Multi-vehicle image processing method and device, electronic equipment and storage medium

Abstract

The invention provides a multi-vehicle image processing method and device, electronic equipment and a storage medium, and relates to the technical field of the Internet of Vehicles, and the method comprises the steps: broadcasting a first request through a first vehicle; in response to a first message from a second vehicle, loading a first image processing module of the first image processing model so as to perform image processing through cooperation of the first image processing module and the second vehicle, the second vehicle being used for loading a second image processing module of the first image processing model so as to perform image processing through cooperation of the first image processing module and the second vehicle; one of the first image processing module and the second image processing module is used for processing the input image data to obtain intermediate image data, and the other one of the first image processing module and the second image processing module is used for processing the intermediate image data to obtain output image data. The image processing effect can be improved through cooperative image processing of at least two vehicles.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle networking, and in particular, to a method, an apparatus, an electronic device, and a storage medium for image processing of multiple vehicles. Background Art

[0002] With the rapid development of vehicle networking, how to coordinate the capabilities between vehicles has become increasingly important.

[0003] In the related art, during the driving process of a vehicle, an image processing model is required to perform image processing on the captured image. For example, when the image collected by the vehicle is interfered by light, the image processing model processes the image interfered by light, so as to reduce the interference of light on the captured image and obtain a clearer image.

[0004] However, the performance of the vehicle is limited, resulting in poor image processing effects. Summary of the Invention

[0005] In view of this, an object of the present invention is to provide a method, an apparatus, an electronic device, and a storage medium for image processing of multiple vehicles to improve the effect of image processing.

[0006] In a first aspect, an embodiment of the present invention provides a method for image processing of multiple vehicles, which is applied to a first vehicle. The method includes: broadcasting a first request, where the first request is used to request a second vehicle within a preset range of the first vehicle to cooperate in image processing; in response to a first message from the second vehicle, loading a first image processing module of a first image processing model to cooperate with the second vehicle in image processing through the first image processing module, where the first message is a message sent by the second vehicle in response to the first request, the second vehicle is used to load a second image processing module of the first image processing model, the first image processing module is different from the second image processing module, and one of the first image processing module and the second image processing module is used to process input image data to obtain intermediate image data, and the other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data.

[0007] In a possible implementation manner, the method further includes: in the case of not receiving the first message from the second vehicle, loading a second image processing model and processing the input image data through the second image processing model to obtain third output image data, where the number of parameters of the second image processing model is less than the number of parameters of the first image processing model.

[0008] In a possible implementation, the first request carries the model identifier of the first image processing model, and the first message is a message sent by the second vehicle to the first vehicle when the first image processing model indicated by the model identifier is stored.

[0009] In a possible implementation, the first message carries the vehicle identification information of the second vehicle. Collaborating with the second vehicle for image processing through the first image processing module includes: establishing a communication channel with the second vehicle based on the vehicle identification information, where the communication channel is used to transmit image data; and collaborating with the second vehicle for image processing through the first image processing module and the communication channel.

[0010] In a possible implementation, collaborating with the second vehicle for image processing through the first image processing module includes at least one of the following: capturing the first input image data, processing the first input image data through the first image processing module to obtain the first intermediate image data, and receiving the first output image data from the second vehicle, where the first output image data is obtained by processing the first intermediate image data through the second image processing module loaded by the second vehicle; receiving the second input image data from the second vehicle, processing the second input image data through the first image processing module to obtain the second intermediate image data, and sending the second intermediate image data to the second vehicle so that the second vehicle processes the second intermediate image data through the second image processing module loaded by it to obtain the second output image data, where the second input image data is captured by the second vehicle.

[0011] In a possible implementation, the first message carries the second available resource information of the second vehicle, where the second available resource information is used to indicate the data processing capability of the second vehicle. In response to the first message from the second vehicle, the first image processing module that loads the first image processing model collaborates with the second vehicle for image processing, including: in response to the first message from the second vehicle, determining the first available resource information of the first vehicle, where the first available resource information is used to indicate the data processing capability of the first vehicle; based on the first available resource information and the second available resource information, sending a second message to the second vehicle, where the second message carries the module identifier of the second image processing module, so that the second vehicle loads the second image processing module based on the module identifier. Among them, if the data processing capability of the first vehicle is greater than that of the second vehicle, the number of parameters of the first image processing module is greater than that of the second image processing module; if the data processing capability of the first vehicle is less than that of the second vehicle, the number of parameters of the first image processing module is less than that of the second image processing module; and collaborating with the second image processing module loaded by the second vehicle through the first image processing module for image processing.

[0012] In a second aspect, an embodiment of the present invention provides another method for image processing of multiple vehicles, which is applied to a second vehicle. The method includes: receiving a first request broadcast by a first vehicle, where the first request is used to request collaborative image processing with a second vehicle within a preset range of the first vehicle; in response to the first request, sending a first message to the first vehicle, and loading a second image processing module of a first image processing model to perform collaborative image processing with the first vehicle through the second image processing module. The first vehicle is used to load a first image processing module of the first image processing model. The first image processing module is different from the second image processing module. One of the first image processing module and the second image processing module is used to process input image data to obtain intermediate image data, and the other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data.

[0013] In a third aspect, an embodiment of the present invention provides an apparatus for image processing of multiple vehicles, which is applied to a first vehicle. The apparatus includes: a broadcasting module, configured to broadcast a first request, where the first request is used to request collaborative image processing with a second vehicle within a preset range of the first vehicle; a first response module, configured to, in response to a first message from the second vehicle, load a first image processing module of a first image processing model to perform collaborative image processing with the second vehicle through the first image processing module. The first message is a message sent by the second vehicle in response to the first request. The second vehicle is used to load a second image processing module of the first image processing model. The first image processing module is different from the second image processing module. One of the first image processing module and the second image processing module is used to process input image data to obtain intermediate image data, and the other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data.

[0014] In a fourth aspect, an embodiment of the present invention further provides an apparatus for image processing of multiple vehicles, which is applied to a second vehicle. The apparatus includes: a receiving module, configured to receive a first request broadcast by a first vehicle, where the first request is used to request collaborative image processing with a second vehicle within a preset range of the first vehicle; a second response module, configured to, in response to the first request, send a first message to the first vehicle, and load a second image processing module of a first image processing model to perform collaborative image processing with the first vehicle through the second image processing module. The first vehicle is used to load a first image processing module of the first image processing model. The first image processing module is different from the second image processing module. One of the first image processing module and the second image processing module is used to process input image data to obtain intermediate image data, and the other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data.

[0015] In a fifth aspect, an embodiment of the present invention provides an electronic device, including a processor and a memory. The memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the method of the first aspect or the second aspect.

[0016] In a sixth aspect, an embodiment of the present invention provides a computer-readable storage medium storing computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions cause the processor to implement the method of the first aspect or the second aspect.

[0017] The embodiments of the present invention bring the following beneficial effects: The first vehicle broadcasts a first request for requesting to cooperate with a second vehicle within a preset range of the first vehicle for image processing; in response to a first message from the second vehicle, a first image processing module of the first image processing model is loaded to cooperate with the second vehicle for image processing through the first image processing module, where the first message is a message sent by the second vehicle in response to the first request, the second vehicle is used to load a second image processing module of the first image processing model, the first image processing module is different from the second image processing module, one of the first image processing module and the second image processing module is used to process input image data to obtain intermediate image data, and the other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data. In this way, image processing can be performed through the cooperation of at least two vehicles, and thus the effect of image processing can be improved.

[0018] Other features and advantages of the present invention will be described in the following description, and, in part, will be obvious from the description, or will be understood by implementing the present invention. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the description, the claims, and the drawings.

[0019] To make the above objectives, features, and advantages of the present invention more obvious and understandable, the following specific preferred embodiments are given, and in conjunction with the accompanying drawings, the detailed description is as follows. Description of the Drawings

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those skilled in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0021] Figure 1Schematic flowchart of a method for image processing of multiple vehicles provided by an embodiment of the present invention;

[0022] Figure 2 Schematic flowchart of another method for image processing of multiple vehicles provided by an embodiment of the present invention;

[0023] Figure 3 Schematic structural diagram of a device for image processing of multiple vehicles provided by an embodiment of the present invention;

[0024] Figure 4 Schematic structural diagram of another device for image processing of multiple vehicles provided by an embodiment of the present invention;

[0025] Figure 5 Schematic structural diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0027] In the related art, during the driving process of a vehicle, an image processing model needs to be used to perform image processing on the captured image. For example, when the image collected by the vehicle is interfered by light, the image processing model processes the image interfered by light, thereby reducing the interference of light on the captured image and obtaining a clearer image.

[0028] However, since the performance of the vehicle is limited, the image processing effect of the image processing model running on the vehicle is also limited. As a result, the image processing effect will be poor. For example, the image processed by the model is not clear enough and there is still light interference. This will have a greater impact on the decision-making of vehicle autonomous driving.

[0029] It should be understood that the embodiments of the present invention are not limited to processing images interfered by light. The technical solutions of this embodiment can be used to perform enhancement processing on the input image to obtain the output image.

[0030] In view of this, the embodiments of the present invention provide a method, device, electronic device, and storage medium for image processing of multiple vehicles, which can improve the image processing effect.

[0031] To facilitate the understanding of this embodiment, an exemplary description of the application scenario of the embodiment of the present invention is first provided. In this embodiment, it is applicable to multiple vehicles and is used for the scenario of collaborative image processing of multiple vehicles.

[0032] Please refer to Figure 1 , Figure 1 A method for image processing of multiple vehicles provided by an embodiment of the present invention. This method can be applied to a first vehicle and may include:

[0033] S110. Broadcast a first request, where the first request is used to request to collaborate with a second vehicle within a preset range of the first vehicle for image processing.

[0034] Among them, the first vehicle and the second vehicle are different vehicles. The preset range is related to the broadcast range ability of the first vehicle. Generally speaking, the preset range can be within the broadcast range ability of the first vehicle. The image processing in this embodiment can be, for example, image enhancement processing, such as image denoising processing.

[0035] S120. In response to a first message from the second vehicle, load the first image processing module of the first image processing model to collaborate with the second vehicle for image processing through the first image processing module. The second vehicle is used to load the second image processing module of the first image processing model. One of the first image processing module and the second image processing module is used to process the input image data to obtain intermediate image data, and the other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data.

[0036] Among them, the first message is a message sent by the second vehicle in response to the first request. It can be understood that the first message is a response message to the first request. The first image processing module is different from the second image processing module. The first image processing module may include one or more modules. The second image processing module may include one or more modules.

[0037] In this embodiment, the first image processing module and the second image processing module may be two adjacent modules in the first image processing model. For example, the first image processing module is the module before the second image processing module, that is to say, the output of the first image processing module is used as the input of the second image processing module. Or, the second image processing module is the module before the first image processing module, that is to say, the output of the second image processing module is used as the input of the first image processing module. Optionally, the output image data may be the data of the finally output image, such as the denoised image data.

[0038] It should be noted that the first image processing model may include a first image processing module and a second image processing module, and may also include other modules. That is to say, the first image processing module and the second image processing module constitute part or all of the modules of the first image processing model.

[0039] It should be understood that generally, the larger the number of parameters of a model, the better the processing effect of the model. For an image processing model, the larger the number of parameters of the image processing model, the better the image processing effect of the image processing model. In this embodiment, by loading the first image processing module by the first vehicle and loading the second image processing module by the second vehicle, the data processing capabilities of the first vehicle and the second vehicle are coordinated, and an image processing model with a larger number of parameters and stronger performance can be loaded.

[0040] In this embodiment, the first vehicle broadcasts a first request; in response to a first message from the second vehicle, the first image processing module of the first image processing model is loaded to perform image processing in cooperation with the second vehicle through the first image processing module. The second vehicle is used to load the second image processing module of the first image processing model. One of the first image processing module and the second image processing module is used to process the input image data to obtain intermediate image data, and the other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data. In this way, image processing can be performed in cooperation by at least two vehicles, and in this way, the effect of image processing can be improved.

[0041] Exemplarily, the first image processing model may include a feature extraction module, a convolution module, a pooling module, a fully connected module, and an activation function module. Among them, the feature extraction module includes one or more feature extraction layers. The convolution module includes one or more convolutional layers. The pooling module includes one or more pooling layers. The fully connected module includes one or more fully connected layers. The activation function module includes one or more activation function layers. Among them, the feature extraction layer is used to extract features related to the image content from the image. The convolutional layer is used to extract local features of the image, such as edges, textures, etc., through convolution operations. Pooling layer: Reduces the size of the feature map through downsampling operations, thereby reducing the amount of computation and overfitting problems, and at the same time extracts global features, such as shape, size, etc. Fully connected layer: Converts the feature map into a vector and performs a non-linear transformation through an activation function to obtain the output result. Activation function: Implements non-linear transformation to enable the model to learn complex patterns and rules. Exemplarily, the first image processing module may include a feature extraction layer, and the second image processing module may include a convolution module, a pooling module, a fully connected module, and an activation function module.

[0042] It should be noted that the first message in this embodiment can be one or more, and one or more first messages come from one or more second vehicles. In this embodiment, if multiple messages are received, the second vehicle with the strongest data processing ability can be selected from multiple second vehicles to cooperate in image processing. Optionally, the available resource information of the second vehicle is carried in the first message, and the greater the available resource information, the stronger the data processing ability. Then, based on the second available resource information of each second vehicle, the second vehicle with the strongest data processing ability can be selected to cooperate in image processing. In addition, the second vehicle with the weakest data processing ability can also be selected to cooperate in image processing. Or, select one of the second vehicles that can meet the requirement of loading and running the first image processing model to cooperate in image processing, which is not limited here.

[0043] In a possible implementation manner, the method further includes:

[0044] In the case where the first message from the second vehicle is not received, load the second image processing model, and process the input image data through the second image processing model to obtain the third output image data, where the number of parameters of the second image processing model is less than the number of parameters of the first image processing model.

[0045] Among them, the third output image data can be the data obtained by the second image processing model processing the input image data.

[0046] In this embodiment, since the number of parameters of the second image processing model is less than the number of parameters of the first image processing model, the processing effect of the second image processing model is worse.

[0047] Exemplarily, it can be that the number of model layers of the second image processing model is less than the number of model layers of the first image processing model. For example, the number of feature extraction layers in the second image processing model is less than the number of feature extraction layers in the first image processing model. Or, for example, the number of layers of other modules is less, which is not limited here.

[0048] In this embodiment, in the case where the first message from the second vehicle is not received, load the second image processing model, and process the input image data through the second image processing model to obtain the third output image data. In this way, it can ensure that the input image data is enhanced processed, and thus the success rate of image processing can be improved.

[0049] In another possible implementation manner, in the case where the first message from the second vehicle is not received, the first request can be re-broadcast until the first message from the second vehicle is received.

[0050] In a possible implementation, the first request carries the model identifier of the first image processing model, and the first message is a message sent by the second vehicle to the first vehicle when the second vehicle stores the first image processing model indicated by the model identifier.

[0051] In this embodiment, the second vehicle sends the first message to the first vehicle in response to the first request only when it stores the first image processing model indicated by the model identifier. In this way, the second vehicle can also load the second image processing module of the first image processing model from the local in a timely manner, which can reduce the time for loading the second image processing module and improve the efficiency of image processing.

[0052] In another possible implementation, each module of the first image processing model can also be stored in the server. If the second vehicle agrees to cooperate with the first vehicle in image processing, it sends the first message to the first vehicle and obtains the second image processing module of the first image processing model from the server.

[0053] In a possible implementation, the first message carries the vehicle identification information of the second vehicle. Cooperating with the second vehicle in image processing through the first image processing module includes:

[0054] Establishing a communication channel with the second vehicle based on the vehicle identification information, where the communication channel is used to transmit image data; and cooperating with the second vehicle in image processing through the first image processing module and the communication channel.

[0055] In this embodiment, based on the vehicle identification information of the second vehicle, the communication channel with the second vehicle, and cooperating with the second vehicle in image processing through this communication channel, in this way, image processing can be carried out through a dedicated channel, which can improve the security and efficiency of image processing.

[0056] In a possible implementation, cooperating with the second vehicle in image processing through the first image processing module includes at least one of the following:

[0057] Capturing the first input image data, processing the first input image data through the first image processing module to obtain the first intermediate image data, and receiving the first output image data from the second vehicle, where the first output image data is obtained by processing the first intermediate image data by the second image processing module loaded by the second vehicle;

[0058] Receive second input image data from a second vehicle, process the second input image data through a first image processing module to obtain second intermediate image data, and send the second intermediate image data to the second vehicle, so that the second vehicle processes the second intermediate image data through a second image processing module loaded thereon to obtain second output image data, where the second input image data is captured by the second vehicle.

[0059] In this embodiment, when the first vehicle and the second vehicle cooperate in image processing, the first vehicle can fixedly load a first image processing module, and the second vehicle can fixedly load a second image processing module.

[0060] For the first vehicle, the first vehicle captures first input image data, then processes the first input image data through the first image processing module to obtain first intermediate image data. Then, the first vehicle sends the first intermediate image data to the second vehicle, and the second vehicle processes the first intermediate image data based on the second image processing module loaded thereon to obtain first output image data. The image corresponding to the first output image data can be understood as an enhanced processing of the image corresponding to the first input image data.

[0061] For the second vehicle, the second vehicle captures second input image data, then sends the second input image data to the first vehicle. The first vehicle processes the second input image data based on the first image processing module loaded thereon to obtain second intermediate image data, and then the first vehicle sends the second intermediate image data to the second vehicle. Then, the second vehicle processes the second intermediate image data based on the second image processing module loaded thereon to obtain second output image data. The image corresponding to the second output image data can be understood as an enhanced processing of the image corresponding to the second input image data.

[0062] In the technical solution of this embodiment, when the first vehicle and the second vehicle cooperate in image processing, the first vehicle can fixedly load a first image processing module, and the second vehicle can fixedly load a second image processing module. This can reduce the latency caused by the first vehicle and the second vehicle loading new image processing modules, thereby improving the efficiency of cooperative image processing.

[0063] In another possible implementation, it is also possible that the second image processing module is before the first image processing module. Just swap the steps executed by the first vehicle and the second vehicle, and details are not described here.

[0064] In another possible implementation, when the first vehicle and the second vehicle cooperate in image processing, the image processing modules loaded by the first vehicle and the second vehicle can be variable. For example, when processing the first input image data, the first vehicle loads the first image processing module, and the second vehicle loads the second image processing module. When processing the second input image data, the first vehicle loads the second image processing module, and the second vehicle loads the first image processing module.

[0065] In a possible implementation, the first message carries the second available resource information of the second vehicle, and the second available resource information is used to indicate the data processing capability of the second vehicle. In response to the first message from the second vehicle, the first image processing module that loads the first image processing model is used to cooperate with the second vehicle in image processing, including:

[0066] In response to the first message from the second vehicle, determine the first available resource information of the first vehicle, and the first available resource information is used to indicate the data processing capability of the first vehicle shown;

[0067] Based on the first available resource information and the second available resource information, send a second message to the second vehicle. The second message carries the module identifier of the second image processing module, so that the second vehicle loads the second image processing module based on the module identifier. Among them, if the data processing capability of the first vehicle is greater than that of the second vehicle, the number of parameters of the first image processing module is greater than that of the second image processing module. If the data processing capability of the first vehicle is less than that of the second vehicle, the number of parameters of the first image processing module is less than that of the second image processing module;

[0068] Cooperate with the second image processing module loaded by the second vehicle through the first image processing module for image processing.

[0069] Among them, the resource information can include but is not limited to the number of cores, frequency, or video memory, etc. In this embodiment, the available resource information can also be referred to as the remaining resource information, and the available resource information is less than or equal to the maximum resource information. In this embodiment, the available resource information can be the product result of the maximum resource information and the resource utilization rate. Among them, the number of cores, frequency, and video memory can be the total resource information of one or more processors of the vehicle. In this embodiment, among the first vehicle and the second vehicle, the party with stronger data processing ability loads a module with a larger number of parameters, while the party with weaker data processing ability loads a module with a smaller number of parameters. In this way, the performance of the first vehicle and the second vehicle can be better exerted, and the efficiency of image processing can be improved.

[0070] In this embodiment, the first message may carry the second available resource information of the second vehicle. Then, the first vehicle may determine the modules respectively loaded by the first vehicle and the second vehicle based on its first available resource information and the second available resource information.

[0071] In another possible implementation, it may also be that the first request carries the first available resource information. Then, the second vehicle makes a decision on the first image processing model to be loaded based on the first available resource information and the second available resource information, or makes a decision on the specific modules in the first image processing module loaded by the first vehicle, and makes a decision on the specific modules in the second image processing module loaded by the second vehicle.

[0072] It should be noted that for how the second vehicle makes a decision on the first image processing model, or makes a decision on the first image processing module and the second image processing module, reference may be made to the description of how the first vehicle makes a decision on the first image processing model, or makes a decision on the first image processing module and the second image processing module, which will not be elaborated here.

[0073] The above embodiments have been described with the first vehicle as the execution subject. The following embodiments will be described with the second vehicle as the execution subject.

[0074] In another possible implementation, the first image processing model may be determined through negotiation between the first vehicle and the second vehicle. For example, according to the sum of the available resource information of the first vehicle and the second vehicle, the first image processing model is determined from multiple preset image processing models. Specifically, if the sum of the available resource information is greater than the number of parameters required to load and run the preset image processing model, the first image processing model may be the preset image processing model with the largest number of parameters among the preset image processing models that can be recorded and run by the sum of the available resource information, so as to give full play to the available resource information of the first vehicle and the second vehicle as much as possible.

[0075] Please refer to Figure 2 , Figure 2 Another method for image processing of multiple vehicles provided by an embodiment of the present invention. This method may be applied to the second vehicle. As Figure 2 shown, the method may include:

[0076] S210. Receive a first request broadcast by the first vehicle. The first request is used to request to cooperate with a second vehicle within a preset range of the first vehicle for image processing.

[0077] S220. In response to the first request, send a first message to the first vehicle and load a second image processing module of the first image processing model, so as to cooperate with the first vehicle to perform image processing through the second image processing module. The first vehicle is used to load a first image processing module of the first image processing model. One of the first image processing module and the second image processing module is used to process the input image data to obtain intermediate image data, and the other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data.

[0078] In this embodiment, the second vehicle receives the first request broadcast by the first vehicle. In response to the first request, the second vehicle sends a first message to the first vehicle and loads a second image processing module of the first image processing model, so as to cooperate with the first vehicle to perform image processing through the second image processing module. The first vehicle is used to load a first image processing module of the first image processing model. One of the first image processing module and the second image processing module is used to process the input image data to obtain intermediate image data, and the other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data. In this way, image processing can be performed cooperatively by at least two vehicles, and thus the effect of image processing can be improved.

[0079] It should be understood that the steps performed by the second vehicle can refer to the description of the above embodiments and will not be elaborated here.

[0080] Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of an image processing device for multiple vehicles provided by an embodiment of the present invention. As Figure 3 shown, the image processing device for multiple vehicles is applied to the first vehicle. The device may include:

[0081] A broadcast module 310, configured to broadcast a first request, where the first request is used to request to cooperate with a second vehicle within a preset range of the first vehicle to perform image processing; a first response module 320, configured to, in response to a first message from the second vehicle, load a first image processing module of the first image processing model, so as to cooperate with the second vehicle to perform image processing through the first image processing module, where the first message is a message sent by the second vehicle in response to the first request, the second vehicle is used to load a second image processing module of the first image processing model, the first image processing module is different from the second image processing module, one of the first image processing module and the second image processing module is used to process the input image data to obtain intermediate image data, and the other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data.

[0082] Please refer to Figure 4 , Figure 4 , which is a schematic structural diagram of an apparatus for image processing of multiple vehicles provided by an embodiment of the present invention. As Figure 4 shown, the apparatus for image processing of multiple vehicles is applied to a second vehicle, and the apparatus may include:

[0083] A receiving module 410, configured to receive a first request broadcast by a first vehicle, where the first request is used to request to cooperate with a second vehicle within a preset range of the first vehicle to perform image processing; a second response module 420, configured to, in response to the first request, send a first message to the first vehicle, and load a second image processing module of a first image processing model, so as to cooperate with the first vehicle to perform image processing through the second image processing module. The first vehicle is configured to load a first image processing module of the first image processing model. The first image processing module is different from the second image processing module. One of the first image processing module and the second image processing module is configured to process input image data to obtain intermediate image data, and the other of the first image processing module and the second image processing module is configured to process the intermediate image data to obtain output image data.

[0084] The apparatus for image processing of multiple vehicles provided by the embodiment of the present invention has the same technical features as the method for image processing of multiple vehicles provided by the above embodiment, so it can also solve the same technical problems and achieve the same technical effects. The apparatus for image processing of multiple vehicles provided by the embodiment of the present invention may refer to the description of the above method embodiment and will not be elaborated herein.

[0085] This embodiment further provides an electronic device, including a processor and a memory. The memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the above method for image processing of multiple vehicles. The electronic device may be a server or a terminal device.

[0086] See Figure 5 shown, the electronic device includes a processor 100 and a memory 101. The memory 101 stores computer-executable instructions that can be executed by the processor 100, and the processor 100 executes the computer-executable instructions to implement the above method for image processing of multiple vehicles.

[0087] Furthermore, Figure 5 the electronic device shown further includes a bus 102 and a communication interface 103. The processor 100, the communication interface 103, and the memory 101 are connected through the bus 102.

[0088] Among them, the memory 101 may include high-speed random access memory (RAM), and may also include non-volatile memory, such as at least one disk memory. The communication connection between this system network element and at least one other network element is realized through at least one communication interface 103 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used. The bus 102 can be an ISA bus, a PCI bus, an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of easy representation, Figure 5 only a bidirectional arrow is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0089] The processor 100 may be an integrated circuit chip with signal processing capabilities. In the implementation process, the steps of the above method can be completed by the integrated logic circuit in the hardware of the processor 100 or instructions in software form. The above-mentioned processor 100 can be a general-purpose processor, including a central processing unit (CPU for short), a network processor (NP for short), etc.; it can also be a digital signal processor (DSP for short), an application specific integrated circuit (ASIC for short), a field-programmable gate array (FPGA for short), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present invention can be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the art such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, register, etc. This storage medium is located in the memory 101, and the processor 100 reads the information in the memory 101 and combines its hardware to complete the steps of the method in the foregoing embodiments.

[0090] The processor in the above electronic device can implement the steps in the method for image processing of multiple vehicles by executing computer-executable instructions.

[0091] This embodiment also provides a computer-readable storage medium storing computer-executable instructions, which, when called and executed by a processor, cause the processor to implement the above-described method for image processing of multiple vehicles.

[0092] The computer-executable instructions stored in the above computer-readable storage medium can, by executing the computer-executable instructions, implement the steps in the above-described method for image processing of multiple vehicles.

[0093] This embodiment also provides a computer program product, including program code, and the instructions included in the program code can be used to execute the methods in the foregoing method embodiments. For specific implementation, reference can be made to the method embodiments and will not be elaborated herein.

[0094] Those skilled in the art can clearly understand that, for the convenience and conciseness of description, the specific working processes of the above-described systems and devices can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0095] In addition, in the description of the embodiments of the present invention, unless otherwise clearly defined and limited, the terms "installation", "connection", and "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0096] If a function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or a part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in various embodiments of the present invention. The foregoing storage medium includes: various media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk, or an optical disc that can store program code.

[0097] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention. In addition, the terms "first", "second", and "third" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance.

[0098] Finally, it should be noted that the above embodiments are only specific embodiments of the present invention, used to illustrate the technical solutions of the present invention, rather than limiting it. The protection scope of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art within the technical scope disclosed by the present invention can still modify the technical solutions described in the foregoing embodiments, or can easily think of changes, or make equivalent replacements for some of the technical features; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for multi-vehicle image processing, characterized in that: Applied to a first vehicle, the method comprises: broadcasting a first request, wherein the first request is used to request collaborative image processing with a second vehicle within a preset range of the first vehicle; In response to a first message from the second vehicle, a first image processing module of a first image processing model is loaded to perform image processing in collaboration with the second vehicle through the first image processing module, wherein the first message is a message sent by the second vehicle in response to the first request, and the second vehicle is used to load the second image processing module of the first image processing model, the first image processing module is different from the second image processing module, one of the first image processing module and the second image processing module is used to process input image data to obtain intermediate image data, and the other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data.

2. The method according to claim 1, characterized in that The first request carries a model identifier of the first image processing model, and the first message is a message sent by the second vehicle to the first vehicle when the second vehicle stores the first image processing model indicated by the model identifier.

3. The method according to claim 1, characterized in that The first message carries the vehicle identification information of the second vehicle, and the first image processing module cooperates with the second vehicle to perform image processing, including: Based on the vehicle identification information, establishing a communication channel with the second vehicle, wherein the communication channel is used to transmit image data; Image processing is performed in collaboration with the second vehicle through the first image processing module and the communication channel.

4. The method according to claim 3, characterized in that The first image processing module cooperates with the second vehicle to perform image processing, including at least one of the following: photographing to obtain first input image data, processing the first input image data by the first image processing module to obtain first intermediate image data, and receiving first output image data from the second vehicle, where the first output image data is obtained by processing the first intermediate image data by the second image processing module loaded on the second vehicle; Receive second input image data from the second vehicle, process the second input image data through the first image processing module to obtain second intermediate image data, and send the second intermediate image data to the second vehicle, so that the second vehicle processes the second intermediate image data through the second image processing module loaded thereon to obtain second output image data, wherein the second input image data is obtained by photographing the second vehicle.

5. The method according to claim 1, characterized in that The method further comprises: In the case where the first message from the second vehicle is not received, a second image processing model is loaded, and the input image data is processed by the second image processing model to obtain third output image data, wherein the number of parameters of the second image processing model is less than the number of parameters of the first image processing model.

6. The method according to any one of claims 1 to 5, characterized in that The first message carries second available resource information of the second vehicle, the second available resource information is used to indicate the data processing capability of the second vehicle, and in response to the first message from the second vehicle, loading a first image processing module of a first image processing model to perform image processing in collaboration with the second vehicle through the first image processing module, including: In response to a first message from the second vehicle, determining first available resource information of the first vehicle, the first available resource information being used to indicate a data processing capability of the first vehicle; Based on the first available resource information and the second available resource information, sending a second message to the second vehicle, the second message carrying a module identifier of the second image processing module, so that the second vehicle loads the second image processing module based on the module identifier, wherein if the data processing capability of the first vehicle is greater than the data processing capability of the second vehicle, the parameter amount of the first image processing module is greater than the parameter amount of the second image processing module, and if the data processing capability of the first vehicle is less than the data processing capability of the second vehicle, the parameter amount of the first image processing module is less than the parameter amount of the second image processing module; Image processing is performed collaboratively by the first image processing module and the second image processing module loaded on the second vehicle.

7. A method for multi-vehicle image processing, characterized in that: Applied to a second vehicle, the method comprises: receiving a first request broadcast by a first vehicle, the first request being used to request collaborative image processing with a second vehicle within a preset range of the first vehicle; In response to the first request, a first message is sent to the first vehicle, and a second image processing module of the first image processing model is loaded, so as to collaboratively perform image processing with the first vehicle through the second image processing module. The first vehicle is used to load the first image processing module of the first image processing model. The first image processing module is different from the second image processing module. One of the first image processing module and the second image processing module is used to process input image data to obtain intermediate image data. The other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data.

8. A device for multi-vehicle image processing, characterized in that: Applied to a first vehicle, the device comprises: a broadcast module, configured to broadcast a first request, wherein the first request is configured to request collaborative image processing with a second vehicle within a preset range of the first vehicle; A first response module is used to load the first image processing module of the first image processing model in response to a first message from the second vehicle, so as to cooperate with the second vehicle to perform image processing through the first image processing module, wherein the first message is a message sent by the second vehicle in response to the first request, and the second vehicle is used to load the second image processing module of the first image processing model, the first image processing module is different from the second image processing module, one of the first image processing module and the second image processing module is used to process the input image data to obtain intermediate image data, and the other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data.

9. A device for processing images of multiple vehicles, characterized in that: Applied to a second vehicle, the device comprises: A receiving module, configured to receive a first request broadcast by a first vehicle, wherein the first request is used to request to perform image processing in collaboration with a second vehicle within a preset range of the first vehicle; A second response module is used to respond to the first request, send a first message to the first vehicle, and load the second image processing module of the first image processing model to collaborate with the first vehicle to perform image processing through the second image processing module. The first vehicle is used to load the first image processing module of the first image processing model. The first image processing module is different from the second image processing module. One of the first image processing module and the second image processing module is used to process input image data to obtain intermediate image data. The other of the first image processing module and the second image processing module is used to process the intermediate image data to obtain output image data.

10. An electronic device, characterized in that: The invention comprises a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method according to any one of claims 1 to 6 or the method according to claim 7.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the method of any one of claims 1 to 6 or the method of claim 7.

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