Laundry washing control method and device

Abstract

The application discloses a clothes washing control method and device, the method comprises the following steps: obtaining a clothes image of clothes to be washed; processing the clothes image to obtain the area where clothes of different materials are located in the clothes image; determining the number of pixel points corresponding to clothes of different materials in each area; determining washing parameters according to the number of pixel points corresponding to clothes of different materials, and controlling a clothes processing device according to the washing parameters. The control method of the application can obtain clothes of different materials by processing the clothes image of clothes to be washed, and determine washing parameters according to the pixel points corresponding to clothes of different materials, so as to ensure that the clothes processing device works with the best washing parameters, the clothes are best washed and protected, the clothes washing effect is effectively improved, and the clothes washing operation is intelligently upgraded.

Description

Technical Field

[0001] This invention relates to the field of household appliance technology, and in particular to a method for controlling laundry washing, a device for controlling laundry washing, an electronic device, and a computer-readable storage medium. Background Technology

[0002] The trend towards smart and interconnected home appliances is rapidly developing, with many appliances now featuring "smart" functions, including washing machines. Typically, smart washing machines automatically calculate the weight of the clothes in the drum using fuzzy weighing algorithms, and then automatically select the appropriate amount of water and detergent based on that weight. This eliminates the need for users to manually set the water volume, making it more convenient and improving the washing machine's intelligence. However, different types of clothing have different densities. Simply weighing the clothes to assess the load and control the water and detergent levels can easily lead to mismatches in water usage and increased wear and tear on clothes. This results in a lower level of intelligence and fails to meet people's demands for a high-quality lifestyle. Summary of the Invention

[0003] This invention aims to at least partially solve one of the technical problems in related technologies. Therefore, the first objective of this invention is to propose a clothing washing control method. By processing images of the clothes to be washed, different materials of clothing can be obtained, and washing parameters can be determined based on the corresponding pixels of different materials. This ensures that the optimal washing parameters are used to control the operation of the clothing processing equipment, resulting in the best washing and care for the clothes, effectively improving the washing effect, and realizing an intelligent upgrade of the clothing washing operation.

[0004] The second objective of this invention is to provide a clothing washing control device.

[0005] The third objective of this invention is to provide an electronic device.

[0006] The fourth objective of this invention is to provide a computer-readable storage medium.

[0007] To achieve the above objectives, a first aspect of the present invention provides a method for controlling the washing of clothes, comprising the following steps: acquiring an image of clothes to be washed; processing the image of clothes to obtain regions of different materials in the image of clothes; determining the number of pixels corresponding to different materials in each region; determining washing parameters based on the number of pixels corresponding to different materials, and controlling the clothes processing equipment based on the washing parameters.

[0008] According to an embodiment of the present invention, a clothing washing control method first acquires an image of the clothing to be washed, processes the image to obtain regions of different materials within the image, determines the number of pixels corresponding to different materials in each region, and finally determines washing parameters based on the number of pixels corresponding to different materials. The method then controls the clothing processing equipment based on these washing parameters. Thus, by processing the image of the clothing to be washed, this method can obtain images of clothing of different materials and determine washing parameters based on the pixels corresponding to each material. This ensures that the optimal washing parameters are used to control the clothing processing equipment, resulting in the best possible washing and care for the clothing, effectively improving the washing effect and achieving an intelligent upgrade in clothing washing operations.

[0009] In addition, the clothing washing control method according to the above embodiments of the present invention may also have the following additional technical features:

[0010] According to one embodiment of the present invention, the washing parameters include the washing water level, wherein determining the washing parameters based on the number of pixels corresponding to different types of clothing includes: obtaining the water absorption coefficient corresponding to the different types of clothing; and determining the washing water level based on the number of pixels corresponding to the different types of clothing and the corresponding water absorption coefficient corresponding to the different types of clothing.

[0011] According to one embodiment of the present invention, the washing water level is calculated using the following formula:

[0012]

[0013] Where l represents the washing water level, w i This represents the water absorption coefficient (s) of the different materials used in the clothing. i This represents the number of pixels corresponding to the different materials of clothing, where N represents the number of types of clothing materials.

[0014] According to one embodiment of the present invention, the washing parameters further include a final washing cycle and a final washing speed. The method further includes: obtaining the washing cycle and maximum washing speed corresponding to the different materials of the clothing; taking the gentlest washing cycle among the washing cycles corresponding to the different materials of the clothing as the final washing cycle, and taking the minimum speed among the maximum washing speeds corresponding to the different materials of the clothing as the final washing speed.

[0015] According to one embodiment of the present invention, processing the clothing image to obtain the regions where clothing of different materials is located in the clothing image includes: using a deep convolutional neural network to segment and predict the clothing image to obtain the regions where clothing of different materials is located.

[0016] According to one embodiment of the present invention, a deep convolutional neural network is used to segment and predict the clothing image to obtain the regions where clothing of different materials are located. This includes: extracting clothing features corresponding to each pixel in the clothing image, and predicting the material classification of each pixel based on the clothing features corresponding to each pixel, so as to obtain the regions where clothing of different materials are located.

[0017] According to one embodiment of the present invention, the clothing washing control method further includes: obtaining the probability value of clothing presence at each pixel in the clothing image; generating a heat map based on the probability value of clothing presence at each pixel; generating a visible image based on the heat map and the clothing image; and controlling the clothing processing device to display the visible image.

[0018] To achieve the above objectives, a second aspect of the present invention provides a clothing washing control device, comprising: an acquisition module for acquiring an image of clothing to be washed; an image processing module for processing the clothing image to obtain regions of clothing of different materials in the clothing image; a determination module for determining the number of pixels corresponding to clothing of different materials in each region, and determining washing parameters based on the number of pixels corresponding to clothing of different materials; and a control module for controlling the clothing processing equipment according to the washing parameters.

[0019] According to an embodiment of the present invention, a clothing washing control device acquires an image of the clothing to be washed via an acquisition module, processes the image via an image processing module to obtain regions of different fabric materials within the image, determines the number of pixels corresponding to different fabric materials within each region via a determination module, and determines washing parameters based on the number of pixels corresponding to different fabric materials. A control module then controls the clothing processing equipment according to these washing parameters. Thus, by processing the image of the clothing to be washed, this device can obtain information about different fabric materials and determine washing parameters based on the corresponding pixels, ensuring that the optimal washing parameters are used to control the clothing processing equipment, resulting in the best possible washing and care for the clothing, effectively improving the washing effect and achieving an intelligent upgrade in clothing washing operations.

[0020] To achieve the above objectives, a third aspect of the present invention provides an electronic device comprising: a memory, a processor, and a laundry washing control program stored in the memory and executable on the processor. When the processor executes the laundry washing control program, it implements the above-described laundry washing control method.

[0021] The electronic device according to the embodiments of the present invention, by executing the above-described clothing washing control method, can ensure that the clothing processing equipment is controlled with the best washing parameters, so that the clothes receive the best washing and care, effectively improving the washing effect of the clothes and realizing the intelligent upgrade of the clothing washing operation.

[0022] To achieve the above objectives, a fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described clothing washing control method.

[0023] According to the computer-readable storage medium of the present invention, by executing the above-described clothing washing control method, it is possible to ensure that the clothing processing equipment is controlled with the best washing parameters, so that the clothes receive the best washing and care, effectively improving the washing effect of the clothes and realizing the intelligent upgrade of the clothing washing operation.

[0024] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0025] Figure 1 A flowchart of a clothing washing control method according to an embodiment of the present invention;

[0026] Figure 2 This is a schematic diagram of the installation of a camera according to an embodiment of the present invention;

[0027] Figure 3 This is a schematic diagram of the area where clothing of different materials is located according to an embodiment of the present invention;

[0028] Figure 4 A flowchart of a clothing washing control method according to a specific embodiment of the present invention;

[0029] Figure 5 This is a block diagram of a clothing washing control device according to an embodiment of the present invention. Detailed Implementation

[0030] The embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0031] The following description, with reference to the accompanying drawings, outlines the clothing washing control method and apparatus, electronic devices, and computer-readable storage media proposed in embodiments of the present invention.

[0032] Figure 1 This is a flowchart of a clothing washing control method according to an embodiment of the present invention. In this embodiment, the clothing washing control method can be applied to a clothing processing device or a server, wherein the clothing processing device includes a washing machine, a dryer combo, a dry cleaning machine, etc.; the server refers to a server that establishes a communication connection with the clothing processing device. For ease of description, a washing machine is used as an example for the following description.

[0033] like Figure 1 As shown, the clothing washing control method of this invention may include the following steps:

[0034] S1, Obtain the image of the clothes to be washed.

[0035] Specifically, the washing machine is equipped with a camera, and the camera's installation position is designed to effectively capture images of the clothes inside the drum. For example, when the washing machine is a front-loading washing machine... Figure 2 As shown, if the washing machine door is on the side, the camera can be positioned in the center of the door, parallel to the horizontal direction, to ensure a complete image of the inside of the drum. If the washing machine is a top-loading model with the door at the top, the camera can be positioned in the center of the door, parallel to the vertical direction, to also capture a complete image of the drum. It's important to note that the camera's installation location is not limited to the washing machine door; it can be placed in other locations as long as a complete image of the drum is captured. Similarly, when the camera is installed on the door, it doesn't have to be in the center; it can be placed in other areas as well, ensuring a complete image of the drum. When the user puts the clothes into the washing machine, closes the door, and presses the start button, the washing machine powers on. At this point, the camera receives a trigger command and begins capturing images of the inside of the drum, including both the clothes and the background area of ​​the drum wall.

[0036] In one possible implementation, the camera sends the acquired images of the clothes to the washing machine control unit, either wirelessly or via wired transmission.

[0037] In another possible implementation, the camera encrypts the acquired images of the clothes before sending them to a server. The server receives the images of the clothes to be washed from the camera. The encryption method used between the washing machine and the server can be found in the field of communication encryption; this embodiment does not specifically limit the encryption method used between the two. Encrypting the images of the clothes before sending them to the server ensures the security of the images during transmission, thereby protecting the user's privacy.

[0038] It's important to note that when the user turns on the washing machine again, adds clothes, and closes the door, the camera receives the trigger command again. It then acquires an image of the inside of the washing machine drum and sends it to the washing machine control unit. This latest image is used as the image for subsequent processing of the clothes. In other words, the washing machine control unit or server updates the image with each received image, using the last received image for subsequent processing to ensure the accuracy of the acquired washing parameters. Furthermore, the command that triggers the camera to capture an image is the washing machine power-on trigger command.

[0039] S2, process the clothing image to obtain the areas where different materials of clothing are located in the clothing image. The materials of the clothing may include: wool, denim, cotton, linen, silk, and down, etc.

[0040] According to one embodiment of the present invention, a deep convolutional neural network is used to process clothing images to obtain the regions where clothing of different materials are located.

[0041] In one possible implementation, the washing machine's control unit uses a deep convolutional neural network to segment and predict the received clothing images to obtain the regions where different materials of clothing are located. Specifically, the clothing features corresponding to each pixel in the clothing image are extracted, and the material classification of each pixel is predicted based on the clothing features corresponding to each pixel to obtain the regions where different materials of clothing are located.

[0042] The deep convolutional neural network can include an upper convolution module and a lower convolution module. The lower convolution module uses dilated convolution to extract the effective features of each pixel in the clothing image. It then performs an upper convolution operation on these effective features to obtain the probability value of clothing presence at each pixel. The probability value ranges from 0 to 1 (0 for no clothing, 1 for clothing). For example, when the clothing image captured by the camera includes both clothing areas and the inner wall of the washing machine drum not covered by clothing, after data processing, the probability value of clothing presence at the pixel corresponding to the inner wall of the washing machine drum not covered by clothing is 0 or close to 0, while the probability value of clothing presence at the pixel corresponding to the location where clothing is completely covered is 1 or close to 1. In this embodiment, the probability threshold for clothing presence can be set to 0.8. When the probability value of clothing presence is less than or equal to 0.8, it is considered that there is no clothing, and the material classification of that pixel is non-clothing. When the probability of clothing presence is greater than 0.8, clothing is considered present. For pixels with a probability greater than 0.8, the material category of each pixel is predicted based on its corresponding clothing features. Finally, based on the location of pixels with a probability greater than 0.8 and their material categories, the location regions of different materials of clothing in the clothing image are determined, thereby determining the location regions of different materials of clothing inside the washing machine drum.

[0043] In another possible implementation, after sending the encrypted image of the clothes to the server, the washing machine camera also sends a prediction request. This prediction request asks the server to predict the clothing regions and materials within the sent image. Upon receiving the prediction request, the server uses a deep convolutional neural network to segment and predict the different materials of the clothing in the received image. The specific calculation method is as described above and will not be repeated here.

[0044] S3, determine the number of pixels corresponding to different clothing materials in each area.

[0045] In other words, after obtaining the number of pixels corresponding to different clothing materials within the area according to the above steps, for example, ... Figure 3 As shown, 1 represents the area containing cotton, 2 represents the area containing linen, 3 represents the area containing silk, 4 represents the area containing wool, and 5 represents the non-clothing area. Therefore, determining the number of pixels corresponding to different clothing materials in each area means: obtaining the number of pixels corresponding to cotton clothing in area 1, the number of pixels corresponding to linen clothing in area 2, the number of pixels corresponding to silk clothing in area 3, and the number of pixels corresponding to wool clothing in area 4, that is, obtaining the number of pixels in each area.

[0046] S4 determines the washing parameters based on the number of pixels corresponding to different types of clothing, and controls the clothing processing equipment according to the washing parameters.

[0047] According to one embodiment of the present invention, the washing parameters may include the washing water level. Determining the washing parameters based on the number of pixels corresponding to different fabric materials includes: obtaining the water absorption coefficient corresponding to different fabric materials; and determining the washing water level based on the number of pixels corresponding to different fabric materials and their corresponding water absorption coefficients.

[0048] Specifically, the first step is to obtain the water absorption coefficients for different fabric materials. These coefficients can be determined through conventional experiments. For example, a unit area of ​​fabric can be placed in water at room temperature and standard atmospheric pressure until saturated, and the weight of the remaining water can be measured. The weight of the remaining water is then subtracted from the initial weight of the water to obtain the absorbed mass of the fabric during the experiment. The ratio of the absorbed mass to the original weight of the fabric is the water absorption coefficient for each material. Alternatively, the water absorption coefficients for different fabric materials can be set based on the standard water absorption coefficients of similar fabrics available on the market. Then, the washing water level is calculated using the following formula, based on the number of pixels corresponding to different fabric materials and their respective water absorption coefficients.

[0049]

[0050] Where l represents the washing water level, w i The coefficient of water absorption (s) represents the water absorption coefficient of clothing made of different materials. i This represents the number of pixels corresponding to different clothing materials, where N represents the number of different clothing material types. The above formula yields the optimal washing water level, ensuring washing effectiveness while avoiding water waste.

[0051] In one embodiment of the present invention, the washing parameters may further include the final washing cycle and the final washing speed. Before controlling the garment processing equipment according to the washing parameters, the method further includes: obtaining the washing cycle and the maximum washing speed corresponding to different types of garments; taking the gentlest washing cycle among the washing cycles corresponding to different types of garments as the final washing cycle, and taking the minimum speed among the maximum washing speeds corresponding to different types of garments as the final washing speed.

[0052] Specifically, different fabric materials have varying washing tolerances, making the setting of the washing cycle and spin speed particularly important. Before executing a washing program based on washing parameters, the final washing cycle and spin speed of the garment processing equipment should be confirmed. The washing cycle is one of the main factors affecting the washing performance and wear resistance of a washing machine. Theoretically, a stronger washing cycle improves washing performance but also increases wear and tear. In daily life, we often see clothes worn down after repeated washing; therefore, the washing cycle needs more scientific design research. Washing cycle design mainly includes washing acceleration, maximum washing speed, washing cycle ON time, and washing cycle OFF time. Washing acceleration refers to the acceleration of the washing machine during the process of reaching its maximum speed. Maximum washing speed refers to the highest speed the washing machine can reach. Washing cycle ON time and washing cycle OFF time refer to the time the washing machine stops spinning. Washing acceleration has a significant impact on the washing ratio but a smaller impact on the wear rate. Therefore, increasing the washing acceleration can effectively improve the washing ratio. Conversely, setting the washing cycle ON time too long results in a larger increase in the washing ratio, but also a higher wear rate. In this case, reducing the washing ON time to increase the washing frequency can also improve the washing ratio and correspondingly reduce the wear rate. Therefore, the suitable washing cycle for different fabric materials needs to be determined through multiple experiments. Specific experimental procedures refer to the standard GB / T 4288-2018 for household and similar electric washing machines, which will not be elaborated here. The washing cycle and maximum washing speed for different fabric materials measured in the experiments should be pre-stored in the washing machine's memory.

[0053] When needed, the corresponding washing cycle and maximum washing speed are directly retrieved based on the material type. The gentlest and lowest combination of washing cycle and maximum washing speed obtained through the image processing described above is used as the final washing cycle and final washing speed. This ensures that clothes of different materials within the area are in a washing environment with optimal washing parameter control, reducing wear and tear on clothes and guaranteeing washing quality.

[0054] According to one embodiment of the present invention, the clothing washing control method may further include: acquiring the probability value of the presence of clothing at each pixel in the clothing image; generating a heat map based on the probability value of the presence of clothing at each pixel; generating a visible image based on the heat map and the clothing image, and controlling the clothing processing device to display the visible image.

[0055] Specifically, after acquiring the image of the clothing, a deep convolutional neural network is used to process the image, calculating the probability of clothing presence at each pixel based on the image's feature values. The probability values ​​are then correlated with displayed colors, and a heatmap is generated using the deep convolutional neural network. This heatmap, based on the correlation between displayed colors and clothing probability values, is overlaid on the original image of the clothing inside the washing machine drum captured by the camera. This process combines the processed heatmap with the corresponding image to create a visible image. This visible image is then displayed on the washing machine's touchscreen and control panel, allowing users to view it directly. This provides a visible effect to the AI ​​algorithm, enabling users to directly experience the algorithm's effects and understand the location of the clothing inside the washing machine drum. The visible image is displayed on the washing machine's touchscreen for easy viewing.

[0056] In summary, the control unit uses a deep convolutional neural network to segment and predict the image, obtains the regions where clothing of different materials is located, and determines the washing water level based on the sum of pixels corresponding to different materials and the water absorption coefficient corresponding to different materials. It also determines the final washing cycle and final washing speed based on the washing cycle and maximum washing speed corresponding to different materials. In this way, the most suitable washing parameters can be determined to ensure that the best washing parameters are matched to control the clothing processing equipment, so that the clothes can receive the best washing and care.

[0057] As a specific example of the present invention, such as Figure 4 As shown, when the user puts the clothes to be washed into the washing machine equipped with a camera and closes the washing machine door, the clothes washing control method includes the following steps:

[0058] Step 401: The washing machine's camera takes pictures of the clothes inside the drum to obtain images of the clothes to be washed.

[0059] Step 402: The camera encrypts the acquired clothing image and sends it to the server, and also sends a prediction request to the server.

[0060] The prediction request is used to request the server to predict the washing parameters corresponding to the clothing contained in the clothing image.

[0061] Step 403: The server processes the received clothing image using a deep convolutional neural network to obtain the regions where different materials of clothing are located in the clothing image.

[0062] Step 404: The server determines the number of pixels in each area based on the location of clothing of different materials.

[0063] Step 405: The server obtains the water absorption coefficient corresponding to different materials of clothing based on the different materials obtained.

[0064] Step 406: The server multiplies the number of pixels in the area corresponding to each material by the water absorption coefficient of that material, sums the products of all materials based on the product obtained for each material, and determines the washing water level based on the summation result.

[0065] Step 407: The server obtains the washing cycle and maximum washing speed corresponding to different types of clothing.

[0066] Step 408: The server takes the gentlest of the obtained washing beats as the final washing beat corresponding to the garment image; and takes the minimum speed among the obtained maximum washing speeds as the final washing speed.

[0067] Step 409: The server combines the predicted washing water level, final washing cycle time, and final washing spin speed into washing parameters and sends them to the washing machine.

[0068] Step 410: The washing machine washes the clothes to be washed according to the washing parameters sent by the server.

[0069] In summary, the clothing control method according to the embodiments of the present invention can obtain clothing of different materials by processing the image of the clothing to be washed, and determine the washing parameters according to the pixel points corresponding to the different materials of the clothing, so as to ensure that the clothing processing equipment is controlled with the best washing parameters, so that the clothing receives the best washing and care, effectively improving the washing effect of the clothing and realizing the intelligent upgrade of the clothing washing operation.

[0070] Corresponding to the above embodiments, the present invention also proposes a clothing washing control device.

[0071] Figure 5 This is a block diagram of a clothing washing control device according to an embodiment of the present invention.

[0072] like Figure 5 As shown, the clothing washing control device of this embodiment may include: an acquisition module 10, an image processing module 20, a determination module 30, and a control module 40.

[0073] The system includes an acquisition module 10 for acquiring images of clothing, an image processing module 20 for processing the images acquired by the acquisition module 10 to identify areas of different clothing materials within the acquired images, a determination module 30 for determining the number of pixels corresponding to different clothing materials within each area, and determining washing parameters based on the number of pixels corresponding to different clothing materials, and a control module 40 for controlling the clothing processing equipment according to the washing parameters.

[0074] According to one embodiment of the present invention, the image processing module 20 processes the clothing image to obtain the regions where different materials of clothing are located in the clothing image, specifically by: using a deep convolutional neural network to segment and predict the clothing image to obtain the regions where different materials of clothing are located.

[0075] According to one embodiment of the present invention, the image processing module 20 uses a deep convolutional neural network to segment and predict the image to obtain the regions where clothing of different materials are located. Specifically, it is used to: extract the clothing features corresponding to each pixel in the clothing image, and predict the material classification of each pixel based on the clothing features corresponding to each pixel, so as to obtain the regions where clothing of different materials are located.

[0076] According to one embodiment of the present invention, the washing parameters determined in the determining module 30 include: washing water level. The washing parameters are determined based on the number of pixels corresponding to different types of clothing, and the operation steps are: obtaining the water absorption coefficient corresponding to different types of clothing; and determining the washing water level based on the number of pixels corresponding to different types of clothing and the water absorption coefficient corresponding to different types of clothing.

[0077] Specifically, module 30 is determined by formula The washing water level is calculated, where l represents the washing water level, and w i The coefficient of water absorption (s) represents the water absorption coefficient of clothing made of different materials. i This represents the number of pixels corresponding to different clothing materials, where N represents the number of different clothing material types. The above formula yields the optimal washing water level, ensuring washing effectiveness while avoiding water waste.

[0078] According to one embodiment of the present invention, the washing parameters determined in the determining module 30 further include the final washing cycle time and the final washing speed. Specifically, before the control module 40 controls the garment processing equipment according to the washing parameters, the determining module 30 is further configured to: obtain the washing cycle time and maximum washing speed corresponding to different types of garments; use the gentlest washing cycle time among the washing cycles corresponding to different types of garments as the final washing cycle time, and use the minimum maximum washing speed among the maximum washing speeds corresponding to different types of garments as the final washing speed, thereby ensuring that garments of different materials within the area are in a washing environment controlled by optimal washing parameters, reducing garment wear and ensuring washing quality.

[0079] According to one embodiment of the present invention, the image processing module 20 is further configured to: acquire the probability value of the presence of clothing at each pixel in the clothing image, and generate a visible image based on the heatmap and the clothing image. The control module 40 is further configured to: control the clothing processing device to display the visible image.

[0080] It should be noted that for details not disclosed in the clothing washing control device of the present invention, please refer to the details disclosed in the clothing washing control method of the above embodiments of the present invention, which will not be repeated here.

[0081] According to the embodiments of the present invention, the clothing washing control device can obtain clothing of different materials by processing the image of the clothing to be washed, and determine the washing parameters according to the pixel points corresponding to the different materials of the clothing, so as to ensure that the clothing processing equipment is controlled with the best washing parameters, so that the clothing receives the best washing and care, effectively improving the washing effect of the clothing and realizing the intelligent upgrade of the clothing washing operation.

[0082] Corresponding to the above embodiments, the present invention also proposes an electronic device.

[0083] The electronic device of the present invention may include: a memory, a processor, and a laundry washing control program stored on the processor and running thereon. When the processor executes the laundry washing control program, it can implement the above-mentioned laundry washing control method.

[0084] The electronic device of this invention, by executing the above-described clothing washing control method, can ensure that the clothing processing equipment is controlled with the best washing parameters, so that the clothes receive the best washing and care, effectively improving the washing effect and realizing the intelligent upgrade of clothing washing operation.

[0085] Corresponding to the above embodiments, the present invention also proposes a computer-readable storage medium.

[0086] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described clothing washing control method.

[0087] According to the computer-readable storage medium of the present invention, by executing the above-described clothing washing control method, it is possible to ensure that the clothing processing equipment is controlled with the best washing parameters, so that the clothes receive the best washing and care, effectively improving the washing effect of the clothes and realizing the intelligent upgrade of the clothing washing operation.

[0088] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device, such as a computer-based system, a processor-based system, or other system that can fetch and execute instructions from, or in conjunction with, an instruction execution system, apparatus, or device. For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. A more specific, non-exhaustive list of examples of computer-readable media includes the following: electronic devices with electrical connections having one or more wires, portable computer disk drives, random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM) or flash memory, fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0089] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0090] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0091] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A laundry control method, characterized by, The method comprises the following steps: obtaining a laundry image of laundry to be washed; processing the laundry image to obtain regions where laundry of different materials is located in the laundry image; determining the number of pixel points corresponding to laundry of different materials in each region; determining a washing parameter according to the number of pixel points corresponding to laundry of different materials, and controlling a laundry processing device according to the washing parameter; wherein the method further comprises: obtaining a probability value of the presence of laundry for each pixel point in the laundry image; generating a heat map according to the probability value of the presence of laundry for each pixel point; generating an explicit image according to the heat map and the laundry image, and controlling the laundry processing device to display the explicit image.

2. The laundry control method according to claim 1, characterized by, The washing parameter comprises a washing water level, wherein determining the washing parameter according to the number of pixel points corresponding to laundry of different materials comprises: obtaining a water absorption coefficient corresponding to the laundry of different materials; determining the washing water level according to the number of pixel points corresponding to the laundry of different materials and the corresponding water absorption coefficient.

3. The laundry control method according to claim 2, characterized by, The washing water level is calculated by the following formula: wherein, , represents the water absorption coefficient corresponding to the clothes of different materials, represents the number of pixel points corresponding to the clothes of different materials, and N represents the number of types of clothes materials.

4. The laundry control method of claim 1, wherein, The washing parameter further comprises a final washing beat and a final washing rotation speed, and the method further comprises: obtaining a washing beat and a maximum washing rotation speed corresponding to the laundry of different materials; taking the softest beat in the washing beat corresponding to the laundry of different materials as the final washing beat, and taking the smallest rotation speed in the maximum washing rotation speed corresponding to the laundry of different materials as the final washing rotation speed.

5. The laundry control method according to any one of claims 1-4, characterized in that, Processing the laundry image to obtain regions where laundry of different materials is located in the laundry image comprises: segmentation prediction of the laundry image is performed by using a deep convolutional neural network to obtain regions where laundry of different materials is located.

6. The laundry control method according to claim 5, characterized by, Segmentation prediction of the laundry image is performed by using a deep convolutional neural network to obtain regions where laundry of different materials is located, comprising: extracting a clothing feature corresponding to each pixel point in the laundry image, and predicting a material classification to which each pixel point belongs according to the clothing feature corresponding to each pixel point to obtain regions where laundry of different materials is located.

7. A laundry control device, characterized by, comprising: an obtaining module configured to obtain a laundry image of laundry to be washed; an image processing module configured to process the laundry image to obtain regions where laundry of different materials is located in the laundry image; a determining module configured to determine the number of pixel points corresponding to laundry of different materials in each region, and determine a washing parameter according to the number of pixel points corresponding to laundry of different materials; a control module configured to control a laundry processing device according to the washing parameter; the image processing module is further configured to obtain a probability value of the presence of laundry for each pixel point in the laundry image, generate a heat map according to the probability value of the presence of laundry for each pixel point, and generate an explicit image according to the heat map and the laundry image; the control module is further configured to control the laundry processing device to display the explicit image.

8. An electronic device, comprising: comprising: A memory, a processor, and a laundry washing control program stored on the memory and executable on the processor, the processor implementing the laundry washing control method of any one of claims 1-6 when executing the laundry washing control program.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The program, when executed by the processor, implements the laundry washing control method of any one of claims 1-6.

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