Food making method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of smart home, and provides a food making method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a food image; determining target recipe information, target cooking equipment information and target cooking control parameters corresponding to the food image based on food material types in the food image; and sending the target cooking control parameter to target cooking equipment corresponding to the target cooking equipment information, wherein the target cooking control parameter is used for making target food corresponding to the target recipe information by the target cooking equipment. According to the invention, the purpose of strong association from the food image to the process of making the target food by the target cooking equipment is realized, the whole food making link does not need to be manually participated by a user, and the intelligence and convenience of the food making process are improved.

Description

Technical Field

[0001] The present invention relates to the field of smart home technology, and in particular to a food preparation method, device, electronic device and storage medium. Background Art

[0002] At present, when users want to make sweet and sour spareribs, braised eggplant or other specific dishes, they can make them according to historical cooking experience or search for recipes on the Internet. However, when users see a picture of a dish they like but do not know the name of the dish, they usually ask others or seek help from the Internet to obtain the recipe information, cooking method and cooking equipment for making the dish, and then manually convert the cooking parameters corresponding to the cooking method into cooking control parameters of the cooking equipment, and finally manually operate the cooking equipment according to the cooking control parameters or turn on the automatic cooking function of the cooking equipment to complete the cooking process of the desired dish.

[0003] However, the existing process of making user-favorite dishes not only relies on the user to manually obtain the recipe information, cooking methods and cooking methods of the favorite dishes, but also requires the user to manually convert the cooking control parameters, resulting in the entire dish making process being cumbersome and not very intelligent. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the related art. To this end, the present invention proposes a food preparation method, which realizes the purpose of strong association from food images to target cooking equipment to prepare target food, without relying on the user's manual participation in the entire food preparation process, thereby improving the intelligence and convenience of the food preparation process, and also greatly improving the user experience.

[0005] The invention also provides a food making device.

[0006] The invention also provides an electronic device.

[0007] The present invention also provides a non-transitory computer-readable storage medium.

[0008] The food preparation method according to the first embodiment of the present invention comprises:

[0009] Get food images;

[0010] Based on the types of ingredients in the food image, determining target recipe information, target cooking equipment information, and target cooking control parameters corresponding to the food image;

[0011] The target cooking control parameter is sent to the target cooking device corresponding to the target cooking device information, and the target cooking control parameter is used by the target cooking device to prepare the target food corresponding to the target recipe information.

[0012] According to the food preparation method of the embodiment of the present invention, the cloud server first automatically adapts the target recipe information, the target cooking device information and the target cooking control parameters for the food image, and then sends the target cooking control parameters to the target cooking device corresponding to the target cooking device information, and the target cooking control parameters are used for the target cooking device to prepare the target food corresponding to the target recipe information. In this way, the target cooking device, the target recipe information and the target cooking control parameters are specifically recommended through the food image, so as to achieve the purpose of strong association from the food image to the target cooking device to prepare the target food, without relying on the user's manual participation in the entire food preparation process, thereby improving the intelligence and convenience of the food preparation process, and also greatly improving the user experience.

[0013] According to an embodiment of the present invention, determining target recipe information, target cooking equipment information, and target cooking control parameters corresponding to the food image based on the type of ingredients in the food image includes:

[0014] Based on the types of ingredients in the food image, determining a recipe information list, a cooking equipment information list, and a cooking control parameter list that match the types of ingredients;

[0015] In response to user selection information for the recipe information list, determining the target recipe information from the recipe information list;

[0016] Determining the target cooking device information from the cooking device information list according to the networking status information and the operating status information of each cooking device in the cooking device information list;

[0017] The cooking control parameters in the cooking control parameter list that are used to prepare the target food based on the target cooking equipment information are determined as the target cooking control parameters.

[0018] According to an embodiment of the present invention, the step of determining a recipe information list, a cooking equipment information list, and a cooking control parameter list matching the ingredient type based on the ingredient type in the food image includes:

[0019] The recipe information list, the cooking equipment information list and the cooking control parameter list are determined based on the types of ingredients in the food image and the preset mapping relationship between the types of ingredients, recipe information, cooking equipment information and cooking control parameters.

[0020] According to an embodiment of the present invention, determining the target cooking device information in the cooking device information list according to the networking status information and the operating status information of each cooking device in the cooking device information list includes:

[0021] Based on a preset mapping relationship between device ID information, device networking status information, and device operation status information, selecting first cooking device information that is currently online and idle from the cooking device information list;

[0022] Based on the number of the first cooking equipment information, the target cooking equipment information is determined.

[0023] According to an embodiment of the present invention, determining the target cooking device information based on the quantity of the first cooking device information includes:

[0024] Based on a determination result that there are multiple pieces of the first cooking device information, sending the multiple pieces of the first cooking device information to a terminal device;

[0025] A selection result fed back by the terminal device is received, where the selection result is used to indicate the target cooking device information among the plurality of first cooking device information.

[0026] According to an embodiment of the present invention, the determining the target cooking device information based on the at least one first cooking device information further includes:

[0027] Based on a determination result that there are multiple pieces of the first cooking device information, priority-ranking the multiple first cooking devices according to the historical usage frequency of the first cooking device corresponding to each piece of the first cooking device information;

[0028] Based on the priority ranking result, the target cooking device information is determined from the plurality of first cooking device information.

[0029] According to one embodiment of the present invention, the method further includes:

[0030] Based on a preset food type recognition model, performing image recognition on the food image to determine the type of food in the food image;

[0031] Among them, the preset food type recognition model is a model determined after training an initial deep learning network model using a sample food image set.

[0032] A food preparation device according to a second aspect of the present invention comprises:

[0033] An image acquisition module, used for acquiring food images;

[0034] an information determination module, for determining target recipe information, target cooking equipment information and target cooking control parameters corresponding to the food image based on the types of ingredients in the food image;

[0035] The food preparation module is used to send the target cooking control parameters to the target cooking device corresponding to the target cooking device information, and the target cooking control parameters are used by the target cooking device to prepare the target food corresponding to the target recipe information.

[0036] According to the food preparation device of the embodiment of the present invention, for the food image, the target recipe information, the target cooking device information and the target cooking control parameters are first automatically adapted, and then the target cooking control parameters are sent to the target cooking device corresponding to the target cooking device information, and the target cooking control parameters are used for the target cooking device to prepare the target food corresponding to the target recipe information. In this way, the target cooking device, the target recipe information and the target cooking control parameters are specifically recommended through the food image, so as to achieve the purpose of strong association from the food image to the target cooking device to prepare the target food, without relying on the user's manual participation in the entire food preparation process, thereby improving the intelligence and convenience of the food preparation process, and also greatly improving the user experience.

[0037] The above one or more technical solutions in the embodiments of the present invention have at least one of the following technical effects: the cloud server first automatically adapts the target recipe information, the target cooking device information and the target cooking control parameters for the food image, and then sends the target cooking control parameters to the target cooking device corresponding to the target cooking device information, and the target cooking control parameters are used for the target cooking device to make the target food corresponding to the target recipe information. In this way, the target cooking device, the target recipe information and the target cooking control parameters are specifically recommended through the food image, so as to achieve the purpose of strong association from the food image to the target cooking device making the target food, without relying on the user's manual participation in the entire food production process, thereby improving the intelligence and convenience of the food production process, and also greatly improving the user experience.

[0038] Furthermore, the cloud server determines the types of ingredients in the food image by first determining the recipe information list, cooking equipment information list and cooking control parameter list that match the ingredient types, and then determines the target recipe information, target cooking equipment information and target cooking control parameters. This greatly improves the flexibility and specificity of determining the target recipe information, target cooking equipment information and target cooking control parameters, thereby also improving the intelligence and convenience of the food production process.

[0039] Furthermore, based on identifying the ingredient types in the food images, the cloud server can automatically adapt the recipe information list, cooking equipment information list and cooking control parameter list that match the food images. By establishing standards for different cooking equipment and different cooking control parameters required for making different foods with different kinds of ingredients, as well as standards for different cooking equipment and different cooking control parameters required for making different foods with the same kind of ingredients, the cloud server can not only automatically adapt to the cooking equipment and cooking control parameters required for making different foods with different kinds of ingredients, but also automatically adapt to the cooking equipment and cooking control parameters required for making different foods with the same kind of ingredients. This greatly improves the richness and completeness of the recipe information list, cooking equipment information list and cooking control parameter list, and provides reliable guarantee for the subsequent determination of target recipe information and target cooking equipment information.

[0040] Furthermore, the cloud server selects the first cooking device information that is currently online and idle from the cooking device information list through the mapping relationship between the preset device ID information-device networking status information-device operating status information, thereby achieving the purpose of determining the target cooking device information based on the first cooking device information, thereby improving the reliability and specificity of determining the target cooking device information.

[0041] Furthermore, the cloud server determines the target cooking equipment information from multiple first cooking equipment information by sending multiple first cooking equipment information to the terminal device and receiving feedback from the terminal device. This not only improves the interactivity between the cloud server and the terminal device, but also improves the high adaptability between the target cooking equipment and the user's current scene, thereby improving the intelligence and reliability of making the target food.

[0042] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 This is one of the flow charts of the food preparation method provided by the embodiment of the present invention;

[0045] Figure 2 is a schematic diagram of an application scenario of the food preparation method provided by an embodiment of the present invention;

[0046] Figure 3 This is the second flow chart of the food preparation method provided by the embodiment of the present invention;

[0047] Figure 4 is a schematic diagram of the structure of a food preparation device provided by an embodiment of the present invention;

[0048] Figure 5 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] Combine the following Figure 1-Figure 5 The food preparation method, device, electronic device and storage medium of the present invention are described, wherein the execution subject of the food preparation method can be a cloud server, and the cloud server has at least image recognition function, deep learning function, information sending function, information receiving function and information processing function. The following method embodiment is described by taking the execution subject as a supplementary food machine as an example.

[0051] Figure 1 A schematic diagram of the food preparation method provided by the present invention is shown in FIG. Figure 1 As shown, the food preparation method comprises the following steps:

[0052] Step 110: Acquire food images.

[0053] The food image may be image information for food, and the food may be any substance that can provide nutrients, energy and water required for human life, and may be raw foods such as meat, vegetables, cereals or fruits that have not been processed or treated, such as potatoes, celery, corn, oats, strawberries, apples, chicken wings, eggs or flour, etc.; or may be other edible items such as dishes, desserts, barbecue, bread or cakes that are made for specific human dietary habits and taste requirements, such as chopped pepper fish head, stir-fried pork, tiramisu, Napoleon cake, toast bread or cream bread, etc. No specific limitation is made here.

[0054] Specifically, the cloud server can obtain food images by sending food images through the terminal device. The terminal device here is installed with a target application for data exchange between the cloud server and the cooking device, and this target application can be opened immediately when receiving the start-up instruction of the terminal device corresponding to the user. At this time, the user can start the shooting operation for the food with the target application in the open state, and the target application sends the captured food image to the cloud server. Furthermore, the terminal device can be other electronic devices such as portable devices, laptops, smart phones, tablet computers and portable wearable devices. No specific limitation is made here.

[0055] Step 120: Based on the types of ingredients in the food image, determine the target recipe information, target cooking equipment information, and target cooking control parameters corresponding to the food image.

[0056] The target cooking device information is the device identification code (Identity document, ID) information of the target cooking device used to prepare the target food corresponding to the target recipe information. The target cooking device is an existing cooking device in the scene where the terminal device corresponds to the user; that is, the target cooking device information includes the device ID information of the target cooking device, and the device ID information is used to uniquely identify the manufacturer and type information of the corresponding cooking device. For example, the target cooking device information can determine that the corresponding cooking device is a microwave oven produced by Midea, or an oven produced by Midea. In addition, the target recipe information includes information such as the recipe name, cooking method, and precautions for preparing the corresponding target food.

[0057] Specifically, the cloud server may first perform image recognition on the food image to obtain food characteristic parameters including size information, shape information, color information, height information, and volume information, and determine the type of ingredients in the food image based on the mapping relationship between the pre-stored food characteristic parameters and food type information;

[0058] Furthermore, the cloud server searches for the food image currently acquired and the food image with the highest similarity in the mapping relationship information table based on a pre-stored mapping relationship information table between food images and ingredient types, and determines the ingredient type corresponding to the food image with the highest similarity as the ingredient type in the currently acquired food image; at this time, the cloud server can further determine the target recipe information corresponding to the food image based on the pre-stored mapping relationship between ingredient types and recipe information, and the target recipe information can be the recipe information with the highest similarity to the food image among multiple recipe information corresponding to the ingredient types.

[0059] Furthermore, the cloud server can also determine the cooking equipment information for the target food corresponding to the target recipe information, that is, determine the target cooking equipment information. For example, when the target food is "honey chicken wings" and the target recipe information contains the cooking equipment for making "honey chicken wings", the device ID information of the cooking equipment for making "honey chicken wings" can be determined as the target cooking equipment information.

[0060] Furthermore, when the cloud server determines the target recipe information and the target cooking equipment information, it can automatically select the cooking parameters for making the target food from the target recipe information, and then convert the selected cooking parameters to determine the target cooking control parameters for making the target food using the target cooking equipment information corresponding to the target cooking equipment.

[0061] It should be noted that there may be multiple food images mapped to each food type in the mapping relationship information between food images and food types, and the multiple food images may be food images under different shooting angles, different food colors, different food sizes, different food volumes and different food heights, so that the accurate food type can be determined for the currently acquired food image.

[0062] Step 130: Send the target cooking control parameters to the target cooking device corresponding to the target cooking device information. The target cooking control parameters are used by the target cooking device to prepare the target food corresponding to the target recipe information.

[0063] Specifically, the cloud server can be responsible for data routing between the terminal device and the cooking device. Based on this, when the cloud server determines the target cooking control parameters, it can send the target cooking control parameters to the terminal device and instruct the terminal device to send the target cooking control parameters to the target cooking device, so that when the corresponding user of the terminal device puts the prepared ingredients into the target cooking device, the target cooking device can prepare the target food according to the target cooking control parameters.

[0064] In the food preparation method provided by the present invention, the cloud server first automatically adapts the target recipe information, the target cooking device information and the target cooking control parameters for the food image, and then sends the target cooking control parameters to the target cooking device corresponding to the target cooking device information, and the target cooking control parameters are used for the target cooking device to prepare the target food corresponding to the target recipe information. In this way, the target cooking device, the target recipe information and the target cooking control parameters are specifically recommended through the food image, so as to achieve the purpose of strong association from the food image to the target cooking device to prepare the target food, without relying on the user to manually participate in the entire food preparation process, thereby improving the intelligence and convenience of the food preparation process, and also greatly improving the user experience.

[0065] It is understandable that the specific implementation process of step 120 may include:

[0066] First, based on the types of ingredients in the food image, a recipe information list, a cooking equipment information list and a cooking control parameter list that match the types of ingredients are determined; then, in response to the user's selection information for the recipe information list, target recipe information is determined from the recipe information list; further, based on the networking status information and operating status information of each cooking equipment in the cooking equipment information list, target cooking equipment information is determined from the cooking equipment information list; then, the cooking control parameters for making the target food based on the target cooking equipment information in the cooking control parameter list are determined as target cooking control parameters.

[0067] Each cooking device information includes the device ID information of the corresponding cooking device, and the device ID information is used to uniquely identify the manufacturer and type information of the corresponding cooking device. For example, the cooking device information can determine that the corresponding cooking device is a microwave oven produced by Midea, or an oven produced by Midea. In addition, each recipe information includes the recipe name, cooking method, precautions, and other information for making the corresponding food.

[0068] Specifically, the cloud server determines the recipe information for making each food using the ingredient type in the food image, thereby determining a recipe information list containing the recipe information. At the same time, the cloud server extracts the cooking equipment information used to make the corresponding food in each recipe information from the determined recipe information, thereby determining a cooking equipment information list containing the cooking equipment information. The cloud server can also first extract the cooking parameters for making the corresponding food using the corresponding cooking equipment in each recipe information from the determined recipe information, and then convert the extracted cooking parameters to determine the cooking control parameters including the number of cooking stages, firepower time, preheating and flipping reminders and other control parameters; thereby determining a cooking control parameter list containing the cooking control parameters.

[0069] Furthermore, the cloud server can send the recipe information list to the terminal device, so that the corresponding user of the terminal device can select the most favorite recipe information from the recipe information list by clicking, thereby responding to the user's selection purpose for the recipe information list. The recipe information contained in the selection information is the target recipe information. At this time, the terminal device feeds back the selection information to the cloud server; in this way, the cloud server determines the target recipe information from the recipe information list.

[0070] Furthermore, since the cloud server can be responsible for data routing between the terminal device and the cooking device, if the cloud server instructs the terminal device to send data to the cooking device, then the cooking device must be currently online and idle. Based on this, the cloud server can first obtain the networking status information and operation status information of each cooking device in the cooking device information list, and then determine whether each cooking device is currently online and currently idle, so as to determine the target cooking device information from the cooking device information list. For example, when the target food is "honey chicken wings", the cooking device information list may include the device ID information of the microwave oven, the device ID information of the oven, the device ID information of the automatic food processor, and the device ID information of the pressure cooker, etc. At this time, if the cloud server determines that the automatic food processor is currently online and idle, the device ID information of the automatic food processor is used as the target cooking device information.

[0071] Furthermore, since each cooking control parameter in the cooking control parameter list is used as a control parameter for the corresponding cooking equipment to make the corresponding food, when the cloud server determines the target recipe information and the target cooking equipment information, the cooking control parameter in the cooking control parameter list that is used to make the target food based on the target cooking equipment information can be automatically determined as the target cooking control parameter.

[0072] The food preparation method provided by the present invention, the cloud server determines the types of ingredients in the food image, by first determining the recipe information list, cooking equipment information list and cooking control parameter list that match the ingredient types, and then determines the target recipe information, target cooking equipment information and target cooking control parameters. This greatly improves the flexibility and specificity of determining the target recipe information, target cooking equipment information and target cooking control parameters, thereby also improving the intelligence and convenience of the food preparation process.

[0073] It is understandable that, based on the types of ingredients in the food image, determining the recipe information list, cooking equipment information list, and cooking control parameter list that match the types of ingredients, the specific implementation process may include:

[0074] Based on the types of ingredients in the food image and the preset mapping relationship between ingredient types-recipe information-cooking equipment information-cooking control parameters, a recipe information list, a cooking equipment information list and a cooking control parameter list are determined.

[0075] Specifically, the cloud server can call the pre-stored mapping relationship between ingredient type-recipe information-cooking equipment information-cooking control parameters for the ingredient type of the food image, and automatically determine the recipe information list, cooking equipment information list and cooking control parameter list that match the ingredient type.

[0076] It should be noted that the mapping relationship between ingredient type-recipe information-cooking equipment information-cooking control parameters can be pre-stored in the recipe information library of the cloud server; and the mapping relationship between ingredient type-recipe information-cooking equipment information-cooking control parameters can be the standards for different cooking equipment and different cooking control parameters required when making different foods with different kinds of ingredients, and can also be the standards for different cooking equipment and different cooking control parameters required when making different foods with the same kind of ingredient. It can not only characterize the cooking equipment and cooking control parameters required when making different foods with different kinds of ingredients, but also characterize the cooking equipment and cooking control parameters required when making different foods with the same kind of ingredients.

[0077] In the food preparation method provided by the present invention, the cloud server can automatically adapt the recipe information list, cooking equipment information list and cooking control parameter list that match the food image based on the ingredient type identified in the food image, thereby establishing standards for different cooking equipment and different cooking control parameters required when making different foods with different kinds of ingredients, as well as standards for different cooking equipment and different cooking control parameters required when making different foods with the same kind of ingredient, not only can the cooking equipment and cooking control parameters required when making different foods with different kinds of ingredients be automatically adapted, but also the cooking equipment and cooking control parameters required when making different foods with the same kind of ingredient can be automatically adapted, thereby greatly improving the richness and completeness of the recipe information list, cooking equipment information list and cooking control parameter list, and providing reliable guarantee for the subsequent determination of target recipe information and target cooking equipment information.

[0078] It is understandable that the specific implementation process of image recognition of food images may include:

[0079] Based on the preset food type recognition model, image recognition is performed on the food image to determine the target food type in the food image.

[0080] Among them, the preset food type recognition model is a model determined after training the initial deep learning network model using a sample food image set.

[0081] Specifically, in the sample food image set obtained by the cloud server, each sample food image carries size information, shape information, color information, height information and volume information; and each sample food image corresponds to a real food type. Based on this, the sample food image set is used to train the initial deep learning network model. The training here is to learn the relationship between the size information, shape information, color information, height information and volume information of the sample food image and the real food type corresponding to the sample food image; obtain the predicted food type output by the intermediate deep learning network model after a preset number of trainings, and then calculate the similarity between the predicted food type and the real food type of the corresponding sample food image. If the calculated similarity reaches the similarity threshold, the intermediate deep learning network model is determined to be a learned preset food type recognition model; conversely, if the calculated similarity does not reach the similarity threshold, the sample food image set is used to continue training the intermediate deep learning network model after the preset number of trainings. Until the preset food type recognition model is determined.

[0082] The food preparation method provided by the present invention improves the accuracy and reliability of determining the types of ingredients by using a preset food type recognition model determined by a cloud server training an initial deep learning network model through a sample food image set to perform image recognition on food images.

[0083] It can be understood that, according to the networking status information and the operation status information of each cooking device in the cooking device information list, the target cooking device information in the cooking device information list is determined, and the specific implementation process may include:

[0084] First, based on the preset mapping relationship between device ID information, device networking status information, and device operation status information, the first cooking device information that is currently online and idle is selected from the cooking device information list; then, based on the number of the first cooking device information, the target cooking device information is determined.

[0085] The device ID information is used to uniquely identify the manufacturer and type of the corresponding cooking device, the device networking status information includes whether the corresponding cooking device is currently offline or online, and the device operation status information includes whether the corresponding cooking device is currently in operation or idle state. In addition, the target cooking device information is the cooking device information of the existing cooking device in the scene where the terminal device corresponds to the user.

[0086] Specifically, the mapping relationship between device ID information, device networking status information, and device operation status information is pre-stored in the user information library of the cloud server. This mapping relationship between device ID information, device networking status information, and device operation status information can be updated in real time or periodically based on the device networking status information and / or device operation status information of each cooking device, so that the cloud server can select accurate first cooking device information from the cooking device information list, and thus can also determine the target cooking device information based on the number of first cooking device information. For example, when the cooking device information list determined by the cloud server includes the device ID information of a microwave oven, the device ID information of an oven, the device ID information of an automatic food processor, and the device ID information of a pressure cooker, if only the automatic food processor is currently online and idle at home, the device ID information of the automatic food processor can be determined as the target cooking device information.

[0087] In the food preparation method provided by the present invention, the cloud server selects the first cooking equipment information that is currently online and idle from the cooking equipment information list through the mapping relationship between the preset equipment ID information-equipment networking status information-equipment operation status information, thereby achieving the purpose of determining the target cooking equipment information based on the first cooking equipment information, thereby improving the reliability and pertinence of determining the target cooking equipment information.

[0088] It can be understood that, based on the quantity of the first cooking device information, the target cooking device information is determined, and its specific implementation process may include:

[0089] Based on the determination result that there are multiple first cooking device information, the multiple first cooking device information is sent to the terminal device, and a selection result fed back by the terminal device is received, where the selection result is used to indicate the target cooking device information among the multiple first cooking device information.

[0090] Specifically, when the cloud server selects multiple first cooking equipment information that is currently online and idle from the cooking equipment information list based on the mapping relationship between device ID information-device networking status information-device operating status information, the cloud server can send multiple first cooking equipment information to the terminal device, so that the corresponding user of the terminal device selects the target cooking equipment information from the multiple first cooking equipment information by clicking, and the terminal device will then feedback the selection result containing the target cooking equipment information to the cloud server; in this way, the cloud server determines the target cooking equipment information from the multiple first cooking equipment information.

[0091] In the food preparation method provided by the present invention, the cloud server determines the target cooking equipment information from the multiple first cooking equipment information by sending the multiple first cooking equipment information to the terminal device and receiving the feedback from the terminal device. This not only improves the interactivity between the cloud server and the terminal device, but also can improve the high adaptability between the target cooking equipment and the user's current scene, thereby improving the intelligence and reliability of preparing the target food.

[0092] It can be understood that, based on the quantity of the first cooking device information, the target cooking device information is determined, and its specific implementation process may also include:

[0093] First, based on the determination result that there are multiple first cooking equipment information, the multiple first cooking equipment are prioritized according to the historical usage frequency of the first cooking equipment corresponding to each first cooking equipment information; then, based on the priority sorting result, the target cooking equipment information is determined from the multiple first cooking equipment information.

[0094] The historical usage frequency may be the cumulative number of times used within a preset historical period, such as the cumulative number of times used within three months, or the cumulative number of times used within one month, which is not specifically limited here.

[0095] Specifically, when the cloud server selects multiple first cooking device information that is currently online and idle from the cooking device information list based on the mapping relationship between device ID information-device networking status information-device operation status information, the cloud server can obtain the historical usage frequency of each first cooking device information corresponding to the first cooking device, and prioritize the multiple first cooking devices according to each historical usage frequency, so as to determine the target cooking device information from the multiple first cooking device information based on the priority sorting result. For example, the multiple first cooking devices are specifically an oven, an automatic food processor, and a pressure cooker, and the historical usage frequency of the oven is 5 times, the historical usage frequency of the automatic food processor is 3 times, and the historical usage frequency of the pressure cooker is 1 time. The priority sorting result shows that the priority of the oven is higher than that of the automatic food processor, and the priority of the automatic food processor is higher than that of the pressure cooker. Then, it can be determined that the target cooking device information is the device ID information of the oven.

[0096] In the food preparation method provided by the present invention, the cloud server determines the target cooking equipment information from multiple first cooking equipment information by prioritizing the historical usage frequencies of multiple first cooking equipment corresponding to the multiple first cooking equipment information, thereby improving the flexibility and reliability of determining the target cooking equipment information.

[0097] Reference Figure 2 , which is a schematic diagram of an application scenario of the food preparation method provided by the present invention, such as Figure 3As shown, the target application in the mobile phone contains an image shooting unit, the cloud server contains a recipe information library and a deep learning unit, the deep learning unit contains an image recognition algorithm or a trained preset food type recognition model, and the terminal device corresponds to each cooking device in the scene where the user is located. Wi-Fi or other wireless image functions, each cooking device can be Figure 2 The cooking device 1, cooking device 2, ..., cooking device N in the cooking device 1, cooking device 2, ..., cooking device N can all be connected to the cloud server and can remotely transmit data between the cloud server.

[0098] based on Figure 2 The present invention also provides a food preparation method, such as Figure 3 As shown, the food preparation method comprises the following steps:

[0099] Step 310: After the user opens the target application in the smartphone, he or she takes a photo of the food or food, and sends the food image to the cloud server;

[0100] Step 320: The cloud server performs image recognition on the received food image, and matches the type of ingredients determined by the image recognition with the recipe information library to determine a recipe information list, a cooking equipment information list, and a cooking control parameter list that match the food image;

[0101] Step 330: The cloud server sends the recipe information list to the terminal device, and receives target recipe information in the recipe information list fed back by the terminal device;

[0102] Step 340: The cloud server matches the cooking device information list with the user information database to determine at least one first cooking device information that is currently online and idle;

[0103] Step 350: The cloud server sends at least one first cooking device information to the terminal device, and receives target cooking device information in the at least one first cooking device information fed back by the terminal device;

[0104] Step 360: The cloud server determines, from the cooking control parameter list, target cooking control parameters for making target food corresponding to target recipe information based on target cooking equipment information, and synchronizes the target cooking control parameters to the mobile phone;

[0105] Step 370: The mobile phone synchronizes the received target cooking control parameters to the target cooking device corresponding to the target cooking device information;

[0106] Step 380: When the user puts the ingredients prepared for the target food into the target cooking device, the automatic cooking process can be started with one button.

[0107] The specific processes involved in steps 310 to 380 may refer to the above-mentioned embodiments, and will not be described in detail here.

[0108] Exemplarily, the user opens the target application in the smartphone and takes a photo of the food, such as chicken wings. The target application in the smartphone uploads the chicken wing image information to the cloud server, and the cloud server recognizes that the food type is chicken wings through the deep learning unit. At this time, the cloud server matches the chicken wing recognition result with the recipe information library and outputs a recipe information list. For example, the recipe information of "honey chicken wings", the recipe information of "Orleans chicken wings", the recipe information of "cola chicken wings", and the recipe information of "grilled chicken wings", etc., and transmits the recipe information list to the target application in the smartphone for presentation.

[0109] At this time, on the target application side of the smartphone, the user selects the target recipe information he likes, such as the recipe information of "honey chicken wings", and the target application in the smartphone will present a list of cooking equipment information that can cook this recipe information. For example: the device ID information of the microwave oven, the device ID information of the oven, the device ID information of the automatic food processor, and the device ID information of the pressure cooker, etc. The user information library is also used to highlight the target cooking equipment that the user already has at home. For example, if the user has an automatic food processor at home, the target application in the smartphone will highlight the device ID information of the target cooking equipment, the automatic food processor. After the user selects the device ID information of the automatic food processor, the target application in the mobile phone transmits the target cooking control parameters for cooking honey chicken wings to the automatic food processor through a wireless connection. Parameter examples: cooking stages, firepower time, preheating, flip reminder and other parameters. When the user puts the prepared chicken wings into the automatic food processor, the cooking can be started with one click, and the cooking is performed according to the established program of the target cooking control parameters.

[0110] The food preparation device provided by the present invention is described below. The food preparation device described below and the food preparation method described above can be referred to each other.

[0111] Reference Figure 4 , is a schematic diagram of the structure of the food preparation device provided by the present invention, such as Figure 4 As shown, the food preparation device 400 comprises:

[0112] An image acquisition module 410 is used to acquire food images;

[0113] An information determination module 420, for determining target recipe information, target cooking equipment information and target cooking control parameters corresponding to the food image based on the types of ingredients in the food image;

[0114] The food preparation module 450 is used to send the target cooking control parameters to the target cooking device corresponding to the target cooking device information, and the target cooking control parameters are used for the target cooking device to prepare the target food corresponding to the target recipe information.

[0115] It can be understood that the information determination module 420 can be specifically used to determine a recipe information list, a cooking equipment information list and a cooking control parameter list that match the ingredient types in the food image; determine target recipe information from the recipe information list in response to user selection information for the recipe information list; determine target cooking equipment information from the cooking equipment information list based on the networking status information and operating status information of each cooking equipment in the cooking equipment information list; and determine the cooking control parameters for preparing the target food based on the target cooking equipment information in the cooking control parameter list as target cooking control parameters.

[0116] It can be understood that the information determination module 420 can also be used to determine the recipe information list, cooking equipment information list and cooking control parameter list based on the ingredient types in the food image and the preset mapping relationship between ingredient types-recipe information-cooking equipment information-cooking control parameters.

[0117] It can be understood that the information determination module 420 can also be used to select the first cooking device information that is currently online and idle from the cooking device information list based on the mapping relationship between the preset device ID information-device networking status information-device operation status information; and determine the target cooking device information based on the number of the first cooking device information.

[0118] It can be understood that the information determination module 420 can also be used to send multiple first cooking equipment information to the terminal device based on the determination result that there are multiple first cooking equipment information; receive the selection result fed back by the terminal device, and the selection result is used to indicate the target cooking equipment information among the multiple first cooking equipment information.

[0119] It can be understood that the information determination module 420 can also be used to prioritize the multiple first cooking equipment based on the determination result that there are multiple first cooking equipment information according to the historical usage frequency of the first cooking equipment corresponding to each first cooking equipment information; and determine the target cooking equipment information from the multiple first cooking equipment information based on the priority sorting result.

[0120] It can be understood that the information determination module 420 can also be used to perform image recognition on food images based on a preset ingredient type recognition model to determine the ingredient types in the food images; wherein the preset ingredient type recognition model is a model determined after training the initial deep learning network model using a sample food image set.

[0121] Figure 5 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 5 As shown, the electronic device 500 may include: a processor 510, a communication interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communication interface 520 and the memory 530 communicate with each other through the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute the following method:

[0122] Get food images;

[0123] Based on the types of ingredients in the food image, determining target recipe information, target cooking equipment information, and target cooking control parameters corresponding to the food image;

[0124] The target cooking control parameters are sent to the target cooking device corresponding to the target cooking device information, and the target cooking control parameters are used by the target cooking device to prepare the target food corresponding to the target recipe information.

[0125] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the relevant technology or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0126] On the other hand, an embodiment of the present invention discloses a computer program product, wherein the computer program product includes a computer program stored on a non-transitory computer-readable storage medium, wherein the computer program includes program instructions. When the program instructions are executed by a computer, the computer can perform the methods provided by the above-mentioned method embodiments, for example, including:

[0127] Get food images;

[0128] Based on the types of ingredients in the food image, determining target recipe information, target cooking equipment information, and target cooking control parameters corresponding to the food image;

[0129] The target cooking control parameters are sent to the target cooking device corresponding to the target cooking device information, and the target cooking control parameters are used by the target cooking device to prepare the target food corresponding to the target recipe information.

[0130] In another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to perform the transmission method provided in the above embodiments, for example, including:

[0131] Get food images;

[0132] Based on the types of ingredients in the food image, determining target recipe information, target cooking equipment information, and target cooking control parameters corresponding to the food image;

[0133] The target cooking control parameters are sent to the target cooking device corresponding to the target cooking device information, and the target cooking control parameters are used by the target cooking device to prepare the target food corresponding to the target recipe information.

[0134] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0135] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, by hardware. Based on this understanding, the above technical solution can be essentially or in other words, the part that contributes to the relevant technology can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiment.

[0136] Finally, it should be noted that the above embodiments are only used to illustrate the present invention, rather than to limit the present invention. Although the present invention is described in detail with reference to the embodiments, it should be understood by those skilled in the art that various combinations, modifications or equivalent substitutions of the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and should be included in the scope of the claims of the present invention.

Claims

1. A food preparation method, characterized in that: include: Get food images; Based on the types of ingredients in the food image, determining target recipe information, target cooking equipment information, and target cooking control parameters corresponding to the food image; The target cooking control parameter is sent to the target cooking device corresponding to the target cooking device information, and the target cooking control parameter is used by the target cooking device to prepare the target food corresponding to the target recipe information.

2. The food preparation method according to claim 1, characterized in that: The determining, based on the types of ingredients in the food image, target recipe information, target cooking equipment information, and target cooking control parameters corresponding to the food image includes: Based on the types of ingredients in the food image, determining a recipe information list, a cooking equipment information list, and a cooking control parameter list that match the types of ingredients; In response to user selection information for the recipe information list, determining the target recipe information from the recipe information list; Determining the target cooking device information from the cooking device information list according to the networking status information and the operating status information of each cooking device in the cooking device information list; The cooking control parameters in the cooking control parameter list that are used to prepare the target food based on the target cooking equipment information are determined as the target cooking control parameters.

3. The food preparation method according to claim 2, characterized in that: The step of determining, based on the types of ingredients in the food image, a recipe information list, a cooking equipment information list, and a cooking control parameter list that match the types of ingredients includes: The recipe information list, the cooking equipment information list and the cooking control parameter list are determined based on the types of ingredients in the food image and the preset mapping relationship between the types of ingredients, recipe information, cooking equipment information and cooking control parameters.

4. The food preparation method according to claim 2, characterized in that: Determining target cooking device information in the cooking device information list according to the networking status information and the operating status information of each cooking device in the cooking device information list includes: Based on a preset mapping relationship between device ID information, device networking status information, and device operation status information, selecting first cooking device information that is currently online and idle from the cooking device information list; Based on the number of the first cooking equipment information, the target cooking equipment information is determined.

5. The food preparation method according to claim 4, characterized in that: The determining the target cooking device information based on the quantity of the first cooking device information includes: Based on a determination result that there are multiple pieces of the first cooking device information, sending the multiple pieces of the first cooking device information to a terminal device; A selection result fed back by the terminal device is received, where the selection result is used to indicate the target cooking device information among the plurality of first cooking device information.

6. The food preparation method according to claim 4, characterized in that: The determining the target cooking device information based on the at least one first cooking device information further includes: Based on a determination result that there are multiple pieces of the first cooking device information, priority-ranking the multiple first cooking devices according to the historical usage frequency of the first cooking device corresponding to each piece of the first cooking device information; Based on the priority ranking result, the target cooking device information is determined from the plurality of first cooking device information.

7. The food preparation method according to any one of claims 1 to 6, characterized in that: The method further comprises: Based on a preset food type recognition model, performing image recognition on the food image to determine the type of food in the food image; Among them, the preset food type recognition model is a model determined after training an initial deep learning network model using a sample food image set.

8. A food preparation device, characterized in that: include: An image acquisition module, used for acquiring food images; an information determination module, for determining target recipe information, target cooking equipment information and target cooking control parameters corresponding to the food image based on the types of ingredients in the food image; The food preparation module is used to send the target cooking control parameters to the target cooking device corresponding to the target cooking device information, and the target cooking control parameters are used by the target cooking device to prepare the target food corresponding to the target recipe information.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the food preparation method according to any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the food preparation method according to any one of claims 1 to 7 is implemented.

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