Cooking food material detection method and device and readable storage medium

Abstract

The invention provides a cooking food material detection method and device, and a readable storage medium, and the method comprises the steps: obtaining a food material image which comprises any one of a preprocessed food material image, an image of the food material in a cooking process, and an image of the food material after cooking; according to the food material image, first description information of the food material is obtained, and the first description information is used for describing the cooking effect of the food material; obtaining first information associated with the first description information in a database, wherein the first information is used for describing a reason for forming the cooking effect; and outputting the first information.

Description

Technical Field

[0001] The present invention relates to the technical field of cooking, and in particular, to a detection method for cooking ingredients, a detection device for cooking ingredients, and a readable storage medium. Background Art

[0002] During the cooking process, due to the lack of cooking experience, users often encounter the situation of cooking failure. Without knowing the reasons for cooking failure, it is difficult for users to improve the cooking process. Summary of the Invention

[0003] The present invention aims to solve one of the technical problems existing in the prior art or related technologies.

[0004] In view of this, in a first aspect, the present invention provides a detection method for cooking ingredients, including: obtaining an ingredient image, where the ingredient image includes any one of an image of the ingredient after pretreatment, an image of the ingredient during the cooking process, and an image of the ingredient after cooking; obtaining first description information of the ingredient according to the ingredient image, where the first description information is used to describe the cooking effect of the ingredient; obtaining first information associated with the first description information in a database, where the first information is used to describe the reason for forming the cooking effect; and outputting the first information.

[0005] During the cooking process, an ingredient image can be obtained by photographing the ingredient, and the ingredient image can indicate the characteristics of the ingredient after being processed. After obtaining the ingredient image, it is necessary to further obtain the first description information of the ingredient, where the first description information of the ingredient is used to describe the cooking effect of the ingredient. For example, the first description information includes the shape information, state information, or color information of the ingredient, etc. Through the shape, state, and color of the ingredient, the cooking situation of the ingredient can be determined.

[0006] In the case of obtaining the first description information, search for the first information in the database. The first information is associated with the first description information and is used to explain how the cooking effect of the ingredient in the current ingredient image is formed. For example, if the color of the ingredient in the ingredient image is too dark, according to the color information of the ingredient, the server or the local database retrieves the reason for the too dark color of the ingredient (the first information), and the first information can be that the heating power is too large or the heating duration is too long, etc. In the case of obtaining the first information, output the first information so that the user can receive the first information, which is convenient for the user to understand the reason for the formation of the current cooking effect of the ingredient.

[0007] During the cooking process, if the user finds that the cooking effect of the ingredient is poor, the user can take a photo of the ingredient. After the server obtains the ingredient image, it processes the ingredient image and outputs the reason for the cooking failure of the ingredient to the user. The user can improve the cooking method according to the reason for the cooking failure, thereby assisting the user to correctly complete the cooking process.

[0008] The detection method in this embodiment can be used for a server, which solves the problem that only relying on user experience after cooking failure and is beneficial to assisting users in improving their cooking skills.

[0009] In addition, according to the cooking device in the above technical solution provided by the present invention, the following additional technical features may also be included:

[0010] In some technical solutions, optionally, after obtaining the first description information of the food ingredient, it further includes: obtaining second information associated with the first description information in the database, and the second information is used to indicate the processing suggestions for the food ingredient.

[0011] The server can obtain the first information associated with the first description information according to the first description information of the food ingredient. However, the first information is only used to explain the reason for cooking failure of the current food ingredient. For some users with poor cooking skills, even if they know the reason for cooking failure, there may still be a situation where they cannot correctly complete the cooking process. Therefore, when the server obtains the first information, it is also necessary to obtain the second information associated with the first description information, and the second information is used to explain the processing suggestions for the food ingredient.

[0012] According to the second information, the user can know the correct processing method for the food ingredient. Therefore, the user can combine the reason for cooking failure and the correct processing method of the food ingredient to improve the cooking process, thereby assisting some users with lower cooking skills to correctly complete the cooking process.

[0013] In some technical solutions, optionally, after obtaining the food ingredient image, it further includes: obtaining user description information; obtaining the first information associated with the first description information in the database, specifically including: obtaining the first information in the database, and the first information is associated with the first description information and the user description information.

[0014] The user can upload their description of the cooking effect of the food ingredient and the food ingredient image to the server together, so that the server determines the first information according to the user description information and the first description information.

[0015] Although the server can obtain the first description information according to the food ingredient image, there may be a problem that the first description information obtained by the server is deviated, or the user is worried that the first description information is not accurate enough. At this time, the user can supplement the description of the cooking effect of the food ingredient, and the server comprehensively determines the first information according to the user's description and the obtained first description information, which is beneficial to improving the matching effect between the first information and the food ingredient image, so as to give the user an accurate analysis of the reason and assist the user in accurately analyzing the reason for cooking failure of the food ingredient.

[0016] In some technical solutions, optionally, after outputting the first information, it further includes: receiving a feedback result on the first information; comparing the user feedback information and the first description information when the feedback result includes user feedback information; and updating the first information according to the user feedback information when the user feedback information matches the first description information.

[0017] After the user obtains the first information, the user can give feedback on the first information, and the user's feedback is used to indicate whether the first information given by the server is correct. When the server obtains the user feedback information, it needs to match the user feedback information and the first description information. If the user feedback information matches the first description information, it indicates that the information feedback by the user is authentic. At this time, the first information can be corrected according to the user feedback information, so as to improve the accuracy of the first information. If the user feedback information does not match the first description information, it indicates that the information feedback by the user is not authentic, and at this time, the first information does not need to be updated.

[0018] In some technical solutions, optionally, obtaining the first description information of the food ingredient includes: performing natural language processing on the food ingredient image to obtain the first description information of the food ingredient.

[0019] The food ingredient image is uploaded to the server or directly parsed locally, and the food ingredient image is converted into a text natural language description, with the description focusing on cooking effects such as the shape, state, and color of the food. This process can use a pre-trained natural language processing model or traditional deep learning methods.

[0020] In a second aspect, the present invention proposes a detection device for cooking food ingredients, including: an acquisition module, configured to acquire a food ingredient image, where the food ingredient image includes any one of an image of the food ingredient after preprocessing, an image of the food ingredient during cooking, and an image of the food ingredient after cooking; the acquisition module is further configured to: obtain the first description information of the food ingredient according to the food ingredient image, where the first description information is used to describe the cooking effect of the food ingredient; the acquisition module is further configured to: obtain the first information associated with the first description information in the database, where the first information is used to describe the reason for forming the cooking effect; and an output module, configured to output the first information.

[0021] In some technical solutions, optionally, after obtaining the first description information of the food ingredient, the acquisition module is further configured to: obtain the second information associated with the first description information in the database, where the second information is used to indicate a processing suggestion for the food ingredient.

[0022] In some technical solutions, optionally, after acquiring the food ingredient image, the acquisition module is further configured to: acquire user description information; specifically, the acquisition module is configured to: acquire the first information in the database, where the first information is associated with the first description information and the user description information.

[0023] In some technical solutions, optionally, the detection device further includes: a receiving module, a comparison module, and an update module; after outputting the first information, the receiving module is configured to: receive a feedback result of the first information; the comparison module is configured to: when the feedback result includes user feedback information, compare the user feedback information with the first description information; the update module is configured to: when the user feedback information matches the first description information, update the first information according to the user feedback information.

[0024] In some technical solutions, optionally, the obtaining module is specifically configured to: perform natural language processing on the food ingredient image to obtain the first description information of the food ingredient.

[0025] In a third aspect, the present invention provides a detection device for cooking food ingredients, including a memory and a processor, where the memory stores a program or instruction that can run on the processor, and when the program or instruction is executed by the processor, the steps of the detection method for cooking food ingredients in the first aspect are implemented.

[0026] In a fourth aspect, the present invention provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by the processor, the steps of the detection method for cooking food ingredients in the first aspect are implemented.

[0027] The additional aspects and advantages of the present invention will become apparent in the following description section, or be learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The above and / or additional aspects and advantages of the present invention will become apparent and be readily understood from the description of the embodiments in conjunction with the following drawings, where:

[0029] Figure 1 One of the flowcharts of the detection method for cooking food ingredients in the embodiments of the present invention is shown;

[0030] Figure 2 Another flowchart of the detection method for cooking food ingredients in the embodiments of the present invention is shown;

[0031] Figure 3 One of the schematic block diagrams of the detection device for cooking food ingredients in the embodiments of the present invention is shown;

[0032] Figure 4 Another schematic block diagram of the detection device for cooking food ingredients in the embodiments of the present invention is shown. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] In order to more clearly understand the above objects, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.

[0034] In the following description, many specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention may be practiced in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited by the specific embodiments disclosed below.

[0035] The following refers to Figures 1 to 4 Describe a method for detecting cooking ingredients, a device for detecting cooking ingredients, and a readable storage medium provided according to some embodiments of the present invention.

[0036] As Figure 1 shown, in an embodiment of the present invention, a method for detecting cooking ingredients is proposed, including:

[0037] Step 102, obtain an ingredient image, where the ingredient image includes any one of an image of the ingredient after pretreatment, an image of the ingredient during cooking, and an image of the ingredient after cooking;

[0038] Step 104, according to the ingredient image, obtain first description information of the ingredient, where the first description information is used to describe the cooking effect of the ingredient;

[0039] Step 106, obtain first information associated with the first description information in the database, where the first information is used to describe the reason for forming the cooking effect;

[0040] Step 108, output the first information.

[0041] During the cooking process, an ingredient image can be obtained by photographing the ingredient, and the ingredient image can indicate the characteristics of the ingredient after being processed. After obtaining the ingredient image, it is necessary to further obtain the first description information of the ingredient. The first description information of the ingredient is used to describe the cooking effect of the ingredient. For example, the first description information includes the shape information, state information, or color information of the ingredient, etc. Through the shape, state, and color of the ingredient, the cooking situation of the ingredient can be determined.

[0042] In the case of obtaining the first description information, search for the first information in the database. The first information is associated with the first description information and is used to explain how the cooking effect of the ingredient in the current ingredient image is formed. For example, if the color of the ingredient in the ingredient image is too dark, according to the color information of the ingredient, the server or the local database retrieves the reason for the too dark color of the ingredient (the first information). The first information can be that the heating power is too large or the heating duration is too long, etc. In the case of obtaining the first information, output the first information so that the user can receive the first information, which is convenient for the user to understand the reason for the formation of the current cooking effect of the ingredient.

[0043] During the cooking process, if the user finds that the cooking effect of the ingredients is poor, the user can take a photo of the ingredients. After the server obtains the ingredient image, it processes the ingredient image and outputs to the user the reason for the failure of cooking the ingredients. The user can improve the cooking method according to the reason for the cooking failure, so as to assist the user to correctly complete the cooking process.

[0044] When obtaining the ingredient image, it can be that the user takes a photo of the baking ingredients, or the cooking device takes a photo of the ingredients.

[0045] The detection method in this embodiment can be used in the server or the cooking device, or the detection method can also be used in user terminals such as mobile phones and tablets, to solve the problem that only relying on the user's experience is possible after cooking fails, which is beneficial to assisting the user to improve the cooking level.

[0046] When the detection method is used in the server, the server can output the first information to the cooking device or the user terminal. When the detection method is used in the cooking device or the user terminal, the first information is displayed by the cooking device or the user terminal.

[0047] In some embodiments, optionally, after the step of obtaining the first description information of the ingredients, it further includes: obtaining second information associated with the first description information in the database, and the second information is used to indicate the processing suggestions for the ingredients.

[0048] The server can obtain the first information associated with the first description information according to the first description information of the ingredients. However, the first information is only used to explain the reason for the failure of cooking the current ingredients. For some users with poor cooking skills, even if they know the reason for the cooking failure, there may still be a situation where they cannot correctly complete the cooking process. Therefore, when the server obtains the first information, it also needs to obtain the second information associated with the first description information, and the second information is used to explain the processing suggestions for the ingredients.

[0049] According to the second information, the user can know the correct processing method for the ingredients. Therefore, the user can combine the reason for the cooking failure and the correct processing method for the ingredients to improve the cooking process, so as to assist some users with lower cooking skills to correctly complete the cooking process.

[0050] In some embodiments, optionally, after the step of obtaining the ingredient image, it further includes: obtaining user description information. The step of obtaining the first information associated with the first description information in the database specifically includes: obtaining the first information in the database, and the first information is associated with the first description information and the user description information.

[0051] The user can upload their description of the cooking effect of the ingredients together with the ingredient image to the server, so that the server determines the first information according to the user description information and the first description information.

[0052] Although the server can obtain the first description information based on the food ingredient image, there may be a problem that the first description information obtained by the server is biased, or the user is worried that the first description information is not accurate enough. At this time, the user can supplement the description of the cooking effect of the food ingredient. The server comprehensively determines the first information based on the user's description and the obtained first description information, which is beneficial to improving the matching effect between the first information and the food ingredient image, so as to accurately analyze the reasons for the user and assist the user in accurately analyzing the reasons for the failure of cooking the food ingredient.

[0053] Combine the first description information generated in the previous step with the user description information, and recall relevant content from the existing database for this text information. The recalled content is the description text corresponding to the failure phenomenon and the corresponding precautions and countermeasures. Feedback the precautions and countermeasures to the user. The above recall process can adopt a pre-trained natural language processing model or traditional deep learning methods.

[0054] In some embodiments, optionally, after the step of outputting the first information, it further includes: receiving a feedback result on the first information; comparing the user feedback information and the first description information based on the condition that the feedback result includes the user feedback information; and updating the first information according to the user feedback information based on the condition that the user feedback information and the first description information match.

[0055] After obtaining the first information, the user can give feedback on the first information, and the user's feedback is used to indicate whether the first information given by the server is correct. When the server obtains the user feedback information, it needs to match the user feedback information and the first description information. If the user feedback information and the first description information match, it indicates that the information feedback by the user is authentic. At this time, the first information can be corrected according to the user feedback information, so as to improve the accuracy of the first information. If the user feedback information and the first description information do not match, it indicates that the information feedback by the user is not authentic, and at this time, the first information does not need to be updated.

[0056] Whether the user feedback result is correct. If not, collect the user feedback real information and confirm it in the background, and update the data in the database after confirmation.

[0057] In some embodiments, optionally, obtaining the first description information of the food ingredient includes: performing natural language processing on the food ingredient image to obtain the first description information of the food ingredient.

[0058] The food ingredient image is uploaded to the server or directly parsed locally, and the food ingredient image is converted into a text natural language description. The description focuses on the cooking effects such as the shape, state, and color of the food. This process can use a pre-trained natural language processing model or traditional deep learning methods.

[0059] In an embodiment of the present invention, a method for analyzing the phenomenon of baking failure is proposed. By taking pictures of baked foods, the possible reasons for cooking failure can be automatically analyzed. Through the image-to-semantics technology, image information can be converted into text information, which is a detailed description of the captured image. Based on this text information description, or by adding user input description information, combined with the background baking problem database, the reasons for baking failure and key steps or information to focus on are output. This process can be extended to cooking preparation and cooking process analysis. During the cooking pretreatment process, images can be taken for automatic analysis. For example, to take a picture of the shape of whipped egg whites to automatically analyze whether further whipping is needed.

[0060] As Figure 2 shown, in a possible embodiment, the detection method of cooking ingredients includes:

[0061] Step 402, the user takes a picture of the food;

[0062] Step 404, parse the image;

[0063] Step 406, convert it into a text description;

[0064] Step 408, combine with the user's description;

[0065] Step 410, recall relevant content from the database;

[0066] Step 412, process with the large model;

[0067] Step 414, return suggestions and measures;

[0068] Step 416, collect user feedback into the database.

[0069] As Figure 3 shown, in an embodiment of the present invention, a detection device 200 for cooking ingredients is proposed, including:

[0070] An acquisition module 210, configured to acquire an ingredient image, where the ingredient image includes any one of an image of the ingredient after pretreatment, an image of the ingredient during the cooking process, and an image of the ingredient after cooking;

[0071] The acquisition module 210 is further configured to: according to the ingredient image, acquire first description information of the ingredient, where the first description information is used to describe the cooking effect of the ingredient;

[0072] The acquisition module 210 is further configured to: acquire first information associated with the first description information in the database, where the first information is used to describe the reason for forming the cooking effect;

[0073] An output module 220, configured to output the first information.

[0074] During the cooking process, an ingredient image can be obtained by photographing the ingredient, and the ingredient image can indicate the characteristics of the ingredient after being processed. After obtaining the ingredient image, it is necessary to further obtain the first description information of the ingredient, and the first description information of the ingredient is used to describe the cooking effect of the ingredient. For example, the first description information includes the shape information, state information, or color information of the ingredient, etc. Through the shape, state, and color of the ingredient, the cooking situation of the ingredient can be determined.

[0075] In the case of obtaining the first description information, search for the first information in the database. The first information is associated with the first description information and is used to explain how the cooking effect of the ingredient in the current ingredient image is formed. For example, if the color of the ingredient in the ingredient image is too dark, according to the color information of the ingredient, the server or the local database retrieves the reason for the ingredient's too-dark color (the first information). The first information can be that the heating power is too large or the heating duration is too long, etc. In the case of obtaining the first information, output the first information so that the user can receive the first information, which is convenient for the user to understand the reason for the formation of the current ingredient cooking effect.

[0076] During the cooking process, if the user finds that the cooking effect of the ingredient is poor, the user can take a photo of the ingredient. After the server obtains the ingredient image, it processes the ingredient image and outputs to the user the reason for the failure of ingredient cooking. The user can improve the cooking method according to the reason for the cooking failure, so as to assist the user to correctly complete the cooking process.

[0077] The detection device in this embodiment can be used in the server or cooking equipment, or the detection method can also be used in user terminals such as mobile phones and tablets, to solve the problem that only relying on user experience is possible after cooking failure, which is beneficial to assisting the user to improve the cooking level.

[0078] In some embodiments, optionally, after obtaining the first description information of the ingredient, the acquisition module is further configured to: acquire second information associated with the first description information in the database, and the second information is used to indicate the processing suggestion for the ingredient.

[0079] The server can obtain the first information associated with the first description information according to the first description information of the ingredient. However, the first information is only used to explain the reason for the failure of ingredient cooking for the current ingredient. For some users with poor cooking skills, even if they know the reason for the cooking failure, there may still be a situation where they cannot correctly complete the cooking process. Therefore, when the server obtains the first information, it is also necessary to obtain the second information associated with the first description information, and the second information is used to explain the processing suggestion for the ingredient.

[0080] According to the second piece of information, the user can know the correct processing method of the food ingredients. Therefore, the user can combine the reasons for cooking failure and the correct processing method of the food ingredients to improve the cooking process, thereby assisting some users with lower cooking skills to correctly complete the cooking process.

[0081] In some embodiments, optionally, after obtaining the food ingredient image, the obtaining module is further configured to: obtain user description information; specifically, the obtaining module is configured to obtain first information in a database, where the first information is associated with the first description information and the user description information.

[0082] The user can upload their description of the cooking effect of the food ingredients together with the food ingredient image to the server, so that the server determines the first information based on the user description information and the first description information.

[0083] Although the server can obtain the first description information based on the food ingredient image, there may be a problem that the first description information obtained by the server is deviated, or the user is worried that the first description information is not accurate enough. At this time, the user can supplement the description of the cooking effect of the food ingredients. The server comprehensively determines the first information based on the user's description and the obtained first description information, which is beneficial to improving the matching effect between the first information and the food ingredient image, thereby enabling the server to give the user accurate analysis reasons and assisting the user to accurately analyze the reasons for cooking failure of the food ingredients.

[0084] In some embodiments, optionally, the detection device further includes: a receiving module, a comparison module, and an update module; after outputting the first information, the receiving module is configured to: receive the feedback result of the first information; the comparison module is configured to: compare the user feedback information and the first description information when the feedback result includes the user feedback information; the update module is configured to: update the first information according to the user feedback information when the user feedback information and the first description information match.

[0085] After obtaining the first information, the user can give feedback on the first information, and the user's feedback is used to indicate whether the first information given by the server is correct. When the server obtains the user feedback information, it needs to match the user feedback information and the first description information. If the user feedback information and the first description information match, it indicates that the information feedback by the user is authentic. At this time, the first information can be corrected according to the user feedback information, thereby improving the accuracy of the first information. If the user feedback information and the first description information do not match, it indicates that the information feedback by the user is not authentic, and at this time, the first information does not need to be updated.

[0086] In some embodiments, optionally, the obtaining module is specifically configured to: perform natural language processing on the food ingredient image to obtain the first description information of the food ingredients.

[0087] The food ingredient image is uploaded to the server or directly parsed locally, and the food ingredient image is converted into a text natural language description. The focus of the description is on cooking effects such as the shape, state, and color of the food. This process can use a pre-trained natural language processing model or traditional deep learning methods.

[0088] As Figure 4 shown, in an embodiment of the present invention, a detection device 300 for cooking ingredients is proposed, including a memory 310 and a processor 320. The memory 310 stores a program or instruction that can run on the processor 320. When the program or instruction is executed by the processor 320, it implements the steps of the detection method for cooking ingredients in any of the above embodiments and can achieve the same technical effects, which will not be elaborated here.

[0089] In an embodiment of the present invention, a readable storage medium is proposed, on which a program or instruction is stored. When the program or instruction is executed by a processor, it implements the steps of the detection method for cooking ingredients in any of the above embodiments and can achieve the same technical effects, which will not be elaborated here.

[0090] The methods can be implemented in various different ways according to specific features and / or example applications. For example, these methods can be implemented through a combination of hardware, firmware, and / or software. For example, in a hardware implementation, the processor can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, electronic devices, other device units for performing the above functions, and / or combinations thereof.

[0091] A computer-readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer-readable storage medium can be an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing devices, without limitation. A non-exhaustive list of more specific examples of the computer-readable storage medium includes: portable computer floppy disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital versatile disks (DVDs), memory cards, floppy disks, encoding mechanical devices (such as punched cards or grooves having raised structures recording instructions), and any suitable combination of the foregoing devices. The computer-readable storage medium used herein should not be construed as a signal per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media, or electrical signals transmitted through wires, etc.

[0093] In the present invention, the term "a plurality of" refers to two or more, unless otherwise clearly defined. Terms such as "mounted", "connected", "coupled", "fixed", etc. should be construed in a broad sense. For example, "connected" can be a fixed connection, a detachable connection, or an integral connection; "coupled" can be a direct connection or an indirect connection through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0094] In the description of this specification, the description of terms such as "one embodiment", "some embodiments", "specific embodiments", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or instance. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0095] The foregoing is only the preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A detection method for cooking ingredients, characterized in that, Including: Obtain a food material image, where the food material image includes any one of an image of the food material after pretreatment, an image of the food material during the cooking process, and an image of the food material after cooking; According to the food material image, obtain first description information of the food material, where the first description information is used to describe the cooking effect of the food material; Obtain first information associated with the first description information in a database, where the first information is used to describe the reason for forming the cooking effect; Output the first information.

2. The detection method according to claim 1, wherein After obtaining the first description information of the food material, the detection method further includes: Obtain second information associated with the first description information in the database, where the second information is used to indicate a processing suggestion for the food material.

3. The detection method according to claim 1 or 2, characterized in that, After obtaining the food material image, the detection method further includes: Obtain user description information; The obtaining of the first information associated with the first description information in the database specifically includes: Obtain first information in the database, where the first information is associated with the first description information and the user description information.

4. The detection method according to claim 1 or 2, characterized in that After outputting the first information, the detection method further includes: Receive a feedback result for the first information; Based on the case that the feedback result includes user feedback information, compare the user feedback information with the first description information; Based on the case that the user feedback information matches the first description information, update the first information according to the user feedback information.

5. The detection method according to claim 1 or 2, characterized in that The obtaining of the first description information of the food material includes: Perform natural language processing on the food material image to obtain the first description information of the food material.

6. A detection device for cooking ingredients, characterized in that, Including: An obtaining module, configured to obtain a food material image, where the food material image includes any one of an image of the food material after pretreatment, an image of the food material during the cooking process, and an image of the food material after cooking; The obtaining module is further configured to: according to the food material image, obtain first description information of the food material, where the first description information is used to describe the cooking effect of the food material; The obtaining module is further configured to: obtain first information associated with the first description information in a database, where the first information is used to describe the reason for forming the cooking effect; An output module, configured to output the first information.

7. The detection device according to claim 6, wherein After obtaining the first description information of the food material, the obtaining module is further configured to: Obtain second information associated with the first description information in the database, where the second information is used to indicate a processing suggestion for the food material.

8. The detection device according to claim 6 or 7, characterized in that, After obtaining the food material image, the obtaining module is further configured to: Obtain user description information, where the user description information is used to describe the status information of the food material; The obtaining module is specifically configured to: Obtain first information in the database, where the first information is associated with the first description information and the user description information.

9. A detection device for cooking ingredients, characterized in that, Including a memory and a processor, where the memory stores a program or instruction that can run on the processor, and when the program or the instruction is executed by the processor, the steps of the detection method according to any one of claims 1 to 5 are implemented.

10. A readable storage medium, characterized in that, Programs or instructions are stored therein, wherein when the programs or the instructions are executed by a processor, the steps of the detection method described in any one of claims 1 to 5 are implemented.

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