CN113283364A - Recipe determination method and apparatus, storage medium, and electronic apparatus - Google Patents
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Abstract
The invention discloses a recipe determining method and device, a storage medium and an electronic device, wherein the method comprises the following steps: inputting food material pictures of food material storage equipment into a visual processing model to obtain food material information of the food material storage equipment, wherein the visual processing model is trained by machine learning by using multiple groups of data, and each group of data in the multiple groups of data comprises: the food material pictures and the food material information corresponding to the food material pictures; determining a food material list of food material storage equipment according to the food material types corresponding to the food material information; under the condition that the recommendation instruction of the target object is obtained, a plurality of recipes to be made are determined according to the food material list, the problems that food material updating information cannot be obtained in real time, recipe recommendation is carried out based on existing food materials and the like are solved, and then the food material list of the food materials is updated according to the storage condition of the food material storage device, so that the recommended recipes have high operability, and the success rate of making by using the recommended recipes is improved.
Description
Technical Field
The present invention relates to the field of communications, and in particular, to a recipe determination method and apparatus, a storage medium, and an electronic apparatus.
Background
In daily life, users often place various food materials (such as vegetables, cooked foods and the like) purchased in a refrigerator, and then select food materials considered to be suitable by the users for cooking when the users need to cook the food materials. With the rapid development of artificial intelligence, more and more recipe recommendation methods are proposed, some reference recipes can be recommended based on the requirements of users when related intelligent food storage home appliances meet food storage requirements, but related recipes need further confirmation of the users, and the recommended recipes are required to be browsed by the users in a long time due to the fact that the types of the food materials are more and the categories of the food materials are not detailed. In addition, the updating condition of the food materials in the intelligent food material storage household appliance is not considered when recommendation is performed, and targeted menu recommendation of the food materials stored in the intelligent food material storage household appliance cannot be performed.
Aiming at the problems that the food updating information cannot be obtained in real time and the recipe recommendation is carried out based on the existing food in the related art, an effective solution is not provided.
Disclosure of Invention
The embodiment of the invention provides a recipe determining method and device, a storage medium and an electronic device, and aims to at least solve the problems that in the related art, food material updating information cannot be obtained in real time, recipe recommendation is carried out based on existing food materials and the like.
According to an aspect of an embodiment of the present invention, there is provided a recipe determination method including: inputting food material pictures of food material storage equipment into a visual processing model to obtain food material information of the food material storage equipment, wherein the visual processing model is trained by machine learning by using multiple groups of data, and each group of data in the multiple groups of data comprises: the food material pictures and the food material information corresponding to the food material pictures; determining a food material list of food material storage equipment according to the food material types corresponding to the food material information; and under the condition of obtaining the recommendation instruction of the target object, determining a plurality of recipes to be made according to the food material list.
In an exemplary embodiment, after determining a plurality of recipes to be produced according to the food material list in the case of obtaining the request instruction of the target object, the method further includes: determining characteristic information of a plurality of recipes, wherein the characteristic information is used for indicating the taste characteristics and the making difficulty corresponding to the recipes; arranging the characteristic information to generate a characteristic list of a plurality of recipes; selection information of the target object is received to determine a target recipe to be made in the feature list.
In an exemplary embodiment, after receiving selection information of the target object to determine the target recipe to be made in the feature list, the method further includes: determining reference information corresponding to the target recipe, wherein the reference information comprises at least one of the following: a target recipe making video, a target recipe making audio and a target recipe making flow chart; determining at least one of the following target recipes from the reference information: the amount of food materials and the preparation process.
In an exemplary embodiment, after inputting the food material picture of the food material storage device into the visual processing model and obtaining the food material information of the food material storage device, the method further includes: determining a change state of food materials in the food material storage device, wherein the change state is used for indicating the number of the food materials and/or whether the types of the food materials are changed; and under the condition that the change state indicates that the number of the food materials and/or the types of the food materials are changed, acquiring a target food material picture after the number of the food materials and/or the types of the food materials are changed, and inputting the target food material picture into the visual processing model.
In an exemplary embodiment, in the case that the recommendation instruction of the target object is acquired, determining a plurality of recipes to be made according to the food material list includes: determining a recipe demand characteristic corresponding to the recommendation instruction, wherein the recipe demand characteristic is used for indicating the food material preference of the target object for the recipe; determining multiple manufacturing modes of the target food material under the condition that the target food material matched with the recipe requirement characteristics exists in the food material list, and determining multiple recipes of the target food material according to the multiple manufacturing modes.
In an exemplary embodiment, after determining a plurality of recipes to be produced according to the food material list under the condition that the recommendation instruction of the target object is obtained, the method further includes: obtaining a making record of a historical recipe of a target object; determining the diet preference of the target object according to the production record so as to determine the food materials needing to increase the number of the food materials.
According to another aspect of the embodiments of the present invention, there is also provided a recipe determination apparatus including: the food material image input device comprises a classification module and a visual processing module, wherein the classification module is used for inputting food material images of food material storage equipment into a visual processing model to obtain food material information of the food material storage equipment, the visual processing model is trained by machine learning by using multiple groups of data, and each group of data in the multiple groups of data comprises: the food material pictures and the food material information corresponding to the food material pictures; the first determining module is used for determining a food material list of the food material storage equipment according to the food material type corresponding to the food material information; and the second determining module is used for determining a plurality of recipes to be made according to the food material list under the condition of obtaining the recommendation instruction of the target object.
In an exemplary embodiment, the apparatus further includes: the third determining module is used for determining characteristic information of a plurality of recipes, wherein the characteristic information is used for indicating the taste characteristics and the making difficulty corresponding to the recipes; arranging the characteristic information to generate a characteristic list of a plurality of recipes; selection information of the target object is received to determine a target recipe to be made in the feature list.
In an exemplary embodiment, the third determining module is further configured to determine reference information corresponding to the target recipe, where the reference information includes at least one of: a target recipe making video, a target recipe making audio and a target recipe making flow chart; determining at least one of the following target recipes from the reference information: the amount of food materials and the preparation process.
In an exemplary embodiment, the apparatus further includes: the fourth determining module is used for determining the changing state of the food materials in the food material storage device, wherein the changing state is used for indicating the number of the food materials and/or whether the types of the food materials are changed; and under the condition that the change state indicates that the number of the food materials and/or the types of the food materials are changed, acquiring a target food material picture after the number of the food materials and/or the types of the food materials are changed, and inputting the target food material picture into the visual processing model.
In an exemplary embodiment, the second determining module is further configured to determine a recipe requirement characteristic corresponding to the recommendation instruction, where the recipe requirement characteristic is used to indicate a food material preference of the target object for the recipe; determining multiple manufacturing modes of the target food material under the condition that the target food material matched with the recipe requirement characteristics exists in the food material list, and determining multiple recipes of the target food material according to the multiple manufacturing modes.
In an exemplary embodiment, the modules further include an obtaining module, further configured to obtain a production record of a historical recipe of the target subject; determining the diet preference of the target object according to the production record so as to determine the food materials needing to increase the number of the food materials.
According to a further aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium having a computer program stored therein, wherein the computer program is configured to execute the method for determining recipes.
According to another aspect of the embodiments of the present invention, there is also provided an electronic apparatus, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the recipe determination method through the computer program.
In the embodiment of the present invention, a food material picture of a food material storage device is input into a visual processing model to obtain food material information of the food material storage device, wherein the visual processing model is trained by machine learning by using multiple groups of data, and each group of data in the multiple groups of data includes: the food material pictures and the food material information corresponding to the food material pictures; determining a food material list of food material storage equipment according to the food material types corresponding to the food material information; under the condition of obtaining the recommendation instruction of the target object, determining a plurality of recipes to be made according to the food material list, namely determining the food material list by obtaining the food material pictures of the food material storage device in real time, and then recommending related recipes to the target object according to the food materials in the food material list.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a block diagram of a hardware configuration of a computer terminal of a recipe determination method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method of recipe determination according to an embodiment of the invention;
fig. 3 is a schematic flow diagram of food material storage according to an alternative embodiment of the invention;
FIG. 4 is a schematic flow chart of obtaining recipes in accordance with an alternative embodiment of the invention;
fig. 5 is a logic flow diagram of an implementation of acquiring food material through Open CV according to an alternative embodiment of the invention;
FIG. 6 is a flow diagram of the software installation of Open CV (one), in accordance with an alternative embodiment of the present invention;
FIG. 7 is a flow chart of the software installation of Open CV (two), in accordance with an alternative embodiment of the present invention;
fig. 8 is a block diagram of a recipe determination apparatus according to an embodiment of the present invention.
Detailed Description
Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings in conjunction with the embodiments.
It is noted that the terms first, second and the like in the description and in the claims, and in the drawings, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
The method provided by the embodiment of the application can be executed in a computer terminal, a mobile terminal or a similar operation device. Taking the example of the method running on a computer terminal, fig. 1 is a block diagram of a hardware structure of the computer terminal of the recipe determination method according to the embodiment of the present invention. As shown in fig. 1, the computer terminal may include one or more (only one shown in fig. 1) processors 102 (the processors 102 may include, but are not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, and in an exemplary embodiment, may also include a transmission device 106 for communication functions and an input-output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration and is not intended to limit the structure of the computer terminal. For example, the computer terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration with equivalent functionality to that shown in FIG. 1 or with more functionality than that shown in FIG. 1.
The memory 104 may be used for storing computer programs, for example, software programs and modules of application software, such as computer programs corresponding to the recipe determining method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, so as to implement the method described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to a computer terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the computer terminal. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
In the present embodiment, a method for determining a recipe is provided, and fig. 2 is a flowchart of a method for determining a recipe according to an embodiment of the present invention, where the flowchart includes the following steps:
step S202, inputting food material pictures of food material storage equipment into a visual processing model to obtain food material information of the food material storage equipment, wherein the visual processing model is trained by using multiple groups of data through machine learning, and each group of data in the multiple groups of data comprises: the method comprises the steps of obtaining a food material picture and food material information corresponding to the food material picture;
step S204, determining a food material list of the food material storage equipment according to the food material type corresponding to the food material information;
and step S206, under the condition that the recommendation instruction of the target object is obtained, determining a plurality of recipes to be made according to the food material list.
Through the steps, food material pictures of the food material storage device are input into the visual processing model, food material information of the food material storage device is obtained, wherein the visual processing model is trained by machine learning by using multiple groups of data, and each group of data in the multiple groups of data comprises: the food material pictures and the food material information corresponding to the food material pictures; determining a food material list of food material storage equipment according to the food material types corresponding to the food material information; under the condition of obtaining the recommendation instruction of the target object, determining a plurality of recipes to be made according to the food material list, namely determining the food material list by obtaining the food material pictures of the food material storage device in real time, and then recommending related recipes to the target object according to the food materials in the food material list.
It should be noted that, in order to facilitate real-time management of food materials in the food material storage device, the food material pictures input to the visual processing model may be automatically updated within a certain period, or when a preset food material picture updating condition is triggered, specifically, a target object finishes consumption of a certain type of food materials in the food material storage device or the target object has a new food material type purchased.
In an exemplary embodiment, after determining a plurality of recipes to be produced according to the food material list in the case of obtaining the request instruction of the target object, the method further includes: determining characteristic information of a plurality of recipes, wherein the characteristic information is used for indicating the taste characteristics and the making difficulty corresponding to the recipes; arranging the characteristic information to generate a characteristic list of a plurality of recipes; selection information of the target object is received to determine a target recipe to be made in the feature list.
In short, in order to improve the use probability of the target object on the recommended recipes to be made, before the food material storage device displays the recipes to be made, the taste characteristics and the making difficulty of the recipes are compared to determine the characteristic list of the recipes, so that when the recommended recipes are displayed, the recommended recipes can be displayed in a priority level according to the eating habits of the target object, and the target recipes to be made are determined in the characteristic list according to the selection information of the target object.
In an exemplary embodiment, after receiving selection information of the target object to determine the target recipe to be made in the feature list, the method further includes: determining reference information corresponding to the target recipe, wherein the reference information comprises at least one of the following: a target recipe making video, a target recipe making audio and a target recipe making flow chart; determining at least one of the following target recipes from the reference information: the amount of food materials and the preparation process.
It can be understood that, in order to enable the target object to know the recipe production flow as fast as possible, after the target recipe selected by the target object is determined, the reference information of the target recipe is determined, and further, the food material usage amount and the production flow for presenting the target recipe to the target object are determined by combining the specific content in the reference information, so that the target object can better realize the target recipe. In addition, the determined reference information can be played on a display interface or an audio playing interface of the food material storage device, or the determined target recipe can be sent to a terminal which is in communication connection with the food material storage device for displaying through information correlation between the devices.
In an exemplary embodiment, after inputting the food material picture of the food material storage device into the visual processing model and obtaining the food material information of the food material storage device, the method further includes: determining a change state of food materials in the food material storage device, wherein the change state is used for indicating the number of the food materials and/or whether the types of the food materials are changed; and under the condition that the change state indicates that the number of the food materials and/or the types of the food materials are changed, acquiring a target food material picture after the number of the food materials and/or the types of the food materials are changed, and inputting the target food material picture into the visual processing model.
That is to say, when the number or the variety of the food materials in the food material storage device is changed, the food material storage device will re-collect the food material pictures of the food materials stored inside, and input the newly collected food material pictures into the visual processing model to update the food material information.
In an exemplary embodiment, in the case that the recommendation instruction of the target object is acquired, determining a plurality of recipes to be made according to the food material list includes: determining a recipe demand characteristic corresponding to the recommendation instruction, wherein the recipe demand characteristic is used for indicating the food material preference of the target object for the recipe; determining multiple manufacturing modes of the target food material under the condition that the target food material matched with the recipe requirement characteristics exists in the food material list, and determining multiple recipes of the target food material according to the multiple manufacturing modes.
In short, in order to enable the requirements of the target object to be matched with the food materials in the food material storage device, when the recipe is recommended, the recommendation instruction sent by the target object can be analyzed, the current diet requirements of the target object are obtained, the food material preference of the recipe to be recommended is determined according to the diet requirements, and then under the condition that the food materials are stored in the food material list, multiple manufacturing modes of the food materials are determined, and multiple recipes corresponding to the multiple manufacturing modes are recommended to the target object.
In an exemplary embodiment, after determining a plurality of recipes to be produced according to the food material list under the condition that the recommendation instruction of the target object is obtained, the method further includes: obtaining a making record of a historical recipe of a target object; determining the diet preference of the target object according to the production record so as to determine the food materials needing to increase the number of the food materials. Namely, in order to ensure that the food material storage device always stores the food materials favored by the target object, the unique dietary preference of the target object is determined by determining the making record of the historical recipe recommended by the target object to the food material storage device, and the target object is regularly reminded to increase the number of the corresponding food materials according to the dietary preference.
In order to better understand the technical solutions of the embodiments and the alternative embodiments of the present invention, the following explains the flow of the recipe determining method with reference to the examples, but is not limited to the technical solutions of the embodiments of the present invention.
In order to better understand the technical solutions of the embodiments and the alternative embodiments of the present invention, the following description is made on keywords that may appear in the embodiments and the alternative embodiments of the present invention, but the present invention is not limited thereto.
Sample preparation: the sum of the characteristics and characteristic values of all articles;
is characterized in that: shape, color, outline, characteristics of the article, etc.;
characteristic value: elliptical, yellow, relatively sharp at both ends, size, etc. characteristic values;
target value: oval, yellow, relatively sharp at both ends, size (about 10cm long, about 5cm wide, about 5cm high), etc.;
discrete value: data are compared and dispersed, namely, the data are called discrete values;
continuous values: data is continuous, called back;
KN algorithm (K-Nearest Neighbor, K-Nearest Neighbor algorithm): judging the classification of the target value according to the k samples with similar neighbors; the nearest neighbor samples are compared.
The scheme for obtaining refrigerator food materials and recommending the menu based on the Open CV technology is provided in the optional embodiment of the invention, the food materials are identified by integrating an Open CV module in a refrigerator, then the food materials are stored in a Redis or database, and a food material list stored in the Redis or database is updated according to the newly added or taken food materials. When a user triggers a menu recommending function, searching a menu according to the existing food materials as keywords, recommending a menu file to a refrigerator, and downloading and playing the menu by the refrigerator according to the menu selected by the user.
As an optional implementation manner, fig. 3 is a schematic view of a process of storing food materials according to an optional embodiment of the present invention, when a food material is changed (newly added or taken out), a refrigerator identifies the changed food material using an Open CV tool, updates change information of the food material into a food material list, and then obtains a recipe file address and a recipe content according to the food material in the food material list and caches the recipe file address and the recipe content in a database, so as to facilitate subsequent calls.
As an alternative implementation, fig. 4 is a schematic flow chart of acquiring a menu according to an alternative embodiment of the present invention, and a user may speak to a refrigerator: and recommending a plurality of menus according to the small priority and the small priority, then pushing information to the user according to the cached menus by the refrigerator, displaying the cached menus on a screen of the refrigerator, selecting the menus according to the needs of the user, downloading the menus selected by the user and playing the menus on the screen of the refrigerator.
As an optional implementation manner, fig. 5 is a logic flow diagram of an implementation of obtaining food materials through Open CV in an optional embodiment of the invention.
Target detection is performed through Open CV, sample library and training image recognition are established, and classifier training is performed by using the characteristics of samples (about hundreds of sample pictures) to obtain a cascaded classifier. The training sample is divided into a positive sample and a negative sample, wherein the positive sample refers to a sample to be inspected (such as fruit or vegetable), the negative sample refers to any other pictures, and all the sample pictures are normalized to the same size (such as 20x 20). After the classifier is trained, it can be applied to the detection of the region of interest (same size as the training sample) in the input image. The classifier output of the target area (fruit or vegetable) is detected to be 1, otherwise the output is 0. To detect the entire image, the search window may be moved through the image, detecting each location to determine a possible target. In order to search for target objects of different sizes, the classifier is designed to be capable of size change, which is more effective than changing the size of the image to be examined. Therefore, in order to detect a target object with unknown size in an image, a scanning program usually needs to scan the image several times by using search windows with different proportional sizes, and a sample grade can be imported from an existing disk file or an embedded base by using a function. And loading the trained cascade classifier from a file or importing the classifier from a classifier database embedded in an Open CV to obtain the path of the trained cascade classifier.
Optionally, the image recognition calculates the characteristics of the object through a CNN (Convolutional Neural Networks, CNN for short) edge algorithm;
the image is converted into gray scale through a computer, then the computer performs binary conversion on the identified image, the place without the image is marked as 0, the identified image is subjected to an operation to obtain a characteristic and a characteristic value, then a KN algorithm is performed in a sample, the nearest article is calculated, and the optimal value is returned and stored in a cloud.
As an optional implementation manner, a system of a refrigerator is generally divided into iOS, Android and Linux environments, as shown in fig. 6, a Software installation flow chart (i) of Open CV according to an optional embodiment of the present invention is shown, when the Open CV is deployed to the Android and iOS in an environment deployment manner through an SDK (Software Development Kit, SDK for short), an SDK corresponding to the Open CV is installed to the refrigerator system first, and then eclipse is installed, and the SDK is enabled to be used, as shown in fig. 7, a Software installation flow chart (ii) of Open CV according to an optional embodiment of the present invention is shown. When Open CV is to be installed in a Linux environment, firstly CMake constructs Open CV, then configures Open CV path parameters, and then constructs a language environment: java or Python, constructing a document in the next step, and finally installing an Open CV library.
According to the optional embodiment, the Open CV technology is used for obtaining and storing the food materials, the food materials are added or taken out for storage, then the menu is searched for by taking the existing food materials as the keywords, the menu file is recommended to the refrigerator, the menu is downloaded by the refrigerator according to the menu selected by the user and played, and the accuracy of recommending the menu to the user is improved.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, an evener, or a network device) to execute the method according to the embodiments of the present invention.
In this embodiment, a recipe determining apparatus is further provided, and the apparatus is used to implement the foregoing embodiments and preferred embodiments, which have already been described and are not described again. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 8 is a block diagram showing a structure of a recipe determining apparatus according to an embodiment of the present invention, as shown in fig. 8, the apparatus including:
the classification module 82 is configured to input a food material picture of a food material storage device into a visual processing model to obtain food material information of the food material storage device, where the visual processing model is trained through machine learning by using multiple groups of data, and each group of data in the multiple groups of data includes: the method comprises the steps of obtaining a food material picture and food material information corresponding to the food material picture;
a first determining module 84, configured to determine a food material list of the food material storage device according to a food material category corresponding to the food material information;
and a second determining module 86, configured to determine, according to the food material list, a plurality of recipes to be made under the condition that the recommendation instruction of the target object is obtained.
Through above-mentioned device, with eating the material picture of material storage device input to the vision processing model in, obtain eating the material information of material storage device, wherein, the vision processing model is trained out for using multiunit data through machine learning, and every group data in the multiunit data all includes: the food material pictures and the food material information corresponding to the food material pictures; determining a food material list of food material storage equipment according to the food material types corresponding to the food material information; under the condition of obtaining the recommendation instruction of the target object, determining a plurality of recipes to be made according to the food material list, namely determining the food material list by obtaining the food material pictures of the food material storage device in real time, and then recommending related recipes to the target object according to the food materials in the food material list.
It should be noted that, in order to facilitate real-time management of food materials in the food material storage device, the food material pictures input to the visual processing model may be automatically updated within a certain period, or when a preset food material picture updating condition is triggered, specifically, a target object finishes consumption of a certain type of food materials in the food material storage device or the target object has a new food material type purchased.
In an exemplary embodiment, the apparatus further includes: the third determining module is used for determining characteristic information of a plurality of recipes, wherein the characteristic information is used for indicating the taste characteristics and the making difficulty corresponding to the recipes; arranging the characteristic information to generate a characteristic list of a plurality of recipes; selection information of the target object is received to determine a target recipe to be made in the feature list.
In short, in order to improve the use probability of the target object on the recommended recipes to be made, before the food material storage device displays the recipes to be made, the taste characteristics and the making difficulty of the recipes are compared to determine the characteristic list of the recipes, so that when the recommended recipes are displayed, the recommended recipes can be displayed in a priority level according to the eating habits of the target object, and the target recipes to be made are determined in the characteristic list according to the selection information of the target object.
In an exemplary embodiment, the third determining module is further configured to determine reference information corresponding to the target recipe, where the reference information includes at least one of: a target recipe making video, a target recipe making audio and a target recipe making flow chart; determining at least one of the following target recipes from the reference information: the amount of food materials and the preparation process.
It can be understood that, in order to enable the target object to know the recipe production flow as fast as possible, after the target recipe selected by the target object is determined, the reference information of the target recipe is determined, and further, the food material usage amount and the production flow for presenting the target recipe to the target object are determined by combining the specific content in the reference information, so that the target object can better realize the target recipe. In addition, the determined reference information can be played on a display interface or an audio playing interface of the food material storage device, or the determined target recipe can be sent to a terminal which is in communication connection with the food material storage device for displaying through information correlation between the devices.
In an exemplary embodiment, the apparatus further includes: the fourth determining module is used for determining the changing state of the food materials in the food material storage device, wherein the changing state is used for indicating the number of the food materials and/or whether the types of the food materials are changed; and under the condition that the change state indicates that the number of the food materials and/or the types of the food materials are changed, acquiring a target food material picture after the number of the food materials and/or the types of the food materials are changed, and inputting the target food material picture into the visual processing model.
That is to say, when the number or the variety of the food materials in the food material storage device is changed, the food material storage device will re-collect the food material pictures of the food materials stored inside, and input the newly collected food material pictures into the visual processing model to update the food material information.
In an exemplary embodiment, the second determining module is further configured to determine a recipe requirement characteristic corresponding to the recommendation instruction, where the recipe requirement characteristic is used to indicate a food material preference of the target object for the recipe; determining multiple manufacturing modes of the target food material under the condition that the target food material matched with the recipe requirement characteristics exists in the food material list, and determining multiple recipes of the target food material according to the multiple manufacturing modes.
In short, in order to enable the requirements of the target object to be matched with the food materials in the food material storage device, when the recipe is recommended, the recommendation instruction sent by the target object can be analyzed, the current diet requirements of the target object are obtained, the food material preference of the recipe to be recommended is determined according to the diet requirements, and then under the condition that the food materials are stored in the food material list, multiple manufacturing modes of the food materials are determined, and multiple recipes corresponding to the multiple manufacturing modes are recommended to the target object.
In an exemplary embodiment, the modules further include an obtaining module, further configured to obtain a production record of a historical recipe of the target subject; determining the diet preference of the target object according to the production record so as to determine the food materials needing to increase the number of the food materials. Namely, in order to ensure that the food material storage device always stores the food materials favored by the target object, the unique dietary preference of the target object is determined by determining the making record of the historical recipe recommended by the target object to the food material storage device, and the target object is regularly reminded to increase the number of the corresponding food materials according to the dietary preference.
It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
Embodiments of the present invention also provide 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.
Alternatively, in the present embodiment, the storage medium may be configured to store a computer program for executing the steps of:
s1, inputting food material pictures of a food material storage device into a visual processing model to obtain food material information of the food material storage device, wherein the visual processing model is trained by machine learning by using multiple groups of data, and each group of data in the multiple groups of data comprises: food material picture and food material information corresponding to food material picture
S2, determining a food material list of the food material storage equipment according to the food material type corresponding to the food material information;
and S3, determining a plurality of recipes to be made according to the food material list under the condition of acquiring the recommendation instruction of the target object.
Embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program is arranged to perform the steps of any of the above-mentioned method embodiments when executed.
In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
In an exemplary embodiment, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
In an exemplary embodiment, the processor may be configured to execute the following steps by a computer program:
s1, inputting food material pictures of a food material storage device into a visual processing model to obtain food material information of the food material storage device, wherein the visual processing model is trained by machine learning by using multiple groups of data, and each group of data in the multiple groups of data comprises: food material picture and food material information corresponding to food material picture
S2, determining a food material list of the food material storage equipment according to the food material type corresponding to the food material information;
and S3, determining a plurality of recipes to be made according to the food material list under the condition of acquiring the recommendation instruction of the target object.
It will be apparent to those skilled in the art that the various modules or steps of the invention described above may be implemented using a general purpose computing device, they may be centralized on a single computing device or distributed across a network of computing devices, and they may be implemented using program code executable by the computing devices, such that they may be stored in a memory device and executed by the computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into various integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method of recipe determination comprising:
inputting food material pictures of food material storage equipment into a visual processing model to obtain food material information of the food material storage equipment, wherein the visual processing model is trained by using multiple groups of data through machine learning, and each group of data in the multiple groups of data comprises: the method comprises the steps of obtaining a food material picture and food material information corresponding to the food material picture;
determining a food material list of the food material storage equipment according to the food material type corresponding to the food material information;
and under the condition of obtaining a recommendation instruction of a target object, determining a plurality of recipes to be made according to the food material list.
2. The method according to claim 1, wherein after determining a plurality of recipes to be produced according to the food material list in a case where the request instruction of the target object is obtained, the method further comprises:
determining characteristic information of the plurality of recipes, wherein the characteristic information is used for indicating corresponding taste characteristics and making difficulty of the recipes;
arranging the characteristic information to generate a characteristic list of the plurality of recipes;
and receiving selection information of the target object so as to determine a target recipe to be made in the feature list.
3. The method of claim 2, wherein receiving selection information of the target object for determining a target recipe to be produced in the feature list further comprises:
determining reference information corresponding to the target recipe, wherein the reference information comprises at least one of the following: a target recipe making video, a target recipe making audio and a target recipe making flow chart;
determining at least one of the following of the target recipe from the reference information: the amount of food materials and the preparation process.
4. The method of claim 1, wherein after inputting the food material picture of the food material storage device into the visual processing model and obtaining the food material information of the food material storage device, the method further comprises:
determining a change state of food materials in the food material storage device, wherein the change state is used for indicating the number of the food materials and/or whether the types of the food materials are changed;
and under the condition that the change state indicates that the number of the food materials and/or the types of the food materials are changed, acquiring a target food material picture after the number of the food materials and/or the types of the food materials are changed, and inputting the target food material picture into the visual processing model.
5. The method of claim 1, wherein determining a plurality of recipes to be made according to the food material list when the recommendation instruction of the target object is obtained comprises:
determining a recipe demand characteristic corresponding to the recommendation instruction, wherein the recipe demand characteristic is used for indicating the food material preference of a target object for a recipe;
and under the condition that the target food material matched with the recipe demand characteristics exists in the food material list, determining multiple manufacturing modes of the target food material, and determining multiple recipes of the target food material according to the multiple manufacturing modes.
6. The method according to claim 1, wherein after determining a plurality of recipes to be produced according to the food material list in a case where the recommendation instruction of the target object is obtained, the method further comprises:
acquiring a making record of a historical recipe of the target object;
determining the diet preference of the target object according to the production record so as to determine the food materials needing to increase the number of the food materials.
7. A recipe determination apparatus, comprising:
the food material information processing system comprises a classification module and a processing module, wherein the classification module is used for inputting food material pictures of food material storage equipment into a visual processing model to obtain food material information of the food material storage equipment, the visual processing model is trained by using multiple groups of data through machine learning, and each group of data in the multiple groups of data comprises: the method comprises the steps of obtaining a food material picture and food material information corresponding to the food material picture;
the first determining module is used for determining a food material list of the food material storage equipment according to the food material type corresponding to the food material information;
and the second determining module is used for determining a plurality of recipes to be made according to the food material list under the condition of obtaining the recommendation instruction of the target object.
8. The apparatus of claim 7, further comprising: the third determining module is used for determining characteristic information of the plurality of recipes, wherein the characteristic information is used for indicating the taste characteristics and the making difficulty corresponding to the recipes; arranging the characteristic information to generate a characteristic list of the plurality of recipes; and receiving selection information of the target object so as to determine a target recipe to be made in the feature list.
9. A computer-readable storage medium, comprising a stored program, wherein the program is operable to perform the method of any one of claims 1 to 6.
10. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method of any of claims 1 to 6 by means of the computer program.
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