Method and system for generating health report based on food image recognition
Through food image recognition and digestion and absorption model evaluation, food categories and nutritional components are automatically identified, which solves the problem of time-consuming, labor-intensive and low accuracy of traditional methods, and achieves efficient and accurate health report generation.
Patent Information
- Application Number
- CN202510443182.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-10
- Publication Date
- 2025-07-18
AI Technical Summary
Traditional food nutrition analysis methods are time-consuming and labor-intensive and susceptible to human factors, resulting in low accuracy of analysis results, and the intake of food cannot be automatically identified and accurate health reports are given.
By obtaining the user's food images and weight, identifying food categories, calculating nutrients and content, combining the user's digestion and absorption model, evaluating health reports, and using digestion and absorption model corrections and exercise information to improve assessment accuracy.
Automatic monitoring and health assessment of users' diet is realized, the accuracy and efficiency of health reports are improved, and human error is reduced.
Smart Images
Figure CN120340740A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of health monitoring, and particularly to a method and system for generating a health report based on food image recognition. Background Art
[0002] With the improvement of people's living standards and the enhancement of health awareness, the demand for nutritional management of food intake is increasing day by day. However, traditional food nutrition analysis methods often require manual weighing, classification, and nutritional calculation of food. This method is not only time-consuming and laborious, but also easily affected by human factors, resulting in low accuracy of analysis results. Therefore, a method that can automatically identify the ingested food and nutrients and accurately give a health report of the eater is needed. Summary of the Invention
[0003] To solve the above technical problems, this application is proposed. Embodiments of this application provide a method and system for generating a health report based on food image recognition.
[0004] According to one aspect of this application, there is provided a method for generating a health report based on food image recognition, including: obtaining first body state data of a user; obtaining a first image and a first weight of the food ingested by the user; recognizing the first image to obtain the category of the ingested food; calculating a first nutrient component and a corresponding first nutrient content of the ingested food based on the category of the ingested food and the first weight; inputting the first nutrient component, the corresponding first nutrient content, and the first body state data into a digestion and absorption model of the user to obtain a second nutrient component and a corresponding second nutrient content actually absorbed by the user; obtaining second body state data of the user after a preset time period; and evaluating to obtain a health report of the user based on a state difference between the first body state data and the second body state data, and the second nutrient component and the corresponding second nutrient content.
[0005] In one embodiment, the method for generating a health report based on food image recognition further includes: correcting the digestion and absorption model based on a state difference between the first body state data and the second body state data, and a content difference between the first nutrient component and the corresponding second nutrient component.
[0006] In one embodiment, correcting the digestion and absorption model based on the state difference between the first body state data and the second body state data and the content difference between the first nutrient component and the corresponding second nutrient component includes: determining the nutrient component that causes the state difference based on the state difference between the first body state data and the second body state data; and correcting the digestion and absorption model based on the ratio between the multiple nutrient components that cause the state difference and the content difference.
[0007] In one embodiment, the first image includes multiple images of the ingested food from the initial state to the eaten state; wherein, identifying the first image to obtain the category of the ingested food includes: identifying the ingredient images included in the initial state of the ingested food to obtain the ingredient categories; and determining the category of the ingested food based on the ingredient categories.
[0008] In one embodiment, calculating the first nutrient component and the corresponding first nutrient content of the ingested food based on the category of the ingested food and the first weight includes: measuring the weight of the ingredients corresponding to the ingredient categories; calculating the weight proportion of each ingredient category based on all the ingredient categories and the corresponding ingredient weights; measuring the eaten weight of the ingested food in the eaten state; and calculating the first nutrient component and the corresponding first nutrient content based on the eaten weight and the weight proportion of each ingredient category.
[0009] In one embodiment, calculating the first nutrient component and the corresponding first nutrient content of the ingested food based on the category of the ingested food and the first weight further includes: measuring the remaining weight of the ingested food in the eaten state; and calculating the first nutrient component and the corresponding first nutrient content based on the eaten weight, the remaining weight, and the weight proportion of each ingredient category.
[0010] In one embodiment, the method for generating a health report based on food image recognition further includes: recording the exercise information of the user; and evaluating to obtain the health report of the user based on the state difference between the first body state data and the second body state data, the second nutrient component and the corresponding second nutrient content includes: evaluating to obtain the health report of the user based on the state difference between the first body state data and the second body state data, the second nutrient component and the corresponding second nutrient content, and the exercise information of the user.
[0011] In one embodiment, the method for generating a health report based on food image recognition further includes: displaying the health report of the user.
[0012] According to another aspect of the present application, there is provided a system for generating a health report based on food image recognition, including: a first status acquisition module for acquiring the first physical status data of a user; an ingested food acquisition module for acquiring a first image and a first weight of the ingested food of the user; a food category recognition module for recognizing the first image to obtain the category of the ingested food; a first nutrition calculation module for calculating a first nutritional component and a corresponding first nutritional content of the ingested food based on the category of the ingested food and the first weight; a second nutrition calculation module for inputting the first nutritional component and the corresponding first nutritional content and the first physical status data into a digestion and absorption model of the user to obtain a second nutritional component and a corresponding second nutritional content actually absorbed by the user; a second status acquisition module for acquiring second physical status data of the user after a preset time period; and a health report evaluation module for evaluating to obtain a health report of the user based on a status difference between the first physical status data and the second physical status data and the second nutritional component and the corresponding second nutritional content.
[0013] In one embodiment, the system for generating a health report based on food image recognition is further configured to: correct the digestion and absorption model based on a status difference between the first physical status data and the second physical status data and a content difference between the first nutritional component and the corresponding second nutritional component in terms of nutritional content.
[0014] The method and system for generating a health report based on food image recognition provided by the present application, by acquiring the first physical status data of a user; acquiring a first image and a first weight of the ingested food of the user; recognizing the first image to obtain the category of the ingested food; calculating a first nutritional component and a corresponding first nutritional content of the ingested food based on the category of the ingested food and the first weight; inputting the first nutritional component and the corresponding first nutritional content and the first physical status data into a digestion and absorption model of the user to obtain a second nutritional component and a corresponding second nutritional content actually absorbed by the user; acquiring second physical status data of the user after a preset time period; evaluating to obtain a health report of the user based on a status difference between the first physical status data and the second physical status data and the second nutritional component and the corresponding second nutritional content; by acquiring the image and weight of the ingested food and recognizing to obtain the first nutritional component and the corresponding first nutritional content ingested, and analyzing based on the digestion and absorption model of the user to obtain the second nutritional component and the corresponding second nutritional content actually absorbed by the user, and combining the status difference between the first physical status data and the second physical status data before and after the user's ingestion, comprehensively evaluating the health report of the user, so as to realize automatic monitoring of the user's diet and conduct a health assessment in combination with the user's digestion and absorption ability, thereby improving the accuracy of the assessment. Brief Description of the Drawings
[0015] The embodiments of the present application will be described in more detail by combining the accompanying drawings. The above and other objects, features, and advantages of the present application will become more apparent. The accompanying drawings are used to provide a further understanding of the embodiments of the present application, and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application, and do not constitute a limitation to the present application. In the accompanying drawings, the same reference numerals generally represent the same components or steps.
[0016] Figure 1 It is a schematic flowchart of a method for generating a health report based on food image recognition provided by an exemplary embodiment of the present application.
[0017] Figure 2 It is a schematic structural diagram of a system for generating a health report based on food image recognition provided by an exemplary embodiment of the present application.
[0018] Figure 3 It is a structural diagram of an electronic device provided by an exemplary embodiment of the present application. Detailed Description of the Embodiments
[0019] Next, exemplary embodiments of the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described herein.
[0020] Figure 1 It is a schematic flowchart of a method for generating a health report based on food image recognition provided by an exemplary embodiment of the present application. As Figure 1 shown, the method for generating a health report based on food image recognition includes the following steps: Step 110: Obtain the first physical condition data of the user.
[0021] By obtaining the first physical condition data of the user before eating, the physical condition of the user before eating can be known, so as to provide a reference basis for subsequent evaluation of the user's health status.
[0022] Step 120: Obtain the first image and the first weight of the food ingested by the user.
[0023] The image of the food ingested by the user is obtained through an image acquisition device such as a camera, and the weight of the food ingested by the user is obtained through a weighing device, so as to provide a basis for subsequent automatic recognition of the nutritional components and nutritional content ingested by the user.
[0024] Step 130: Identify the first image to obtain the category of the ingested food.
[0025] By identifying the first image to obtain the category of the food ingested by the user. Specifically, in this application, the first image of the ingested food can be compared with the stored images of foods in the database. Based on the similarity between the first image and the stored images, if there is a stored image with a similarity greater than the threshold, the food category corresponding to the stored image is taken as the category of the ingested food identified by the first image.
[0026] Step 140: Calculate the first nutrient components and the corresponding first nutrient contents of the ingested food based on the category of the ingested food and the first weight.
[0027] After obtaining the category and weight of the ingested food, calculate the first nutrient components and the corresponding first nutrient contents of the food ingested by the user according to the nutrient components and the corresponding nutrient contents of various foods stored in the system.
[0028] Step 150: Input the first nutrient components and the corresponding first nutrient contents, and the first physical condition data of the user into the digestion and absorption model of the user to obtain the second nutrient components and the corresponding second nutrient contents actually absorbed by the user.
[0029] Since the digestion and absorption abilities of different users are different, in this application, a digestion and absorption model of the user is trained based on multiple historical data of the user, and the first nutrient components and the corresponding first nutrient contents, and the first physical condition data of the user are input into the digestion and absorption model of the user to obtain the second nutrient components and the corresponding second nutrient contents actually digested and absorbed by the user.
[0030] Step 160: Obtain the second physical condition data of the user after a preset time period.
[0031] After a preset time period (such as 1 hour) after the user's diet, obtain the second physical condition data of the user again to be used as the basis for evaluating the user's health status. In this application, the physical condition data of the user can also be obtained at multiple times after the user's diet, and the second physical condition data of the user is comprehensively determined based on the multiple physical condition data.
[0032] Step 170: Evaluate and obtain the health report of the user based on the state difference between the first physical condition data and the second physical condition data, and the second nutrient components and the corresponding second nutrient contents.
[0033] Combine the state difference between the first physical condition data and the second physical condition data, and the second nutrient components and the corresponding second nutrient contents to comprehensively evaluate the health status of the user, so as to obtain the health report of the user.
[0034] The method for generating a health report based on food image recognition provided by this application includes: obtaining the first physical condition data of the user; obtaining the first image and the first weight of the food consumed by the user; recognizing the first image to obtain the categories of the consumed food; calculating the first nutrient components and the corresponding first nutrient contents of the consumed food based on the categories of the consumed food and the first weight; inputting the first nutrient components, the corresponding first nutrient contents, and the first physical condition data into the digestion and absorption model of the user to obtain the second nutrient components and the corresponding second nutrient contents actually absorbed by the user; obtaining the second physical condition data of the user after a preset time period; evaluating to obtain the health report of the user based on the state difference between the first physical condition data and the second physical condition data, the second nutrient components, and the corresponding second nutrient contents; by obtaining the image and weight of the consumed food and recognizing the first nutrient components and the corresponding first nutrient contents, and analyzing through the digestion and absorption model of the user to obtain the second nutrient components and the corresponding second nutrient contents actually absorbed, combining the state difference between the first physical condition data and the second physical condition data before and after the user's intake, comprehensively evaluating the health report of the user, so as to realize automatic monitoring of the user's diet and conduct a health assessment in combination with the user's digestion and absorption ability, thereby improving the accuracy of the assessment.
[0035] In one embodiment, the method for generating a health report based on food image recognition described above may further include: correcting the digestion and absorption model based on the state difference between the first physical condition data and the second physical condition data, and the content difference between the first nutrient components and the corresponding second nutrient contents.
[0036] After this application obtains the first physical condition data, the second physical condition data, the first nutrient components, and the corresponding second nutrient components of the user, it corrects the digestion and absorption model in combination with the state difference between the first physical condition data and the second physical condition data, and the content difference between the first nutrient components and the corresponding second nutrient contents.
[0037] In one embodiment, the specific correction method of the digestion and absorption model may be: determining the nutrient components that cause the state difference based on the state difference between the first physical condition data and the second physical condition data; correcting the digestion and absorption model based on the proportion and content difference between the multiple nutrient components that cause the state difference.
[0038] Specifically, the present application can calculate the state differences of each state parameter between the first body state data and the second body state data respectively, and based on the corresponding relationship between the state parameter and the nutrient component, determine the nutrient component that causes the state difference, and modify the digestion and absorption model according to the ratio and content differences between multiple nutrient components that cause the state difference. For example, if a certain state parameter difference between the first body state data and the second body state data is large, while the content of the nutrient component (the second nutrient component) that causes the change in this state parameter is very small (the content ratio is very low), then the parameter value of the digestion and absorption model can be modified at this time to improve the corresponding accuracy between the nutrient components actually digested and absorbed by the user and the ingested nutrient components.
[0039] In one embodiment, the first image includes multiple images of the ingested food from the initial state to the eaten state; wherein, the specific implementation manner of the above step 130 can be: identifying the ingredient images included in the initial state of the ingested food to obtain the ingredient categories; and determining the category of the ingested food based on the ingredient categories.
[0040] Since the food ingested by the user may be a combination of multiple ingredients, such as stir-fried dishes, etc., by identifying the ingredient images included in the initial state of the ingested food to obtain the category of each ingredient, and determining the category of the ingested food according to the ingredient categories.
[0041] In one embodiment, the specific implementation manner of the above step 140 can be: measuring the weight of the ingredients corresponding to the ingredient categories; calculating the weight proportion of each ingredient category based on all ingredient categories and the corresponding ingredient weights; measuring the eaten weight of the ingested food in the eaten state; and calculating the first nutrient component and the corresponding first nutrient content based on the eaten weight and the weight proportion of each ingredient category.
[0042] By measuring the weight of the ingredients corresponding to each ingredient category, combining all ingredient categories and the corresponding ingredient weights, calculating the weight proportion of each ingredient category, and measuring the eaten weight of the ingested food in the eaten state, combining the weight proportion of each ingredient category to calculate the intake of each ingredient, and then calculating the first nutrient component and the corresponding first nutrient content.
[0043] In one embodiment, the specific implementation manner of the above step 140 can be: measuring the remaining weight of the ingested food in the eaten state; and calculating the first nutrient component and the corresponding first nutrient content based on the eaten weight, the remaining weight, and the weight proportion of each ingredient category.
[0044] By calculating the remaining weight of the ingested food, and combining the total weight (eaten weight) of the food, the remaining weight, and the weight proportion of the ingredient categories to calculate the first nutrient component and the corresponding first nutrient content.
[0045] In one embodiment, the method for generating a health report based on food image recognition may further include: recording the user's exercise information; the specific implementation manner of the above step 170 may be: based on the state difference between the first physical state data and the second physical state data, the second nutrient component and the corresponding second nutrient content, and the user's exercise information, a health report of the user is evaluated and obtained.
[0046] This application may also record the user's exercise information in real time based on devices such as smart bracelets, and calculate data such as the user's energy consumption based on the exercise information. Combining the state difference between the first physical state data and the second physical state data, the second nutrient component and the corresponding second nutrient content, and the user's exercise information, a health report of the user is evaluated and obtained to improve the accuracy of the health report.
[0047] In one embodiment, the method for generating a health report based on food image recognition may further include: displaying the user's health report.
[0048] After obtaining the user's health report, this application may use a visual device to display the user's health report to visually inform the user of their health status.
[0049] Figure 2 It is a schematic structural diagram of a system for generating a health report based on food image recognition provided by an exemplary embodiment of this application. As Figure 2 shown, the system 20 for generating a health report based on food image recognition includes: a first state acquisition module 21, configured to acquire the first physical state data of the user; an ingested food acquisition module 22, configured to acquire the first image and the first weight of the user's ingested food; a food category recognition module 23, configured to recognize the first image to obtain the category of the ingested food; a first nutrition calculation module 24, configured to calculate the first nutrient component and the corresponding first nutrient content of the ingested food based on the category of the ingested food and the first weight; a second nutrition calculation module 25, configured to input the first nutrient component and the corresponding first nutrient content, and the first physical state data into the user's digestion and absorption model to obtain the second nutrient component and the corresponding second nutrient content actually absorbed by the user; a second state acquisition module 26, configured to acquire the second physical state data of the user after a preset time period; a health report evaluation module 27, configured to evaluate and obtain a health report of the user based on the state difference between the first physical state data and the second physical state data, and the second nutrient component and the corresponding second nutrient content.
[0050] The system for generating a health report based on food image recognition provided by this application obtains the first physical condition data of the user through the first condition acquisition module 21; the ingested food acquisition module 22 obtains the first image and the first weight of the food ingested by the user; the food category recognition module 23 recognizes the first image to obtain the category of the ingested food; the first nutrition calculation module 24 calculates the first nutritional components and the corresponding first nutritional content of the ingested food based on the category and the first weight of the ingested food; the second nutrition calculation module 25 inputs the first nutritional components, the corresponding first nutritional content, and the first physical condition data into the digestion and absorption model of the user to obtain the second nutritional components and the corresponding second nutritional content actually absorbed by the user; the second condition acquisition module 26 obtains the second physical condition data of the user after a preset time period; the health report evaluation module 27 evaluates and obtains the health report of the user based on the condition difference between the first physical condition data and the second physical condition data, and the second nutritional components and the corresponding second nutritional content; by obtaining the image and weight of the ingested food and identifying the first nutritional components and the corresponding first nutritional content, and analyzing the second nutritional components and the corresponding second nutritional content actually absorbed by the user based on the digestion and absorption model of the user, and combining the condition difference between the first physical condition data and the second physical condition data before and after the user's ingestion, comprehensively evaluate the health report of the user, so as to realize automatic monitoring of the user's diet and combine the user's digestion and absorption ability for health assessment, so as to improve the accuracy of the assessment.
[0051] In one embodiment, the above-mentioned system 20 for generating a health report based on food image recognition can be further configured to: correct the digestion and absorption model based on the condition difference between the first physical condition data and the second physical condition data, and the content difference between the first nutritional components and the corresponding second nutritional components.
[0052] In one embodiment, the above-mentioned system 20 for generating a health report based on food image recognition can be further configured to: determine the nutritional components that cause the condition difference based on the condition difference between the first physical condition data and the second physical condition data; correct the digestion and absorption model based on the proportion and content difference between the multiple nutritional components that cause the condition difference.
[0053] In one embodiment, the first image includes multiple images of the ingested food from the initial state to the eaten state; wherein, the above-mentioned food category recognition module 23 can be further configured to: recognize the ingredient images included in the initial state of the ingested food to obtain the ingredient categories; determine the category of the ingested food based on the ingredient categories.
[0054] In one embodiment, the first nutrition calculation module 24 may be further configured to: measure the weight of the food ingredients corresponding to the food ingredient categories; calculate the weight percentage of each food ingredient category based on all the food ingredient categories and the corresponding food ingredient weights; measure the consumed weight of the ingested food in the consumed state; and calculate the first nutrient components and the corresponding first nutrient contents based on the consumed weight and the weight percentage of each food ingredient category.
[0055] In one embodiment, the first nutrition calculation module 24 may be further configured to: measure the remaining weight of the ingested food in the consumed state; and calculate the first nutrient components and the corresponding first nutrient contents based on the consumed weight, the remaining weight, and the weight percentage of each food ingredient category.
[0056] In one embodiment, the system 20 for generating a health report based on food image recognition may be further configured to record the user's exercise information; and the health report evaluation module 27 may be further configured to: evaluate the user's health report based on the state difference between the first physical state data and the second physical state data, the second nutrient components and the corresponding second nutrient contents, and the user's exercise information.
[0057] In one embodiment, the system 20 for generating a health report based on food image recognition may be further configured to: display the user's health report.
[0058] Next, refer to Figure 3 to describe the electronic device according to an embodiment of the present application. The electronic device may be any one or both of the first device and the second device, or a stand-alone device independent of them, and the stand-alone device may communicate with the first device and the second device to receive the input signals collected from them.
[0059] Figure 3 The block diagram of the electronic device according to an embodiment of the present application is illustrated.
[0060] As Figure 3 shown, the electronic device 10 includes one or more processors 11 and a memory 12.
[0061] The processor 11 may be a central processing unit (CPU) or other form of processing unit having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.
[0062] The memory 12 may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage media, and the processor 11 may run the program instructions to implement the methods of the various embodiments of the present application described above and / or other desired functions. Various contents such as input signals, signal components, noise components, etc. may also be stored in the computer-readable storage media.
[0063] In one example, the electronic device 10 may further include: an input device 13 and an output device 14, and these components are interconnected through a bus system and / or other forms of connection mechanisms (not shown).
[0064] When the electronic device is a stand-alone device, the input device 13 may be a communication network connector for receiving the collected input signals from the first device and the second device.
[0065] In addition, the input device 13 may further include, for example, a keyboard, a mouse, and the like.
[0066] The output device 14 may output various information to the outside, including the determined distance information, direction information, etc. The output device 14 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.
[0067] Of course, for simplicity, Figure 3 only some of the components related to the present application in the electronic device 10 are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application scenarios, the electronic device 10 may further include any other appropriate components.
[0068] In addition to the above methods and devices, the embodiments of the present application may also be a computer program product, which includes computer program instructions, and when the computer program instructions are run by a processor, the processor is caused to execute the steps in the methods according to the various embodiments of the present application described in the "Exemplary Method" section above of this specification.
[0069] The computer program product may be written in any combination of one or more programming languages for executing the program code of the operations of the embodiments of the present application. The programming languages include object-oriented programming languages such as Java, C++, etc., and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's device, executed as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.
[0070] In addition, an embodiment of the present application may also be a computer-readable storage medium having computer program instructions stored thereon. When the computer program instructions are run by a processor, the processor is caused to execute the steps in the methods according to various embodiments of the present application described in the above "Exemplary Method" section of this specification.
[0071] The computer-readable storage medium may employ any combination of one or more readable media. The readable media may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.
[0072] The basic principles of the present application have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, benefits, effects, etc. mentioned in the present application are only examples and not limitations. It cannot be considered that these advantages, benefits, effects, etc. are essential for each embodiment of the present application. In addition, the above-disclosed specific details are only for the purposes of illustration and facilitating understanding, and are not limitations. The above details do not limit the present application to necessarily adopt the above specific details for implementation.
[0073] The block diagrams of the devices, apparatuses, equipment, and systems involved in the present application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "comprising," "including," "having," etc. are open-ended terms meaning "including but not limited to" and can be used interchangeably with each other. The words "or" and "and" used herein refer to the phrase "and / or" and can be used interchangeably with it, unless the context clearly indicates otherwise. The phrase "such as" used herein refers to the phrase "such as but not limited to" and can be used interchangeably with it.
[0074] It should also be noted that in the devices, equipment, and methods of the present application, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of the present application.
[0075] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.
[0076] The above description has been given for purposes of illustration and description. In addition, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.
Claims
1. A method for generating a health report based on food image recognition, characterized in that, Including: Obtain the first physical condition data of the user; Obtain the first image and the first weight of the food ingested by the user; Identify the first image to obtain the category of the ingested food; Based on the category of the ingested food and the first weight, calculate the first nutritional components and the corresponding first nutritional contents of the ingested food; Input the first nutritional components and the corresponding first nutritional contents, and the first physical condition data into the digestion and absorption model of the user to obtain the second nutritional components and the corresponding second nutritional contents actually absorbed by the user; Obtain the second physical condition data of the user after a preset time period; Based on the state difference between the first physical condition data and the second physical condition data, and the second nutritional components and the corresponding second nutritional contents, evaluate and obtain the health report of the user.
2. The method for generating a health report based on food image recognition according to claim 1, wherein The method for generating a health report based on food image recognition further includes: Based on the state difference between the first physical condition data and the second physical condition data, and the content difference between the first nutritional components and the corresponding second nutritional contents, correct the digestion and absorption model.
3. The method for generating a health report based on food image recognition according to claim 2, wherein, The correcting the digestion and absorption model based on the state difference between the first physical condition data and the second physical condition data, and the content difference between the first nutritional components and the corresponding second nutritional contents includes: Based on the state difference between the first physical condition data and the second physical condition data, determine the nutritional components that cause the state difference; Based on the ratio between multiple nutritional components that cause the state difference and the content difference, correct the digestion and absorption model.
4. The method for generating a health report based on food image recognition according to claim 1, wherein The first image includes multiple images of the ingested food from the initial state to the consumed state; wherein, the identifying the first image to obtain the category of the ingested food includes: Identify the ingredient images included in the initial state of the ingested food to obtain the ingredient categories; Based on the ingredient categories, determine the category of the ingested food.
5. The method for generating a health report based on food image recognition according to claim 4, characterized in that, The calculating the first nutritional components and the corresponding first nutritional contents of the ingested food based on the category of the ingested food and the first weight includes: Measure the weight of the ingredients corresponding to the ingredient categories; Based on all ingredient categories and the corresponding ingredient weights, calculate the weight proportion of each ingredient category; Measure the consumed weight of the ingested food in the consumed state; Based on the consumed weight and the weight proportion of each ingredient category, calculate the first nutritional components and the corresponding first nutritional contents.
6. The method for generating a health report based on food image recognition according to claim 5, wherein The calculating the first nutritional components and the corresponding first nutritional contents of the ingested food based on the category of the ingested food and the first weight further includes: Measure the remaining weight of the ingested food in the consumed state; The calculating the first nutritional components and the corresponding first nutritional contents based on the consumed weight and the weight proportion of each ingredient category includes: Based on the consumed weight, the remaining weight and the weight proportion of each ingredient category, calculate the first nutritional components and the corresponding first nutritional contents.
7. The method for generating a health report based on food image recognition according to claim 1, characterized in that The method for generating a health report based on food image recognition further includes: Record the exercise information of the user; The health report of the user obtained by evaluation based on the state difference between the first physical condition data and the second physical condition data, the second nutrient component and the corresponding second nutrient content includes: Based on the state difference between the first physical condition data and the second physical condition data, the second nutrient component and the corresponding second nutrient content, and the exercise information of the user, the health report of the user is obtained by evaluation.
8. The method for generating a health report based on food image recognition according to claim 1, wherein, The method for generating a health report based on food image recognition further includes: Display the health report of the user.
9. A system for generating a health report based on food image recognition, characterized in that, Including: A first state acquisition module for acquiring the first physical condition data of the user; An ingested food acquisition module for acquiring the first image and the first weight of the ingested food of the user; A food category recognition module for recognizing the first image to obtain the category of the ingested food; A first nutrient calculation module for calculating the first nutrient component and the corresponding first nutrient content of the ingested food based on the category of the ingested food and the first weight; A second nutrient calculation module for inputting the first nutrient component and the corresponding first nutrient content and the first physical condition data into the digestion and absorption model of the user to obtain the second nutrient component actually absorbed by the user and the corresponding second nutrient content; A second state acquisition module for acquiring the second physical condition data of the user after a preset time period; A health report evaluation module for obtaining the health report of the user by evaluation based on the state difference between the first physical condition data and the second physical condition data, and the second nutrient component and the corresponding second nutrient content.
10. The system for generating a health report based on food image recognition according to claim 9, characterized in that, The system for generating a health report based on food image recognition is further configured to: Modify the digestion and absorption model based on the state difference between the first physical condition data and the second physical condition data, and the content difference between the first nutrient content and the corresponding second nutrient content.