CN113455989A - Control method for dish washing machine, cooking image processing method and processor - Google Patents

Control method for dish washing machine, cooking image processing method and processor Download PDF

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CN113455989A
CN113455989A CN202110695814.1A CN202110695814A CN113455989A CN 113455989 A CN113455989 A CN 113455989A CN 202110695814 A CN202110695814 A CN 202110695814A CN 113455989 A CN113455989 A CN 113455989A
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food
image
identification information
dishwasher
cooking
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CN113455989B (en
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谢定超
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Foshan Shunde Midea Washing Appliances Manufacturing Co Ltd
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Foshan Shunde Midea Washing Appliances Manufacturing Co Ltd
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    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L15/00—Washing or rinsing machines for crockery or tableware
    • A47L15/42—Details
    • A47L15/46—Devices for the automatic control of the different phases of cleaning ; Controlling devices
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24C—DOMESTIC STOVES OR RANGES ; DETAILS OF DOMESTIC STOVES OR RANGES, OF GENERAL APPLICATION
    • F24C15/00—Details
    • F24C15/20—Removing cooking fumes
    • F24C15/2021—Arrangement or mounting of control or safety systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L2401/00—Automatic detection in controlling methods of washing or rinsing machines for crockery or tableware, e.g. information provided by sensors entered into controlling devices
    • A47L2401/34—Other automatic detections
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L2501/00—Output in controlling method of washing or rinsing machines for crockery or tableware, i.e. quantities or components controlled, or actions performed by the controlling device executing the controlling method
    • A47L2501/36—Other output
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B40/00—Technologies aiming at improving the efficiency of home appliances, e.g. induction cooking or efficient technologies for refrigerators, freezers or dish washers

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Abstract

The embodiment of the invention provides a control method for a dish-washing machine, a cooking image processing method and a processor, and belongs to the field of electric appliances. The above-mentioned control method for dish washer, dish washer and lampblack absorber communication, the lampblack absorber includes image acquisition equipment, includes: acquiring identification information of food, wherein the identification information of the food is obtained from an image of a cooking area acquired by an image acquisition device; and determining a recommended washing mode of the dishwasher according to the identification information of the food based on the corresponding relation between the pre-stored identification information and the washing mode. The technical scheme can improve the efficiency of determining the washing mode of the dishwasher.

Description

Control method for dish washing machine, cooking image processing method and processor
Technical Field
The invention relates to the field of electric appliances, in particular to a control method for a dish washing machine, a cooking image processing method and a processor.
Background
Along with the intellectualization of household appliances, the intelligent dish washing machine brings great convenience to the life of people. At present, in the washing process of a dish washing machine, a user is usually required to judge the oil stain degree of tableware in advance, and the user selects a corresponding washing mode of the dish washing machine according to the oil stain degree.
In the prior art, the oil stain degree is judged and the cleaning mode is selected by a user, so that the steps of user operation are increased, and the efficiency of determining the cleaning mode is low.
Disclosure of Invention
An object of an embodiment of the present invention is to provide a control method, a cooking image processing method, a processor and a storage medium for a dishwasher, so as to solve the problem of low washing efficiency of the dishwasher in the prior art.
In order to achieve the above object, a first aspect of the present invention provides a control method for a dishwasher, the dishwasher being in communication with a range hood, the range hood including an image capturing device, the control method comprising:
acquiring identification information of food, wherein the identification information of the food is obtained from an image of a cooking area acquired by an image acquisition device;
and determining a recommended washing mode of the dishwasher according to the identification information of the food based on the corresponding relation between the pre-stored identification information and the washing mode.
In an embodiment of the present invention, the identification information of the food includes a kind of the food and/or an amount of oil.
In an embodiment of the invention, the food category comprises at least one of meat, vegetables, fruits and soup.
In an embodiment of the present invention, the recommended washing mode includes at least one of an ultra-strong washing mode, a standard washing mode, and a gentle washing mode.
A second aspect of the present invention provides a cooking image processing method, including:
acquiring an image of a cooking area acquired by image acquisition equipment of the range hood;
judging whether the image contains food or not;
in the event that it is determined that food is contained in the image, identifying information of the food is determined, and a dishwasher in communication with the range hood is used to determine a washing pattern based on the identifying information of the food.
In an embodiment of the present invention, the identification information of the food includes a kind of the food and/or an amount of oil.
In the embodiment of the present invention, determining whether the image contains food includes: carrying out difference processing on the image of the current frame and a first frame image stored in advance to obtain a region image after difference processing; and carrying out edge detection on the area image to identify whether the image contains food or not.
In the embodiment of the present invention, in the case where it is determined that food is contained in the image, the region image is a food image; determining the identification information of the food includes: recognizing the food image through a pre-trained neural network model to obtain the food type corresponding to the food; and/or performing histogram statistics on the gray value of the food image to obtain the average gray value of the food image; comparing the average gray value with a preset gray threshold value; and determining the oil quantity condition of the food according to the comparison result.
In the embodiment of the invention, the determining the oil quantity condition of the food according to the comparison result comprises the following steps: determining the oil quantity condition of the food as heavy oil under the condition that the average gray value is greater than a preset gray threshold value; and determining the oil quantity condition of the food as light oil under the condition that the average gray value is less than or equal to a preset gray threshold value.
In the embodiment of the present invention, the cooking image processing method is applied to at least one of: a range hood; a dishwasher; a server in communication with the range hood and the dishwasher, respectively.
A third aspect of the present invention provides a processor configured to perform the control method for a dishwasher according to any one of the above or the cooking image processing method according to any one of the above.
A fifth aspect of the present invention provides a machine-readable storage medium having stored thereon instructions which, when executed by a processor, cause the processor to execute a control method for a dishwasher according to any one of the above or a cooking image processing method according to any one of the above.
According to the technical scheme, the dishwasher is communicated with the range hood to acquire the identification information of food, the range hood comprises the image acquisition device, the identification information of the food can be acquired from the image of the cooking area acquired by the image acquisition device, and therefore the recommended cleaning mode of the dishwasher is determined according to the identification information of the food based on the corresponding relation between the pre-stored identification information and the cleaning mode. According to the control process, the user does not need to judge the oil stain degree of the tableware and manually set or fixedly execute the default cleaning mode, the dish washing machine can determine the corresponding recommended cleaning mode according to the identification information of the food, the steps of user operation are omitted, the time of the user is saved, and the efficiency of determining the cleaning mode by the dish washing machine is improved.
Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention. In the drawings:
FIG. 1 schematically illustrates an application scenario of a control method for a dishwasher in an embodiment of the present invention;
FIG. 2 schematically illustrates a flow chart of a control method for a dishwasher in accordance with an embodiment of the present invention;
FIG. 3 is a flow chart illustrating a cooking image processing method according to an embodiment of the present invention;
fig. 4 is a view schematically showing an application scenario of the cooking image processing method according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.
The control method for the dishwasher can be applied to the application environment as shown in FIG. 1. The dishwasher 102 communicates with the range hood 104 through a network. The dishwasher can acquire the identification information of the food sent by the range hood, so that the recommended cleaning mode of the dishwasher is determined according to the identification information of the food based on the corresponding relation between the pre-stored identification information and the cleaning mode.
Fig. 2 schematically shows a flow chart of a control method for a dishwasher in an embodiment of the present invention. As shown in fig. 2, in an embodiment of the present invention, there is provided a control method for a dishwasher, the dishwasher is in communication with a range hood, the range hood includes an image acquisition device, and the method is exemplified by being applied to a processor of the dishwasher, and the method may include the following steps:
step S202, identification information of the food is acquired. The identification information of the food is obtained from the image of the cooking area acquired by the image acquisition device.
It can be understood that the range hood includes image acquisition equipment (for example, image sensor), can be used for gathering the image, and the gear of range hood can be controlled according to the image of gathering usually to the range hood, and in this embodiment, the image that the image acquisition equipment of range hood gathered can be used for the control of dish washer. The identification information of the food is the food material information cooked by the user in the cooking process. The cooking area is an area for cooking including cooking utensils such as kitchen ware or cookers. In the cooking process of a user, the image acquisition equipment on the range hood can shoot a cooking area, so that the image of the cooking area is acquired, and the identification information of corresponding food is obtained from the image of the cooking area.
The dish washer can be configured with communication module, can carry out data interaction through communication module with the lampblack absorber. Specifically, in some embodiments, the communication module may be a wireless communication module, and the wireless communication module is accessed to a signal of a wireless local area network configured in advance, so as to perform data interaction with a range hood accessed to the wireless local area network.
In other embodiments, the communication module of the dishwasher configuration may be a wired communication module that may be connected to the communication module of the range hood through a network cable for data interaction.
Specifically, in the culinary art in-process, the communication module of dish washer can communicate with the communication module of lampblack absorber to the identification information of the food of transmission culinary art in-process, the treater of dish washer can obtain the identification information of the food that the communication module of lampblack absorber that the communication module of dish washer received is regularly or send immediately, wherein the identification information of this food can be carried out image recognition by the treater of lampblack absorber to the image of the culinary art region that image acquisition equipment gathered and obtain.
In one embodiment, the identification information of the food includes a food type and/or an oil amount condition.
It is understood that the food category is the category of food that is in the process of cooking, such as meat or vegetables. The oil amount condition is a degree of greasiness of the food being cooked, i.e., an oil content of the food being cooked, and in some embodiments, the oil amount condition may include, but is not limited to, at least one of heavy oil, medium oil, light oil, and low oil.
In some embodiments, the identification information of the food includes a food type.
In some embodiments, the identification information of the food includes an oil amount condition.
In some embodiments, the identification information of the food includes a food type and an oil amount condition.
In one embodiment, the food categories may include at least one of meat, vegetables, fruits, and soup.
And step S204, determining a recommended washing mode of the dishwasher according to the identification information of the food based on the corresponding relation between the pre-stored identification information and the washing mode.
It is understood that the recommended washing mode is a washing function mode of the dishwasher corresponding to different degrees of contamination respectively obtained from the identification information of the food, such as a strong washing mode or a standard washing mode.
In one embodiment, the recommended wash mode may include at least one of a super wash mode, a standard wash mode, and a soft wash mode. The super-strong washing mode can be used for washing the tableware with the larger dirty degree, the standard washing mode can be used for washing the tableware with the medium dirty degree, the soft washing mode can be used for washing the tableware with the smaller dirty degree, and the judgment of the specific dirty degree can be determined based on the preset dirty degree interval or threshold value.
In some embodiments, the recommended washing mode of the dishwasher may be set by setting a plurality of predetermined contamination level thresholds to determine different intervals, each interval corresponding to a level, the different levels corresponding to different recommended washing modes, for example, level 1 corresponds to a level with minimum contamination level, and level 5 corresponds to a level with maximum contamination level.
Specifically, the processor of the dishwasher may determine a recommended washing mode corresponding to the dishwasher according to the identification information of the food based on the correspondence between the pre-stored identification information and the washing mode. The corresponding relationship between the pre-stored identification information and the washing mode, for example, when the identification information of the food is that the food type is meat or/and the oil amount is heavy oil, the washing mode corresponding to the dishwasher may be an ultra-strong washing mode; when the identification information of the food is vegetables and/or light oil, soup and/or heavy oil, the corresponding washing mode of the dishwasher may be a standard washing mode; when the identification information of the food is soup and/or light oil, the washing mode corresponding to the dishwasher may be a soft washing mode.
Further, when the user needs to wash the tableware, a washing starting instruction can be sent to the dishwasher through the control panel of the dishwasher. The processor can acquire a recommended cleaning mode which is determined in advance according to the identification information of the food after receiving a cleaning starting instruction triggered by a user, and also can acquire the identification information of the food when receiving the cleaning starting instruction triggered by the user, so that the recommended cleaning mode is determined according to the identification information of the food based on the corresponding relation between the pre-stored identification information and the cleaning mode, the dishwasher is controlled to execute the recommended cleaning mode, and the cleaning work of the greasy dirt tableware is finished. In some embodiments, the dishwasher may also control the dishwasher to perform the recommended washing mode after a preset time interval (e.g., 1 hour after cooking).
According to the control method for the dish washing machine, the dish washing machine is communicated with the range hood to obtain the identification information of food, the range hood comprises the image acquisition device, the identification information of the food can be obtained from the image of the cooking area acquired by the image acquisition device, and therefore the recommended cleaning mode of the dish washing machine is determined according to the identification information of the food based on the corresponding relation between the pre-stored identification information and the cleaning mode. According to the control process, the user does not need to judge the oil stain degree of the tableware and manually set or fixedly execute the default cleaning mode, the dish washing machine can determine the corresponding recommended cleaning mode according to the identification information of the food, the steps of user operation are omitted, the time of the user is saved, and the efficiency of determining the cleaning mode by the dish washing machine is improved.
Fig. 3 is a flow chart schematically illustrating a cooking image processing method according to an embodiment of the present invention. As shown in fig. 3, in the embodiment of the present invention, a cooking image processing method is provided, which is described by taking an example that the method is applied to a processor of a range hood, and the method may include the following steps:
and S302, acquiring an image of the cooking area acquired by the image acquisition equipment of the range hood.
Specifically, an image acquisition device (e.g., an image sensor) of the range hood may acquire an image of the cooking area in real time or at preset intervals in the cooking process, and correspondingly, the processor may acquire the image of the cooking area acquired by the image acquisition device (e.g., the image sensor) in real time or at preset intervals, for example, the image acquisition device acquires an image of a first frame of the cooking area when the range hood is turned on, and subsequently acquires an image of one frame of the cooking area every 5 seconds. The cooking area is an area for cooking including cooking utensils such as kitchen ware or cookers.
Step S304, judging whether the image contains food.
Specifically, the processor may determine whether food is contained in the image from the image of the cooking area based on a pre-trained model or algorithm.
In one embodiment, determining whether the image contains food comprises: carrying out difference processing on the image of the current frame and a first frame image stored in advance to obtain a region image after difference processing; and carrying out edge detection on the area image to identify whether the image contains food or not.
It can be understood that the area image is an image block obtained by performing difference processing on the current frame image and the first frame image, for example, the first frame image is a cooking area image not including an apple, the current frame image is a cooking area image including an apple, and then the partial image block where the apple is located is the area image.
Specifically, the processor can acquire an image of a first frame of cooking area acquired by the image acquisition device when the range hood is started, the image of the first frame of cooking area does not contain any food, the image information is stored, when a frame of image is acquired subsequently, the image of the current frame and the first frame of image stored in advance are subjected to difference processing, namely, the image of the current frame and the first frame of image are subjected to subtraction processing to obtain an image block subjected to difference processing, namely, the area image subjected to difference processing, and the processor continues to perform edge detection on the area image, so that whether the area image is an image of food or not can be identified, namely whether the image of the current frame contains food or not is judged.
And S306, in the case that the food is determined to be contained in the image, determining the identification information of the food, wherein the identification information of the food is used for determining a recommended washing mode for a dishwasher in communication with the range hood.
It is understood that the identification information of the food is the information of the food material cooked by the user during the cooking process, such as the type of the food. The recommended washing mode is a washing function mode of the dishwasher corresponding to different dirt degrees obtained according to the identification information of the food, such as a strong washing mode or a standard washing mode.
In particular, in case it is determined that the food is contained in the image, the processor may determine identification information of the food based on a relevant model or algorithm, so that the dishwasher in communication with the range hood may determine a corresponding washing pattern according to the identification information of the food.
According to the cooking image processing method, the image of the cooking area acquired by the image acquisition device of the range hood is acquired, whether the image contains food or not is judged, and under the condition that the image contains the food, the identification information of the food is determined, wherein the identification information of the food is used for determining the recommended cleaning mode for the dish washing machine communicated with the range hood. Above-mentioned culinary art image processing's process carries out image acquisition to the culinary art region through the image acquisition equipment on the lampblack absorber, carry out image acquisition to the image recognition processing in order to judge whether to contain food to the image of culinary art region, when confirming the image contains food, further confirm the identifying information of food, dish washer and lampblack absorber communication, the efficiency of the definite cleaning mode of dish washer has been improved, do not need the user to judge greasy dirt degree and select the cleaning mode of dish washer, corresponding recommended cleaning mode can be confirmed according to the identifying information of the food that obtains after the culinary art image processing to the dish washer, household appliance's intelligent degree has greatly been improved, user experience degree has been improved.
In one embodiment, the identification information of the food includes a food type and/or an oil amount condition.
It is understood that the food category is the category of food that is in the process of cooking, such as meat or vegetables. The oil amount condition is the degree of greasiness of the food during cooking, i.e., the oil content of the food during cooking. In some embodiments, the oil volume condition may include, but is not limited to, at least one of heavy oil, medium oil, light oil, and low oil.
In some embodiments, the identification information of the food includes a food type.
In some embodiments, the identification information of the food includes an oil amount condition.
In some embodiments, the identification information of the food includes a food type and an oil amount condition.
In one embodiment, the recommended wash mode may include at least one of a super wash mode, a standard wash mode, and a soft wash mode. The super-strong washing mode can be used for washing the tableware with the larger dirty degree, the standard washing mode can be used for washing the tableware with the medium dirty degree, the soft washing mode can be used for washing the tableware with the smaller dirty degree, and the judgment of the specific dirty degree can be determined based on the preset dirty degree interval or threshold value.
In some embodiments, the recommended washing mode of the dishwasher may be set by presetting a plurality of contamination level thresholds to determine different intervals, each interval corresponding to a level, the different levels corresponding to different washing modes, for example, level 1 corresponds to a level with minimum contamination level, and level 5 corresponds to a level with maximum contamination level.
In one embodiment, in a case where it is determined that the food is contained in the image, the region image is a food image; in the case where the identification information of the food includes the food kind, determining the identification information of the food includes: and identifying the food image through a pre-trained neural network model to obtain the food type corresponding to the food.
It is understood that the pre-trained neural network model may be used to identify the type of food contained in the food image, and further, the neural network model may include a deep convolutional neural network algorithm, that is, the deep convolutional neural network algorithm may be used to identify the food image to obtain the type of food. The gray value, namely the brightness of a single pixel point, ranges from 0 to 255, the larger the gray value is, the brighter the gray value is, the 0 represents the full black, and the 255 represents the full bright. The average gray value is the average of the gray values of the black and white image, and represents the average brightness of the image. The preset gray threshold is a preset threshold of an average gray value used for judging the brightness degree of the image.
Specifically, when it is determined that the image of the current frame contains food, that is, when it is determined that the image of the region is a food image, the processor may input the food image into a pre-trained neural network model, perform image recognition on the food image through the neural network model, and obtain an output value of the model, that is, a food type corresponding to the food contained in the food image.
In one embodiment, in a case where it is determined that the food is contained in the image, the region image is a food image; in the case where the identification information of the food includes the oil amount condition, determining the identification information of the food includes: performing histogram statistics on the gray value of the food image to obtain the average gray value of the food image; comparing the average gray value with a preset gray threshold value; and determining the oil quantity condition of the food according to the comparison result.
Specifically, the processor may acquire gray value data of a food image, perform histogram statistics on each gray value data to obtain an average gray value of the food image according to a result of the histogram statistics, so as to compare the average gray value with a pre-stored preset gray threshold to obtain a comparison result, and according to the comparison result, the oil quantity condition of the food may be determined.
In one embodiment, in a case where it is determined that the food is contained in the image, the region image is a food image; in the case where the identification information of the food includes the food type and the oil amount condition, determining the identification information of the food includes: recognizing the food image through a pre-trained neural network model to obtain the food type corresponding to the food; performing histogram statistics on the gray value of the food image to obtain the average gray value of the food image; comparing the average gray value with a preset gray threshold value; and determining the oil quantity condition of the food according to the comparison result.
Specifically, when it is determined that the image of the current frame contains food, that is, when it is determined that the image of the region is a food image, the processor may input the food image into a pre-trained neural network model, perform image recognition on the food image through the neural network model, and obtain an output value of the model, that is, a food type corresponding to the food contained in the food image. When the identification information of the food comprises the oil quantity condition besides the food type, the processor can also acquire the gray value data of the food image after determining the food type of the food, perform histogram statistics on each gray value data to obtain the average gray value of the food image according to the result of the histogram statistics, so as to compare the average gray value with the pre-stored preset gray threshold value to obtain the comparison result, and determine the oil quantity condition of the food according to the comparison result.
In one embodiment, determining the oil amount of the food according to the comparison result includes: determining the oil quantity condition of the food as heavy oil under the condition that the average gray value is greater than a preset gray threshold value; and determining the oil quantity condition of the food as light oil under the condition that the average gray value is less than or equal to a preset gray threshold value.
Specifically, the processor determines the oil amount condition of the food as heavy oil when determining that the average gray value of the food image is greater than a preset gray threshold value. The processor determines the oil amount condition of the food as light oil when it is determined that the average gray value of the food image is less than or equal to a preset gray threshold value.
In some embodiments, the number of the preset grayscale threshold may be set as a number of different levels, so as to compare the average grayscale value with the preset grayscale thresholds one by one, thereby determining different levels corresponding to the oil quantity conditions of the food, where the oil quantity conditions of different levels may include, for example, heavy oil, medium oil, low oil, or light oil.
It is noted that the above cooking image processing method may be applied to at least one of: a range hood; a dishwasher; a server in communication with the range hood and the dishwasher, respectively.
Specifically, the application scenario illustrated in fig. 4 may be described, as illustrated in fig. 4, in one embodiment, taking the cooking image processing method applied to the range hood 104 as an example for explanation, the processor of the range hood 104 can directly acquire the image of the cooking area acquired by the image acquisition device, and judge whether the image contains food or not, in the case where it is determined that the food is contained in the image, the identification information of the food is determined, and the identification information of the food may be transmitted to the dishwasher 102 communicating with each other through a network (e.g., a local area network), and after the dishwasher 102 receives the identification information of the food, the processor of the dishwasher 102 may be based on a pre-stored correspondence of the identification information to the washing pattern, the corresponding recommended washing mode is determined according to the identification information of the food, and the dishwasher 102 can be controlled to execute the recommended washing mode when the dishwasher needs to work.
Continuing to refer to fig. 4, in an embodiment, taking an example that a cooking image processing method is applied to the dishwasher 102 as an illustration, the dishwasher 102 may communicate with the range hood 104 through a network (e.g., a local area network), the processor of the dishwasher 102 may obtain an image of a cooking area acquired by an image acquisition device of the range hood 104, determine whether the image contains food, determine identification information of the food when it is determined that the image contains food, determine a corresponding recommended washing mode according to the identification information of the food based on a correspondence between pre-stored identification information and washing modes, and further control the dishwasher 102 to execute the recommended washing mode when the dishwasher needs to operate.
Continuing to refer to fig. 4, in an embodiment, taking an example that the cooking image processing method is applied to a server (e.g., a cloud server) respectively communicating with the range hood 104 and the dishwasher 102, the server (e.g., the cloud server) may communicate with the range hood 104 to obtain an image of the cooking area acquired by the image acquisition device of the range hood 104, determine whether the image includes food, in the case where it is determined that the food is contained in the image, the identification information of the food is determined and transmitted to the dishwasher 102 in communication with a server (e.g., a cloud server), the processor of the dishwasher 102 determines the washing pattern based on the correspondence between the pre-stored identification information and the washing pattern, the corresponding washing mode is determined according to the received identification information of the food, and the dishwasher 102 can be controlled to execute the recommended washing mode when the dishwasher needs to operate. In some embodiments, the servers in communication with the range hood 104 and the dishwasher 102, respectively, may include, but are not limited to, a cloud server and a local server.
Embodiments of the present invention provide a processor configured to perform a control method for a dishwasher according to any of the above embodiments.
Embodiments of the present invention provide a processor configured to execute a cooking image processing method according to any of the above embodiments.
Embodiments of the present invention provide a machine-readable storage medium having stored thereon instructions which, when executed by a processor, cause the processor to perform a control method for a dishwasher according to any of the above embodiments.
Embodiments of the present invention provide a machine-readable storage medium having stored thereon instructions that, when executed by a processor, cause the processor to perform a cooking image processing method according to any of the above embodiments.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims (12)

1. A control method for a dishwasher, the dishwasher being in communication with a range hood, the range hood comprising an image acquisition device, the control method comprising:
acquiring identification information of food, wherein the identification information of the food is obtained from the image of the cooking area acquired by the image acquisition device;
and determining a recommended washing mode of the dishwasher according to the identification information of the food based on the corresponding relation between the pre-stored identification information and the washing mode.
2. The control method according to claim 1, wherein the identification information of the food includes a food type and/or an oil amount condition.
3. The control method for a dishwasher of claim 2, wherein the food category includes at least one of meat, vegetables, fruits and soups.
4. The control method for a dishwasher according to claim 1, wherein the recommended washing mode includes at least one of an ultra-strong washing mode, a standard washing mode, and a gentle washing mode.
5. A cooking image processing method, comprising:
acquiring an image of a cooking area acquired by image acquisition equipment of the range hood;
judging whether the image contains food or not;
and under the condition that the food is determined to be contained in the image, determining the identification information of the food, wherein the identification information of the food is used for determining a recommended washing mode for a dishwasher communicated with the range hood.
6. The cooking image processing method according to claim 5, wherein the identification information of the food includes a kind of food and/or an amount of oil.
7. The cooking image processing method according to claim 6, wherein the determining whether the image contains food comprises:
carrying out difference processing on the image of the current frame and a first frame image stored in advance to obtain a region image after difference processing;
and carrying out edge detection on the area image to identify whether the image contains food or not.
8. The cooking image processing method according to claim 7, wherein in a case where it is determined that the image contains food, the region image is a food image; the determining the identification information of the food includes:
identifying the food image through a pre-trained neural network model to obtain a food type corresponding to the food; and/or
Performing histogram statistics on the gray value of the food image to obtain an average gray value of the food image;
comparing the average gray value with a preset gray threshold value;
and determining the oil quantity condition of the food according to the comparison result.
9. The cooking image processing method according to claim 8, wherein the determining the oil amount of the food according to the comparison result comprises:
determining the oil quantity condition of the food as heavy oil under the condition that the average gray value is larger than a preset gray threshold value;
and determining the oil quantity condition of the food as light oil under the condition that the average gray value is less than or equal to a preset gray threshold value.
10. The cooking image processing method according to any one of claims 5 to 9, wherein the cooking image processing method is applied to at least one of:
the range hood;
the dishwasher;
a server in communication with the range hood and the dishwasher, respectively.
11. A processor characterized by being configured to execute the control method for a dishwasher according to any one of claims 1 to 4 or the cooking image processing method according to any one of claims 5 to 10.
12. A machine-readable storage medium having stored thereon instructions, characterized in that the instructions, when executed by a processor, cause the processor to execute the control method for a dishwasher according to any one of claims 1 to 4 or the cooking image processing method according to any one of claims 5 to 10.
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