Vehicle pet mode control method, device, equipment and medium

Abstract

A vehicle pet mode control method, device, equipment and medium belong to the field of automotive technology. The method includes: during vehicle driving, if it is detected that the pet mode is turned on, obtaining target data of the pet in the vehicle, the target data including first image data; analyzing and processing the target data to identify the pet type of the pet in the vehicle; obtaining second image data of the pet adjacent to the vehicle within a preset radius with the vehicle as the center point; analyzing and processing the second image data to identify the pet type of the pet adjacent to the vehicle; determining whether the pet type of the pet in the vehicle and the pet type of the pet adjacent to the vehicle are the same; if the two are the same, triggering a pet interaction reminder for the pet in the vehicle to interact with the pet adjacent to the vehicle. This application can realize the interaction between the pet in the vehicle and the pet outside the vehicle while the vehicle is driving, adding to the fun of pet travel.

Description

Technical Field

[0001] The present application relates to the field of automotive technology, and in particular to a vehicle pet mode control method, device, equipment and computer-readable storage medium. Background Art

[0002] Currently, more and more people are keeping pets, which has led to many scenarios where pets are needed for travel. To address similar scenarios, new energy vehicles have successively launched scenario modes that meet user needs, namely pet modes. In related technologies, after turning on pet mode, the driver and passengers get off the vehicle and keep the vehicle powered on. The vehicle will automatically adjust the air conditioning and lighting to take care of the pet, ensuring that the pet will not cause safety accidents in the car due to high temperatures in summer or low temperatures in winter, thereby protecting the safety of the pets in the car. However, this pet mode only provides care for pets when they are left alone in the car while parked, and cannot add fun to pet travel while the vehicle is in motion. Summary of the Invention

[0003] The present application provides a vehicle pet mode control method, device, equipment and computer-readable storage medium, which can solve the technical problem that the existing pet mode in the prior art only provides care for pets when the pet is left alone in the car when parked, and cannot add fun to the pet's travel during the vehicle's driving.

[0004] In a first aspect, an embodiment of the present application provides a vehicle pet mode control method, the vehicle pet mode control method comprising:

[0005] During the driving of the vehicle, if it is detected that the pet mode is turned on, target data of the pet in the vehicle is obtained, the target data including first image data;

[0006] Analyzing and processing the target data to identify the pet type of the pet in the vehicle;

[0007] Acquire second image data of a pet adjacent to the vehicle within a preset radius with the vehicle as the center point;

[0008] analyzing and processing the second image data to identify the pet type of the pet adjacent to the vehicle;

[0009] Determining whether the pet type of the pet in the own vehicle and the pet type of the pet adjacent to the own vehicle are the same;

[0010] When the two are the same, a pet interaction reminder is triggered so that the pet in the vehicle can interact with the pet adjacent to the vehicle.

[0011] In conjunction with the first aspect, in one embodiment, analyzing and processing the target data to identify the pet type of the pet in the vehicle includes:

[0012] Performing feature extraction on the first image data in the target data to obtain appearance features of the pet in the car;

[0013] Matching the appearance characteristics of the pet in the car with the basic information of the pet recorded in the cloud;

[0014] If the match is successful, the pet type identified from the pet in the car is the pet type recorded in the cloud.

[0015] In conjunction with the first aspect, in one embodiment, after the step of matching the appearance features of the pet in the vehicle with the basic information of the pet recorded in the cloud, the method further includes:

[0016] If the match is not successful, the appearance features of the pet in the car are input into the first pet type model, and the pet type of the pet in the car is output.

[0017] In conjunction with the first aspect, in one embodiment, analyzing and processing the second image data to identify the pet type of the pet adjacent to the vehicle includes:

[0018] performing feature extraction on the second image data to obtain appearance features of the pet adjacent to the vehicle;

[0019] The appearance features of the pets adjacent to the vehicle are input into the first pet type model, and the pet type of the pets adjacent to the vehicle is output.

[0020] In conjunction with the first aspect, in one implementation, the target data further includes first audio data;

[0021] Accordingly, the target data is analyzed and processed to identify the pet type of the pet in the vehicle, including:

[0022] Performing feature extraction on the first image data in the target data to obtain appearance features of the pet in the car;

[0023] Performing feature extraction on the first audio data in the target data to obtain a sound feature of a pet in the car;

[0024] Matching the appearance and sound characteristics of the pet in the car with the basic information of the pet recorded in the cloud;

[0025] If the match is successful, the pet type identified from the pet in the car is the pet type recorded in the cloud.

[0026] In conjunction with the first aspect, in one embodiment, after the step of matching the appearance characteristics and sound characteristics of the pet in the car with the basic information of the pet recorded in the cloud, the method further includes:

[0027] If the match is not successful, the appearance features and sound features of the pet in the car are input into the second pet type model, and the pet type of the pet in the car is output.

[0028] In combination with the first aspect, in one embodiment, the method of triggering the pet interaction reminder includes: voice broadcast, graphic display and flashing of the light strip in the car.

[0029] In a second aspect, an embodiment of the present application provides a vehicle pet mode control device, the vehicle pet mode control device comprising:

[0030] A first acquisition module is configured to acquire target data of a pet in the vehicle when the pet mode is detected to be turned on during the vehicle's driving, wherein the target data includes first image data;

[0031] a first identification module, configured to analyze and process the target data to identify the pet type of the pet in the vehicle;

[0032] A second acquisition module is configured to acquire second image data of a pet adjacent to the vehicle within a preset radius with the vehicle as the center point;

[0033] a second recognition module, configured to analyze and process the second image data to identify a pet type of a pet adjacent to the vehicle;

[0034] a judgment module, configured to judge whether the pet type of the pet in the vehicle is the same as the pet type of the pet adjacent to the vehicle;

[0035] The trigger module is used to trigger a pet interaction reminder when the two are the same, so that the pet in the vehicle and the pet adjacent to the vehicle can interact.

[0036] In the third aspect, an embodiment of the present application provides a vehicle pet mode control device, which includes a processor, a memory, and a vehicle pet mode control program stored on the memory and executable by the processor, wherein when the vehicle pet mode control program is executed by the processor, the steps of the vehicle pet mode control method as described in any one of the first aspects are implemented.

[0037] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a vehicle pet mode control program is stored, wherein when the vehicle pet mode control program is executed by a processor, the steps of the vehicle pet mode control method as described in any one of the first aspects are implemented.

[0038] The beneficial effects of the technical solutions provided in the embodiments of the present application include:

[0039] During vehicle driving, if it is detected that the pet mode is turned on, the target data of the pet in the vehicle is obtained, and the target data includes first image data; the target data is analyzed and processed to identify the pet type of the pet in the vehicle; then, within a preset radius with the vehicle as the center point, second image data of the pet adjacent to the vehicle is obtained; and the second image data is analyzed and processed to identify the pet type of the pet adjacent to the vehicle; it is further determined whether the pet type of the pet in the vehicle and the pet type of the pet adjacent to the vehicle are the same; if the two are the same, a pet interaction reminder is triggered for the pet in the vehicle to interact with the pet adjacent to the vehicle. The present application provides a personalized pet mode, which can realize the interaction between the pet in the vehicle and the pet outside the vehicle during vehicle driving, thereby increasing the fun of pet travel. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a flow chart of the first embodiment of the vehicle pet mode control method of the present application;

[0041] Figure 2 This is a functional module diagram of an embodiment of a vehicle pet mode control device of the present application;

[0042] Figure 3 This is a schematic diagram of the hardware structure of the vehicle pet mode control device involved in the embodiment of the present application. DETAILED DESCRIPTION

[0043] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0044] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0045] In a first aspect, an embodiment of the present application provides a vehicle pet mode control method, which is applied to a vehicle having cameras arranged on the left and right sides of the vehicle body. Preferably, the cameras are arranged on the B-pillars on the left and right sides of the vehicle, with at least one arranged on each side.

[0046] In one embodiment, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the vehicle pet mode control method of this application. Figure 1 As shown, the vehicle pet mode control method includes:

[0047] Step 110: While the vehicle is traveling, if it is detected that the pet mode is turned on, obtaining target data of the pet in the vehicle, wherein the target data includes first image data;

[0048] In specific implementation, while the vehicle is in motion, the driver or passenger can activate the pet mode of this application through various methods such as voice, manual operation, automatic triggering of scene mode, etc. After the vehicle detects that the pet mode is activated, the vehicle collects target data from the pet in the vehicle through the camera, microphone, etc. in the vehicle, and the target data includes first video data, first image data, and first audio data.

[0049] Step 120: Analyze and process the target data to identify the pet type of the pet in the vehicle;

[0050] After acquiring the target data, the target data is uploaded to the cloud. The cloud can perform pre-processing on the target data, such as denoising and filtering, and then perform feature extraction on the pre-processed target data to identify the type of the pet in the vehicle. Pet types include, but are not limited to, cats and dogs. After the cloud identifies the type of the pet in the vehicle, the cloud transmits the information to the vehicle.

[0051] Step 130: Acquire second image data of a pet adjacent to the vehicle within a preset radius with the vehicle as the center point;

[0052] Specifically, within a preset radius centered on the vehicle, second image data of pets adjacent to the vehicle is captured using cameras positioned on the left and right exteriors of the vehicle. The pets adjacent to the vehicle can be inside a vehicle in an adjacent lane or on the side of the road. It will be appreciated that if a vehicle is detected in an adjacent lane with its windows open within the preset radius centered on the vehicle, the exterior cameras will then capture second image data of the pets adjacent to the vehicle.

[0053] Step 140: Analyze and process the second image data to identify the pet type of the pet adjacent to the vehicle;

[0054] Similarly, after obtaining second image data of a pet adjacent to the vehicle, the second image data is uploaded to the cloud. The cloud can perform pre-processing such as denoising and filtering on the second image data, and then perform feature extraction on the pre-processed second image data to identify the pet type adjacent to the vehicle. After the cloud identifies the pet type adjacent to the vehicle, the cloud transmits the data to the vehicle.

[0055] Step 150: Determine whether the pet type of the pet in the vehicle is the same as the pet type of the pet adjacent to the vehicle;

[0056] Step 160: If the two are the same, trigger a pet interaction reminder to allow the pet in the vehicle to interact with the pet adjacent to the vehicle.

[0057] Furthermore, the vehicle determines whether the pet type of the pet inside the vehicle is the same as the pet type of the adjacent pet, such as cat-cat or dog-dog. If the two are the same, the vehicle triggers a pet interaction reminder to alert the vehicle occupants and provides a rough location of the pet outside the vehicle, such as the left front / left / right / right front / right rear of the vehicle. The pet interaction reminder can be triggered by voice announcement, graphic display, flashing interior lights, etc., or any user-defined method.

[0058] After receiving the pet interaction reminder, the passengers in the car can find the location of the pet outside the car through the car window, then open the car window, hug the pet and greet the pet outside the car.

[0059] In this embodiment, during the driving of the vehicle, if it is detected that the pet mode is turned on, the target data of the pet in the vehicle is obtained, and the target data includes first image data; and the target data is analyzed and processed to identify the pet type of the pet in the vehicle; then, within a preset radius with the vehicle as the center point, second image data of the pet adjacent to the vehicle is obtained; and the second image data is analyzed and processed to identify the pet type of the pet adjacent to the vehicle; and it is further determined whether the pet type of the pet in the vehicle and the pet type of the pet adjacent to the vehicle are the same; if the two are the same, a pet interaction reminder is triggered for the pet in the vehicle and the pet adjacent to the vehicle to interact. The present application provides a personalized pet mode, which can realize the interaction between the pet in the vehicle and the pet outside the vehicle during the driving of the vehicle, thereby increasing the fun of pet travel.

[0060] Furthermore, in one embodiment, the analyzing and processing the target data to identify the pet type of the pet in the vehicle includes:

[0061] Step 210: extract features from the first image data in the target data to obtain appearance features of the pet in the car;

[0062] It should be noted that if the collected target data is first video data, the first image data needs to be extracted from the first video data.

[0063] The first image data in the target data is subjected to shape, fur color and other features extraction to obtain the shape, fur color and other appearance features of the pet in the car.

[0064] Step 220: Match the appearance characteristics of the pet in the vehicle with the basic information of the pet recorded in the cloud;

[0065] Passengers in the car can enter the pet type and basic information of their pets, such as coat color, appearance, voiceprint, etc., into the cloud in advance.

[0066] By matching the appearance features of the pet in the car with the basic pet information recorded in the cloud item by item, the efficiency of determining the pet type of the pet in the car can be improved when the pet in the car is a pet raised by the car passengers.

[0067] Step 230: If the match is successful, the pet type of the pet in the car is identified as the pet type recorded in the cloud.

[0068] In specific implementation, if the appearance characteristics of the pet in the car match the basic information of the pet recorded in the cloud, the pet type of the pet in the car is identified as the pet type recorded in the cloud. It can also be understood that the pet in the car is a pet raised by the passengers in the car.

[0069] In this embodiment, feature extraction is performed on the first image data in the target data to obtain the appearance features of the pet in the car, and the appearance features of the pet in the car are matched with the basic information of the pet recorded in the cloud. If the match is successful, the pet type of the pet in the car is identified as the pet type recorded in the cloud. This can improve the efficiency of determining the pet type of the pet in the car when the pet in the car is a pet raised by the passengers in the car.

[0070] Furthermore, in one embodiment, after the step of matching the appearance features of the pet in the vehicle with the basic information of the pet recorded in the cloud, the method further includes:

[0071] If the match is not successful, the appearance features of the pet in the car are input into the first pet type model, and the pet type of the pet in the car is output.

[0072] The first pet type model is a model implemented based on a neural network and is used to determine the pet type.

[0073] Furthermore, if the appearance features of the pet in the car do not match the basic pet information recorded in the cloud, the appearance features of the pet in the car are input into the first pet type model to output the pet type of the pet in the car.

[0074] At the same time, the appearance characteristics and pet types of pets in the car can be entered into the cloud to achieve recording and archiving in the cloud, so as to automatically identify and retrieve existing records later.

[0075] In this embodiment, if the match is not successful, the appearance features of the pet in the car are input into the first pet type model, and the pet type of the pet in the car is output, so that when the pet in the car is not a pet raised by the passengers in the car, the pet type of the pet in the car can be quickly determined.

[0076] Furthermore, in one embodiment, the analyzing and processing the second image data to identify the pet type of the pet adjacent to the vehicle includes:

[0077] Step 310: performing feature extraction on the second image data to obtain appearance features of the pet adjacent to the vehicle;

[0078] Step 320: Input the appearance features of the pet adjacent to the vehicle into the first pet type model, and output the pet type of the pet adjacent to the vehicle.

[0079] Specifically, the second image data is subjected to shape, fur color and other features extraction to obtain the shape, fur color and other appearance features of the pet adjacent to the vehicle; then the shape, fur color and other appearance features of the pet adjacent to the vehicle are input into the first pet type model to output the pet type of the pet adjacent to the vehicle.

[0080] In this embodiment, by performing feature extraction on the second image data, the appearance features of the pet adjacent to the vehicle are obtained; then the appearance features of the pet adjacent to the vehicle are input into the first pet type model, and the pet type of the pet adjacent to the vehicle is output. The pet type is determined using a model implemented by a neural network, which can improve the efficiency of determining the pet type.

[0081] Furthermore, in one embodiment, the target data further includes first audio data;

[0082] Accordingly, the target data is analyzed and processed to identify the pet type of the pet in the vehicle, including:

[0083] Step 410: extract features from the first image data in the target data to obtain appearance features of the pet in the car;

[0084] During specific implementation, the first image data in the target data is subjected to shape, fur color and other features extraction to obtain the appearance features of the pet in the car, such as the shape and fur color.

[0085] Step 420: Extract features from the first audio data in the target data to obtain sound features of the pet in the car.

[0086] The first audio data in the target data is subjected to voiceprint, frequency and other feature extraction to obtain the voiceprint, frequency and other sound features of the pet in the car.

[0087] Step 430: Match the appearance and sound characteristics of the pet in the car with the basic information of the pet recorded in the cloud;

[0088] Furthermore, the appearance and sound characteristics of the pet in the car are matched item by item with the basic information of the pet recorded in the cloud. When the acquired image data is unclear, the pet type can be determined in combination with the audio data, which can improve the accuracy and efficiency of determining the pet type.

[0089] Step 440: If the match is successful, the pet type of the pet in the car is identified as the pet type recorded in the cloud.

[0090] If the appearance and sound characteristics of the pet in the car successfully match the basic information of the pet recorded in the cloud, the pet type of the pet in the car is identified as the pet type recorded in the cloud. It can also be understood that the pet in the car is a pet raised by the passengers in the car.

[0091] In this embodiment, by performing feature extraction on the first image data in the target data, the appearance features of the pet in the car are obtained; and by performing feature extraction on the first audio data in the target data, the sound features of the pet in the car are obtained; the appearance features and sound features of the pet in the car are further matched with the basic information of the pet recorded in the cloud; if the match is successful, the pet type of the pet in the car is identified as the pet type recorded in the cloud; this can improve the efficiency of determining the pet type of the pet in the car when the pet in the car is a pet raised by the car passengers.

[0092] Furthermore, in one embodiment, after the step of matching the appearance characteristics and sound characteristics of the pet in the vehicle with the basic information of the pet recorded in the cloud, the method further includes:

[0093] If the match is not successful, the appearance features and sound features of the pet in the car are input into the second pet type model, and the pet type of the pet in the car is output.

[0094] The second pet type model is a model implemented based on a neural network and is used to determine the pet type.

[0095] Furthermore, if the appearance features and sound features of the pet in the car do not match the basic pet information recorded in the cloud, the appearance features and sound features of the pet in the car are input into the second pet type model to output the pet type of the pet in the car.

[0096] At the same time, the appearance characteristics and pet types of pets in the car can be entered into the cloud to achieve recording and archiving in the cloud, so as to automatically identify and retrieve existing records later.

[0097] In this embodiment, if the match is not successful, the appearance characteristics and sound characteristics of the pet in the car are input into the second pet type model, and the pet type of the pet in the car is output, so that when the pet in the car is not a pet raised by the passengers in the car, the pet type of the pet in the car can be quickly determined.

[0098] In a second aspect, an embodiment of the present application also provides a vehicle pet mode control device.

[0099] In one embodiment, referring to Figure 2 , Figure 2 This is a functional module diagram of an embodiment of the vehicle pet mode control device of the present application. Figure 2 As shown, the vehicle pet mode control device 200 includes:

[0100] A first acquisition module 210 is configured to acquire target data of a pet in the vehicle when the pet mode is detected to be turned on during vehicle driving, wherein the target data includes first image data;

[0101] a first identification module 220 for analyzing and processing the target data to identify the pet type of the pet in the vehicle;

[0102] The second acquisition module 230 is configured to acquire second image data of a pet adjacent to the vehicle within a preset radius with the vehicle as the center point;

[0103] a second recognition module 240 for analyzing and processing the second image data to identify the pet type of the pet adjacent to the vehicle;

[0104] A determination module 250 is configured to determine whether the pet type of the pet in the vehicle is the same as the pet type of the pet adjacent to the vehicle;

[0105] The trigger module 260 is used to trigger a pet interaction reminder when the two are the same, so that the pet in the vehicle can interact with the pet adjacent to the vehicle.

[0106] Furthermore, in one embodiment, the first identification module 220 is specifically configured to:

[0107] Performing feature extraction on the first image data in the target data to obtain appearance features of the pet in the car;

[0108] Matching the appearance characteristics of the pet in the car with the basic information of the pet recorded in the cloud;

[0109] If the match is successful, the pet type identified from the pet in the car is the pet type recorded in the cloud.

[0110] Furthermore, in one embodiment, the first identification module 220 is specifically configured to:

[0111] If the match is not successful, the appearance features of the pet in the car are input into the first pet type model, and the pet type of the pet in the car is output.

[0112] Furthermore, in one embodiment, the second identification module 240 is specifically configured to:

[0113] performing feature extraction on the second image data to obtain appearance features of the pet adjacent to the vehicle;

[0114] The appearance features of the pets adjacent to the vehicle are input into the first pet type model, and the pet type of the pets adjacent to the vehicle is output.

[0115] Furthermore, in one embodiment, the target data further includes first audio data;

[0116] Accordingly, the first identification module 220 is specifically configured to:

[0117] Performing feature extraction on the first image data in the target data to obtain appearance features of the pet in the car;

[0118] Performing feature extraction on the first audio data in the target data to obtain a sound feature of a pet in the car;

[0119] Matching the appearance and sound characteristics of the pet in the car with the basic information of the pet recorded in the cloud;

[0120] If the match is successful, the pet type identified from the pet in the car is the pet type recorded in the cloud.

[0121] Furthermore, in one embodiment, the first identification module 220 is specifically configured to:

[0122] If the match is not successful, the appearance features and sound features of the pet in the car are input into the second pet type model, and the pet type of the pet in the car is output.

[0123] Furthermore, in one embodiment, the manner of triggering the pet interaction reminder includes: voice broadcast, graphic display, and flashing of the light strip inside the car.

[0124] Among them, the functional implementation of each module in the above-mentioned vehicle pet mode control device corresponds to the various steps in the above-mentioned vehicle pet mode control method embodiment, and its functions and implementation processes will not be repeated here one by one.

[0125] In a third aspect, an embodiment of the present application provides a vehicle pet mode control device, which may be a personal computer (PC), a laptop computer, a server, or other device with data processing capabilities.

[0126] Reference Figure 3 , Figure 3FIG2 is a hardware structure diagram of a vehicle pet mode control device involved in an embodiment of the present application. In the embodiment of the present application, the vehicle pet mode control device may include a processor, a memory, a communication interface, and a communication bus.

[0127] The communication bus may be of any type and is used to interconnect the processor, memory, and communication interface.

[0128] Communication interfaces include input / output (I / O) interfaces, physical interfaces, and logical interfaces, used to interconnect components within the vehicle pet mode control device, as well as interfaces used to interconnect the vehicle pet mode control device with other devices (e.g., other computing devices or user devices). Physical interfaces can include Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc. User devices can include displays, keyboards, etc.

[0129] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0130] The processor may be a general-purpose processor that can call a vehicle pet mode control program stored in a memory and execute the vehicle pet mode control method provided in the embodiments of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the vehicle pet mode control program is called can be referenced to the various embodiments of the vehicle pet mode control method of the present application and will not be further described here.

[0131] Those skilled in the art will understand that Figure 3 The hardware structure shown in the figure does not constitute a limitation to the present application and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0132] In a fourth aspect, an embodiment of the present application also provides a computer-readable storage medium.

[0133] The computer-readable storage medium of the present application stores a vehicle pet mode control program, wherein when the vehicle pet mode control program is executed by the processor, the steps of the vehicle pet mode control method as described above are implemented.

[0134] Among them, the method implemented when the vehicle pet mode control program is executed can refer to the various embodiments of the vehicle pet mode control method of the present application, and will not be repeated here.

[0135] It should be noted that the serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0136] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings 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. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit the "first", "second" and "third" to different types.

[0137] In the description of the embodiments of this application, the words "exemplary," "for example," or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary," "for example," or "for example" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary," "for example," or "for example" is intended to present the relevant concepts in a concrete manner.

[0138] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0139] In some processes described in the embodiments of the present application, multiple operations or steps are included that appear in a specific order. However, it should be understood that these operations or steps may not be performed in the order in which they appear in the embodiments of the present application or may be performed in parallel. The sequence numbers of the operations are only used to distinguish between different operations, and the sequence numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations or steps may be performed in sequence or in parallel, and these operations or steps may be combined.

[0140] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device to execute the methods described in each embodiment of the present application.

[0141] The above are only preferred embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A vehicle pet mode control method, characterized in that: The vehicle pet mode control method includes: During the driving of the vehicle, if it is detected that the pet mode is turned on, target data of the pet in the vehicle is obtained, the target data including first image data; Analyzing and processing the target data to identify the pet type of the pet in the vehicle; Acquire second image data of a pet adjacent to the vehicle within a preset radius with the vehicle as the center point; analyzing and processing the second image data to identify the pet type of the pet adjacent to the vehicle; Determining whether the pet type of the pet in the own vehicle and the pet type of the pet adjacent to the own vehicle are the same; When the two are the same, a pet interaction reminder is triggered so that the pet in the vehicle can interact with the pet adjacent to the vehicle.

2. The vehicle pet mode control method according to claim 1, wherein: The analyzing and processing the target data to identify the pet type of the pet in the vehicle includes: Performing feature extraction on the first image data in the target data to obtain appearance features of the pet in the car; Matching the appearance characteristics of the pet in the car with the basic information of the pet recorded in the cloud; If the match is successful, the pet type identified from the pet in the car is the pet type recorded in the cloud.

3. The vehicle pet mode control method according to claim 2, wherein: After the step of matching the appearance features of the pet in the vehicle with the basic information of the pet recorded in the cloud, the method further includes: If the match is not successful, the appearance features of the pet in the car are input into the first pet type model, and the pet type of the pet in the car is output.

4. The vehicle pet mode control method according to claim 1, wherein: The analyzing and processing the second image data to identify the pet type of the pet adjacent to the vehicle includes: performing feature extraction on the second image data to obtain appearance features of the pet adjacent to the vehicle; The appearance features of the pets adjacent to the vehicle are input into the first pet type model, and the pet type of the pets adjacent to the vehicle is output.

5. The vehicle pet mode control method according to claim 1, wherein: The target data further includes first audio data; Accordingly, the target data is analyzed and processed to identify the pet type of the pet in the vehicle, including: Performing feature extraction on the first image data in the target data to obtain appearance features of the pet in the car; Performing feature extraction on the first audio data in the target data to obtain a sound feature of a pet in the car; Matching the appearance and sound characteristics of the pet in the car with the basic information of the pet recorded in the cloud; If the match is successful, the pet type identified from the pet in the car is the pet type recorded in the cloud.

6. The vehicle pet mode control method according to claim 5, characterized in that: After the step of matching the appearance and sound characteristics of the pet in the car with the basic information of the pet recorded in the cloud, the method further includes: If the match is not successful, the appearance features and sound features of the pet in the car are input into the second pet type model, and the pet type of the pet in the car is output.

7. The vehicle pet mode control method according to claim 1, wherein: The methods of triggering pet interaction reminders include: voice broadcast, graphic display, and flashing lights in the car.

8. A vehicle pet mode control device, characterized in that: The vehicle pet mode control device includes: A first acquisition module is configured to acquire target data of a pet in the vehicle when the pet mode is detected to be turned on during the vehicle's driving, wherein the target data includes first image data; a first identification module, configured to analyze and process the target data to identify the pet type of the pet in the vehicle; A second acquisition module is configured to acquire second image data of a pet adjacent to the vehicle within a preset radius with the vehicle as the center point; a second recognition module, configured to analyze and process the second image data to identify a pet type of a pet adjacent to the vehicle; a judgment module, configured to judge whether the pet type of the pet in the vehicle is the same as the pet type of the pet adjacent to the vehicle; The trigger module is used to trigger a pet interaction reminder when the two are the same, so that the pet in the vehicle and the pet adjacent to the vehicle can interact.

9. A vehicle pet mode control device, characterized in that: The vehicle pet mode control device includes a processor, a memory, and a vehicle pet mode control program stored on the memory and executable by the processor, wherein when the vehicle pet mode control program is executed by the processor, the steps of the vehicle pet mode control method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a vehicle pet mode control program, wherein when the vehicle pet mode control program is executed by a processor, the steps of the vehicle pet mode control method according to any one of claims 1 to 7 are implemented.

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