include: the first weight value and the second weight value.

8. A brightness adjustment device, characterized in that, include: The acquisition module is used to acquire images of the target area where the refrigerator is located through the image acquisition device on the refrigerator when the target object is detected by the infrared sensor of the refrigerator, so as to obtain a target image; The determining module is used to determine a first brightness of the target image using a first brightness detection algorithm, and to determine a second brightness of the target image using a second brightness detection algorithm; An adjustment module is used to determine the ambient brightness of the target area based on the first brightness and the second brightness, and to adjust the brightness of the refrigerator's display based on the ambient brightness. The first brightness detection algorithm is an algorithm that uses the pixel value of each pixel in the RGB channel to detect the brightness of the image; the second brightness detection algorithm is an algorithm that uses a deep learning algorithm to detect the brightness of the image.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method described in any one of claims 1 to 7.

10. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method described in any one of claims 1 to 7 through the computer program.

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