CN117894431A - Recipe generation method and device, electronic equipment and readable storage medium - Google Patents
Recipe generation method and device, electronic equipment and readable storage medium Download PDFInfo
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Abstract
The application discloses a recipe generation method, a recipe generation device, electronic equipment and a readable storage medium, wherein the recipe generation method comprises the following steps: determining abnormal physical examination data from the first physical examination data of the user based on the standard physical examination data index; determining a first food material from preset food materials based on abnormal physical examination data; acquiring a first kitchen ware type held by a user; according to the first kitchen ware type and the first food material generation target recipe, corresponding recipes can be generated for the user according to the abnormal physical examination data of the user and the existing kitchen ware type, and the suitability between the recipes and the user is improved to a certain extent.
Description
Technical Field
The application belongs to the technical field of data processing, and particularly relates to a recipe generation method, a recipe generation device, electronic equipment and a readable storage medium.
Background
With the increase of health consciousness, people pay more attention to the influence of diet on health. A wide variety of foods may contain various substances required for the human body, such as sugar, salt, protein, trace elements, etc. For health reasons, people often need to consider matching between foods when taking foods, so that various substances taken into the foods have reasonable taking proportion.
In the related art, a recommendation can be made to a user based on an existing health recipe so that food ingested by the user meets health requirements.
However, in this method, the suitability of the recipe to the user is poor, and the actual demands of the user cannot be satisfied.
Disclosure of Invention
An object of the embodiments of the present application is to provide a recipe generation method, apparatus, electronic device, and readable storage medium, which can solve the problem of poor suitability of a recommended recipe and a user in the related art.
In a first aspect, an embodiment of the present application provides a recipe generation method, including:
determining abnormal physical examination data from the first physical examination data of the user based on the standard physical examination data index;
determining a first food material from preset food materials based on the abnormal physical examination data;
acquiring a first kitchen ware type held by the user;
generating a target recipe according to the first kitchen ware type and the first food material.
Optionally, the determining the first food material from the preset food materials based on the abnormal physical examination data includes:
determining an abnormal difference value between the abnormal physical examination data and the standard physical examination data index;
determining the proportion of the nutritional ingredients of the preset food materials based on the nutritional ingredient content contained in the preset food materials;
and determining the first food material from the preset food materials based on the nutrient component proportion of the preset food materials and the abnormal difference value.
Optionally, the generating a target recipe according to the first kitchen ware category and the first food material includes:
determining a first cooking mode from preset cooking modes based on a first kitchen ware type of the user;
a target recipe is generated based on the first food material and the first cooking mode.
Optionally, the determining a first cooking mode from preset cooking modes based on the first kitchen ware type of the user includes:
determining a second kitchen tool type from the first kitchen tool types of the user based on the abnormal physical examination data;
and determining a first cooking mode from preset cooking modes based on the second kitchen appliance type.
Optionally, the generating a target recipe based on the first food material and the first cooking mode includes:
determining a target cooking regimen from the first cooking regimen based on the nutritional ingredients of the first food material;
the target recipe is generated based on the target cooking regime and the first food material.
Optionally, the generating a target recipe based on the first food material and the first cooking mode includes:
determining a second food material from the first food material based on the first kitchen ware category;
the target recipe is generated based on the second food material and the first cooking mode.
Optionally, the determining the first food material from the preset food materials based on the abnormal physical examination data includes:
determining historical disease information of the user from the first biopsy data;
and determining the first food material from the preset food materials based on the historical disease information and the abnormal physical examination data.
In a second aspect, the present application provides a recipe generation apparatus, the apparatus comprising:
the first determining module is used for determining abnormal physical examination data from first physical examination data of a user based on standard physical examination data indexes;
the second determining module is used for determining a first food material from preset food materials based on the abnormal physical examination data;
the acquisition module is used for acquiring a first kitchen ware type held by the user;
the generation module is used for generating a target recipe according to the first kitchen ware type and the first food materials.
Optionally, the second determining module includes:
the first determining submodule is used for determining an abnormal difference value between the abnormal physical examination data and the standard physical examination data index;
a second determining submodule, configured to determine a nutritional ingredient proportion of the preset food material based on a nutritional ingredient content included in the preset food material;
and a third determining sub-module for determining the first food material from the preset food materials based on the nutrient component proportion and the abnormal difference value of the preset food materials.
Optionally, the generating module includes:
a fourth determining sub-module for determining a first cooking mode from preset cooking modes based on the first kitchen ware type of the user;
and the generation submodule is used for generating a target recipe based on the first food materials and the first cooking mode.
Optionally, the fourth determining sub-module includes:
a first determining unit configured to determine a second kitchen tool type from among the first kitchen tool types of the user based on the abnormal physical examination data;
and the second determining unit is used for determining a first cooking mode from preset cooking modes based on the second kitchen appliance type.
Optionally, the generating sub-module includes:
a third determining unit configured to determine a target cooking mode from the first cooking modes based on the nutritional ingredients of the first food material;
a first generation unit for generating the target recipe based on the target cooking mode and the first food material.
Optionally, the generating sub-module includes:
a fourth determining unit configured to determine a second food material from the first food materials based on the first kitchen ware category;
and a second generation unit configured to generate the target recipe based on the second food material and the first cooking mode.
Optionally, the second determining module includes:
a fourth determination sub-module for determining historical disease information of the user from the first biopsy data;
and a fifth determining sub-module, configured to determine the first food material from the preset food materials based on the historical disease information and the abnormal physical examination data.
In a third aspect, an embodiment of the present application provides an electronic device, including a recipe generation apparatus as described above, configured to implement a recipe generation method as described in any one of the above.
In a fourth aspect, embodiments of the present application provide a readable storage medium having stored thereon a program or instructions which, when executed by a processor, implement a recipe generation method as described in any one of the above.
In an embodiment of the present application, a recipe generation method is provided, including: determining abnormal physical examination data from the first physical examination data of the user based on the standard physical examination data index; determining a first food material from preset food materials based on abnormal physical examination data; acquiring a first kitchen ware type held by a user; according to the first kitchen ware type and the first food material generation target recipe, corresponding recipes can be generated for the user according to the abnormal physical examination data of the user and the existing kitchen ware type, and the suitability between the recipes and the user is improved to a certain extent.
Drawings
FIG. 1 is a flowchart illustrating steps of a recipe generation method according to an embodiment of the present application;
FIG. 2 is a flow chart of steps of another recipe generation method provided by an embodiment of the present application;
FIG. 3 is a flow chart of a specific implementation of recipe generation provided by an embodiment of the present application;
FIG. 4 is a logic block diagram of a recipe generation device provided in an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Technical solutions in the embodiments of the present application will be clearly described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application are within the scope of the protection of the present application.
The terms first, second and the like in the description and in the claims, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged, as appropriate, such that embodiments of the present application may be implemented in sequences other than those illustrated or described herein, and that the objects identified by "first," "second," etc. are generally of a type and not limited to the number of objects, e.g., the first object may be one or more. Furthermore, in the description and claims, "and/or" means at least one of the connected objects, and the character "/", generally means that the associated object is an "or" relationship.
The recipe generation method provided in the embodiment of the present application is described in detail below by means of specific embodiments and application scenarios thereof with reference to the accompanying drawings.
As shown in fig. 1, fig. 1 is a flowchart illustrating steps of a recipe generation method according to an embodiment of the present application, where the method may include:
step 101, determining abnormal physical examination data from first physical examination data of a user based on standard physical examination data indexes.
In an embodiment of the present application, the first body test data of the user may include trace element test data of height, weight, blood pressure, blood fat, cholesterol, calcium, vitamins, and the like. The method comprises the steps of firstly, sending a data authorization request for physical examination data to a user, and receiving a physical examination report uploaded by the user or physical index data filled by the user after the authorization of the user for the physical examination data is obtained. Before data analysis is performed on physical examination reports or filled physical index data of the user, desensitization treatment can be performed on the physical examination reports or filled physical index data of the user, personal information of the user is shielded, and meanwhile, association with account information of the user can be not established. And then, carrying out data analysis on physical examination reports or filled body index data of the user to obtain first physical examination data of the user. Data analysis methods include, but are not limited to, semantic recognition, text recognition, and the like. After the first body test data of the user is obtained, abnormal body test data can be determined from the first body test data according to the standard body test data index. The standard physical examination data index may be a reference range, and if one item of physical examination data of the user is outside the reference range, the item of physical examination data may be considered as abnormal physical examination data.
Step 102, determining a first food material from preset food materials based on the abnormal physical examination data.
In the embodiment of the present application, the preset food materials may include food materials commonly found in the market, such as meats, eggs, vegetables, rice and flour, edible oil, etc., and specific food materials included in various food materials, for example, meats may include chicken, beef, fish, etc. After the abnormal physical examination data of the user is obtained, the first food material can be determined from the preset food materials according to the nutrient elements corresponding to the abnormal physical examination data.
For example, if the glutamic pyruvic transaminase index of the user is high, it means that the liver function of the user is poor, and at this time, foods with high fat content, such as animal viscera, are not suitable for being taken, and vegetables and fruits are suitable for being taken, so that the first food material may include vegetables and fruits, and may not include foods with high fat content such as animal viscera.
Step 103, obtaining a first kitchen ware type held by the user.
In an embodiment of the present application, a first kitchen ware category held by a user may be obtained. The first kitchen ware category may be entered by a user. The user input data may include kitchen ware brands, kitchen ware models, etc. After the brand and model of the kitchen ware are obtained, the type of the kitchen ware corresponding to the model of the kitchen ware can be inquired from the system.
Step 104, generating a target recipe according to the first kitchen ware type and the first food material.
In the embodiment of the application, after the first kitchen ware type held by the user is obtained, the cooking mode corresponding to the first kitchen ware type can be determined, then the target recipe can be generated according to the cooking mode corresponding to the first kitchen ware type and the first food material, and the target recipe can also be obtained by screening the target recipe according to the kitchen ware required by the preset recipe corresponding to the first food material and the first kitchen ware type held by the user. The target recipe may include a seasoning type and a seasoning ratio corresponding to the first food material, and a cooking time of the first food material. The processing of the first food material according to the target recipe may be performed by a first kitchen ware kind.
In an embodiment of the present application, abnormal physical examination data is determined from first physical examination data of a user by based on a standard physical examination data index; determining a first food material from preset food materials based on abnormal physical examination data; acquiring a first kitchen ware type held by a user; according to the first kitchen ware type and the first food material generation target recipe, corresponding recipes can be generated for the user according to the abnormal physical examination data of the user and the existing kitchen ware type, and the suitability between the recipes and the user is improved to a certain extent.
As shown in fig. 2, fig. 2 is a flowchart illustrating steps of another recipe generation method according to an embodiment of the present application, where the method may include:
in step 201, abnormal physical examination data is determined from the first physical examination data of the first user based on the standard physical examination data index.
In the embodiment of the present application, the implementation content of this step may refer to the implementation content of step 101, which is not described herein.
Step 202, determining a first food material from preset food materials based on the abnormal physical examination data.
In the embodiment of the present application, the implementation content of this step may refer to the implementation content of step 102, which is not described herein.
Optionally, in step 202, the following sub-steps may be included:
sub-step 2021, determining an anomaly difference between the anomaly detection data and the standard physical detection data indicator.
In the embodiment of the application, if the abnormal physical examination data is lower than the minimum value of the reference interval of the standard physical examination data index, taking the difference value between the abnormal physical examination data and the minimum value of the reference interval as an abnormal difference value; and if the abnormal physical examination data is higher than the maximum value of the reference interval of the standard physical examination data index, taking the difference value between the abnormal physical examination data and the maximum value of the reference interval as an abnormal difference value.
A sub-step 2022, determining a nutritional ingredient ratio of the preset food material based on the nutritional ingredient content contained in the preset food material.
In the embodiment of the present application, the nutritional ingredients included in each preset food material have corresponding nutritional ingredient contents, and the nutritional ingredient proportion of each preset food material may be determined according to each nutritional ingredient content of the preset food material. The mass or amount of a substance may be used as a measure of the proportion of the nutritional ingredients.
For example, the main nutrients in eggs are protein and cholesterol, and the ratio between protein and cholesterol can be determined according to the protein content and cholesterol content in eggs. If the protein content is 40% and the cholesterol content is 5%, the nutrition component ratio of the egg is "protein: cholesterol=8: 1".
A sub-step 2023, determining the first food material from the preset food materials based on the nutritional component proportions of the preset food materials and the abnormal differences.
In the embodiment of the application, the first food material is obtained by screening the preset food materials according to the abnormal difference values of the abnormal physical examination data and the standard physical examination data indexes and the nutrition component proportion of the preset food materials. If the abnormal physical examination data is higher than the standard physical examination data index, the larger the abnormal difference value is, the user can reduce the intake of the first nutrient element corresponding to the abnormal index; if the abnormal physical examination data is lower than the standard physical examination data index, the larger the abnormal difference value is, the user can increase the intake of the second nutrient element corresponding to the abnormal index. After determining the first nutrient element that the user can reduce intake and the second nutrient element that the user can increase intake, a first food material that matches the nutrient ratio may be selected from the preset food materials according to the nutrient ratios of the first nutrient element and the second nutrient element and the nutrient composition ratio of the preset food materials.
For example, beef and animal viscera contain different fat contents, and the ratio of each amino acid is also different, and if the body fat rate of the user is high, beef with low fat content can be determined as the first food.
In the embodiment of the application, the abnormal difference between the abnormal physical examination data and the standard physical examination data index is determined, the nutrition component proportion of the preset food is determined based on the nutrition components contained in the preset food, the first food is determined from the preset food based on the nutrition component proportion and the abnormal difference of the preset food, the first food can be determined according to the abnormal difference between the abnormal physical examination data and the standard physical examination data index of the user, and the suitability of the first food and the user is improved.
Substep 2024 determines historical disease information for the user from the first biopsy data.
In embodiments of the present application, historical disease information of a user may be determined from the first biopsy data. It should be noted that, the historical disease information can only be viewed by the user, and the historical disease information at the server side must not include any personal information of the user.
A substep 2025 determines the first food material from the preset food materials based on the historical disease information and the abnormal physical examination data.
In the embodiment of the application, first risk food materials which are not suitable for being eaten by a user can be determined according to historical disease information, second risk food materials which are not suitable for being eaten by the user can be determined according to abnormal physical examination data, and then the first risk food materials and the second risk food materials can be removed from preset food materials, so that the first food materials are obtained. The first suitable food material suitable for the user to eat can be determined according to the historical disease information, the second suitable food material suitable for the user to eat is determined according to the abnormal physical examination data, and the first suitable food material and the second suitable food material are determined to be the first food material.
For example, if a user suffers from chronic rhinitis and the body fat rate in abnormal physical examination data is high, the user may consider that the user is not likely to eat excessive amounts of fish food and food containing a pungent odor, and may determine other food than the fish food and food containing a pungent odor as the first food.
In the embodiment of the application, the historical disease information of the user is determined from the first body detection data, the first food material is determined from the preset food material based on the historical disease information and the abnormal body detection data, and the first food material can be determined from the preset food material according to the historical disease information and the abnormal body detection data of the user, so that the suitability of the first food material and the user is improved.
Step 203, obtaining a first kitchen ware type held by the first user.
In the embodiment of the present application, the implementation content of this step may refer to the implementation content of step 103, which is not described herein.
Step 204, determining a first cooking mode from preset cooking modes based on the first kitchen ware type of the user.
In embodiments of the present application, the preset cooking regimen may include, but is not limited to, frying, boiling, steaming, roasting, stewing, stirring, and the like. After the first kitchen ware type held by the user is obtained, the first cooking mode suitable for the first kitchen ware type can be selected and determined from preset cooking modes according to the first kitchen ware type.
For example, if the first kitchen ware comprises a multipurpose electric cooker, the first cooking mode may be determined to be boiling, steaming, stewing, etc.; if the first kitchen ware category includes spoons and cold mix boxes, the first cooking mode may be determined to be mixing.
Optionally, in step 204, the following sub-steps may be included:
a substep 2041, determining a second kitchen ware category from the first kitchen ware categories of the user based on the abnormal physical examination data.
In the embodiment of the application, the element unsuitable for the user to ingest too much can be determined according to the abnormal physical examination data, then the unsuitable kitchen ware with more elements is determined to be released from the first kitchen ware type, the unsuitable kitchen ware is removed from the first kitchen ware type, and the second kitchen ware type is obtained. The cooking mode of the unsuitable user can be determined according to the abnormal physical examination data, the unsuitable kitchen ware is determined according to the cooking mode of the unsuitable user, the unsuitable kitchen ware is removed from the first kitchen ware, and the second kitchen ware type is obtained.
For example, if the body fat rate of the user is high, the user is not likely to eat the fried or fried food material, and thus other kitchen ware types other than the wok and the fryer may be determined from the first kitchen ware types as the second kitchen ware types, such as a stewing cup or an autoclave.
In a sub-step 2042, a first cooking recipe is determined from the preset cooking recipes based on the second kitchen appliance category.
In an embodiment of the present application, the first cooking mode may be determined from preset cooking modes according to the second kitchen appliance type. The first cooking mode can be performed by the second kitchen appliance.
In the embodiment of the application, the second kitchen appliance type is determined from the first kitchen appliance type of the user based on the abnormal physical examination data, the first cooking mode is determined from the preset cooking mode based on the second kitchen appliance type, the kitchen appliance type held by the user can be screened according to the abnormal physical examination data of the user, and the suitability of the first cooking mode and the user is improved.
Step 205, generating a target recipe based on the first food material and the first cooking mode.
In embodiments of the present application, the target recipe may be generated from the first food material and the first cooking mode. The target recipe may further include a seasoning for cooking the first food item using the first cooking mode and a cooking time.
Optionally, in step 205, the following sub-steps may be included:
substep 2051, determining a target cooking regimen from the first cooking regimen based on the nutritional composition of the first food material.
In an embodiment of the present application, the improper cooking mode of the first food material may be determined according to the nutritional ingredients of the first food material, and then the improper cooking mode of the first food material is removed from the first cooking mode, to obtain the target cooking mode.
For example, if the first food material is a fruit food material having a high vitamin C content, it is not preferable to use a high-temperature cooking method such as frying or frying. Cut or fished fruit is often used as the target cooking mode for fruit-like food.
A substep 2052 generates the target recipe based on the target cooking regime and the first food material.
In an embodiment of the present application, after confirming the target cooking mode of the first food material, a target recipe may be generated according to the target cooking mode and the first food material. For example, a first recipe corresponding to the first food material may be acquired, a target recipe for cooking the first food material may be determined from the first recipe, or a second recipe for cooking the first food material may be acquired, and a target recipe for cooking the first food material may be determined from the second recipe.
The relevant implementation content of the target recipe can refer to the embodiment content of step 104 and step 205, and will not be described herein.
In the embodiment of the application, the target cooking mode is determined from the first cooking modes based on the nutritional ingredients of the first food material, the target recipe is generated based on the target cooking mode and the first food material, the cooking mode matched with the first food material can be screened, the target recipe is further generated, and the usability of the target recipe is improved.
Substep 2053, determining a second food material from the first food material based on the first kitchen ware category.
In an embodiment of the present application, the food material unsuitable for cooking using the first kitchen ware type may be removed from the first food material according to the first kitchen ware type, resulting in the second food material. And a second food material which is suitable for being cooked by using the first kitchen ware type can be selected from the first food materials according to the first kitchen ware type.
For example, if the first food material includes rice food materials and the first kitchen ware does not include an electric rice cooker, other food materials than the rice food materials in the first food material may be used as the second food material.
Substep 2054, generating the target recipe based on the second food material and the first cooking mode.
In an embodiment of the present application, first a third recipe corresponding to the second food material may be determined, and then a target recipe adopting the first cooking mode may be determined from the third recipe. A fourth recipe for the first cooking mode may also be determined, and then a target recipe for cooking the second food material is determined from the fourth recipe.
In the embodiment of the application, through determining the second food material from the first food material based on the first kitchen ware type, the target recipe is generated based on the second food material and the first cooking mode, and the second food material can be screened from the first food material according to the first kitchen ware type, so that the target recipe is generated, and the suitability of the target recipe and a user is improved.
In the embodiment of the application, the first cooking mode is determined from the preset cooking modes based on the first kitchen ware type of the user, the target recipe is generated based on the first food materials and the first cooking mode, the corresponding cooking mode can be determined according to the first kitchen ware type of the user, the target recipe is further generated, and the suitability of the target recipe and the user is improved.
In the embodiment of the application, through determining abnormal physical examination data from the first physical examination data of the first user based on the standard physical examination data index, determining the first food material from the preset food material based on the abnormal physical examination data, acquiring the first kitchen ware type held by the first user, determining the first cooking mode from the preset cooking mode based on the first kitchen ware type of the user, generating the target recipe based on the first food material and the first cooking mode, determining the first cooking mode of the first food material according to the first kitchen ware type held by the user, and generating the target recipe based on the first cooking mode and the first food material, so that the suitability of the target recipe and the user is improved.
As shown in fig. 3, fig. 3 is a flowchart of a specific implementation of a recipe generation method according to an embodiment of the present application. In the figure, firstly, the process can be started, then the user scans and uploads the physical examination report, then the physical examination report uploaded by the user can be desensitized, then physical examination data in the physical examination report of the user are analyzed and abnormal physical examination data are determined, then prompt information is sent to the user, the user confirms whether the physical examination data are correct or not, if the physical examination data are confirmed to be incorrect by the user, the user corrects the data, if the user confirms to be correct or the user corrects the physical examination data, the user inputs the type of the kitchen ware, then the food material can be selected according to the abnormal physical examination data, the cooking mode can be selected according to the type of the kitchen ware held by the user, then a recipe can be generated, and finally the process is ended.
As shown in fig. 4, fig. 4 is a logic block diagram of a recipe generation apparatus 400 according to an embodiment of the present application, where the apparatus may include:
a first determining module 401, configured to determine abnormal physical examination data from first physical examination data of a user based on a standard physical examination data index;
a second determining module 402, configured to determine a first food material from preset food materials based on the abnormal physical examination data;
an obtaining module 403, configured to obtain a first kitchen ware category held by the user;
a generating module 404, configured to generate a target recipe according to the first kitchen ware type and the first food material.
Optionally, the second determining module 402 includes:
the first determining submodule is used for determining an abnormal difference value between the abnormal physical examination data and the standard physical examination data index;
a second determining submodule, configured to determine a nutritional ingredient proportion of the preset food material based on a nutritional ingredient content included in the preset food material;
and a third determining sub-module for determining the first food material from the preset food materials based on the nutrient component proportion and the abnormal difference value of the preset food materials.
Optionally, the generating module 404 includes:
a fourth determining sub-module for determining a first cooking mode from preset cooking modes based on the first kitchen ware type of the user;
and the generation submodule is used for generating a target recipe based on the first food materials and the first cooking mode.
Optionally, the fourth determining sub-module includes:
a first determining unit configured to determine a second kitchen tool type from among the first kitchen tool types of the user based on the abnormal physical examination data;
and the second determining unit is used for determining a first cooking mode from preset cooking modes based on the second kitchen appliance type.
Optionally, the generating sub-module includes:
a third determining unit configured to determine a target cooking mode from the first cooking modes based on the nutritional ingredients of the first food material;
a first generation unit for generating the target recipe based on the target cooking mode and the first food material.
Optionally, the generating sub-module includes:
a fourth determining unit configured to determine a second food material from the first food materials based on the first kitchen ware category;
and a second generation unit configured to generate the target recipe based on the second food material and the first cooking mode.
Optionally, the second determining module 402 includes:
a fourth determination sub-module for determining historical disease information of the user from the first biopsy data;
and a fifth determining sub-module, configured to determine the first food material from the preset food materials based on the historical disease information and the abnormal physical examination data.
In summary, a recipe generation device provided in an embodiment of the present application includes: the first determining module is used for determining abnormal physical examination data from first physical examination data of a user based on standard physical examination data indexes; the second determining module is used for determining a first food material from preset food materials based on the abnormal physical examination data; the acquisition module is used for acquiring a first kitchen ware type held by the user; the generation module is used for generating a target recipe according to the first kitchen ware type and the first food material, and generating a corresponding recipe for the user according to abnormal physical examination data of the user and the existing kitchen ware type, so that the suitability between the recipe and the user is improved to a certain extent.
The recipe generation device in the embodiment of the present application may be an electronic device, or may be a component in an electronic device, for example, an integrated circuit or a chip. The electronic device may be a terminal, or may be other devices than a terminal. By way of example, the electronic device may be a GPU BOX, a mobile phone, a tablet, a notebook, a palmtop, a vehicle-mounted electronic device, a mobile internet appliance (Mobile Internet Device, MID), an augmented reality (augmented reality, AR)/Virtual Reality (VR) device, a robot, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), or the like, and may also be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a Television (TV), a teller machine, a self-service machine, or the like.
The recipe generation device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, a Linux, windows operating system or the like, and may also be other possible operating systems, which are not specifically limited in the embodiments of the present application.
The recipe generation device provided in the embodiment of the present application can implement each process implemented by the embodiments of the methods of fig. 1 to 3, and in order to avoid repetition, a detailed description is omitted here.
Optionally, as shown in fig. 5, the embodiment of the present application further provides an electronic device M00, including a processor M01 and a memory M02, where a program or an instruction that can be executed on the processor M01 is stored in the memory M02, and the program or the instruction when executed by the processor M01 implements each step of the foregoing embodiment of the recipe generation method, and can achieve the same technical effect, so that repetition is avoided, and no further description is given here.
In the embodiment of the present application, the memory M02 may be used to store a software program as well as various data. The memory M02 may mainly include a first memory area storing programs or instructions and a second memory area storing data, wherein the first memory area may store an operating system, application programs or instructions (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like. Further, the memory M02 may include a volatile memory or a nonvolatile memory, or the memory M02 may include both a volatile and nonvolatile memory. The nonvolatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable EPROM (EEPROM), or a flash Memory. The volatile memory may be random access memory (Random Access Memory, RAM), static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (ddr SDRAM), enhanced SDRAM (Enhanced SDRAM), synchronous DRAM (SLDRAM), and Direct RAM (DRRAM). Memory M02 in embodiments of the present application includes, but is not limited to, these and any other suitable types of memory.
The processor M01 may include one or more processing units; optionally, the processor M01 integrates an application processor that primarily processes operations involving an operating system, user interface, application programs, etc., and a modem processor that primarily processes wireless communication signals, such as a baseband processor. It will be appreciated that the modem processor described above may not be integrated into the processor M01.
The embodiment of the application also provides an electronic device, which comprises the recipe generation device, and is used for realizing the processes of the recipe generation method embodiment, and can achieve the same technical effects, and for avoiding repetition, the description is omitted here.
The embodiment of the present application further provides a readable storage medium, where a program or an instruction is stored, and when the program or the instruction is executed by a processor, the program or the instruction realizes each process of the embodiment of the recipe generation method, and the same technical effect can be achieved, so that repetition is avoided, and no redundant description is provided herein.
Wherein the processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes computer readable storage medium such as computer readable memory ROM, random access memory RAM, magnetic or optical disk, etc.
The embodiment of the application further provides a chip, the chip includes a processor and a communication interface, the communication interface is coupled with the processor, and the processor is used for running a program or an instruction, so as to implement each process of the embodiment of the recipe generation method, and achieve the same technical effect, so that repetition is avoided, and no redundant description is provided here.
It should be understood that the chips involved in the embodiments of the present application may also be referred to as system-on-chip, chip system, or system-on-chip chips, etc.
The embodiments of the present application provide a computer program product stored in a storage medium, where the program product is executed by at least one processor to implement the respective processes of the embodiments of the recipe generation method described above, and achieve the same technical effects, and are not repeated herein.
It should be noted that, in this document, 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 one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Furthermore, it should be noted that the scope of the methods and apparatus in the embodiments of the present application is not limited to performing the functions in the order shown or discussed, but may also include performing the functions in a substantially simultaneous manner or in an opposite order depending on the functions involved, e.g., the described methods may be performed in an order different from that described, and various steps may also be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the related art in the form of a computer software product stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), including several instructions for causing a terminal (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method described in the embodiments of the present application.
The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those of ordinary skill in the art without departing from the spirit of the present application and the scope of the claims, which are also within the protection of the present application.
Claims (10)
1. A recipe generation method, the method comprising:
determining abnormal physical examination data from the first physical examination data of the user based on the standard physical examination data index;
determining a first food material from preset food materials based on the abnormal physical examination data;
acquiring a first kitchen ware type held by the user;
generating a target recipe according to the first kitchen ware type and the first food material.
2. The method of claim 1, wherein the determining a first food material from a preset food material based on the abnormal physical examination data comprises:
determining an abnormal difference value between the abnormal physical examination data and the standard physical examination data index;
determining the proportion of the nutritional ingredients of the preset food materials based on the nutritional ingredient content contained in the preset food materials;
and determining the first food material from the preset food materials based on the nutrient component proportion of the preset food materials and the abnormal difference value.
3. The method of claim 1, wherein the generating a target recipe from the first kitchen ware category and the first food material comprises:
determining a first cooking mode from preset cooking modes based on a first kitchen ware type of the user;
a target recipe is generated based on the first food material and the first cooking mode.
4. The method of claim 3, wherein the determining a first cooking profile from a preset cooking profile based on the first kitchen ware category of the user comprises:
determining a second kitchen tool type from the first kitchen tool types of the user based on the abnormal physical examination data;
and determining a first cooking mode from preset cooking modes based on the second kitchen appliance type.
5. A method according to claim 3, wherein the generating a target recipe based on the first food material and the first cooking recipe comprises:
determining a target cooking regimen from the first cooking regimen based on the nutritional ingredients of the first food material;
the target recipe is generated based on the target cooking regime and the first food material.
6. A method according to claim 3, wherein the generating a target recipe based on the first food material and the first cooking recipe comprises:
determining a second food material from the first food material based on the first kitchen ware category;
the target recipe is generated based on the second food material and the first cooking mode.
7. The method of claim 1, wherein the determining a first food material from a preset food material based on the abnormal physical examination data comprises:
determining historical disease information of the user from the first biopsy data;
and determining the first food material from the preset food materials based on the historical disease information and the abnormal physical examination data.
8. A recipe generation device, the device comprising:
the first determining module is used for determining abnormal physical examination data from first physical examination data of a user based on standard physical examination data indexes;
the second determining module is used for determining a first food material from preset food materials based on the abnormal physical examination data;
the acquisition module is used for acquiring a first kitchen ware type held by the user;
the generation module is used for generating a target recipe according to the first kitchen ware type and the first food materials.
9. An electronic device comprising the recipe generation apparatus of claim 8 to implement the recipe generation method of any one of claims 1 to 7.
10. A readable storage medium, characterized in that a program or instructions is stored on the readable storage medium, which when executed by a processor implements the recipe generation method of any one of claims 1 to 7.
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|---|---|---|---|
| CN202311800003.9A CN117894431A (en) | 2023-12-25 | 2023-12-25 | Recipe generation method and device, electronic equipment and readable storage medium |
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| CN202311800003.9A CN117894431A (en) | 2023-12-25 | 2023-12-25 | Recipe generation method and device, electronic equipment and readable storage medium |
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