Clothes processing device and control method thereof

Abstract

The present invention belongs to the technical field of clothing processing equipment and aims to solve the problem that a large amount of clothing information significantly interferes with the user's ability to set clothing processing parameters based on the clothing information, resulting in low accuracy of clothing processing parameters and poor clothing processing effects. To this end, the present invention provides a clothing processing device and a control method thereof. The clothing processing device is equipped with an image acquisition device, and the control method includes: acquiring an image of the clothing to be processed; judging whether the clothing to be processed is clothing that has been processed by the clothing processing device based on the image of the clothing to be processed; selectively determining clothing processing parameters based on historical data of the clothing to be processed based on the judgment result; and operating the clothing processing device according to the determined clothing processing parameters. Through such a setting, the user does not need to set clothing processing parameters based on the specific information of the clothing to be processed, which provides greater convenience to the user, improves the accuracy of the clothing processing parameters, and ensures the clothing processing effect.

Description

Technical Field

[0001] The present invention belongs to the technical field of clothing processing equipment, and specifically provides a clothing processing equipment and a control method thereof. Background Art

[0002] As people's living standards improve, laundry processing equipment such as washing machines, dryers, washer-dryers, and shoe washers have become common household appliances in our daily lives. The variety and quantity of clothing people carry is also increasing. Different materials require different processing parameters for clothing, and the same piece of clothing may require different processing parameters in different states.

[0003] Usually, users need to set clothing treatment parameters according to the specific information of the clothes to be treated. However, the numerous clothing information greatly interferes with the user's setting of clothing treatment parameters according to the clothing information, resulting in low accuracy of the clothing treatment parameters and poor clothing treatment effect.

[0004] Therefore, this field needs a new technical solution to solve the above problems. Summary of the Invention

[0005] In order to solve the above-mentioned problems in the prior art, that is, to solve the problem that the numerous clothing information greatly interferes with the user's setting of clothing processing parameters according to the clothing information, resulting in low accuracy of clothing processing parameters and poor clothing processing effect, on the one hand, the present invention provides a control method for a clothing processing device, the clothing processing device is equipped with an image acquisition device, and the control method includes: acquiring an image of the clothing to be processed; judging whether the clothing to be processed is clothing that has been processed by the clothing processing device based on the image of the clothing to be processed; selectively determining the clothing processing parameters based on the historical data of the clothing to be processed according to the judgment result; and operating the clothing processing device according to the determined clothing processing parameters.

[0006] In the preferred technical solution of the above-mentioned control method, the step of "selectively determining the clothing processing parameters according to the historical data of the clothing to be processed based on the judgment result" includes: if the clothing to be processed is clothing that has been processed by the clothing processing equipment, then determining the clothing processing parameters according to the historical data of the clothing to be processed.

[0007] In the preferred technical solution of the above-mentioned control method, the step of "selectively determining the clothing processing parameters based on the historical data of the clothing to be processed according to the judgment result" includes: if the clothing to be processed does not belong to the clothing processed by the clothing processing equipment, then obtaining the material information of the clothing to be processed based on the image of the clothing to be processed; and determining the clothing processing parameters based on the material information of the clothing to be processed.

[0008] In the preferred technical solution of the above-mentioned control method, the historical data includes the color depth of the clothes to be processed before the last treatment, and the step of "determining the clothes processing parameters based on the historical data of the clothes to be processed" includes: retrieving the color depth of the clothes to be processed before the last treatment; acquiring and storing the current color depth of the clothes to be processed based on the image of the clothes to be processed; determining the depth difference between the current color depth of the clothes to be processed and the color depth before the last treatment; and determining the clothes processing parameters based on the depth difference.

[0009] In the preferred technical solution of the above-mentioned control method, the historical data also includes the historical processing times of the clothes to be processed, and the step of "determining the clothes processing parameters according to the depth difference" includes: retrieving the historical processing times of the clothes to be processed; and determining the clothes processing parameters according to the depth difference and the historical processing times.

[0010] In the preferred technical solution of the above control method, the step of "determining clothing processing parameters based on historical data" includes: acquiring and storing current data of the clothing to be processed based on the image of the clothing to be processed; and determining clothing processing parameters based on the historical data and the current data.

[0011] In a preferred technical solution of the above control method, the current data includes the degree of damage of the clothes to be processed and the degree of wrinkles of the clothes to be processed.

[0012] In the preferred technical solution of the above-mentioned control method, the degree of damage of the clothes to be processed is determined by: determining it based on the number of damaged areas, the area of the damaged areas and the material information of the clothes to be processed; and / or the degree of wrinkles of the clothes to be processed is determined by: determining it based on the number of wrinkles and the material information of the clothes to be processed.

[0013] In the preferred technical solution of the above-mentioned control method, the step of "determining whether the clothes to be processed are clothes that have been processed by the clothes processing equipment based on the image of the clothes to be processed" includes: inputting the image of the clothes to be processed into a trained deep learning model; and determining whether the clothes to be processed are clothes that have been processed by the clothes processing equipment based on the output result of the deep learning model.

[0014] In the technical solution of the present invention, the clothing processing device is equipped with an image acquisition device, and the control method includes: acquiring an image of the clothing to be processed; judging whether the clothing to be processed is clothing that has been processed by the clothing processing device based on the image of the clothing to be processed; selectively determining clothing processing parameters based on historical data of the clothing to be processed according to the judgment result; and operating the clothing processing device according to the determined clothing processing parameters.

[0015] This configuration allows the determination of clothing treatment parameters based on the captured image of the clothing to be treated, and the operation of the clothing treatment device in accordance with the determined clothing treatment parameters. This eliminates the need for the user to set clothing treatment parameters based on the specific information of the clothing to be treated, providing greater convenience for the user. The clothing treatment parameters are selectively determined based on the historical data of the clothing to be treated, depending on whether the clothing to be treated has been treated by the clothing treatment device. This improves the accuracy of the clothing treatment parameters and ensures the clothing treatment effect. By determining whether the clothing to be treated has been treated by the clothing treatment device based on the captured clothing treatment image, there is no need to add labels to the clothing to be treated, making the determination method simpler and more convenient.

[0016] On the other hand, the present invention also provides a clothing processing device, comprising: a memory; a processor; and a computer program, wherein the computer program is stored in the memory and is configured to be executed by the processor to implement the control method of the clothing processing device in any of the above technical solutions.

[0017] It should be noted that the clothing processing device has all the technical effects of the above-mentioned control method, which will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The preferred embodiments of the present invention are described below with reference to the accompanying drawings, in which:

[0019] Figure 1 This is a diagram showing the main steps of the control method for the clothes processing device of the present invention;

[0020] Figure 2 is a flow chart of a method for controlling a washing machine according to a first embodiment of the present invention;

[0021] Figure 3 4 is a flow chart of a method for controlling a washing machine according to a second embodiment of the present invention. DETAILED DESCRIPTION

[0022] First, those skilled in the art should understand that the embodiments described below are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention. For example, the control method of the laundry processing device of the present invention is applicable to drum washing machines, wheel washing machines, dryers, washer-dryers, shoe washers, and the like. Such adjustments to the specific types of applications do not constitute limitations on the present invention and are intended to be within the scope of protection of the present invention.

[0023] It should be noted that, in the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance.

[0024] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the term "connection" should be understood in a broad sense. For example, it can mean a fixed connection, a detachable connection, or an integral connection; it can mean a mechanical connection or an electrical connection; it can mean a direct connection, an indirect connection through an intermediate medium, or internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0025] Reference Figure 1 , to introduce the control method of the clothes processing equipment of the present invention. Figure 1 1 is a diagram showing the main steps of the control method of the clothes processing device of the present invention.

[0026] Based on the problem mentioned in the background technology that the numerous clothing information causes great interference to the user in setting clothing processing parameters according to the clothing information, resulting in low accuracy of clothing processing parameters and poor clothing processing effect, the present invention provides a control method for a clothing processing device, which is equipped with an image acquisition device.

[0027] like Figure 1 As shown, the control method of the clothes processing device of the present invention mainly includes the following steps:

[0028] Step S100: Acquire an image of the clothes to be processed.

[0029] For example, the image acquisition device is a camera module connected to a controller of the clothing processing device. The controller controls the camera module to take pictures inside the clothing processing device, and extracts images of the clothes to be processed in the clothing processing device from the taken pictures.

[0030] Step S200: determining, based on the image of the clothes to be processed, whether the clothes to be processed are clothes that have been processed by a clothes processing device.

[0031] For example, different clothes have different patterns or designs. For clothes that have been treated by a clothes treatment device, the clothes treatment device stores information about the patterns or designs on the clothes. The extracted image of the clothes to be treated is compared with the pattern or design information of clothes treated by the clothes treatment device stored in the clothes treatment device to determine whether the clothes to be treated are clothes that have been treated by the clothes treatment device.

[0032] Step S300: Determine clothing treatment parameters selectively based on historical data of the clothing to be treated according to the judgment result.

[0033] If the laundry to be processed is laundry that has been processed by a laundry processing device, the laundry processing parameters are determined based on the historical data of the laundry to be processed. For example, each time the laundry is processed using the laundry processing device, the laundry to be processed is photographed and an image of the laundry to be processed is extracted, and the color depth of the laundry to be processed is obtained and stored from the image of the laundry to be processed. The next time the laundry is processed using the laundry processing device, the stored color depth of the laundry to be processed before the last treatment is retrieved, and the depth difference between the color depth of the laundry to be processed obtained this time and the color depth before the last treatment is determined. The laundry processing parameters are determined based on the depth difference. For example, when washing the laundry, the greater the depth difference, the shorter the set washing time, the lower the washing intensity, and / or the lower the washing water temperature.

[0034] Step S400: operating the laundry processing device according to the determined laundry processing parameters.

[0035] This setup eliminates the need for users to set clothing treatment parameters based on the specific information of the clothing being treated, providing greater convenience. The clothing treatment parameters are selectively determined based on the historical data of the clothing being treated, depending on whether the clothing has been treated by the clothing treatment device. This improves the accuracy of the clothing treatment parameters and ensures the clothing treatment effect. By determining whether the clothing has been treated by the clothing treatment device based on the captured clothing treatment image, there is no need to add labels to the clothing being treated, making the determination method simpler and more convenient.

[0036] Refer to the following Figure 2 The first embodiment of the present invention is introduced in conjunction with a washing machine. Figure 2 4 is a flow chart of a method for controlling a washing machine according to a first embodiment of the present invention.

[0037] In the first embodiment of the present invention, the washing machine is a drum washing machine (hereinafter referred to as washing machine), and a camera module as an image acquisition device is provided at the clothing loading port on the front side panel of the washing machine. The camera module is connected to the controller of the washing machine, and the controller is connected to the cloud server. Figure 2 As shown, the control method of the washing machine includes:

[0038] Step S110: Acquire an image of the clothes to be washed.

[0039] The controller controls the camera module to take pictures inside the washing machine, obtains the pictures, and transmits the pictures to the cloud server. The cloud server uses a target detection algorithm (such as FCOS, SSD, YOLOv3 or Faster R-CNN, etc.) to process the pictures and obtain images of the clothes to be washed in the pictures.

[0040] Step S210: Input the image of the clothes to be washed into the trained deep learning model.

[0041] When the washing machine is used for the first time, after the laundry is placed in the washing machine, the drum can rotate at a low speed to position the laundry in different positions and states. The camera module captures a large number of images at different times and transmits them to the cloud server to train the deep learning model. The deep learning model can then be used to identify the laundry when the laundry is washed again. It is understood that after replacing the drum washing machine with a new one, the deep learning model from the original drum washing machine can be downloaded from the cloud server to identify the laundry.

[0042] Step S220: Obtain the output result of the deep learning model.

[0043] For example, if an image of clothes to be washed is input into a trained deep learning model (such as ResNet101, ResNeXt, or R-CNN), the deep learning model extracts features from the image of clothes to be washed and represents them as a 512-dimensional vector. The features of the image of clothes to be washed are compared with the features of all clothes washed by the washing machine, and the Euler distance between the features of the image of clothes to be washed and the features of each piece of clothes washed by the washing machine is output.

[0044] Step S230: Determine whether the clothes to be washed are clothes that have been washed by a washing machine. If yes, execute step S311; otherwise, execute step S321.

[0045] The output of the deep learning model is used to determine whether the laundry to be washed is laundry that has been washed in a washing machine. Specifically, if the Euler distance between the features of the laundry to be washed and the features of a piece of laundry that has been washed in a washing machine is greater than a preset value, the laundry to be washed is determined to be the same piece of laundry; otherwise, the laundry to be washed is determined to be different from the piece of laundry. It should be noted that the deep learning model can also directly output a result to determine whether the laundry to be washed is laundry that has been washed in a washing machine, and the conclusion of whether the laundry to be washed is laundry that has been washed in a washing machine can be directly drawn based on the output of the deep learning model.

[0046] Step S311: retrieve the color depth of the laundry before the last wash.

[0047] Each time the washing machine is used to wash clothes, a photo of the clothes is taken and an image of the clothes is extracted. The color depth of the clothes is obtained and stored from the image of the clothes. If the clothes are previously washed in the washing machine, the cloud server retrieves the color depth of the clothes before the last wash.

[0048] Step S312: Acquire and store the current color depth of the laundry according to the image of the laundry.

[0049] Step S313: Determine the depth difference between the current color depth of the laundry and the color depth before the last wash.

[0050] The depth difference between the current color depth of the laundry and the color depth before the last wash is calculated.

[0051] Step S314: retrieve the historical washing times of the clothes to be washed.

[0052] For the same piece of clothing, the washing machine counts the number of washes each time it washes. The cloud server retrieves the historical wash counts of the clothing to be washed.

[0053] Step S315: Determine laundry washing parameters based on the depth difference and the number of historical washes.

[0054] The cloud server determines the washing parameters of the clothes based on the depth difference between the current color depth of the clothes to be washed and the color depth before the last wash, as well as the historical washing times of the clothes to be washed. For example, the basic washing time is set with the depth difference as 0 and the historical washing times as 1. If the depth difference is greater than 2 bits, the washing time is further reduced by 1 minute. If the historical washing times increase by 5 times, the washing time is further reduced by 1 minute. If the depth difference is greater than 2 bits and the historical washing times increase by 5 times, the washing time is further reduced by 2 minutes. It should be noted that this is only an exemplary description. In actual applications, the specific values can be adjusted. The washing temperature can also be lowered to a preset temperature when the depth difference is greater than the preset value and / or the washing temperature can be lowered to a preset temperature every time the washing times increase by a preset number. Through such a setting, the fading of clothes is improved during the washing process and the washing effect of clothes is optimized.

[0055] Step S321: Obtain material information of the clothes to be washed.

[0056] The material information of the clothes to be washed is analyzed by the images of the clothes to be washed.

[0057] Step S322: Determine the washing parameters of the clothes according to the material information of the clothes to be washed.

[0058] The memory stores the recommended washing time and recommended washing temperature for clothes of different material types. The cloud server determines the washing time and washing temperature of the clothes based on the material information of the clothes to be washed, and sends the determined washing time and washing temperature to the controller of the washing machine.

[0059] After step S315 and step S322, step S410 is executed.

[0060] Step S410: The washing machine is operated according to the determined laundry washing parameters.

[0061] The controller of the washing machine controls the washing machine to operate according to the determined washing time and washing temperature.

[0062] By capturing images of laundry, determining whether the laundry has been washed in a washing machine based on the images, and determining washing parameters based on historical data if the laundry has been washed, or based on material information if the laundry has not been washed, the user is no longer required to set washing parameters based on the specific information of the laundry, providing greater convenience. By determining whether the laundry has been washed in a washing machine and then determining washing parameters in different ways, the accuracy of the washing parameters is improved, ensuring effective washing. If the laundry has been washed in a washing machine, the washing parameters are determined based on the difference in color depth between the laundry and the previous color depth, as well as the number of times the laundry has been washed historically. This can further improve color fading during the washing process and optimize the washing effect. By using a deep learning model to identify images of laundry, it can more accurately determine whether the laundry has already been washed in a washing machine. Furthermore, after the laundry has been washed for the first time, the deep learning model can autonomously learn and store the corresponding laundry information based on the image, allowing for automatic identification of the laundry during subsequent washes. This eliminates the need for the user to input information about unwashed laundry into the washing machine to identify the laundry. Using a cloud server to extract images of the laundry from photos taken by the camera module, determine whether the laundry has already been washed, and determine washing parameters can reduce the size of the washing machine, increase computing speed, and facilitate data migration during washing machine upgrades, optimizing the user experience.

[0063] It should be noted that step S311 and step S312 can be executed simultaneously or in a different order, as long as they are executed before step S313. In addition, if the laundry to be washed is laundry that has been washed by a washing machine, step S314 can also be executed at any step between step S230 and step S315. That is, if the laundry to be washed is laundry that has been washed by a washing machine, it can be executed simultaneously with any one of step S311, step S312, and step S313, or before or after any one of step S311, step S312, and step S313.

[0064] Refer to the following Figure 3 , and the second embodiment of the present invention is introduced in combination with a washing machine. Figure 34 is a flow chart of a method for controlling a washing machine according to a second embodiment of the present invention.

[0065] In a second embodiment of the present invention, the washing machine is a drum washing machine, and a camera module serving as an image acquisition device is provided at the clothing loading port on the front side panel of the drum washing machine. The camera module is connected to a controller of the washing machine, and the controller is connected to a cloud server. Figure 3 As shown, the control method of the washing machine includes:

[0066] Step S110: Acquire an image of the clothes to be washed.

[0067] Step S210: Input the image of the clothes to be washed into the trained deep learning model.

[0068] Step S220: Obtain the output result of the deep learning model.

[0069] Step S230: Determine whether the clothes to be washed are clothes that have been washed by a washing machine. If yes, execute step S311; otherwise, execute step S321.

[0070] Step S311: retrieve the color depth of the laundry before the last wash.

[0071] Step S312: Acquire and store the current color depth of the laundry according to the image of the laundry.

[0072] Step S313: Determine the depth difference between the current color depth of the laundry and the color depth before the last wash.

[0073] Step S314: retrieve the historical washing times of the clothes to be washed.

[0074] Step S315: Acquire and store the degree of damage and wrinkle of the laundry according to the image of the laundry.

[0075] For example, a cloud server uses an object detection algorithm (such as RetinaNet, SSD, YOLOv3, or Faster R-CNN) to extract the number of damaged areas, the area of damaged areas, the number of wrinkles, and material information from images of laundry. The degree of damage is determined based on the number, area, and material information. For example, damage degree = area of damaged areas × number of damaged areas × damage coefficient. Different materials have different corresponding damage coefficients (e.g., the damage coefficient for pure cotton is 0.9, the damage coefficient for 80% cotton + 20% polyester is 0.7, the damage coefficient for polyester is 0.2, and the damage coefficient for silk is 0.5). The wrinkle degree is determined based on the number of wrinkles and material information of the clothes to be washed, such as wrinkle degree = number of wrinkles × wrinkle coefficient. Different materials correspond to different wrinkle coefficients (the wrinkle coefficient of pure cotton is 0.2, the breakage coefficient of 80% cotton + 20% polyester is 0.4, the breakage coefficient of polyester is 0.9, the breakage coefficient of silk is 0.95, etc.).

[0076] Step S316: Determine the laundry washing parameters based on the depth difference, the number of historical washes, the degree of damage, and the degree of wrinkles.

[0077] The cloud server determines the washing parameters based on the difference between the current color depth of the laundry and the color depth before the last wash, the number of washes, the degree of damage, and the degree of wrinkles. For example, a base wash time is set with a depth difference of 0 and a historical wash count of 1. If the depth difference exceeds 2 bits, the wash time is further reduced by 1 minute. For every increase of 5 washes, the wash time is further reduced by 1 minute. For every preset increase in the degree of damage, the wash time is further reduced by 0.5 minutes. For every preset increase in the degree of wrinkles, the forward and reverse rotation frequency of the drum is reduced by 2 times per minute.

[0078] It should be noted that this is merely an example description. In actual use, the specific values can be adjusted. Alternatively, the washing temperature can be lowered by a preset temperature when the depth difference is greater than a preset value, lowered by a preset temperature each time the number of washes increases by a preset value, and / or lowered by a preset temperature each time the wrinkle degree increases by a preset value. Such settings can further reduce damage to clothing during the washing process.

[0079] Step S321: Obtain material information of the clothes to be washed.

[0080] Step S322: Determine the washing parameters of the clothes according to the material information of the clothes to be washed.

[0081] After step S316 and step S322, step S410 is executed.

[0082] Step S410: The washing machine is operated according to the determined laundry washing parameters.

[0083] It should be noted that, when the clothes to be washed are clothes that have been washed by a washing machine, step S315 can also be performed at any step between step S230 and step S316.

[0084] In another feasible embodiment, a cloud server may not be set up, and the controller of the washing machine can be used to extract images of the clothes to be washed from photos taken by the camera module, determine whether the clothes to be washed are clothes that have been washed by the washing machine, and determine the washing parameters of the clothes.

[0085] It should also be noted that in the above embodiments, controlling the camera module to take pictures of the washing machine to obtain pictures of the clothes to be washed is only a specific implementation method, and it can be adjusted in specific applications. For example, when the clothes are about to be put into the washing machine, the camera module captures the clothes in the user's hand that are about to be put into the washing machine. The camera can also be used to capture a video of the process of putting the clothes into the washing machine or the process of the clothes turning over in the washing machine, and multiple pictures are obtained from the video, and then the image of the clothes is obtained from the pictures. In addition, although the above embodiments are introduced using drum washing machines as an example, the control method of the present invention is also applicable to clothing processing equipment such as pulsator washing machines, dryers, integrated washing and drying machines, and shoe washing machines, and adaptively adjusts the historical data and clothing processing parameters of the clothes to be processed. For example, for a dryer, the historical data of the clothes to be processed includes the historical drying times, and the clothing processing data includes the drying time and drying temperature, etc.

[0086] On the other hand, the present invention also provides a clothing processing device, including: a memory, a processor and a computer program, the computer program is stored in the memory and is configured to be executed by the processor to implement the control method of the clothing processing device of any of the above embodiments.

[0087] It should be noted that the memory in the above embodiments includes, but is not limited to, random access memory, flash memory, read-only memory, programmable read-only memory, volatile memory, non-volatile memory, serial memory, parallel memory, or registers, and the processor includes, but is not limited to, CPLD / FPGA, DSP, ARM processor, MIPS processor, etc. In addition, the clothing processing device may be a drum washing machine, a pulsator washing machine, a dryer, a washer-dryer, a shoe washer, etc.

[0088] As can be seen from the above description, in the technical solution of the present invention, the clothing processing device is equipped with an image acquisition device, and the control method includes: acquiring an image of the clothing to be processed; judging whether the clothing to be processed is clothing that has been processed by the clothing processing device based on the image of the clothing to be processed; selectively determining clothing processing parameters based on the historical data of the clothing to be processed based on the judgment result; and operating the clothing processing device according to the determined clothing processing parameters. Through such a setting, the user does not need to set the clothing processing parameters based on the specific information of the clothing to be processed, which provides more convenience for the user. By selectively determining the clothing processing parameters based on the historical data of the clothing to be processed based on whether the clothing to be processed is clothing that has been processed by the clothing processing device, the accuracy of the clothing processing parameters is improved and the clothing processing effect is guaranteed. By judging whether the clothing to be processed is clothing that has been processed by the clothing processing device based on the acquired clothing processing image, there is no need to add labels to the clothing to be processed, and the judgment method is simpler and more convenient.

[0089] Those skilled in the art will appreciate that although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features from different embodiments is intended to be within the scope of the present invention and to form different embodiments. For example, in the claims of the present invention, any one of the claimed embodiments may be used in any combination.

[0090] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

Claims

1. A method for controlling a clothes processing device, characterized in that: The laundry processing device is equipped with an image acquisition device, and the control method includes: Acquiring an image of the clothing to be processed; determining, based on the image of the clothes to be processed, whether the clothes to be processed are clothes that have been processed by the clothes processing device; selectively determining clothing treatment parameters based on historical data of the clothing to be treated according to the judgment result; operating the laundry processing device according to the determined laundry processing parameters; The step of "selectively determining the clothing treatment parameters based on the historical data of the clothing to be treated according to the judgment result" includes: If the clothes to be processed are clothes that have been processed by the clothes processing device, determining clothes processing parameters according to historical data of the clothes to be processed; The historical data includes the color depth of the laundry to be processed before the last treatment, and the step of "determining laundry treatment parameters based on the historical data of the laundry to be processed" includes: Retrieving the color depth of the laundry to be processed before the last processing; acquiring and storing the current color depth of the clothes to be processed according to the image of the clothes to be processed; Determining a depth difference between a current color depth of the laundry to be processed and a color depth before the last processing; A laundry treatment parameter is determined according to the depth difference.

2. The control method according to claim 1, characterized in that: The step of "selectively determining the clothing treatment parameters based on the historical data of the clothing to be treated according to the judgment result" includes: If the clothes to be processed are not clothes that have been processed by the clothes processing device, obtaining material information of the clothes to be processed according to the image of the clothes to be processed; The clothing processing parameters are determined according to the material information of the clothing to be processed.

3. The control method according to claim 1, wherein: The historical data also includes the historical number of times the laundry to be processed is processed. The step of "determining laundry processing parameters according to the depth difference" includes: Retrieving the historical processing times of the clothes to be processed; The laundry treatment parameter is determined according to the depth difference and the historical number of treatments.

4. The control method according to claim 1, wherein: The steps of "determining clothing processing parameters based on historical data" include: acquiring and storing current data of the clothes to be processed according to the image of the clothes to be processed; determining laundry treatment parameters according to the historical data and the current data; The current data includes the degree of damage of the laundry to be processed and the degree of wrinkles of the laundry to be processed.

5. The control method according to claim 4, characterized in that: The degree of damage of the clothes to be processed is determined by: determining the degree of damage according to the number of damaged areas, the area of the damaged areas and the material information of the clothes to be processed; and / or The wrinkle degree of the clothes to be processed is determined according to the number of wrinkles and material information of the clothes to be processed.

6. The control method according to any one of claims 1 to 5, characterized in that: The step of “determining whether the clothes to be processed are clothes that have been processed by the clothes processing device based on the image of the clothes to be processed” includes: Inputting the image of the clothing to be processed into a trained deep learning model; Determine whether the clothes to be processed are clothes that have been processed by the clothes processing device according to the output result of the deep learning model.

7. A clothes processing device, characterized in that: include: Memory; processor; as well as A computer program is stored in the memory and is configured to be executed by the processor to implement the control method of the laundry processing device according to any one of claims 1 to 6.

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