Data processing method, device, electronic device and storage medium

Abstract

The embodiments of the present application provide a data processing method, device, electronic device and storage medium. The method includes: receiving physiological data of a virtual pet from a first user device, wherein the first user device is a device of a user of the virtual pet; sending physiological data to a second user device; receiving a diagnosis and treatment plan for the virtual pet from the second user device, wherein the diagnosis and treatment plan is a diagnosis and treatment plan made by a virtual pet physician for the virtual pet based on the physiological data; sending the diagnosis and treatment plan to the first user device so that the user can treat the virtual pet based on the diagnosis and treatment plan; receiving recovery data of the virtual pet from the first user device; and assessing the virtual pet physician based on the diagnosis and treatment plan, recovery data and professional information of the virtual pet physician to obtain a target assessment result of the virtual pet physician. The embodiments of the present application fill the technical gap in assessing virtual pet physicians.

Description

Technical Field

[0001] The present application relates to the field of electronic technology, and in particular to a data processing method, device, electronic device and storage medium. Background Art

[0002] At present, with the booming pet market, many people want to keep pets, but there are some other problems in pet keeping, such as being busy at work; or the life span of pets is relatively short; or the place where they live is not allowed to keep pets. For various reasons, many people who want to keep pets cannot keep pets as they wish. In recent years, virtual pets have appeared. Virtual pets have the following characteristics: long life; can be kept anytime and anywhere, no special feeding and care are required; not restricted by the living environment, users only need to install the corresponding application and complete the raising of virtual pets through network operations. Therefore, virtual pets have gradually become active in people's lives, and with the advancement of technology, the difference between virtual pets and physical pets is getting smaller and smaller, which also causes virtual pets to have the same birth, aging, illness and death as physical pets. Therefore, virtual pet doctors have also come into being. Virtual pet doctors are pet doctors who diagnose diseases for virtual pets. However, since virtual pets themselves are an emerging industry, the evaluation of the diagnosis of virtual pet doctors to improve the diagnosis quality of virtual pet doctors is still in a blank stage. Summary of the invention

[0003] The embodiments of the present application provide a data processing method, device, electronic device and storage medium, which evaluate the diagnosis process of the virtual pet doctor through the virtual pet doctor's treatment plan and the recovery data of the virtual pet, filling the gap in the prior art.

[0004] In a first aspect, an embodiment of the present application provides a data processing method comprising:

[0005] receiving physiological data of a virtual pet from a first user device, wherein the first user device is a device of a user of the virtual pet;

[0006] Sending the physiological data to a second user device so as to diagnose a disease of the virtual pet, wherein the second user device is a device of a virtual pet physician;

[0007] receiving a diagnosis and treatment plan for the virtual pet from the second user device, wherein the diagnosis and treatment plan is a diagnosis and treatment plan made by the virtual pet physician for the virtual pet based on the physiological data;

[0008] Sending the diagnosis and treatment plan to the first user device so that the user can treat the virtual pet based on the diagnosis and treatment plan;

[0009] receiving restoration data of the virtual pet from the first user device;

[0010] The virtual pet physician is assessed according to the diagnosis and treatment plan, the recovery data and the professional information of the virtual pet physician to obtain a target assessment result of the virtual pet physician.

[0011] In a second aspect, an embodiment of the present application provides a data processing device, including: a receiving unit, a processing unit, and a sending unit;

[0012] The receiving unit is used to obtain physiological data of the virtual pet from a first user device, wherein the first user device is a device of a user of the virtual pet;

[0013] The sending unit is used to send the physiological data to a second user device so as to diagnose a disease of the virtual pet, wherein the second user device is a device of a virtual pet doctor;

[0014] The receiving unit is further configured to receive a diagnosis and treatment plan for the virtual pet from the second user device, wherein the diagnosis and treatment plan is a diagnosis and treatment plan made by the virtual pet physician for the virtual pet based on the physiological data;

[0015] The sending unit is further used to send the diagnosis and treatment plan to the first user device so that the user can treat the virtual pet based on the diagnosis and treatment plan;

[0016] The receiving unit is further configured to receive the recovery data of the virtual pet from the first user device;

[0017] The processing unit is used to evaluate the virtual pet physician according to the diagnosis and treatment plan, the recovery data and the professional information of the virtual pet physician to obtain a target evaluation result of the virtual pet physician.

[0018] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, the processor is connected to a memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device performs the method described in the first aspect.

[0019] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program enables a computer to execute the method described in the first aspect.

[0020] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer is operable to cause the computer to execute the method described in the first aspect.

[0021] Implementing the embodiments of the present application has the following beneficial effects:

[0022] It can be seen that in the embodiment of the present application, the data processing device acts as an intermediate device. When the user needs to diagnose the virtual pet, the data processing device forwards the physiological data of the virtual pet to the second user device, and forwards the diagnosis and treatment plan of the virtual pet doctor to the first user device; then, the recovery data of the virtual pet after the diagnosis and treatment based on the diagnosis and treatment plan is obtained. Finally, the virtual pet doctor is evaluated based on the diagnosis and treatment plan, the recovery data and the professional information of the virtual pet doctor, and the evaluation result of the virtual pet doctor is obtained, thereby realizing the evaluation of the diagnosis process of the virtual pet doctor, filling the gap in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0024] Figure 1 A schematic diagram of a data processing system provided in an embodiment of the present application;

[0025] Figure 2 A flowchart of a data processing method provided in an embodiment of the present application;

[0026] Figure 3 A schematic diagram of sending physiological data of a virtual pet provided in an embodiment of the present application;

[0027] Figure 4 A schematic diagram of determining a target score for each virtual pet physician provided in an embodiment of the present application;

[0028] Figure 5 A schematic diagram of generating a virtual pet provided in an embodiment of the present application;

[0029] Figure 6 A schematic diagram of target detection provided in an embodiment of the present application;

[0030] Figure 7 A schematic diagram of generating a target virtual environment provided in an embodiment of the present application;

[0031] Figure 8A block diagram of the functional units of a data processing device provided in an embodiment of the present application;

[0032] Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0034] The terms "first", "second", "third" and "fourth" etc. in the specification and claims of the present application and the drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0035] Reference to "embodiments" herein means that a particular feature, result, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0036] See also Figure 1 , Figure 1 A data processing system is provided for an embodiment of the present application. The data processing system includes a first user device 10, a data processing apparatus 20, and a second user device 30. The first user device 10 is a device of a user of a virtual pet, the second user device 30 is a device of a virtual pet physician, the data processing apparatus 20 is used to manage the generation of the user's virtual pet, the cancellation of the virtual pet, and the recycling of the virtual pet, that is, to maintain the entire life cycle of the virtual pet, and the data processing apparatus 20 maintains a front-end application, so that the user can generate a virtual pet, diagnose a virtual pet, dress up a virtual pet, interact with a virtual pet, cancel the virtual pet, and so on through the front-end application. This application focuses on describing the diagnosis process of the virtual pet, and other life processes are not described in detail.

[0037] Exemplarily, the first user device 10 sends the physiological data of the virtual pet to the data processing device 20; the data processing device 20 sends the physiological data to the second user device 30 so that the virtual pet physician diagnoses the virtual pet based on the physiological data; the second user device 30 sends a diagnosis and treatment plan to the data processing device 20, wherein the diagnosis and treatment plan is a diagnosis and treatment plan made by the virtual pet physician for the virtual pet based on the physiological data; the first user device 10 sends the recovery data of the virtual pet to the data processing device 20; finally, the data processing device 20 assesses the virtual pet physician based on the diagnosis and treatment plan, the recovery data and the professional information of the virtual pet physician, and obtains the target assessment result of the virtual pet physician.

[0038] It can be seen that in the embodiment of the present application, the data processing device acts as an intermediate device. When the user needs to diagnose the virtual pet, the data processing device forwards the physiological data of the virtual pet to the second user device, and forwards the diagnosis and treatment plan of the virtual pet doctor to the first user device; then, the recovery data of the virtual pet after the diagnosis and treatment based on the diagnosis and treatment plan is obtained. Finally, the virtual pet doctor is evaluated based on the diagnosis and treatment plan, the recovery data and the professional information of the virtual pet doctor, and the evaluation result of the virtual pet doctor is obtained, thereby realizing the evaluation of the diagnosis process of the virtual pet doctor, filling the gap in the prior art.

[0039] See also Figure 2 , Figure 2 A data processing method is provided in an embodiment of the present application. The data processing method is applied to the above-mentioned data processing system. The method includes but is not limited to the following steps:

[0040] 201: The first user equipment sends physiological data of the virtual pet to the data processing device.

[0041] Exemplarily, a front-end application maintained by a data processing device is installed on the first user device. Accordingly, the user first completes registration on the front-end application to become a registered user of the data processing device, and during the registration process, the user grants the data processing device the right to access the user's operating behavior, geographic location, and other access rights. Further, if Figure 3 As shown, the front-end application has a virtual pet diagnosis function button, so when the above user needs to diagnose the virtual pet, he can do so by clicking the function button. Figure 3 As shown, when the function button is clicked, an information input page will be displayed on the interface of the first user device, and the information input page includes multiple information input fields. The user can enter the physiological data of the virtual pet in the multiple information input fields, and when "Confirm" is clicked, the physiological data of the virtual pet will be sent to the data processing device.

[0042] Exemplarily, the physiological data of the virtual pet includes, but is not limited to, the attribute parameters and user parameters of the virtual pet, wherein the attribute parameters include the height, weight, growth cycle, etc. of the virtual pet. The user parameters include the companionship time, number of interactions, number of equipment upgrades, number of appearance image adjustments, number of care, etc. of the virtual pet within a preset time period.

[0043] 202: The data processing device sends physiological data to the second user equipment.

[0044] The data processing device forwards the physiological data to the second user device so that the user of the second user device (ie, the virtual pet doctor) can diagnose the disease of the virtual pet.

[0045] 203: The second user equipment sends a diagnosis and treatment plan for the virtual pet to the data processing device.

[0046] Among them, the diagnosis and treatment plan is the diagnosis and treatment plan made by the virtual pet doctor for the virtual pet based on physiological data.

[0047] Similarly, the above-mentioned application is installed on the second user device, and the virtual pet doctor can register and log in as a doctor. The virtual pet doctor can then receive the physiological data forwarded by the data processing device through the second user device, and can input the diagnosis and treatment plan for the above-mentioned virtual pet through the second user device, and send the diagnosis and treatment plan to the data processing device.

[0048] 204: The data processing device sends the diagnosis and treatment plan to the first user device so that the user can treat the virtual pet based on the diagnosis and treatment plan.

[0049] Exemplarily, after receiving the diagnosis and treatment plan sent by the second user device, the data processing device will forward the diagnosis and treatment plan to the first user device so that the first user device can treat the virtual pet based on the diagnosis and treatment plan.

[0050] 205: The first user equipment sends the recovery data of the virtual pet to the data processing device.

[0051] Exemplarily, when the data processing device detects that the user uses the diagnosis and treatment plan to treat the virtual pet, it will send an instruction message to the first user device, instructing the first user device to report the recovery data of the virtual pet. Correspondingly, after receiving the instruction message, the first user device will display the prompt message on the visual interface, and the user can input the recovery data of the virtual pet through the visual interface.

[0052] 206: The data processing device evaluates the virtual pet physician according to the diagnosis and treatment plan, the recovery data, and the professional information of the virtual pet physician, and obtains a target evaluation result of the virtual pet physician.

[0053] For example, according to the diagnosis and treatment plan, a first assessment result in the resource consumption dimension is obtained; according to the recovery data, the degree of cure of the virtual pet is determined; according to the professional information of the virtual pet doctor, the authority of the virtual pet doctor is determined; according to the first assessment result, the degree of cure and the authority, the target assessment result of the virtual pet doctor is determined. For example, the first assessment result, the degree of cure and the authority can be multiplied to obtain the target assessment result of the virtual pet doctor.

[0054] Specifically, the name of the disease suffered by the virtual pet is determined according to the diagnosis and treatment plan. Exemplarily, when the virtual pet doctor inputs the diagnosis and treatment plan, he needs to input the name of the disease suffered by the virtual pet. Therefore, the data processing device can perform keyword recognition on the above-mentioned diagnosis and treatment plan, and extract the name of the disease suffered by the virtual pet from the diagnosis and treatment plan, wherein the disease names of the virtual pet include: depression, hunger, lack of interaction, etc. Then, according to the above-mentioned disease name, the average resource consumption of the disease name is determined. Exemplarily, the data processing device counts the historical diagnosis records to obtain the resource consumption when any registered user treats a virtual pet suffering from the disease name, and averages the resource consumption of all registered users to obtain the average resource consumption corresponding to the above-mentioned disease name.

[0055] It should be noted that the resource consumption of this application includes time consumption and cost consumption, wherein time consumption mainly refers to the operation time of the user in the process of treating the virtual pet; cost consumption refers to the cost investment (for example, money investment) of the user in the process of treating the virtual pet. Therefore, the above average resource consumption includes the average operation time and the average cost investment.

[0056] Furthermore, according to the diagnosis and treatment plan, the resource consumption of the virtual pet is determined. It should be understood that the resource consumption of the virtual pet includes the target operation time and the target cost investment.

[0057] Exemplarily, the above-mentioned diagnosis and treatment scheme includes multiple diagnosis and treatment projects. For example, the multiple diagnosis and treatment projects include companionship, interaction, equipment upgrade, appearance change, beauty care, and feeding, etc.; for each diagnosis and treatment project, multiple operation processes required by the user of each diagnosis and treatment project are obtained. For example, for the diagnosis and treatment project of feeding, the multiple operation processes of the diagnosis and treatment project include food acquisition, food matching, food production, and food feeding, etc. Then, for each operation process under each diagnosis and treatment project, according to the user's operation habits, the user's operation time in each operation process is determined, wherein the operation habit is the user's proficiency in mastering the growth process of the virtual pet, and the proficiency can be characterized by the number of times the user browses the virtual pet. Then, according to the mapping relationship between the proficiency, the operation process, and the operation time, the user's operation time in each operation process is determined. Further, the user's operation time in each operation process is summed to obtain the user's operation time in each diagnosis and treatment project. Finally, according to the weight of each diagnosis and treatment project, the operation time of multiple diagnosis and treatment projects is weighted to obtain the target operation time. Among them, the weight of each diagnosis and treatment item is pre-set.

[0058] Exemplarily, the cost investment that the user needs to make for each diagnosis and treatment item is obtained. Similarly, for each operation process of each diagnosis and treatment item, the cost investment of the user for each operation process is obtained. For example, the element that the user needs to purchase for each operation process is obtained, and the amount required for the element is used as the cost investment of the user for the operation process. Then, the cost investment of multiple diagnosis and treatment items on each operation item is summed up to obtain the cost investment of the user for each diagnosis and treatment item. Finally, the cost investment of multiple diagnosis and treatment items is summed up to obtain the target cost investment.

[0059] Further, the first assessment result of the virtual pet doctor is determined based on the average resource consumption and the resource consumption of the virtual pet. Exemplarily, the second assessment result is determined based on the average operation time and the target operation time; the third assessment result is determined based on the average cost input and the target cost input; the first assessment result is determined based on the second assessment result and the third assessment result.

[0060] Exemplarily, the second assessment result can be expressed by formula (1):

[0061]

[0062] Among them, achievement2 is the second assessment result, t target is the target operation duration, t average is the average operation time.

[0063] Exemplarily, the third assessment result can be expressed by formula (2):

[0064]

[0065] Among them, achievement3 is the third assessment result, c average is the average input cost, c target Invest costs into your goals.

[0066] Exemplarily, the first assessment result can be expressed by formula (3):

[0067] achievement1=achievement3*achievement2 formula (3);

[0068] Among them, achievement1 is the first assessment result.

[0069] Furthermore, the recovery data of the virtual pet includes the current physiological state of the virtual pet, wherein the current physiological state includes the height, weight, appearance, mood, and other physiological parameters of the virtual pet. The growth time of the virtual pet from the time of receiving the recovery data is obtained; the current growth state of the virtual pet is predicted according to the growth time and the growth rule of the virtual pet. The degree of recovery of the virtual pet is determined according to the current growth state and the current physiological state, that is, the values ​​of each physiological parameter in the current growth state and the current physiological state are compared, and the normal physiological parameters among the physiological parameters are determined, wherein the normal physiological parameter is the difference between the current growth state and the current physiological state of the physiological parameter is less than the threshold value corresponding to the physiological parameter; then, the ratio of the normal physiological parameter to the total number of physiological parameters is counted, and the ratio is used as the degree of recovery of the virtual pet.

[0070] Furthermore, the professional information of the virtual pet doctor includes the school where the virtual pet doctor graduated, years of work experience, honors received, etc. Therefore, the authority of the virtual pet doctor can be determined based on the correspondence between the professional information of the virtual pet doctor and the authority, wherein the authority is used to characterize the credibility of the diagnosis and treatment plan given by the virtual pet doctor.

[0071] It can be seen that in the embodiment of the present application, the data processing device acts as an intermediate device. When the user needs to diagnose the virtual pet, the data processing device forwards the physiological data of the virtual pet to the second user device, and forwards the diagnosis and treatment plan of the virtual pet doctor to the first user device; then, the recovery data of the virtual pet after the diagnosis and treatment based on the diagnosis and treatment plan is obtained. Finally, the virtual pet doctor is evaluated based on the diagnosis and treatment plan, the recovery data and the professional information of the virtual pet doctor, and the evaluation result of the virtual pet doctor is obtained, thereby realizing the evaluation of the diagnosis process of the virtual pet doctor, filling the gap in the prior art.

[0072] In one embodiment of the present application, after determining the target assessment result of the veterinarian, multiple target assessment results of the virtual veterinarian within a preset time can be obtained; based on the multiple target assessment results, the display strategy of the virtual veterinarian is determined. Exemplarily, based on the multiple target assessment results, the compliance rate of the virtual veterinarian is determined, wherein the compliance rate is the ratio between the number of target assessment results greater than a threshold value in the multiple target assessment results and the number of multiple target assessment results. Based on the compliance rate of the virtual veterinarian, the display strategy of the virtual veterinarian is determined, wherein the display strategy includes top display, bottom display or center display, etc. Finally, according to the above-mentioned display strategy of the virtual veterinarian, the personal information of the virtual veterinarian is displayed on the front-end web page. For example, when the display strategy is top display, the personal information of the virtual veterinarian is displayed at the top of the veterinarian display page.

[0073] It can be seen that in the implementation mode of the present application, after the assessment results of the virtual pet physician are determined, the personal information of the virtual pet can also be personalized based on the assessment results of the virtual pet physician, which can motivate the virtual pet to strive to improve the quality of diagnosis, thereby improving the diagnosis quality of the virtual pet.

[0074] In one embodiment of the present application, a plurality of first indicators, a plurality of second indicators and a third indicator are first set, wherein the plurality of first indicators are composed of the occupation information of the virtual pet doctor and the diagnosis information of the virtual pet doctor. Figure 4 As shown, multiple first indicators include: the working years of the virtual pet doctor, the graduating school, the highest honors received, the number of visits, the duration of the visit, the number of times the diagnosis and treatment plan is adopted, and the score of the diagnosis and treatment plan. Among them, multiple second indicators include but are not limited to: professional credibility and treatment credibility, and the third indicator is the target score. It should be explained that the reason for setting the above two second indicators is that for the virtual pet doctor, its credibility can be comprehensively determined by its personal education and work, as well as the actual treatment situation. For example, in general, the better the professional credibility, that is, the better the graduating school, the higher the years of work, the higher the credibility of the given diagnosis and treatment plan, and the target score of such a virtual pet will be relatively higher. Similarly, the better the actual treatment situation, the higher the corresponding target score should be. Therefore, the above two second indicators are set to comprehensively score each virtual pet doctor, so that the score of each virtual pet doctor is relatively accurate.

[0075] Furthermore, if Figure 4As shown, multiple first indicators are used as multiple indicators in the solution layer, multiple second indicators are used as multiple indicators in the criterion layer, and the third indicator is used as an indicator in the target layer. Therefore, according to the hierarchical analysis method, multiple first weights of multiple first indicators in the solution layer relative to each second indicator in the criterion layer are determined, wherein multiple first indicators correspond to multiple first weights one by one. For example, multiple first weights of working years, graduation school, highest honors received, number of visits, duration of visits, number of times the diagnosis and treatment plan is adopted, and the score of the diagnosis and treatment plan relative to the professional credibility can be determined.

[0076] Specifically, for each second indicator, the first importance of the influence of any two first indicators in the plurality of first indicators on each second indicator is obtained. According to the first importance of the influence of any two first indicators on each second indicator, a pairwise comparison matrix corresponding to each second indicator is constructed.

[0077] Optionally, the first importance of any two first indicators on the second indicator is preset. For example, it is preset that compared with the first importance of working years and the graduate school on the occupational credibility, working years is slightly more important than the graduate school. Therefore, the ratio of working years to the graduate school in the pairwise comparison matrix is ​​3.

[0078] Furthermore, the first maximum eigenvalue of the pairwise comparison matrix corresponding to each second indicator is obtained; the first eigenvector corresponding to the first maximum eigenvalue is obtained, and each value in the first eigenvector is used as a plurality of first weights of the plurality of first indicators relative to each second indicator.

[0079] Furthermore, similar to the above-mentioned method of constructing a pairwise comparison matrix corresponding to each second indicator, a pairwise comparison matrix corresponding to the third indicator is constructed based on multiple second indicators. Then, according to the pairwise comparison matrix corresponding to the third indicator, the second weights corresponding to the multiple second indicators relative to the third indicator are determined. Similarly, the second maximum eigenvalue of the pairwise comparison matrix corresponding to the third indicator can be obtained; the second eigenvector corresponding to the second maximum eigenvalue is obtained, and each value in the second eigenvector is used as a plurality of second weights of the multiple second indicators relative to the third indicator.

[0080] Further, according to the medical information of each virtual doctor in the preset time period and the professional information of each virtual pet doctor, the value of each virtual pet doctor under multiple first indicators is determined. Among them, the medical information of each virtual doctor in the preset time period includes the number of visits of the virtual pet doctor in the preset time period, the duration of each visit, the number of times the diagnosis and treatment plan for each pet doctor is adopted in the preset time period, and the score of the diagnosis and treatment plan. It should be noted that based on the professional information of the virtual pet doctor, the values ​​of the first indicators such as working years, graduation school, and highest honors received by the virtual pet doctor can be determined; then, based on the duration of each visit and the number of visits, the total duration of the visit in the preset time period is determined, and the total duration of the visit is used as the value under the first indicator of the duration of the visit; if there are multiple diagnosis and treatment plans in the preset time period, the average of the scores of the multiple diagnosis and treatment plans is used as the value under the first indicator of the score of the diagnosis and treatment plan. In this way, after the above processing, the values ​​of each virtual pet doctor under multiple first indicators can be obtained.

[0081] Furthermore, for each virtual pet doctor, according to the scoring table corresponding to each first indicator and the value of each first indicator, the first score of each virtual pet doctor under each first indicator is obtained; then, according to the multiple first weights of the multiple first indicators relative to each second indicator, the first score of each virtual pet doctor under each first indicator is weighted to obtain the second score of each virtual pet doctor under each second indicator; then, according to the multiple second weights of the multiple second indicators relative to the third indicator, the second score of each virtual pet doctor under each second indicator is weighted to obtain the score of each virtual pet doctor under the third indicator, that is, the target score of each virtual pet doctor.

[0082] For example, the virtual pet doctors are sorted according to the target scores of the virtual pet doctors from large to small, and the display order of the virtual pet doctors is obtained. Finally, the personal information of each virtual pet doctor is displayed based on the display order of each virtual pet doctor.

[0083] It can be seen that in the embodiment of the present application, the display order of each virtual pet doctor is determined based on the hierarchical analysis method, and then the personal information of the virtual pet doctor is displayed based on the display order, rather than simply displayed based on the registration time, thereby improving the diversity of the display of the virtual pet doctor's personal information.

[0084] In one embodiment of the present application, the data processing device can also generate a virtual pet for the user. Figure 5 The process of generating a virtual pet in this application is specifically described.

[0085] Figure 5A schematic diagram of the process of a virtual pet generation method provided in an embodiment of the present application. The method includes but is not limited to the following steps:

[0086] 501: The first user equipment sends a plurality of pet images to a data processing device. The plurality of pet images are obtained by photographing the physical pet at a plurality of shooting angles. The plurality of shooting angles correspond one-to-one to the plurality of pet images.

[0087] Optionally, the multiple shooting angles of the present application include but are not limited to: a front shooting angle, a rear shooting angle, a left shooting angle, a right shooting angle and a top-down shooting angle.

[0088] 502: The data processing device extracts features from each of the multiple pet images to obtain features of each body part of the physical pet.

[0089] Exemplarily, target detection is performed on the pet image corresponding to each shooting angle to obtain the body part of the pet captured at each shooting angle.

[0090] Exemplarily, target detection is performed on the pet image corresponding to each shooting angle through end-to-end target detection to obtain the target in the pet image corresponding to each shooting angle and the category of the target, thereby obtaining the body part of the pet captured at each shooting angle.

[0091] For example, Figure 6 As shown, feature extraction is performed on the pet image corresponding to each shooting angle to obtain a first feature map corresponding to the pet image; the first feature map is split, for example, tiled, to obtain multiple first feature vectors; the multiple first feature vectors are respectively fused with the position code to obtain multiple second feature vectors, wherein the multiple first feature vectors correspond to the multiple second feature vectors one-to-one, and the position code is used to characterize the spatial relationship between each pixel in the pet image; the multiple second feature vectors are encoded to obtain multiple third feature vectors, for example, the second feature vectors are further feature extracted to obtain multiple third feature vectors; the type of the entity pet is obtained; according to each shooting angle and the type, multiple query vectors corresponding to each shooting angle are obtained, wherein the multiple query vectors are pre-trained, and each query vector is used to characterize a body feature of the entity pet of the above type at the shooting angle, for example, a query vector at the front shooting angle is used to characterize the head feature of the pet when it is shot at the front shooting angle; then the multiple third feature vectors and the multiple query vectors are subjected to attention processing to obtain multiple fourth feature vectors; finally, target detection is performed based on the multiple fourth feature vectors to obtain the body part photographed at each shooting angle.

[0092] It should be noted that different shooting angles capture different body parts. For example, the front shooting angle can capture the pet's mouth and nose, and the left side shooting angle can capture the left outline. Different pets also have different body parts at the same shooting angle. Therefore, corresponding query vectors are set for each pet at different shooting angles to improve the efficiency and accuracy of target detection.

[0093] Furthermore, after obtaining the body part in the pet image corresponding to each shooting angle, a candidate image corresponding to the body part can be cut out from the pet image; and feature extraction is performed on the candidate image to obtain features corresponding to the body part. Exemplarily, the features of the body part captured at each shooting angle include but are not limited to the size, hair sparseness, and hair color of the body part, wherein the size can be represented by the area of ​​the body part in the pet image.

[0094] Specifically, the multi-task model can be used to extract features from the candidate images and perform multi-task prediction to obtain features corresponding to the above-mentioned body parts.

[0095] Finally, the features of the body parts captured at multiple shooting angles are fused to obtain the features of each body part of the pet. Specifically, the features of the body parts captured at each shooting angle are merged to obtain the features of each body part of the pet. For example, the features of the mouth captured at the front shooting angle are merged with the features of the back captured at the top shooting angle to obtain the features of the mouth of the physical pet, as well as the features of the back, and so on.

[0096] 503: The data processing device determines the appearance of the virtual pet according to the characteristics of each body part of the physical pet.

[0097] Exemplarily, the pet sticker corresponding to each body part is determined according to the characteristics of each body part, that is, the pet sticker corresponding to each body part is determined according to the mapping relationship between the characteristics of the body part and the pet sticker. For example, if the physical pet is a cat, and the body part is a head, and the color of the head is black and white, then a pet sticker that can generate a black and white cat can be obtained from a pet sticker library, wherein each pet sticker in the pet sticker library is pre-configured. Finally, the pet stickers corresponding to each determined body part are superimposed to obtain the appearance of the virtual pet.

[0098] 504: The data processing device generates a virtual pet according to the appearance and image, and places the virtual pet in a virtual environment to obtain a target virtual environment.

[0099] Exemplarily, after generating the virtual pet, the data processing device may also obtain an adapted virtual environment. For example, the data processing device obtains a basic virtual environment corresponding to the type of the virtual pet, such as Figure 7 As shown, the type of virtual pet is a cat, and the elements in the basic virtual environment adapted to the cat include grass and pine trees; then the weather in the basic virtual environment is adjusted in combination with the current weather information to obtain the above-mentioned adapted virtual environment, such as Figure 7 As shown in the figure, the current weather is rainy and windy, then add wind and rain elements to the basic virtual environment to generate an adapted virtual environment; finally, place the virtual pet in the adapted virtual environment to generate the target virtual environment. For example, place the virtual pet in the area with the least elements to generate the target virtual environment. Figure 7 As shown, placing a cat in an adapted virtual environment can generate a target virtual environment.

[0100] 505: The data processing device sends a target virtual environment to the first user equipment, where the target virtual environment includes a virtual pet.

[0101] Exemplarily, the data processing device sends the target virtual environment to the first user device, which essentially sends the relevant parameters of the target virtual environment to the first user device; after receiving the relevant parameters, the first user device can perform rendering, so that the target virtual environment and the virtual pet can be displayed on the interface.

[0102] It can be seen that when a user wants to generate a virtual pet, multiple pet images taken of a physical pet at multiple shooting angles can be uploaded to the data processing device. The data processing device can extract features from the multiple pet images to obtain features of each body part of the physical pet. Then, based on the features of each body part, the appearance of the virtual pet is first configured, that is, a virtual pet identical to the physical pet is configured, without the user having to do any complicated configuration work, thereby simplifying the generation of the virtual pet, reducing the complexity of generating the virtual pet, and improving the generation efficiency of the virtual pet and the user experience.

[0103] See also Figure 8 , Figure 8 The present invention provides a block diagram of the functional units of a data processing device. The data processing device 800 includes: a receiving unit 801, a processing unit 802 and a sending unit 803, wherein:

[0104] The receiving unit 801 is configured to receive physiological data of a virtual pet from a first user device, wherein the first user device is a device of a user of the virtual pet;

[0105] The sending unit 803 is used to send the physiological data to a second user device so as to diagnose a disease of the virtual pet, wherein the second user device is a device of the virtual pet doctor;

[0106] The receiving unit 801 is further configured to receive a diagnosis and treatment plan for the virtual pet from the second user device, where the diagnosis and treatment plan is a diagnosis and treatment plan made by the virtual pet physician for the virtual pet based on the physiological data;

[0107] The sending unit 803 is further configured to send the diagnosis and treatment plan to the first user device so that the user can treat the virtual pet based on the diagnosis and treatment plan;

[0108] The receiving unit 801 is further configured to receive the recovery data of the virtual pet from the first user equipment;

[0109] The processing unit 802 is used to evaluate the virtual pet physician according to the diagnosis and treatment plan, the recovery data and the professional information of the virtual pet physician to obtain a target evaluation result of the virtual pet physician.

[0110] In one embodiment of the present application, in terms of evaluating the virtual pet physician according to the diagnosis and treatment plan, the recovery data, and the professional information of the virtual pet physician, and obtaining a target evaluation result of the virtual pet physician, the processing unit 802 is specifically used to:

[0111] According to the diagnosis and treatment plan, a first assessment result in a resource consumption dimension is obtained;

[0112] determining the degree of recovery of the virtual pet according to the recovery data;

[0113] Determining the authority of the virtual pet doctor according to the professional information of the virtual pet doctor;

[0114] A target assessment result of the virtual pet doctor is determined according to the first assessment result, the degree of cure, and the authority.

[0115] In one embodiment of the present application, in terms of obtaining a first assessment result in a resource consumption dimension according to the diagnosis and treatment plan, the processing unit 802 is specifically configured to:

[0116] Determine the name of the disease suffered by the virtual pet according to the diagnosis and treatment plan;

[0117] According to the disease name, determine the average resource consumption of the disease name;

[0118] Determining resource consumption of the virtual pet according to the diagnosis and treatment plan;

[0119] The first assessment result is determined according to the average resource consumption and the resource consumption.

[0120] In one embodiment of the present application, in determining the resource consumption of the virtual pet according to the diagnosis and treatment plan, the processing unit 802 is specifically configured to:

[0121] Obtain multiple operation processes required by users for each diagnosis and treatment project;

[0122] Determining the operation duration of each operation process of the user in multiple operation processes of each diagnosis and treatment project according to the operation habits of the user;

[0123] Sum up the operation time of the user in each operation process to obtain the operation time of the user in each diagnosis and treatment item;

[0124] According to the weight of each diagnosis and treatment item, weight the operation time of the multiple diagnosis and treatment items to obtain a target operation time;

[0125] Obtain the cost investment that the user needs to make on each diagnosis and treatment item;

[0126] Summing the cost inputs of the multiple diagnosis and treatment items to obtain a target cost input;

[0127] The target operation duration and the target cost investment are used as resource consumption of the virtual pet.

[0128] In one embodiment of the present application, the recovery data includes the current physiological state of the virtual pet; in determining the degree of recovery of the virtual pet according to the recovery data, the processing unit 802 is specifically configured to:

[0129] Obtaining the growth time of the virtual pet from the time when the recovery data is received;

[0130] Predicting the current growth state of the virtual pet according to the growth rule of the virtual pet and the growth time;

[0131] The degree of recovery of the virtual pet is determined according to the current growth state and the current physiological state.

[0132] In one embodiment of the present application, in determining the target assessment result of the virtual pet doctor according to the first assessment result, the degree of cure, and the authority, the processing unit 802 is specifically configured to:

[0133] The first assessment result, the degree of cure, and the authority are multiplied to obtain a target assessment result of the virtual pet doctor.

[0134] In one embodiment of the present application, the processing unit 802 is further configured to:

[0135] Obtaining multiple target assessment results of the virtual pet doctor within a preset time;

[0136] Determining a display strategy of the virtual pet doctor according to the multiple target assessment results;

[0137] According to the display strategy, the personal information of the virtual pet doctor is displayed on the front-end web page.

[0138] See also Fig. 9 , Fig. 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Fig. 9 As shown, the electronic device 900 includes a transceiver 901, a processor 902 and a memory 903. They are connected via a bus 904. The memory 903 is used to store computer programs and data, and can transmit the data stored in the memory 903 to the processor 902.

[0139] The processor 902 is used to read the computer program in the memory 903 and perform the following operations:

[0140] Controlling the transceiver 901 to receive physiological data of the virtual pet from a first user device, wherein the first user device is a device of a user of the virtual pet;

[0141] Sending the physiological data to a second user device so as to diagnose a disease of the virtual pet, wherein the second user device is a device of a virtual pet physician;

[0142] receiving a diagnosis and treatment plan for the virtual pet from the second user device, wherein the diagnosis and treatment plan is a diagnosis and treatment plan made by the virtual pet physician for the virtual pet based on the physiological data;

[0143] Sending the diagnosis and treatment plan to the first user device so that the user can treat the virtual pet based on the diagnosis and treatment plan;

[0144] receiving restoration data of the virtual pet from the first user device;

[0145] The virtual pet physician is assessed according to the diagnosis and treatment plan, the recovery data and the professional information of the virtual pet physician to obtain a target assessment result of the virtual pet physician.

[0146] In one embodiment of the present application, in terms of evaluating the virtual pet physician according to the diagnosis and treatment plan, the recovery data, and the professional information of the virtual pet physician, and obtaining a target evaluation result of the virtual pet physician, the processor 902 is specifically configured to perform the following operations:

[0147] According to the diagnosis and treatment plan, a first assessment result in a resource consumption dimension is obtained;

[0148] determining the degree of recovery of the virtual pet according to the recovery data;

[0149] Determining the authority of the virtual pet doctor according to the professional information of the virtual pet doctor;

[0150] A target assessment result of the virtual pet doctor is determined according to the first assessment result, the degree of cure, and the authority.

[0151] In one embodiment of the present application, in terms of obtaining a first assessment result in a resource consumption dimension according to the diagnosis and treatment plan, the processor 902 is specifically configured to perform the following operations:

[0152] Determine the name of the disease suffered by the virtual pet according to the diagnosis and treatment plan;

[0153] According to the disease name, determine the average resource consumption of the disease name;

[0154] Determining resource consumption of the virtual pet according to the diagnosis and treatment plan;

[0155] The first assessment result is determined according to the average resource consumption and the resource consumption.

[0156] In one embodiment of the present application, in determining the resource consumption of the virtual pet according to the diagnosis and treatment plan, the processor 902 is specifically configured to perform the following operations:

[0157] Obtain multiple operation processes required by users for each diagnosis and treatment project;

[0158] Determining the operation duration of each operation process of the user in multiple operation processes of each diagnosis and treatment project according to the operation habits of the user;

[0159] Sum up the operation time of the user in each operation process to obtain the operation time of the user in each diagnosis and treatment item;

[0160] According to the weight of each diagnosis and treatment item, weight the operation time of the multiple diagnosis and treatment items to obtain a target operation time;

[0161] Obtain the cost investment that the user needs to make on each diagnosis and treatment item;

[0162] Summing the cost inputs of the multiple diagnosis and treatment items to obtain a target cost input;

[0163] The target operation duration and the target cost investment are used as resource consumption of the virtual pet.

[0164] In one embodiment of the present application, the recovery data includes the current physiological state of the virtual pet; in determining the degree of recovery of the virtual pet according to the recovery data, the processor 902 is specifically configured to perform the following operations:

[0165] Obtaining the growth time of the virtual pet from the time when the recovery data is received;

[0166] Predicting the current growth state of the virtual pet according to the growth rule of the virtual pet and the growth time;

[0167] The degree of recovery of the virtual pet is determined according to the current growth state and the current physiological state.

[0168] In one embodiment of the present application, in determining the target assessment result of the virtual pet doctor according to the first assessment result, the degree of cure, and the authority, the processor 902 is specifically configured to perform the following operations:

[0169] The first assessment result, the degree of cure, and the authority are multiplied to obtain a target assessment result of the virtual pet doctor.

[0170] In one embodiment of the present application, the processor 902 is further configured to perform the following operations:

[0171] Obtaining multiple target assessment results of the virtual pet doctor within a preset time;

[0172] Determining a display strategy of the virtual pet doctor according to the multiple target assessment results;

[0173] According to the display strategy, the personal information of the virtual pet doctor is displayed on the front-end web page.

[0174] Specifically, the transceiver 901 may be Figure 8 The receiving unit 801 and the sending unit 803 of the data processing device 800 of the embodiment described above, the processor 902 may be Figure 8 The processing unit 802 of the data processing device 800 of the described embodiment.

[0175] It should be understood that the electronic devices in this application may include smart phones (such as Android phones, iOS phones, Windows Phone phones, etc.), tablet computers, PDAs, laptops, mobile Internet devices MID (Mobile Internet Devices, referred to as: MID) or wearable devices, etc. The above electronic devices are only examples, not exhaustive, and include but are not limited to the above electronic devices. In practical applications, the above electronic devices may also include: smart vehicle terminals, computer equipment, etc.

[0176] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. The computer program is executed by a processor to implement part or all of the steps of any data processing method recorded in the above method embodiments.

[0177] An embodiment of the present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute part or all of the steps of any data processing method recorded in the above method embodiments.

[0178] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0179] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0180] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the device or unit can be electrical or other forms.

[0181] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0182] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of a software program module.

[0183] If the integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0184] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated as: ROM), a random access memory (English: Random Access Memory, abbreviated as: RAM), a magnetic disk or an optical disk, etc.

[0185] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A data processing method, characterized in that: include: receiving physiological data of a virtual pet from a first user device, wherein the first user device is a device of a user of the virtual pet; Sending the physiological data to a second user device so as to diagnose a disease of the virtual pet, wherein the second user device is a device of a virtual pet physician; receiving a diagnosis and treatment plan for the virtual pet from the second user device, wherein the diagnosis and treatment plan is a diagnosis and treatment plan made by the virtual pet physician for the virtual pet based on the physiological data; Sending the diagnosis and treatment plan to the first user device so that the user can treat the virtual pet based on the diagnosis and treatment plan; receiving restoration data of the virtual pet from the first user device; According to the diagnosis and treatment plan, the recovery data and the professional information of the virtual pet doctor, the virtual pet doctor is assessed to obtain a target assessment result of the virtual pet doctor; the diagnosis and treatment plan includes a plurality of diagnosis and treatment items; including: Determine the name of the disease suffered by the virtual pet according to the diagnosis and treatment plan; According to the disease name, determine the average resource consumption of the disease name, wherein the average resource consumption includes the average operation time and the average cost input; Obtain multiple operation processes required by users for each diagnosis and treatment project; Determine the operation time of each operation process of the user in multiple operation processes of each diagnosis and treatment project according to the operation habit of the user, wherein the operation habit is the user's proficiency in mastering the growth process of the virtual pet, and the proficiency can be represented by the number of times the user browses the virtual pet; sum the operation time of the user in each operation process to obtain the operation time of the user on each diagnosis and treatment project; weight the operation time of the multiple diagnosis and treatment projects according to the weight of each diagnosis and treatment project to obtain the target operation time; Obtaining the elements that the user needs to purchase for each operation of each diagnosis and treatment item, taking the amount of the elements as the user's cost investment in the operation process, summing the cost investment of multiple diagnosis and treatment items on each operation item to obtain the user's cost investment in each diagnosis and treatment item; summing the cost investment of the multiple diagnosis and treatment items to obtain the target cost investment; Determine the second assessment result based on the average operation time and the target operation time; determine the third assessment result based on the average cost input and the target cost input; determine the first assessment result based on the second assessment result and the third assessment result; determining the degree of recovery of the virtual pet according to the recovery data; Determining the authority of the virtual pet doctor according to the professional information of the virtual pet doctor; A target assessment result of the virtual pet doctor is determined according to the first assessment result, the degree of cure, and the authority.

2. The method according to claim 1, characterized in that The recovery data includes the current physiological state of the virtual pet; and determining the degree of recovery of the virtual pet according to the recovery data includes: Obtaining the growth time of the virtual pet from the time when the recovery data is received; Predicting the current growth state of the virtual pet according to the growth rule of the virtual pet and the growth time; The degree of recovery of the virtual pet is determined according to the current growth state and the current physiological state.

3. The method according to claim 1 or 2, characterized in that: Determining a target assessment result of the virtual pet doctor according to the first assessment result, the degree of cure, and the authority includes: The first assessment result, the degree of cure, and the authority are multiplied to obtain a target assessment result of the virtual pet doctor.

4. The method according to claim 1 or 2, characterized in that: The method further comprises: Obtaining multiple target assessment results of the virtual pet doctor within a preset time; Determining a display strategy of the virtual pet doctor according to the multiple target assessment results; According to the display strategy, the personal information of the virtual pet doctor is displayed on the front-end web page.

5. A data processing device, characterized in that: The device is used to implement the method described in any one of claims 1 to 4; the device comprises: a receiving unit, a processing unit and a sending unit; The receiving unit is used to obtain physiological data of the virtual pet from a first user device, wherein the first user device is a device of a user of the virtual pet; The sending unit is used to send the physiological data to a second user device so as to diagnose a disease of the virtual pet, wherein the second user device is a device of a virtual pet doctor; The receiving unit is further configured to receive a diagnosis and treatment plan for the virtual pet from the second user device, wherein the diagnosis and treatment plan is a diagnosis and treatment plan made by the virtual pet physician for the virtual pet based on the physiological data; The sending unit is further used to send the diagnosis and treatment plan to the first user device so that the user can treat the virtual pet based on the diagnosis and treatment plan; The receiving unit is further configured to receive the recovery data of the virtual pet from the first user device; The processing unit is used to evaluate the virtual pet physician according to the diagnosis and treatment plan, the recovery data and the professional information of the virtual pet physician to obtain a target evaluation result of the virtual pet physician.

6. An electronic device, characterized in that: include: A processor and a memory, wherein the processor is connected to the memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method according to any one of claims 1 to 4.

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