Pet information display method and device, equipment and storage medium

Abstract

The invention discloses a pet information display method and device, equipment and a storage medium, and the method comprises the steps: obtaining a face image of a target pet; performing nose print recognition on the face image to obtain nose print features of the target pet; acquiring pet information of the target pet based on the nose print features; and displaying the pet information. According to the method and the device, the pet information is associated with the nose pattern of the pet, so that a purchaser can directly acquire the pet information of the pet by shooting the face of the pet, the pet information does not need to be displayed in a label or two-dimensional code form, and the maintenance cost is reduced.

Description

Technical Field

[0001] The present application relates to the field of information display technology, and in particular to a pet information display method, device, equipment and storage medium. Background Art

[0002] At present, offline pet stores often use QR codes or simple labels to introduce relevant information about pets for sale. However, the label area is small and cannot record detailed information, so the amount of information that buyers can obtain is relatively low. Although QR codes can store a lot of information, once the corresponding pet is sold, they need to be replaced, which has high maintenance costs. Summary of the invention

[0003] The present application provides a pet information display method, device, equipment and storage medium, which can reduce maintenance costs.

[0004] In a first aspect, a pet information display method provided in an embodiment of the present application includes:

[0005] Get the facial image of the target pet;

[0006] Performing nose print recognition on the facial image to obtain nose print features of the target pet;

[0007] Acquire pet information of the target pet based on the nose print feature;

[0008] The pet information is displayed.

[0009] It can be seen that in this method, by associating the pet information with the nose print of the pet, the buyer can directly obtain the facial image of the target pet by photographing the face of the target pet, and then perform nose print recognition on the facial image to obtain the nose print features of the target pet, and then obtain the corresponding pet information through the nose print features. Therefore, there is no need to display the pet information in the form of labels or QR codes, which reduces maintenance costs.

[0010] In combination with the first aspect, in a possible implementation, the facial image includes a plurality of continuous facial image frames, based on which, performing nose print recognition on the facial image to obtain the nose print features of the target pet includes:

[0011] Performing image segmentation on each facial image frame to obtain a plurality of nose print image frames, wherein the plurality of nose print image frames correspond one to one to the plurality of facial image frames;

[0012] Inputting the multiple nose print image frames into a depth model to obtain multiple depth image frames, wherein the depth model is obtained by training an original model based on a brightness difference factor and a coordinate difference factor, and the multiple depth image frames correspond one-to-one to the multiple nose print image frames;

[0013] Based on the multiple depth image frames and shooting parameters, nose print features of the target pet's nose are acquired, wherein the shooting parameters are parameters used when shooting the facial image.

[0014] In combination with the first aspect, in a possible implementation manner, the deep model is obtained by the following training method:

[0015] Inputting a plurality of sample image frame sets and a plurality of sample shooting parameters into the original model, determining a first loss and a second loss, wherein each sample image frame set includes at least a first sample nose print image and a second sample nose print image that are continuous, the first sample nose print image is acquired before the second sample nose print image, the plurality of sample shooting parameters correspond to the plurality of sample image frame sets one by one, each sample shooting parameter is a parameter used when shooting a sample nose print image in the corresponding sample image frame set, the first loss is used to represent a brightness difference between image frames, and the second loss is used to represent a coordinate difference between image frames;

[0016] Determine a training loss based on the first loss and the second loss;

[0017] Based on the training loss, the model parameters of the original model are adjusted to obtain the deep model.

[0018] In conjunction with the first aspect, in a possible implementation, determining the first loss includes:

[0019] For each of the sample image frame sets, volume rendering is performed based on the first sample nose print image and the sample shooting parameters corresponding to each of the sample image frame sets to obtain a first reconstructed image corresponding to each of the sample image frame sets;

[0020] The first loss is determined based on a brightness difference between a first sample nose print image corresponding to each sample image frame set and a first reconstructed image corresponding to each sample image frame set.

[0021] In combination with the first aspect, in a possible implementation manner, determining the second loss includes:

[0022] Determine a first coordinate of a target pixel point in a first sample nose print image, wherein the target pixel point is any pixel point in the first sample nose print image;

[0023] Determine a second coordinate of the target pixel in the second sample nose print image based on optical flow tracking;

[0024] The second loss is determined based on a coordinate difference between the first coordinate and the second coordinate.

[0025] In combination with the first aspect, in a possible implementation, acquiring nose print features of the target pet's nose based on the multiple depth image frames and the shooting parameters includes:

[0026] Obtain the depth information contained in each depth image frame;

[0027] Based on the multiple depth information and the shooting parameters, point cloud data of the nose of the target pet is generated, wherein the point cloud data includes point cloud features of each pixel point in each nose print image frame in three-dimensional space;

[0028] constructing a three-dimensional model of the nose of the target pet based on the point cloud data;

[0029] Feature extraction is performed on the three-dimensional model to obtain nose print features of the target pet's nose.

[0030] In combination with the first aspect, in a possible implementation, displaying the pet information includes:

[0031] Obtain user identity information and preference information;

[0032] Layout the pet information based on the identity information and the preference information;

[0033] Display the pet information after typeset.

[0034] In a second aspect, a pet information display device provided in an embodiment of the present application includes:

[0035] An acquisition module, used for acquiring a facial image of a target pet;

[0036] A recognition module, used for performing nose print recognition on the facial image to obtain nose print features of the target pet;

[0037] The acquisition module is further used to acquire the pet information of the target pet based on the nose print feature;

[0038] The display module is used to display the pet information.

[0039] A third aspect is an electronic device provided for an embodiment of the present application, comprising a processor, a memory, and a computer program or instructions stored on the memory, wherein the processor executes the computer program or instructions to implement the steps in the method designed in the first aspect above.

[0040] In a fourth aspect, a computer-readable storage medium is provided for an embodiment of the present application, wherein a computer program or instruction is stored therein, and when the computer program or instruction is executed, the steps in the method designed in the first aspect are implemented. For example, the computer program or instruction is executed by a processor.

[0041] In a fifth aspect, a computer program product provided by an embodiment of the present application includes a computer program or an instruction, wherein when the computer program or the instruction is executed, the steps in the method designed in the first aspect are executed. For example, the computer program or the instruction is executed by a processor.

[0042] The beneficial effects brought about by the technical solutions of the second to fifth aspects can be referred to the technical effects brought about by the technical solution of the first aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some implementation methods recorded in one or more of the present specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0044] Figure 1 is a schematic diagram of a pet information display system proposed in an embodiment of the present application;

[0045] Figure 2 A schematic diagram of an application scenario of a pet information display method proposed in an embodiment of the present application;

[0046] Figure 3 It is a terminal interface schematic diagram of a pet information display method proposed in an embodiment of the present application;

[0047] Figure 4 A schematic diagram of a pet information display method proposed in an embodiment of the present application;

[0048] Figure 5 This is a functional module composition block diagram of a pet information display device proposed in an embodiment of the present application;

[0049] Figure 6 It is a structural schematic diagram of an electronic device proposed in an embodiment of the present application. DETAILED DESCRIPTION

[0050] It should be understood that the terms "first", "second", etc. involved in the embodiments of the present application 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, software, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products, or devices.

[0051] The "implementation method" involved in the embodiments of the present application means that the specific features, structures or characteristics described in conjunction with the implementation method may be included in at least one implementation method of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same implementation method, nor is it an independent or alternative implementation method that is mutually exclusive with other implementation methods. It is explicitly and implicitly understood by those skilled in the art that the implementation methods described herein may be combined with other implementation methods.

[0052] The “and / or” in the implementation manner of the present application describes the association relationship of the associated objects, indicating that three types of relationships may exist.

[0053] In the implementation manner of the present application, the symbol " / " can indicate that the previously associated objects are in an "or" relationship.

[0054] "At least one item" or similar expressions in the embodiments of the present application refers to any combination of these items, including any combination of single items or plural items, and refers to one or more, and multiple refers to two or more.

[0055] In the embodiments of the present application, "higher than" can be expressed as the same concept as "greater than", "lower than" can be expressed as the same concept as "less than", "not lower than" can be expressed as the same concept as "higher than or equal to" or "greater than or equal to", and "not higher than" can be expressed as the same concept as "lower than or equal to" or "less than or equal to". In the present application, for the same scheme, "equal to" can be used in conjunction with "less than", and can also be used in conjunction with "greater than", but not used in conjunction with "less than" and "greater than" at the same time. When "equal to" is used in conjunction with "less than", it is applicable to the technical scheme adopted by "less than". When "equal to" is used in conjunction with "greater than", it is applicable to the technical scheme adopted by "greater than".

[0056] In the embodiments of the present application, the terms "of", "corresponding / relevant", "corresponding", "indicated", "associated", etc. may be used interchangeably.

[0057] In the implementation manner of this application, the words "associated", "corresponding", "corresponding", "is", "of", "for", "belonging to", "as", and "regarded as" can sometimes be used interchangeably.

[0058] The "connection" in the embodiments of the present application refers to various connection methods such as direct connection or indirect connection to achieve communication between devices, and there is no limitation on this.

[0059] The "network" in the implementation manner of the present application can be expressed as the same concept as the "system", and the communication system is the communication network.

[0060] The following is an explanation of the relevant contents, concepts, meanings, technical issues, technical solutions and beneficial effects involved in the implementation of the present application.

[0061] First, see Figure 1 , Figure 1 Schematic diagram of a pet information display system proposed in the embodiment of the present application. Figure 1 As shown, the pet information display system may include a terminal device, an identification device and a database.

[0062] In this embodiment, the user takes or scans the facial image of the target pet through the terminal device. After taking the facial image of the target pet, the terminal device sends the facial image to the server. After the server obtains the facial image, it performs nose print recognition on the facial image to obtain the nose print features of the target pet. Then, the server matches the nose print features in the database to obtain the pet information associated with the nose print features. Finally, the server sends the obtained pet information back to the terminal device to display it to the user through the terminal device.

[0063] Understandably, Figure 1 The forms and quantities of the terminal devices, identification devices and databases shown in the figure are for illustrative purposes only and do not constitute limitations on the implementation modes of the present application.

[0064] In this embodiment, the terminal device and the identification device may be a device with a communication function, which may be referred to as a terminal, user equipment (UE), mobile station (MS), mobile terminal (MT), access terminal equipment, vehicle-mounted terminal equipment, industrial control terminal equipment, UE unit, UE station, mobile station, remote station, remote terminal equipment, mobile equipment, UE terminal equipment, wireless communication equipment, UE agent or UE device, etc. The terminal device may be fixed or mobile. It should be noted that the terminal device and the identification device may support at least one wireless communication technology, such as LTE, new radio (NR), wideband code division multiple access (WCDMA), etc. For example, the terminal device and the identification device can be a mobile phone, a tablet computer (pad), a desktop computer, a laptop computer, an all-in-one computer, a vehicle-mounted terminal, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal in industrial control, a wireless terminal in self driving, a wireless terminal in remote medical surgery, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, a wireless terminal in a smart home, a cellular phone, a cordless phone, a session initiation protocol (SIP) phone, a wireless local loop (WLL) station, a personal digital assistant (PDA), a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a wearable device, a terminal device in a future mobile communication network, or a terminal device in a future evolved public mobile land network (PLMN), etc. In some embodiments of the present application, the terminal device and the identification device may also be a device with a transceiver function, such as a chip system, wherein the chip system may include a chip and may also include other discrete devices.

[0065] In this embodiment, the terminal device and the identification device may also be a server, for example, it may be an independent server, or it may be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms. This application does not make specific limitations on this.

[0066] In this embodiment, the database may also be a server, or a memory that provides data storage services, such as: a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, and this application does not make any specific limitations on this.

[0067] In this embodiment, the database may also be a storage unit integrated in the terminal device and / or the identification device, and may be a component of the terminal device and / or the identification device.

[0068] Second, see Figure 2 , Figure 2 Schematic diagram of an application scenario of a pet information display method proposed in the embodiment of the present application. Figure 2 As shown, users can install the corresponding APP in the terminal device, or call the corresponding applet to open Figure 3 The interface shown in Figure (a) is used to shoot or scan the face of the target pet. During the shooting or scanning process, some prompt words can be displayed on the interface according to the current shooting situation of the terminal device, such as Figure 3 In the interface shown in Figure (b), the user can perform corresponding operations through the prompt word to complete the acquisition of the facial image of the target pet.

[0069] In this embodiment, after the terminal device obtains the facial image of the target pet, the facial image can be sent to the recognition device for recognition. During this process, the terminal device can display the following information: Figure 3 The interface shown in Figure (c) in the figure is displayed to inform the user that the identification is in progress. After receiving the pet information returned by the identification device, the pet information of the target pet is displayed to the user, such as Figure 3 As shown in Figure (d).

[0070] See also Figure 4 , Figure 4 A flowchart of a pet information display method proposed in the embodiment of the present application, the method is applied to Figure 1 The pet information display system shown in the figure can be implemented by the identification device in the pet information display system. Figure 4 As shown, the method includes:

[0071] S401: Acquire a facial image of a target pet.

[0072] In this embodiment, the facial image may include a plurality of continuous facial image frames, and the plurality of facial image frames may be a collection of image frames corresponding to a video acquired by the terminal device. Exemplarily, the video may be a video obtained by the terminal device shooting the face of the target pet in real time, or the video may also be a historical video containing the facial area of ​​the target pet, such as a video shot by a merchant and sent to a user, and the embodiment of the present application does not limit this.

[0073] In this embodiment, the multiple facial image frames may be all the image frames corresponding to the video, or may also be image frames corresponding to a partial segment of the video containing the face of the target pet. In other words, the multiple facial image frames may be multiple image frames with continuous frame numbers, or may also be multiple image frames with discontinuous frame numbers, which is not limited in the embodiment of the present application.

[0074] S402: Perform nose print recognition on the facial image to obtain nose print features of the target pet.

[0075] In this embodiment, after acquiring a facial image including a plurality of facial image frames, each facial image frame can first be segmented to segment the nose portion of the target pet in each facial image frame to obtain a plurality of nose print image frames. The plurality of nose print image frames correspond one-to-one to the plurality of facial image frames, that is, after segmenting each facial image frame, a nose print image frame corresponding to the facial image frame is obtained.

[0076] In this embodiment, the edge of the nose part in the facial image frame can be determined by edge detection and other methods, and then the nose part is segmented from the facial image frame. Of course, other image segmentation methods in the art can also be used to segment the facial image frame, and the embodiment of the present application is not limited to this.

[0077] After obtaining multiple nose print image frames, the multiple nose print image frames can be input into a depth model to obtain multiple depth image frames. The multiple depth image frames correspond to the multiple nose print image frames one by one, that is, after each nose print image frame is input into the depth model, a depth image frame corresponding to the nose print image frame is obtained.

[0078] In this embodiment, the depth model is obtained by training the original model based on the brightness difference factor and the coordinate difference factor.

[0079] Specifically, during the training process, a plurality of sample image frame sets and a plurality of sample shooting parameters are first input into the original model to determine a first loss and a second loss. Each of the plurality of sample image frame sets includes at least a first sample nose print image and a second sample nose print image that are continuous, and the first sample nose print image is acquired before the second sample nose print image. The plurality of sample image frame sets correspond one-to-one to the plurality of sample shooting parameters, that is, each sample image frame set corresponds to a sample shooting parameter, which is a parameter used when shooting the sample nose print image in the corresponding sample image frame set, such as shooting device parameters and shooting environment parameters.

[0080] In this embodiment, the first loss is used to represent the brightness difference between image frames. Specifically, for each set of sample image frames, the initial model performs volume rendering based on the first sample nose print image in the sample image set and the sample shooting parameters corresponding to the set to obtain the first reconstructed image corresponding to the sample image set. Based on the brightness difference between the first sample nose print image corresponding to the sample image set and the first reconstructed image corresponding to the sample image set, the first loss corresponding to the sample image set is determined. Thus, for each set of sample image frames, a first loss can be obtained, and then the first loss of this training can be determined based on the first losses of these sample image sets.

[0081] Exemplarily, the first losses of these sample image sets can be averaged to obtain the first loss of this training; or, the first losses of these sample image sets can be weighted summed based on the weight of each sample image set to obtain the first loss of this training; or, the median of the first losses of these sample image sets can be calculated to obtain the first loss of this training, which is not limited to the embodiments of the present application.

[0082] In this embodiment, the second loss is used to represent the coordinate difference between image frames. Specifically, the first coordinate of the target pixel in the first sample nose print image can be determined, and the target pixel is any pixel in the first sample nose print image. Then, the second coordinate of the target pixel in the second sample nose print image is determined based on optical flow tracking. Finally, based on the coordinate difference between the first coordinate and the second coordinate, the second loss corresponding to the sample image set to which the first sample nose print image belongs is determined.

[0083] Exemplarily, the above-mentioned first coordinate and second coordinate can be determined for each pixel in the first sample nose print image, and then based on the position of each pixel in the first sample nose print image, the first coordinate of each pixel is used to form a first coordinate matrix, and the second coordinate of each pixel is used to form a second coordinate matrix. Thus, the second loss corresponding to the sample image set to which the first sample nose print image belongs can be determined through the coordinate difference between the first coordinate matrix and the second coordinate matrix.

[0084] Similarly, the second losses of these sample image sets can be averaged to obtain the second loss of this training; or, the second losses of these sample image sets can be weighted summed based on the weight of each sample image set to obtain the second loss of this training; or, the median of the second losses of these sample image sets can be found to obtain the second loss of this training, and the implementation methods of the present application are not limited to this.

[0085] In this embodiment, after determining the first loss and the second loss of this training, the training loss of this training can be determined based on the first loss and the second loss. Specifically, the first loss and the second loss can be averaged to obtain the training loss of this training; or, based on the weights of the first loss and the second loss, the first loss and the second loss can be weighted summed to obtain the second loss of this training, which is not limited in the embodiment of this application.

[0086] Finally, the model parameters of the original model can be adjusted based on the training loss to obtain a deep model. In this embodiment, N iterative trainings can be performed. After each training, the model obtained by this training is verified by the verification set. If the verification fails, the next iterative training is performed based on the current training until a model that can pass the verification is trained as the final deep model.

[0087] In this embodiment, after a plurality of depth image frames are acquired through a depth model, the nose print features of the target pet's nose can be acquired based on the plurality of depth image frames and shooting parameters. Specifically, the shooting parameters are the parameters used when shooting the facial image of the target pet. Exemplarily, if the facial image of the target pet is obtained by real-time shooting with a mobile phone, the shooting parameters can be the parameters of the camera when the mobile phone is shooting, such as: aperture parameters, focal length, sensitivity, etc., and the parameters of the shooting environment, such as: lighting parameters. Each depth image frame contains the depth information of the nose print image frame corresponding to the depth image frame, and then based on the plurality of depth information and shooting parameters, the point cloud data of the target pet's nose can be generated, and the point cloud data includes the point cloud features of each pixel in each nose print image frame in three-dimensional space. Thus, the nose of the target pet can be reconstructed through the three-dimensional point cloud to obtain a three-dimensional model of the nose of the target pet. Finally, the three-dimensional model can be feature extracted to obtain the nose print features of the target pet's nose.

[0088] S403: Obtain pet information of the target pet based on the nose print feature.

[0089] In this embodiment, after the pet information is edited, it will be associated with the nose print feature of the pet and stored in the database. After the nose print feature of the target pet is obtained, it can be matched in the database based on the nose print feature of the target pet, and the pet information corresponding to the matched nose print feature is used as the pet information of the target pet. Exemplarily, the similarity between the nose print feature of the target pet and each nose print feature stored in the database can be calculated, and then the nose print feature with the highest similarity can be used as the matched nose print feature.

[0090] S404: Display pet information.

[0091] In this embodiment, the pet information can be sent to a terminal device or a preset display device for display to the user. Before sending the pet information to the terminal device or the display device, the pet information can be typeset according to the user's personal information and preference information, and then the typeset pet information is sent to the terminal device or the display device for display to the user, so as to improve the user experience.

[0092] Specifically, the user's personal information may include the user's age, gender and other information, which can be authorized by the user when registering or logging into the corresponding APP on the terminal device. Through the user's personal information, it is possible to determine the group to which the user belongs, such as a young female group, an elderly male group, etc., and then obtain the group portrait of the group. Through the overall portrait, the group's interest information in pets can be obtained, and the interest information can indicate which factors of the pet the group is more interested in. For example: young female groups are more interested in factors such as the appearance and personality of pets; elderly male groups are more interested in factors such as the price and breed of pets.

[0093] Then, the factors included in the information of interest determined by the personal information can be sorted and supplemented according to the user's preference information. Specifically, the user's preference information can represent the user's preference for certain factors of the pet, and this information can be determined by analyzing the user's historical data when browsing pet information using the APP. Specifically, the user's preference for each factor in the pet information is determined by determining the time and number of times the user browses the pet information, as well as the average browsing time and number of times for the factor.

[0094] Thus, through the user's preference information, the factors determined by the personal information can be sorted, and the relevant information of the factors that the user prefers more can be placed in front, while the factors not determined by the personal information can be supplemented. The pet information is then typeset in the order of the arranged factors, and the typeset pet information is sent to the terminal device for display. It should be noted that the typesetting process can also be executed by the terminal device, that is, after the terminal device obtains the pet information sent by the identification device, it obtains the user's personal information and preference information, typesets the pet information, and then displays it to the user.

[0095] In summary, by associating pet information with the pet's nose print, the purchaser can directly obtain the target pet's facial image by photographing the target pet's face, and then perform nose print recognition on the facial image to obtain the target pet's nose print features, and then obtain the corresponding pet information through the nose print features. As a result, there is no need to display pet information in the form of labels or QR codes, which reduces maintenance costs. When displaying information, the pet information can be typeset in combination with the user's personal information and preference information, so that the information that the user likes or pays attention to is displayed to the user first, improving the user experience.

[0096] The above mainly introduces the scheme of the implementation mode of the present application from the perspective of the method side. It is understandable that in order to realize the above functions, the training device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the implementation mode disclosed in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0097] The implementation method of the present application can divide the functional units of the terminal device according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one functional module. The above integrated module can be implemented in the form of hardware or in the form of a software program module. It should be noted that the division of modules in the implementation method of the present application is schematic and is only a logical function division, and there may be other division methods in actual implementation.

[0098] In the case of integrated modules, Figure 5 The pet information display device 500 includes an acquisition module 501 , an identification module 502 and a display module 503 .

[0099] In this implementation, the acquisition module 501, the identification module 502 and the display module 503 may be a module for receiving and processing signals, information, etc. or determining a monitoring mechanism, and there is no specific limitation on this.

[0100] In this embodiment, the pet information display device 500 may further include a storage module for computer program codes or instructions executed by the pet information display device 500. The storage module may be a memory.

[0101] In this embodiment, the pet information display device 500 may be a chip or a chip module.

[0102] In this embodiment, the acquisition module 501, the identification module 502 and the display module 503 can be integrated in a communication module, wherein the communication module can be a communication interface, a transceiver, a transceiver circuit, and the like.

[0103] In this embodiment, the acquisition module 501, the identification module 502 and the display module 503 can be integrated into a processor.

[0104] It should be noted that the processor can be a baseband processor, a baseband chip, a central processing unit (CPU), a general processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processing module can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of DSPs and microprocessors, etc.

[0105] In this embodiment, the pet information display device 500 is used to execute any step executed by the terminal device / chip / chip module, etc. in the above method implementation.

[0106] In specific implementation, the acquisition module 501, the identification module 502 and the display module 503 are used to execute any step in the above method implementation, and when executing actions such as sending, other modules can be selectively called to complete the corresponding operation.

[0107] An acquisition module 501 is used to acquire a facial image of a target pet;

[0108] The recognition module 502 is used to perform nose print recognition on the facial image to obtain the nose print features of the target pet;

[0109] The acquisition module 501 is further used to acquire the pet information of the target pet based on the nose print feature;

[0110] The display module 503 is used to display the pet information.

[0111] In this embodiment, the facial image includes a plurality of continuous facial image frames. In the aspect of performing nose print recognition on the facial image to obtain the nose print features of the target pet, the recognition module 502 is specifically used to:

[0112] Performing image segmentation on each facial image frame to obtain a plurality of nose print image frames, wherein the plurality of nose print image frames correspond one to one to the plurality of facial image frames;

[0113] Inputting the multiple nose print image frames into a depth model to obtain multiple depth image frames, wherein the depth model is obtained by training an original model based on a brightness difference factor and a coordinate difference factor, and the multiple depth image frames correspond one-to-one to the multiple nose print image frames;

[0114] Based on the multiple depth image frames and shooting parameters, nose print features of the target pet's nose are acquired, wherein the shooting parameters are parameters used when shooting the facial image.

[0115] In this embodiment, the pet information display device 500 further includes a training module (not shown), which is used to obtain a deep model by training in the following manner:

[0116] Inputting a plurality of sample image frame sets and a plurality of sample shooting parameters into the original model, determining a first loss and a second loss, wherein each sample image frame set includes at least a first sample nose print image and a second sample nose print image that are continuous, the first sample nose print image is acquired before the second sample nose print image, the plurality of sample shooting parameters correspond to the plurality of sample image frame sets one by one, each sample shooting parameter is a parameter used when shooting a sample nose print image in the corresponding sample image frame set, the first loss is used to represent a brightness difference between image frames, and the second loss is used to represent a coordinate difference between image frames;

[0117] Determine a training loss based on the first loss and the second loss;

[0118] Based on the training loss, the model parameters of the original model are adjusted to obtain the deep model.

[0119] In this embodiment, in determining the first loss, the training module is specifically used to:

[0120] For each of the sample image frame sets, volume rendering is performed based on the first sample nose print image and the sample shooting parameters corresponding to each of the sample image frame sets to obtain a first reconstructed image corresponding to each of the sample image frame sets;

[0121] The first loss is determined based on a brightness difference between a first sample nose print image corresponding to each sample image frame set and a first reconstructed image corresponding to each sample image frame set.

[0122] In this embodiment, in determining the second loss, the training module is specifically used to:

[0123] Determine a first coordinate of a target pixel point in a first sample nose print image, wherein the target pixel point is any pixel point in the first sample nose print image;

[0124] Determine a second coordinate of the target pixel in the second sample nose print image based on optical flow tracking;

[0125] The second loss is determined based on a coordinate difference between the first coordinate and the second coordinate.

[0126] In this embodiment, in acquiring the nose print features of the target pet's nose based on the multiple depth image frames and the shooting parameters, the recognition module 502 is specifically used to:

[0127] Obtain the depth information contained in each depth image frame;

[0128] Based on the multiple depth information and the shooting parameters, point cloud data of the nose of the target pet is generated, wherein the point cloud data includes point cloud features of each pixel point in each nose print image frame in three-dimensional space;

[0129] constructing a three-dimensional model of the nose of the target pet based on the point cloud data;

[0130] Feature extraction is performed on the three-dimensional model to obtain nose print features of the target pet's nose.

[0131] In this implementation, in terms of displaying the pet information, the display module 503 is specifically used to:

[0132] Obtain user identity information and preference information;

[0133] Layout the pet information based on the identity information and the preference information;

[0134] Display the pet information after typeset.

[0135] See also Figure 6 , Figure 6 6 is a schematic diagram of a structure of an electronic device proposed in an embodiment of the present application. The electronic device 600 may include a processor 610, a memory 620, and a communication bus for connecting the processor 610 and the memory 620.

[0136] Optionally, the memory 620 includes but is not limited to random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or portable read-only memory (CD-ROM), and the memory 620 is used to store the program code executed by the electronic device 600 and the transmitted data.

[0137] In this embodiment, the electronic device 600 further includes a communication interface for receiving and sending data.

[0138] In this implementation, the processor 610 may be one or more CPUs. When the processor 610 is a CPU, the CPU may be a single-core CPU or a multi-core CPU.

[0139] In this embodiment, the processor 610 can be a baseband chip, a chip, a CPU, a general processor, a DSP, an ASIC, an FPGA or other programmable logic devices, transistor logic devices, hardware components or any combination thereof.

[0140] In a specific implementation, the processor 610 in the electronic device 600 is used to execute the computer program or instruction 621 stored in the memory 620 to perform the following operations:

[0141] Get the facial image of the target pet;

[0142] Performing nose print recognition on the facial image to obtain nose print features of the target pet;

[0143] Acquire pet information of the target pet based on the nose print feature;

[0144] The pet information is displayed.

[0145] It should be noted that Figure 6 The specific implementation of each operation in the implementation method can be found in the description of the method implementation method shown above, and will not be described in detail here.

[0146] The present application also provides a computer-readable storage medium storing a computer program or instructions, which implements the steps described in the above method implementation when executed.

[0147] The embodiment of the present application also provides a computer program product, including a computer program or instructions, which implement the steps described in the above method embodiment when executed.

[0148] It should be noted that, for the above-mentioned various embodiments, for the sake of simple description, they are all expressed as a series of action combinations. Those skilled in the art should be aware that the present application is not limited by the described order of actions, because some steps in the embodiments of the present application can be performed in other orders or simultaneously. In addition, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions, steps, modules or units involved are not necessarily required for the embodiments of the present application.

[0149] In the above-mentioned embodiments, the description of each embodiment of the present application has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0150] The steps of the method or algorithm described in the embodiments of the present application can be implemented in hardware or by executing software instructions by a processor. The software instructions can be composed of corresponding software modules, and the software modules can be stored in RAM, flash memory, ROM, EPROM, electrically erasable programmable read-only memory (electrically EPROM, EEPROM), registers, hard disks, mobile hard disks, read-only compact disks (CD-ROMs) or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC. In addition, the ASIC can be located in a terminal device or a management device. Of course, the processor and the storage medium can also be present in a terminal device or a management device as discrete components.

[0151] Those skilled in the art should be aware that in one or more of the above examples, the functions described in the embodiments of the present application can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiments of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrations. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0152] The modules / units included in the devices and products described in the above embodiments may be software modules / units or hardware modules / units, or may be partially software modules / units and partially hardware modules / units. For example, for the devices and products applied to or integrated in the chip, the modules / units included therein may all be implemented in the form of hardware such as circuits, or at least some of the modules / units may be implemented in the form of software programs, which run on the processor integrated inside the chip, and the remaining (if any) modules / units may be implemented in the form of hardware such as circuits; for the devices and products applied to or integrated in the chip module, the modules / units included therein may all be implemented in the form of hardware such as circuits, and different modules / units may be located in the same component (such as a chip, circuit module, etc.) or in different components of the chip module, or at least some of the modules / units may be implemented in the form of software programs. The software programs run on the processor integrated inside the chip, and the remaining (if any) modules / units may be implemented in the form of hardware such as circuits. It is implemented in the form of a software program, which runs on a processor integrated inside the chip module, and the remaining (if any) modules / units can be implemented in hardware such as circuits; for various devices and products applied to or integrated in the terminal equipment, the various modules / units contained therein can be implemented in hardware such as circuits, and different modules / units can be located in the same component (for example, chip, circuit module, etc.) or in different components in the terminal equipment, or, at least some modules / units can be implemented in the form of a software program, which runs on a processor integrated inside the terminal equipment, and the remaining (if any) modules / units can be implemented in hardware such as circuits.

[0153] The specific implementation methods described above further illustrate the purpose, technical solutions and beneficial effects of the implementation methods of the present application. It should be understood that the above description is only the specific implementation method of the implementation method of the present application and is not intended to limit the protection scope of the implementation method of the present application. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solutions of the implementation methods of the present application should be included in the protection scope of the implementation methods of the present application.

Claims

1. A pet information display method, characterized in that: The method comprises: Obtain a facial image of the target pet; Performing nose print recognition on the facial image to obtain nose print features of the target pet; Acquire pet information of the target pet based on the nose print feature; The pet information is displayed.

2. The method according to claim 1, characterized in that The facial image includes a plurality of consecutive facial image frames, The performing nose print recognition on the facial image to obtain the nose print features of the target pet includes: Performing image segmentation on each facial image frame to obtain a plurality of nose print image frames, wherein the plurality of nose print image frames correspond one to one to the plurality of facial image frames; Inputting the multiple nose print image frames into a depth model to obtain multiple depth image frames, wherein the depth model is obtained by training an original model based on a brightness difference factor and a coordinate difference factor, and the multiple depth image frames correspond one-to-one to the multiple nose print image frames; Based on the multiple depth image frames and shooting parameters, nose print features of the target pet's nose are acquired, wherein the shooting parameters are parameters used when shooting the facial image.

3. The method according to claim 2, characterized in that The depth model is obtained by the following training method: Inputting a plurality of sample image frame sets and a plurality of sample shooting parameters into the original model, determining a first loss and a second loss, wherein each sample image frame set includes at least a first sample nose print image and a second sample nose print image that are continuous, the first sample nose print image is acquired before the second sample nose print image, the plurality of sample shooting parameters correspond to the plurality of sample image frame sets one by one, each sample shooting parameter is a parameter used when shooting a sample nose print image in the corresponding sample image frame set, the first loss is used to represent a brightness difference between image frames, and the second loss is used to represent a coordinate difference between image frames; Determine a training loss based on the first loss and the second loss; Based on the training loss, the model parameters of the original model are adjusted to obtain the deep model.

4. The method according to claim 3, characterized in that Determine the first loss, including: For each of the sample image frame sets, volume rendering is performed based on the first sample nose print image and the sample shooting parameters corresponding to each of the sample image frame sets to obtain a first reconstructed image corresponding to each of the sample image frame sets; The first loss is determined based on a brightness difference between a first sample nose print image corresponding to each sample image frame set and a first reconstructed image corresponding to each sample image frame set.

5. The method according to claim 4, characterized in that Determine the secondary loss, including: Determine a first coordinate of a target pixel point in a first sample nose print image, wherein the target pixel point is any pixel point in the first sample nose print image; Determine a second coordinate of the target pixel in the second sample nose print image based on optical flow tracking; The second loss is determined based on a coordinate difference between the first coordinate and the second coordinate.

6. The method according to claim 2, characterized in that The step of acquiring nose print features of the target pet's nose based on the multiple depth image frames and the shooting parameters includes: Obtain the depth information contained in each depth image frame; Based on the multiple depth information and the shooting parameters, point cloud data of the nose of the target pet is generated, wherein the point cloud data includes point cloud features of each pixel point in each nose print image frame in three-dimensional space; constructing a three-dimensional model of the nose of the target pet based on the point cloud data; Feature extraction is performed on the three-dimensional model to obtain nose print features of the target pet's nose.

7. The method according to any one of claims 1 to 5, characterized in that: The displaying of the pet information includes: Obtain user identity information and preference information; Layout the pet information based on the identity information and the preference information; Display the pet information after typeset.

8. A pet information display device, characterized in that: The device comprises: An acquisition module, used for acquiring a facial image of a target pet; A recognition module, used for performing nose print recognition on the facial image to obtain nose print features of the target pet; The acquisition module is further used to acquire the pet information of the target pet based on the nose print feature; The display module is used to display the pet information.

9. An electronic device comprising a processor, a memory and a computer program or instruction stored in the memory, characterized in that: The processor executes the computer program or instructions to implement the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program or instructions, and when the computer program or instructions are executed, the steps of the method according to any one of claims 1 to 7 are performed.

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