CN108197635A - Methods of exhibiting and device, the smoke exhaust ventilator of cooking method - Google Patents
Methods of exhibiting and device, the smoke exhaust ventilator of cooking method Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 87
- 238000010411 cooking Methods 0.000 title claims abstract description 56
- 239000000779 smoke Substances 0.000 title claims abstract description 53
- 230000001747 exhibiting effect Effects 0.000 title claims abstract description 13
- 235000013305 food Nutrition 0.000 claims abstract description 141
- 239000000463 material Substances 0.000 claims abstract description 138
- 235000013311 vegetables Nutrition 0.000 claims abstract description 59
- 230000008569 process Effects 0.000 claims description 10
- 238000010801 machine learning Methods 0.000 claims description 9
- 235000005911 diet Nutrition 0.000 claims description 3
- 230000037213 diet Effects 0.000 claims description 3
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- 238000005516 engineering process Methods 0.000 abstract description 5
- 230000006870 function Effects 0.000 description 11
- 238000012549 training Methods 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 210000004556 brain Anatomy 0.000 description 3
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- 238000005859 coupling reaction Methods 0.000 description 3
- 238000013135 deep learning Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
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- 230000008878 coupling Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 210000002569 neuron Anatomy 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000005086 pumping Methods 0.000 description 2
- 238000013526 transfer learning Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 235000002566 Capsicum Nutrition 0.000 description 1
- 240000008574 Capsicum frutescens Species 0.000 description 1
- 241000406668 Loxodonta cyclotis Species 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 239000001390 capsicum minimum Substances 0.000 description 1
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- 239000002699 waste material Substances 0.000 description 1
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Abstract
The invention discloses methods of exhibiting and device, the smoke exhaust ventilators of a kind of cooking method.Wherein, this method includes：Obtain the first image information of current food materials；The type of food materials is determined based on the first image information；Type according to food materials determines the corresponding at least one vegetable of food materials；The cooking method of food materials is determined according to vegetable, and cooking method is shown on smoke exhaust ventilator.The present invention solves the technical issues of smoke exhaust ventilator function is single in the relevant technologies.
Description
Technical field
The present invention relates to smoke exhaust ventilator field, methods of exhibiting and device in particular to a kind of cooking method, oil pumping
Smoke machine.
Background technology
At present, smoke exhaust ventilator function is relatively simple, is only the suction function for completing kitchen ventilator, and as people's personalization needs
Ask more and more, the single experience that can influence people to product of function, meanwhile, also limit the application scenarios of kitchen ventilator.
For it is above-mentioned the problem of, currently no effective solution has been proposed.
Invention content
An embodiment of the present invention provides methods of exhibiting and device, the smoke exhaust ventilator of a kind of cooking method, at least to solve phase
The technical issues of smoke exhaust ventilator function is single in the technology of pass.
One side according to embodiments of the present invention provides a kind of methods of exhibiting of cooking method, including：It obtains current
First image information of food materials；The type of food materials is determined based on the first image information；Type according to food materials determines that food materials correspond to
At least one vegetable；The cooking method of food materials is determined according to vegetable, and cooking method is shown on smoke exhaust ventilator.
Optionally, the type of food materials is determined based on the first image information, including：Using the first image information as the first model
Input, determine the types of the food materials corresponding to the first image information, wherein, the first model is using more in first database
Group data are trained by machine learning, and every group of data in first database in multi-group data include：Food materials image
Information and food materials type corresponding with food materials image information.
Optionally, the corresponding at least one vegetable of food materials is determined according to the type of food materials, including：Type according to food materials is true
Determine vegetable list, wherein, the food materials of each vegetable include the corresponding food materials of type of food materials in vegetable list in forming；It receives
Selection instruction and corresponding with food materials vegetable is selected from vegetable list according to the selection instruction.
Optionally, the corresponding at least one vegetable of food materials is determined according to the type of food materials, including：Type according to food materials is true
Determine vegetable list, wherein, the food materials of each vegetable include the corresponding food materials of type of food materials in vegetable list in forming；It obtains
The user images of smoke exhaust ventilator；The identity information of the user using smoke exhaust ventilator is determined according to user images；
Vegetable corresponding with food materials is selected from vegetable list based on history diet corresponding with identity information record.
Optionally, the type of food materials is determined based on the first image information, including：Using user images as the defeated of the second model
Enter, determine the identity information corresponding to user images, wherein, the second model is passes through using the multi-group data in the second database
What machine learning was trained, every group of data in the second database in multi-group data include：User images and and user
The corresponding identity information of image.
Optionally, the above method further includes：The second image information in the cooking process of food materials is obtained, wherein, the second figure
As information is used for the cooking status for reflecting food materials；Second image information is sent to terminal device.
Optionally, the above method further includes：Cooking status based on the second image information acquisition food materials；It is in cooking status
During designated state, send a notification message to terminal device, wherein, which is used to that terminal device food materials to be notified to be in
Designated state.
Another aspect according to embodiments of the present invention additionally provides one kind and includes control panel and smoke exhaust barrel, and smoke exhaust barrel is set
Side on the control panel is put, including：Image collecting device is arranged on the bottom of control panel, for obtaining the of current food materials
One image information；Processor, for determining the type of food materials based on the first image information；Type according to food materials determines food materials pair
At least one vegetable answered；And the cooking method of food materials is determined according to vegetable；Display device, setting on the control panel, are used
In showing cooking method on smoke exhaust ventilator.
An embodiment of the present invention provides the displaying device of another cooking method, applied in smoke exhaust ventilator, wherein, the exhibition
Showing device includes：Acquisition module, for obtaining the first image information of current food materials；First determining module, for being based on first
Image information determines the type of food materials；Second determining module determines the corresponding at least one of food materials for the type according to food materials
Vegetable；Third determining module, for determining the cooking method of food materials according to vegetable；Display module, for being shown on smoke exhaust ventilator
Show cooking method.
Optionally, the first determining module for the input using the first image information as the first model, determines the first image
The type of food materials corresponding to information, wherein, the first model is to pass through machine learning using the multi-group data in first database
What training obtained, every group of data in first database in multi-group data include：Food materials image information and with food materials image
The corresponding food materials type of information.
Another aspect according to embodiments of the present invention provides a kind of storage medium, and storage medium includes the program of storage,
Wherein, equipment performs the exhibition method of above-described cooking method where controlling storage medium when program is run.
Another aspect according to embodiments of the present invention provides a kind of processor, and processor is used to run program, wherein,
Program performs the methods of exhibiting of above-described cooking method when running.
In embodiments of the present invention, corresponding vegetable is determined, and determine and show according to vegetable using the type according to food materials
Show the mode of the corresponding cooking method of such food materials, achieved the purpose that extend the application scenarios of kitchen ventilator, so as to improve use
Family is experienced, and then solves the technical issues of smoke exhaust ventilator function is single in the relevant technologies.
Description of the drawings
Attached drawing described herein is used to provide further understanding of the present invention, and forms the part of the application, this hair
Bright illustrative embodiments and their description do not constitute improper limitations of the present invention for explaining the present invention.In the accompanying drawings：
Fig. 1 is the structure diagram according to a kind of smoke exhaust ventilator of the embodiment of the present application；
Fig. 2 is the flow chart according to a kind of methods of exhibiting of optional cooking method of the embodiment of the present application；
Fig. 3 is a kind of structure diagram of the displaying device of optional cooking method according to embodiments of the present invention.
Specific embodiment
In order to which those skilled in the art is made to more fully understand the present invention program, below in conjunction in the embodiment of the present invention
The technical solution in the embodiment of the present invention is clearly and completely described in attached drawing, it is clear that described embodiment is only
The embodiment of a part of the invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
Member's all other embodiments obtained without making creative work should all belong to the model that the present invention protects
It encloses.
It should be noted that term " first " in description and claims of this specification and above-mentioned attached drawing, "
Two " etc. be the object for distinguishing similar, and specific sequence or precedence are described without being used for.It should be appreciated that it uses in this way
Data can be interchanged in the appropriate case, so as to the embodiment of the present invention described herein can in addition to illustrating herein or
Sequence other than those of description is implemented.In addition, term " comprising " and " having " and their any deformation, it is intended that cover
Cover it is non-exclusive include, be not necessarily limited to for example, containing the process of series of steps or unit, method, system, product or equipment
Those steps or unit clearly listed, but may include not listing clearly or for these processes, method, product
Or the intrinsic other steps of equipment or unit.
First, understand the embodiment of the present invention for convenience, below by part term or noun involved in the present invention into
Row illustrates：
Pixel：It is the least unit that can be shown on computer screen, for representing the unit of image, referring to can show
Horizontal and vertical pixel array, the pixel in screen is more, and the resolution ratio of picture is higher, and image is finer and smoother and forces
Very；Pixel：Refer to the numerical value of pixel.
Binaryzation：Refer to the picture shot to camera, most of is coloured image, and coloured image information contained amount is huge
Greatly, for the content of picture, it can simply be divided into prospect and background, first cromogram is handled, picture is made there was only prospect
Information and background information can simply define foreground information as black, and background information is white, and here it is binary pictures.
CNN：Convolutional neural networks refer to describe the operation to input picture, export one group and describe dividing for picture material
Class or the probability of classification, i.e., be identified the image of input, to export the probability of the object in image；Pass through a series of convolution
Level builds up more abstract concept, including establishing multiple neurons, and establishes corresponding input layer and output layer, thus will
The node of input is constantly associated with by neuron, obtains optimization object, can generally include convolutional layer, filter layer, by preceding to biography
Lead, loss function, backward conduction and function update as a learning cycle, to each trained picture, program will repeat solid
Fixed number purpose periodic process, to continue to optimize trained learning outcome.
To scheme to search figure：Refer to after image is got, result is ranked up, and pass through user record by deep learning
Triple data (inquiry picture, click picture and do not click on picture) carry out the sequence loss function of training pattern, so as to obtain
Ranking results, after an image is inputted, model can detect main body automatically, and it is related right then to be discharged according to ranking score height
The result of elephant.
Transfer learning：Essence is images match, is applied model in every field by transfer learning, specifically data
The vector representation X of picture in library is moved to by linear transformation on the image X1 in other field, by quoting random Fourier
Migration transformation is changed into nonlinear function, the image then needed by function.
Naive Bayesian：It is to show a pictures, can be classified with returning an object value, using picture recognition as a simple state
Degree, to obtain corresponding object.
Dependency grammar：Refer to build the relationship between subject term and the word for describing subject term, do not have in dependency grammar phrase this
Level, each node is corresponding with the word in sentence, can directly handle the relationship in sentence between word and word, in order to
Analysis and information extraction.
Decision tree：Referring to be classified according to feature, each node proposes a problem, splits data into two classes, and after
Continuous to put question to, these problems are the learning trainings in existing data, with when putting into new data, on the tree according to where data
The problem of, data are divided on corresponding leaf.
Deep learning：It is a kind of based on the method that data are carried out with representative learning in machine learning, concept is derived from artificial god
Research through network, motivation are to establish, simulate the neural network of human brain progress analytic learning, the mechanism of its imitation human brain
Explain data, such as image, sound and text.By combine low-level feature formed it is more abstract it is high-rise represent attribute classification or
Feature represents that the multilayer perceptron containing more hidden layers is exactly a kind of deep learning structure with the distributed nature for finding data.
KNN algorithms：If the sample of the k in feature space, a sample most like (i.e. closest in feature space)
In it is most of belong to some classification, then the sample also belongs to this classification.In KNN algorithms, selected neighbours are
Object through correctly classifying.
Fig. 1 is according to a kind of structure diagram of smoke exhaust ventilator of the embodiment of the present application, as shown in Figure 1, the smoke exhaust ventilator
Including：Control panel 1 and smoke exhaust barrel 2, smoke exhaust barrel 2 are arranged on 1 top of control panel；Image collecting device is arranged on control plane
The bottom of plate 1, for obtaining the first image information of current food materials；Processor 3, for determining food materials based on the first image information
Type；Type according to food materials determines the corresponding at least one vegetable of food materials；And the culinary art side of food materials is determined according to vegetable
Formula；Display device 4 is arranged on control panel 1, for showing cooking method on smoke exhaust ventilator.Optionally, above-mentioned processor
3 can be set to the inside of control panel 1, it should be noted that the processor is in Fig. 1 inside control panel
Convenience, it is included in 1 outer surface of control panel, but those skilled in the art are it is to be understood that it should be in control panel
Portion is sightless.
According to embodiments of the present invention, a kind of embodiment of the method for the methods of exhibiting of cooking method is provided, this method can be with
It runs in structure shown in Fig. 1, but not limited to this.It should be noted that step shown in the flowchart of the accompanying drawings can be all
As a group of computer-executable instructions computer system in perform, although also, show logical order in flow charts,
Be in some cases, can be with the steps shown or described are performed in an order that is different from the one herein.
Fig. 2 is the flow chart according to a kind of methods of exhibiting of optional cooking method of the embodiment of the present application.Such as Fig. 2 institutes
Show, this method includes：
Step S202 obtains the first image information of current food materials；
In the embodiment of the present application, one or more can be set in the specified region being provided in the room of above-mentioned smoke exhaust ventilator
A image collecting device, (for example, camera), to acquire the image information of food materials, for the setting position of camera in the application
It puts and does not limit, for example, by taking above-mentioned smoke exhaust ventilator is arranged on ordinarily resident family as an example, can be, but not limited to the stir-fry in kitchen
Be at the top of the house of pot region, with smoke exhaust ventilator the same area (such as same room) other home appliances (such as
Refrigerator), a camera is set respectively.
In one alternate embodiment, image collecting device can also be arranged on smoke exhaust ventilator, for example, being arranged on oil pumping
At the control panel of smoke machine, alternatively, being arranged on the marginal position of smoke exhaust ventilator.
Step S204 determines the type of food materials based on the first image information；
Optionally, there are many realization methods of the step, for example, it is true based on the first image information that in the following manner may be used
Determine the type of food materials：Using the first image information as the input of the first model, food materials corresponding to the first image information are determined
Type, wherein, the first model is what is trained using the multi-group data in first database by machine learning, the first data
Every group of data in library in multi-group data include：Food materials image information and food materials type corresponding with food materials image information.
The image of the oil smoke of region can be acquired respectively by the camera for being arranged on different location, in acquisition image
When, can shoot an image every preset time period (for example, every one minute), then according to above-mentioned image analysis food materials
Type.In one alternate embodiment, the working condition of smoke exhaust ventilator can also be controlled according to the type or vegetable of food materials,
For example, for generate oil smoke it is more or generate penetrating odor (such as capsicum) food materials or vegetable, by the air draught of smoke exhaust ventilator
Ability improves.
It should be noted that the classification in the application for the image of shooting does not limit, including but not limited to：Artwork master
As (gray level image), coloured image (RGB image).It, can be according to binary image processing mode analysis chart when analyzing image
Information as in specifically, in analysis, can carry out the pixel position in pixels multiple in image and history image
Compare, whether, to determine the pixel having differences, then there will be the pixels of difference distinguishes, obtain depositing in image
In the image information of oil smoke.
It is alternatively possible to the identity information of user is determined in the following manner, but not limited to this：It is determined according to user images
Using the identity information of the user of smoke exhaust ventilator, using user images as the input of the second model, determine corresponding to user images
Identity information, wherein, the second model is what is trained using the multi-group data in the second database by machine learning,
Every group of data in two databases in multi-group data include：User images and identity information corresponding with user images.
Step S206, the type according to food materials determine the corresponding at least one vegetable of food materials；
In one alternate embodiment, step S206 can be realized by one below mode, but not limited to this：1) foundation
The type of food materials determines vegetable list, wherein, the food materials of each vegetable include the type pair of food materials in vegetable list in forming
The food materials answered；It receives selection instruction and vegetable corresponding with food materials is selected from vegetable list according to the selection instruction.2) according to
Vegetable list is determined according to the type of food materials, wherein, the food materials of each vegetable include the type of food materials in vegetable list in forming
Corresponding food materials；Obtain the user images of smoke exhaust ventilator；It determines to believe using the identity of the user of smoke exhaust ventilator according to user images
Breath；Vegetable corresponding with food materials is selected from vegetable list based on history diet corresponding with identity information record.
Step S208 determines the cooking method of food materials, and cooking method is shown on smoke exhaust ventilator according to vegetable.
In order to realize the monitoring to cooking process, in one alternate embodiment, the above method can also include it is following it
One process：1) the second image information in the cooking process of food materials is obtained, wherein, the second image information is used to reflect cooking for food materials
It prepares food state；Second image information is sent to terminal device.2) cooking status based on the second image information acquisition food materials；It is cooking
When state of preparing food is designated state, send a notification message to terminal device, wherein, which is used to notify terminal device food materials
It has been in designated state.Specifically, the cooking process of food materials is monitored in real time by the camera on smoke extractor, user can lead to
The terminal devices such as mobile phone are crossed, the progress of the culinary art of food materials is checked in any one place in room, prevents food from being burnt.It is optional
Ground, with reference to current detection food image judge that food is made in the case of, notify user by terminal devices such as mobile phones, keep away
Exempt from the trouble that user frequently passes in and out kitchen.
An embodiment of the present invention provides the displaying device of another cooking method, applied in smoke exhaust ventilator, wherein, such as scheme
Shown in 3, which includes：Acquisition module 30, for obtaining the first image information of current food materials；First determining module
32, for determining the type of food materials based on the first image information；Second determining module 34 determines to eat for the type according to food materials
The corresponding at least one vegetable of material；Third determining module 36, for determining the cooking method of food materials according to vegetable；Display module
38, for showing cooking method on smoke exhaust ventilator.
Optionally, the first determining module 32 for the input using the first image information as the first model, determines the first figure
The type of food materials as corresponding to information, wherein, the first model is to pass through engineering using the multi-group data in first database
Practise what training obtained, every group of data in first database in multi-group data include：Food materials image information and with food materials figure
As the corresponding food materials type of information.
The embodiment of the present invention additionally provides a kind of storage medium, and storage medium includes the program of storage, wherein, it is transported in program
Equipment performs the exhibition method of above-described cooking method where controlling storage medium during row.
The embodiment of the present invention additionally provides a kind of processor, and processor is used to run program, wherein, program performs when running
The methods of exhibiting of above-described cooking method.
It is not fine that user experience effect is disliked in happiness.In addition, people often use electricity in the cooking method for inquiring food materials
The terminal devices such as brain, mobile terminal connect network, to be inquired on a search engine, still, after result is inquired, if
The cooking process of vegetable is more complicated, and people often go to check on terminal device repeatedly, in this way, waste user time.
The embodiments of the present invention are for illustration only, do not represent the quality of embodiment.
In the above embodiment of the present invention, all emphasize particularly on different fields to the description of each embodiment, do not have in some embodiment
The part of detailed description may refer to the associated description of other embodiment.
In several embodiments provided herein, it should be understood that disclosed technology contents can pass through others
Mode is realized.Wherein, the apparatus embodiments described above are merely exemplary, such as the division of the unit, Ke Yiwei
A kind of division of logic function, can there is an other dividing mode in actual implementation, for example, multiple units or component can combine or
Person is desirably integrated into another system or some features can be ignored or does not perform.Another point, shown or discussed is mutual
Between coupling, direct-coupling or communication connection can be INDIRECT COUPLING or communication link by some interfaces, unit or module
It connects, can be electrical or other forms.
The unit illustrated as separating component may or may not be physically separate, be shown as unit
The component shown may or may not be physical unit, you can be located at a place or can also be distributed to multiple
On unit.Some or all of unit therein can be selected according to the actual needs to realize the purpose of this embodiment scheme.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, it can also
That each unit is individually physically present, can also two or more units integrate in a unit.Above-mentioned integrated list
The form that hardware had both may be used in member is realized, can also be realized in the form of SFU software functional unit.
If the integrated unit is realized in the form of SFU software functional unit and is independent product sale or uses
When, it can be stored in a computer read/write memory medium.Based on such understanding, technical scheme of the present invention is substantially
The part to contribute in other words to the prior art or all or part of the technical solution can be in the form of software products
It embodies, which is stored in a storage medium, is used including some instructions so that a computer
Equipment (can be personal computer, server or network equipment etc.) perform each embodiment the method for the present invention whole or
Part steps.And aforementioned storage medium includes：USB flash disk, read-only memory (ROM, Read-Only Memory), arbitrary access are deposited
Reservoir (RAM, Random Access Memory), mobile hard disk, magnetic disc or CD etc. are various can to store program code
Medium.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications also should
It is considered as protection scope of the present invention.
Claims (12)
1. a kind of methods of exhibiting of cooking method, which is characterized in that including：
Obtain the first image information of current food materials；
The type of the food materials is determined based on described first image information；
Type according to the food materials determines the corresponding at least one vegetable of the food materials；
The cooking method of the food materials is determined according to the vegetable, and the cooking method is shown on smoke exhaust ventilator.
2. according to the method described in claim 1, it is characterized in that, the kind of the food materials is determined based on described first image information
Class, including：
Using described first image information as the input of the first model, the kind of the food materials corresponding to described first image information is determined
Class, wherein, first model is what is trained using the multi-group data in first database by machine learning, described
Every group of data in one database in multi-group data include：Food materials image information and food materials corresponding with food materials image information
Type.
3. according to the method described in claim 1, it is characterized in that, the type according to the food materials determines that the food materials are corresponding
At least one vegetable, including：
Type according to the food materials determines vegetable list, wherein, in the vegetable list in the food materials composition of each vegetable
The corresponding food materials of type including the food materials；
It receives selection instruction and vegetable corresponding with the food materials is selected from the vegetable list according to the selection instruction.
4. according to the method described in claim 1, it is characterized in that, the type according to the food materials determines that the food materials are corresponding
At least one vegetable, including：
Type according to the food materials determines vegetable list, wherein, in the vegetable list in the food materials composition of each vegetable
The corresponding food materials of type including the food materials；
Obtain the user images of the smoke exhaust ventilator；
The identity information of the user using the smoke exhaust ventilator is determined according to the user images；
It is selected from the vegetable list based on history diet corresponding with identity information record corresponding with the food materials
Vegetable.
5. it according to the method described in claim 4, it is characterized in that, determines to use the smoke exhaust ventilator according to the user images
User identity information, including：
Using the user images as the input of the second model, the identity information corresponding to the user images is determined, wherein, institute
It is what is trained using the multi-group data in the second database by machine learning to state the second model, in second database
Every group of data in multi-group data include：User images and identity information corresponding with user images.
6. according to the method described in claim 1, it is characterized in that, the method further includes：
The second image information in the cooking process of the food materials is obtained, wherein, second image information is described for reflecting
The cooking status of food materials；Second image information is sent to terminal device.
7. according to the method described in claim 6, it is characterized in that, the method further includes：
Cooking status based on food materials described in second image information acquisition；
When the cooking status is designated state, send a notification message to the terminal device, wherein, which is used for
Food materials described in the terminal device is notified to be in the designated state.
8. a kind of smoke exhaust ventilator, including control panel and smoke exhaust barrel, the smoke exhaust barrel is arranged on above the control panel, special
Sign is, including：
Image collecting device is arranged on the bottom of the control panel, for obtaining the first image information of current food materials；
Processor, for determining the type of the food materials based on described first image information；Type according to the food materials determines
The corresponding at least one vegetable of the food materials；And the cooking method of the food materials is determined according to the vegetable；
Display device is arranged on the control panel, for showing the cooking method on smoke exhaust ventilator.
9. a kind of displaying device of cooking method, applied in smoke exhaust ventilator, which is characterized in that described device includes：
Acquisition module, for obtaining the first image information of current food materials；
First determining module, for determining the type of the food materials based on described first image information；
Second determining module, for determining the corresponding at least one vegetable of the food materials according to the type of the food materials；
Third determining module, for determining the cooking method of the food materials according to the vegetable；
Display module, for showing the cooking method on smoke exhaust ventilator.
10. device according to claim 9, which is characterized in that first determining module, for by described first image
Input of the information as the first model determines the type of the food materials corresponding to described first image information, wherein, first mould
Type is what is trained using the multi-group data in first database by machine learning, multi-group data in the first database
In every group of data include：Food materials image information and food materials type corresponding with food materials image information.
11. a kind of storage medium, which is characterized in that the storage medium includes the program of storage, wherein, it is run in described program
When control the storage medium where cooking method in equipment perform claim requirement 1 to 7 described in any one exhibition method.
12. a kind of processor, which is characterized in that the processor is used to run program, wherein, right of execution when described program is run
Profit requires the methods of exhibiting of the cooking method described in any one in 1 to 7.
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