阅读说明：本技术 摆放餐具的方法及装置 (Method and device for placing tableware ) 是由 易斌 高丹 万会 徐洪伟 于 2018-09-13 设计创作，主要内容包括：本申请提供了一种摆放餐具的方法及装置,其中,该方法包括：通过摄像头获取当前洗碗机中的餐具的第一照片,使用预先训练好的机器学习模型对第一照片进行分析,得出当前餐具的总数量,以及餐具类型等信息,依据该信息计算出摆放餐具的方式,洗碗机依据该方式在存储位置摆放餐具,采用上述方案,解决了相关技术中洗碗机内的餐具需要人工摆放的问题,洗碗机自动化地实现了餐具摆放,不需要人工参与,节省了人力资源。(The application provides a method and a device for placing tableware, wherein the method comprises the following steps: acquire the first photo of the tableware in current dish washer through the camera, use the machine learning model that trains in advance to carry out the analysis to first photo, reach the total number of current tableware, and information such as tableware type, calculate the mode of putting the tableware according to this information, the dish washer is put the tableware at memory location according to this mode, adopt above-mentioned scheme, the problem that the tableware needs the manual work to put in the dish washer among the correlation technique has been solved, the dish washer has realized the tableware automatically and has been put, do not need artifical the participation, manpower resources have been saved.)

1. A method of holding dishes, comprising:

acquiring a first picture of tableware in the dishwasher through a camera;

obtaining first tableware information having an association relation with the first photo by using a machine learning model, wherein the machine learning model is obtained by training an original model by using first sample information as input information of the original model, the first sample information comprises a first rule and a plurality of groups of photos, and the first rule is a rule for judging tableware information in the photos according to the result of recognizing the photos;

and acquiring placing operation information of placing tableware in the dishwasher according to the first tableware information, and controlling the dishwasher to execute the placing operation information.

2. The method of claim 1, wherein prior to obtaining the first piece of dining information having an association relationship with the first photo using a machine learning model, the method further comprises:

step one, a plurality of groups of photos of the first sample information are used as input information to be input into the original model, and the plurality of groups of photos are recognized in the original model according to the first rule to obtain a recognition result;

step two, checking the recognition result according to the tableware information actually corresponding to the multiple groups of photos of the first sample information, and acquiring a recognition standard group rate;

step three, under the condition that the identification accuracy is lower than a threshold value, adjusting the original model;

and step four, repeatedly executing the step one to the step three until the identification accuracy is higher than a threshold value, and outputting a model as the machine learning model.

3. The method of claim 1, wherein obtaining first meal information having an association relationship with the first photograph using a machine learning model comprises:

identifying a total number of utensils, a type of utensils, and/or a number of utensils of each type in the first photograph using a machine learning model;

the total number of dishes, the type of dishes, and/or the number of dishes per type are used as the first meal information.

4. The method of claim 1, wherein obtaining placement information for placing dishes in the dishwasher based on the first meal information comprises:

acquiring specification information of a tableware placing area of the dish washing machine;

and acquiring the placing operation information according to the first tableware information and the specification information, wherein the placing operation information comprises placing the tableware of the same type to adjacent positions.

5. The method of claim 4, wherein the specification information includes at least one of:

placing a first maximum number of the various types of tableware in the tableware placing area respectively;

placing a second maximum number of the plurality of types of cutlery simultaneously within the cutlery placement area.

6. A device for placing tableware, comprising:

the first acquisition module is used for acquiring a first picture of tableware in the dish washing machine through the camera;

the second obtaining module is used for obtaining first tableware information which has an incidence relation with the first photo by using a machine learning model, wherein the machine learning model is obtained by training an original model by using first sample information as input information of the original model, the first sample information comprises a first rule and a plurality of groups of photos, and the first rule is a rule for judging the tableware information in the photos according to the result of recognizing the photos;

and the third acquisition module is used for acquiring the placing operation information of the tableware placed in the dishwasher according to the first tableware information and controlling the dishwasher to execute the placing operation information.

7. The apparatus of claim 6, wherein the second obtaining module, before obtaining the first piece of tableware information having an association relationship with the first photo using a machine learning model, is further configured to perform the following steps:

step one, a plurality of groups of photos of the first sample information are used as input information to be input into the original model, and the plurality of groups of photos are recognized in the original model according to the first rule to obtain a recognition result;

step two, checking the recognition result according to the tableware information actually corresponding to the multiple groups of photos of the first sample information, and acquiring a recognition standard group rate;

step three, under the condition that the identification accuracy is lower than a threshold value, adjusting the original model;

and step four, repeatedly executing the step one to the step three until the identification accuracy is higher than a threshold value, and outputting a model as the machine learning model.

8. The apparatus of claim 6, wherein the second acquisition module is further configured to identify a total number of utensils, a type of utensils, and/or a number of utensils of each type in the first photograph using a machine learning model;

and for using the total number of dishes, the type of dishes and/or the number of dishes of each type as the first meal information.

9. A storage medium, in which a computer program is stored, wherein the computer program is arranged to perform the method of any of claims 1 to 5 when executed.

10. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and wherein the processor is arranged to execute the computer program to perform the method of any of claims 1 to 5.

Technical Field

The application relates to the field of but not limited to electric appliances, in particular to a method and a device for placing tableware.

Background

In the related art, as the home appliance industry develops, the popularity of the dish washer becomes more and more widespread. The dish washer completes the washing of tableware through spraying high temperature and high pressure with the spray head. Generally, dish washer all has functions such as having washed, drying, storage, not only can replace the function that the user accomplished the dish washing, can also replace sterilizer or cupboard, stores the tableware and puts. However, in the related art, although the dishwasher can automatically complete the washing operation without waiting for people during the washing process, the dishwasher needs to manually place the dishes after completing the washing operation, which not only causes inconvenience to users, but also causes the cleaned dishes to be polluted again due to human intervention, and thus, the placing manner of the dishes needs to be improved.

Aiming at the problem that tableware in a dish washer in the related art needs to be manually placed, no effective solution is available at present.

Disclosure of Invention

The embodiment of the application provides a method and a device for placing tableware, which are used for at least solving the problem that the tableware in a dish washing machine needs to be placed manually in the related art.

According to an embodiment of the present application, there is provided a method of placing tableware, including: acquiring a first picture of tableware in the dishwasher through a camera; obtaining first tableware information having an association relation with the first photo by using a machine learning model, wherein the machine learning model is obtained by training an original model by using first sample information as input information of the original model, the first sample information comprises a first rule and a plurality of groups of photos, and the first rule is a rule for judging tableware information in the photos according to the result of recognizing the photos; and acquiring placing operation information of placing tableware in the dishwasher according to the first tableware information, and controlling the dishwasher to execute the placing operation information.

According to another embodiment of the present application, there is also provided a device for holding dishes, including: the first acquisition module is used for acquiring a first picture of tableware in the dish washing machine through the camera; the second obtaining module is used for obtaining first tableware information which has an incidence relation with the first photo by using a machine learning model, wherein the machine learning model is obtained by training an original model by using first sample information as input information of the original model, the first sample information comprises a first rule and a plurality of groups of photos, and the first rule is a rule for judging the tableware information in the photos according to the result of recognizing the photos; and the third acquisition module is used for acquiring the placing operation information of the tableware placed in the dishwasher according to the first tableware information and controlling the dishwasher to execute the placing operation information.

According to a further embodiment of the present application, there is also provided a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.

According to yet another embodiment of the present application, there is also provided an electronic device, comprising a memory in which a computer program is stored and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.

Through this application, acquire the first photo of the tableware in the current dish washer through the camera, use the machine learning model that trains in advance to carry out the analysis to first photo, reach the total number of current tableware, and information such as tableware type, calculate the mode of putting the tableware according to this information, the dish washer is put the tableware at memory location according to this mode, adopt above-mentioned scheme, the problem that the tableware needs the manual work to put in the dish washer among the correlation technique has been solved, the dish washer has realized the tableware automatically and has been put, do not need artifical participation, manpower resources have been saved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

fig. 1 is a block diagram of a hardware structure of a computer terminal of a method for placing tableware according to an embodiment of the present application;

FIG. 2 is a flow chart of a method for placing dishes according to an embodiment of the present application;

fig. 3 is a flow chart of a method for placing dishes based on a neural network according to another embodiment of the present application.

Detailed Description

The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.

It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.