Image display method, device and storage medium

Abstract

The application discloses an image display method, device and storage medium, and the image display method comprises the following steps: acquiring vehicle driving information of a target vehicle, and acquiring a risk score of the target vehicle according to the vehicle driving information; if the risk score meets a target condition, starting a target mini-program, and acquiring a vehicle driving image shot by a target vehicle event data recorder through the target mini-program, the target vehicle event data recorder being installed on the target vehicle; identifying the vehicle driving image, and determining whether the vehicle driving image contains a target object; when the vehicle driving image contains the target object, determining a target display ratio of the vehicle driving image according to the target object; and displaying the vehicle driving image based on the target display ratio. In the embodiment of the application, the vehicle driving image can be quickly browsed and played without downloading a special APP, the display effect of the vehicle driving image can be improved, and safe driving of the user can be facilitated.

Description

Technical Field

[0001] This application relates to the field of image display technology, specifically to an image display method, apparatus, and storage medium. Background Technology

[0002] A dashcam is a device that records video and audio information during a vehicle's journey. A dashcam installed in a vehicle can record video and audio of the entire driving process, providing evidence in case of traffic accidents. Small, screenless dashcams are increasingly popular due to their low cost and lack of obstruction of the user's view. However, because they lack a screen, users need to download a dedicated application (APP) or insert the dashcam's SD card into another device to view the recorded images, which is time-consuming and inconvenient. Summary of the Invention

[0003] This application provides an image display method, apparatus, and storage medium that allows for quick browsing and playback of vehicle driving images without the need to download a dedicated app, and can improve the display effect of vehicle driving images, helping users to drive safely.

[0004] On one hand, this application provides an image display method, the image display method comprising:

[0005] Obtain the vehicle driving information of the target vehicle, obtain the risk score of the target vehicle based on the vehicle driving information, and trigger the opening of the target mini-program if the risk score meets the target conditions;

[0006] If the risk score meets the target conditions, the target mini-program is activated, and the vehicle driving image captured by the target dashcam is obtained through the target mini-program. The target dashcam is installed on the target vehicle.

[0007] The vehicle driving image is identified to determine whether the vehicle driving image contains a target object;

[0008] When the vehicle driving image contains a target object, the target display ratio of the vehicle driving image is determined based on the target object;

[0009] The vehicle driving image is displayed based on the target display ratio.

[0010] In some embodiments of this application, before obtaining the vehicle driving information of the target vehicle, the method includes:

[0011] Get hotspot connection requests;

[0012] Based on the hotspot connection request, a request message for requesting a hotspot connection is sent to the target dashcam;

[0013] Receive hotspot information returned by the target dashcam based on the request message;

[0014] Based on the hotspot information, connect to the wireless network hotspot of the target dashcam.

[0015] In some embodiments of this application, the vehicle driving information includes vehicle speed, vehicle location, and driver information, and the step of obtaining a risk score based on the vehicle driving information includes:

[0016] A risk score is determined based on the vehicle's speed, location, and driver information.

[0017] If the risk score meets the target conditions, the target mini-program is activated, including:

[0018] The risk score is compared with a preset risk threshold. When the risk score is greater than the risk threshold, the target mini-program is activated.

[0019] In some embodiments of this application, the step of identifying the vehicle driving image and determining whether the vehicle driving image contains a target object includes:

[0020] The vehicle driving image is input into a trained target prediction model, and the target prediction model outputs the target confidence score of each object in the vehicle driving image belonging to the target object.

[0021] Based on the target confidence level, determine whether the vehicle driving image contains a target object.

[0022] In some embodiments of this application, determining the target display ratio of the vehicle driving image based on the target object includes:

[0023] Obtain the pixel coordinates of the target object and the object type of the target object;

[0024] Based on the pixel coordinates and the object type, the target display ratio of the vehicle driving image is determined.

[0025] In some embodiments of this application, determining the target display ratio of the vehicle driving image based on the pixel coordinates and the object type includes:

[0026] Based on the pixel coordinates, the distance information between the target object and the target vehicle is determined;

[0027] Based on the distance information and the object type, the target display ratio of the vehicle driving image is determined.

[0028] In some embodiments of this application, determining the distance information between the target object and the target vehicle based on the pixel coordinates includes:

[0029] The pixel coordinates are transformed to obtain the target coordinates of the target object, where the target coordinates are the three-dimensional coordinates of the target object in the target vehicle coordinate system.

[0030] Based on the target coordinates, the distance information between the target object and the target vehicle is determined.

[0031] In some embodiments of this application, determining the target display ratio of the vehicle driving image based on the distance information and the object type includes:

[0032] Based on the object type, determine the display ratio range of the vehicle driving image;

[0033] Based on the distance information and the display ratio range, the target display ratio of the vehicle driving image is determined.

[0034] On the other hand, this application provides an image display device, the image display device comprising:

[0035] The information acquisition unit is used to acquire the vehicle driving information of the target vehicle, and to acquire the risk score of the target vehicle based on the vehicle driving information. The risk score can trigger the opening of the target applet if the target conditions are met.

[0036] An image acquisition unit is used to, if the risk score meets the target conditions, open the target mini-program and acquire vehicle driving images captured by the target dashcam through the target mini-program, wherein the target dashcam is installed on the target vehicle;

[0037] An image recognition unit is used to recognize the vehicle driving image and determine whether the vehicle driving image contains a target object;

[0038] A ratio determination unit is used to determine the target display ratio of the vehicle driving image based on the target object when the vehicle driving image contains a target object.

[0039] An image display unit is used to display the vehicle driving image based on the target display ratio.

[0040] In some embodiments of this application, the image display device further includes:

[0041] The request retrieval unit is used to retrieve hotspot connection requests;

[0042] The message sending unit is configured to send a request message for requesting hotspot connection to the target dashcam according to the hotspot connection request;

[0043] A message receiving unit is used to receive hotspot information returned by the target dashcam based on the request message;

[0044] A hotspot connection unit is used to connect to the wireless network hotspot of the target dashcam based on the hotspot information.

[0045] In some embodiments of this application, the vehicle driving information includes vehicle speed, vehicle location, and driver information, and the information acquisition unit is specifically used for:

[0046] A risk score is determined based on the vehicle's speed, location, and driver information.

[0047] In some embodiments of this application, the image acquisition unit is specifically used for:

[0048] The risk score is compared with a preset risk threshold. When the risk score is greater than the risk threshold, the target mini-program is activated.

[0049] In some embodiments of this application, the image recognition unit is specifically used for:

[0050] The vehicle driving image is input into a trained target prediction model, and the target prediction model outputs the target confidence score of each object in the vehicle driving image belonging to the target object.

[0051] Based on the target confidence level, determine whether the vehicle driving image contains a target object.

[0052] In some embodiments of this application, the ratio determination unit is specifically used for:

[0053] Obtain the pixel coordinates of the target object and the object type of the target object;

[0054] Based on the pixel coordinates and the object type, the target display ratio of the vehicle driving image is determined.

[0055] In some embodiments of this application, the ratio determination unit is further configured to:

[0056] Based on the pixel coordinates, the distance information between the target object and the target vehicle is determined;

[0057] Based on the distance information and the object type, the target display ratio of the vehicle driving image is determined.

[0058] In some embodiments of this application, the ratio determination unit is further configured to:

[0059] The pixel coordinates are transformed to obtain the target coordinates of the target object, where the target coordinates are the three-dimensional coordinates of the target object in the target vehicle coordinate system.

[0060] Based on the target coordinates, the distance information between the target object and the target vehicle is determined.

[0061] In some embodiments of this application, the ratio determination unit is further configured to:

[0062] Based on the object type, determine the display ratio range of the vehicle driving image;

[0063] Based on the distance information and the display ratio range, the target display ratio of the vehicle driving image is determined.

[0064] On the other hand, this application also provides a computer device, the computer device comprising:

[0065] One or more processors;

[0066] Memory; and

[0067] One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the image display method described in any one of the first aspects.

[0068] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, the computer program being loaded by a processor to perform the steps of the image display method according to any one of the first aspects.

[0069] This application obtains vehicle driving images captured by the target dashcam through the target mini-program. The vehicle driving images can be quickly viewed and played without downloading a dedicated APP. The target mini-program is automatically opened based on the vehicle driving information, and the display ratio of the vehicle driving images is adjusted according to the target objects contained in the vehicle driving images, which can improve the display effect of the vehicle driving images and help users drive safely. Attached Figure Description

[0070] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0071] Figure 1 This is a scene diagram of the image display system provided in the embodiments of this application;

[0072] Figure 2 This is a schematic flowchart of an embodiment of the image display method provided in this application;

[0073] Figure 3 This is a schematic flowchart of a specific embodiment of the image display method provided in this application;

[0074] Figure 4 This is a schematic diagram of an embodiment of the image display device provided in this application.

[0075] Figure 5 This is a schematic diagram of an embodiment of the computer device provided in this application. Detailed Implementation

[0076] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0077] In the description of this application, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "multiple" means two or more, and "several" includes one or more, unless otherwise explicitly specified.

[0078] In this application, the term "exemplary" is used to mean "used as an example, illustration, or description." Any embodiment described as "exemplary" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use this application. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that this application can be made without using these specific details. In other instances, well-known structures and processes are not described in detail to avoid obscuring the description of this application with unnecessary detail. Therefore, this application is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0079] It should be noted that since the method in this application embodiment is executed in a computer device, the processing objects of each computer device exist in the form of data or information, such as time, which is essentially time information. It is understood that if size, quantity, position, etc. are mentioned in subsequent embodiments, they are all corresponding data that exist so that the computer device can process them. Specific details will not be elaborated here.

[0080] This application provides an image display method, apparatus, and storage medium, which will be described in detail below.

[0081] Please see Figure 1 , Figure 1 This is a schematic diagram of a scene of an image display system provided in an embodiment of this application. The image display system may include a computer device 100, which integrates an image display device, such as... Figure 1 Computer equipment in the country.

[0082] In this embodiment, the computer device 100 and the target dashcam installed on the target vehicle are on the same local area network. The computer device 100 can open the target mini-program through its installed applications, such as WeChat or Alipay. After the computer device 100 opens the target mini-program, the target mini-program, which is on the same local area network as the dashcam, can obtain the vehicle driving images of the target vehicle captured by the dashcam.

[0083] In this embodiment, the computer device 100 is mainly used to acquire vehicle driving information of a target vehicle, obtain a risk score for the target vehicle based on the vehicle driving information, and trigger the opening of a target mini-program if the risk score meets the target conditions; if the risk score meets the target conditions, the target mini-program is opened, and vehicle driving images captured by a target dashcam (the target dashcam is installed on the target vehicle) are acquired through the target mini-program; the vehicle driving images are identified to determine whether a target object is contained in the vehicle driving images; when the vehicle driving images contain a target object, a target display ratio for the vehicle driving images is determined based on the target object; based on the target display ratio, the vehicle driving images are displayed. The computer device 100 can quickly browse and play vehicle driving images without downloading a dedicated APP, and can improve the display effect of vehicle driving images, helping users to drive safely.

[0084] In this embodiment, the computer device 100 can be a standalone server, a server network, or a server cluster. For example, the computer device 100 described in this embodiment includes, but is not limited to, a computer, a network host, a single network server, a set of multiple network servers, or a cloud server composed of multiple servers. The cloud server is composed of a large number of computers or network servers based on cloud computing.

[0085] It is understood that the computer device 100 used in the embodiments of this application can be a device that includes both receiving and transmitting hardware, that is, a device having receiving and transmitting hardware capable of performing bidirectional communication on a bidirectional communication link. Such a device may include: cellular or other communication devices having a single-line display, a multi-line display, or a cellular or other communication device without a multi-line display. Specifically, the computer device 100 may be a desktop terminal or a mobile terminal, and may also be one of a mobile phone, tablet computer, laptop computer, etc.

[0086] Those skilled in the art will understand that Figure 1 The application environment shown is merely one application scenario of the solution in this application and does not constitute a limitation on the application scenario of the solution in this application. Other application environments may include those that are more specific to this application. Figure 1 The number of computer devices shown is more or less, for example Figure 1 Only one computer device is shown in the image. It is understood that the image display system may also include one or more other services, which are not limited here.

[0087] In addition, such as Figure 1As shown, the image display system may also include a memory 200 for storing data, such as vehicle driving information, such as vehicle speed, vehicle location, and driver information, and a target display ratio, specifically, such as a target display ratio of 130% for vehicle driving image A and a target display ratio of 160% for vehicle driving image B.

[0088] It should be noted that, Figure 1 The schematic diagram of the image display system shown is merely an example. The image display system and scenario described in this application are for the purpose of more clearly illustrating the technical solutions of this application, and do not constitute a limitation on the technical solutions provided in this application. As those skilled in the art will know, with the evolution of image display systems and the emergence of new business scenarios, the technical solutions provided in this application are also applicable to similar technical problems.

[0089] First, this application provides an image display method, the execution subject of which is an image display device applied to a computer device. The image display method includes: acquiring vehicle driving information of a target vehicle; acquiring a risk score of the target vehicle based on the vehicle driving information, wherein the risk score can trigger the opening of a target mini-program if the target conditions are met; if the risk score meets the target conditions, opening the target mini-program and acquiring a vehicle driving image captured by a target dashcam installed on the target vehicle through the target mini-program; identifying the vehicle driving image to determine whether the vehicle driving image contains a target object; when the vehicle driving image contains a target object, determining a target display ratio of the vehicle driving image based on the target object; and displaying the vehicle driving image based on the target display ratio.

[0090] like Figure 2 The diagram shown is a flowchart of an embodiment of the image display method in this application. The image display method may include the following steps 301 to 305, as detailed below:

[0091] 301. Obtain the vehicle driving information of the target vehicle, and obtain the risk score of the target vehicle based on the vehicle driving information. If the risk score meets the target conditions, the target mini-program can be triggered to open.

[0092] The target vehicle is the vehicle currently being driven by the user. The vehicle driving information refers to the driving status information of the target vehicle, which is obtained by a computer device. The computer device can directly obtain the driving status information of the target vehicle, or it can obtain driving status information collected by other devices via network, Bluetooth, and infrared. The target mini-program is an application developed specifically for the target dashcam that can be used without downloading or installation. The target mini-program can be opened through applications already installed on the computer device, such as WeChat or Alipay. The risk score is used to characterize the probability of the target vehicle being involved in a traffic accident. For example, a risk score of 20% indicates that the target vehicle has a 20% probability of being involved in a traffic accident. The target mini-program can be triggered to open when the risk score meets the target conditions. In existing technologies, users need to manually open a dedicated app to view vehicle driving images. To improve user driving safety, this embodiment allows the computer device to obtain the vehicle driving information of the target vehicle during its operation, obtain a risk score based on the vehicle driving information, and trigger the opening of the target mini-program based on the risk score, thus achieving automatic opening of the target mini-program.

[0093] It should be noted that the target mini-program can be triggered to open when the risk score meets the target condition, but this does not mean that the target mini-program can only be opened when the risk score meets the target condition. The target mini-program can also be opened manually by the user. For example, a user can open the target mini-program by entering WeChat and clicking on it. In one specific implementation, the vehicle driving information includes the vehicle's speed, location, and driver information. Step 301, which obtains the risk score based on the vehicle driving information, may include the following step 401, as detailed below:

[0094] 401. Determine the risk score of the target vehicle based on its speed, location, and driver information.

[0095] In one specific implementation, vehicle driving information includes vehicle speed, vehicle location, and driver information. The vehicle speed can be obtained through a speed sensor pre-installed on the computer device, the vehicle location can be obtained through a position sensor pre-installed on the computer device, and the driver information can be pre-entered into the computer device by the user. Accordingly, obtaining the risk score of the target vehicle based on the vehicle driving information specifically includes: determining the risk score of the target vehicle based on the vehicle speed, vehicle location, and driver information.

[0096] In one embodiment, a pre-set correspondence can be established between vehicle speed and a first score, between vehicle location and a second score, and between driver information and a third score. For example, a vehicle speed of 50 km / h to 60 km / h corresponds to score A1, a vehicle location A corresponds to score A2, and driver information A corresponds to score A3. Accordingly, when determining the risk score of the target vehicle, the first score can be determined first based on the vehicle speed and the pre-set correspondence between vehicle speed and the first score; the second score can be determined based on the vehicle location and the pre-set correspondence between vehicle location and the second score; and the third score can be determined based on the driver information and the pre-set correspondence between driver information and the third score. Then, the risk score of the target vehicle is determined based on the first, second, and third scores. Specifically, when determining the risk score based on the first, second, and third scores, the first, second, and third scores can be summed, or a weighted sum can be performed, or the sums can be averaged. This application does not limit this approach.

[0097] In one specific implementation, such as Figure 3 As shown, before obtaining the vehicle driving information of the target vehicle in step 301, the following steps 402 to 405 may be included, as detailed below:

[0098] 402. Get hotspot connection request;

[0099] 403. Based on the hotspot connection request, send a request message to the target dashcam to request a hotspot connection;

[0100] 404. Receive hotspot information returned by the target dashcam based on the request message;

[0101] 405. Based on hotspot information, connect to the target dashcam's wireless network hotspot.

[0102] The target dashcam comes pre-installed with a file service. This file service starts automatically upon the dashcam's power-on. Once started, it automatically creates a wireless network hotspot, which becomes the dashcam's wireless network hotspot. For example, if the wireless network hotspot is a Wi-Fi hotspot, the file service will automatically create one upon startup. A hotspot connection request is a command sent by the user to the computer device to connect to the target dashcam's wireless network hotspot. This connection request can include, but is not limited to, touch commands, mouse commands, remote control commands, and voice commands. For example, the user might tap the target dashcam's wireless network hotspot on the touchscreen, tap it on the screen with a mouse, or issue a voice command saying "Connect to the target dashcam's wireless network hotspot."

[0103] The request message is a message sent by a computer device to the target dashcam to request a hotspot connection. The request message includes the device identifier of the computer device. The hotspot information is the information returned by the target dashcam to the computer device based on the request message. The hotspot information includes the hotspot name and the plaintext key of the hotspot.

[0104] To ensure that the computer device and the target dashcam are on the same local area network, in this embodiment, before obtaining the target vehicle's driving information, the user can send a hotspot connection request to the computer device. After receiving the hotspot connection request, the computer device sends a hotspot connection request message to the target dashcam. Upon receiving the request message, the target dashcam authenticates the device identifier carried in the request message. If authentication is successful, it returns hotspot information to the computer device. The computer device then connects to the target dashcam's wireless network hotspot based on this information. In this embodiment, the computer device connecting to the target dashcam's wireless network hotspot based on hotspot information improves hotspot connection speed and reduces operational steps.

[0105] 302. If the risk score meets the target conditions, the target mini-program is activated, and the vehicle driving images captured by the target dashcam are obtained through the target mini-program. The target dashcam is installed on the target vehicle.

[0106] The target dashcam is installed on the target vehicle, and the vehicle driving images are images of the surrounding environment captured by the target dashcam during the vehicle's movement. In this embodiment, after obtaining the risk score of the target vehicle, it is determined whether the risk score meets the target conditions. When the risk score meets the target conditions, the target mini-program is activated. Since the target mini-program and the target dashcam are on the same local area network, the vehicle driving images captured by the target dashcam can be obtained through the target mini-program. This allows the target mini-program to automatically activate and display vehicle driving images in situations where traffic accidents are likely to occur, such as when driving at high speeds, driving on accident-prone sections of road, or when the driver is a novice. This enables the user to have a more comprehensive understanding of the current road conditions and reminds the user to drive safely.

[0107] In one specific implementation, if the risk score meets the target conditions in step 302, the target applet is activated, which may include the following step 406, as detailed below:

[0108] 406. Compare the risk score with the preset risk threshold. When the risk score is greater than the risk threshold, start the target mini-program.

[0109] The risk threshold is a pre-set critical value used to measure whether the risk score meets the target conditions. When the risk score is greater than the risk threshold, the risk score meets the target conditions, and the target mini-program can be triggered to open. Conversely, when the risk score is not greater than the risk threshold, the risk score does not meet the target conditions, and the target mini-program cannot be triggered to open. In this embodiment, after obtaining the risk score of the target vehicle, the risk score is compared with the preset risk threshold. When the risk score is greater than the risk threshold, the target mini-program is opened; otherwise, the risk score of the target vehicle continues to be obtained, and the risk score is compared with the preset risk threshold.

[0110] 303. Recognize the vehicle driving image to determine whether the vehicle driving image contains the target object.

[0111] The target object refers to an object in the environment surrounding the target vehicle that needs attention, including but not limited to vehicles and pedestrians. In order to remind the user to drive safely when there is an object in the surrounding environment that needs attention, this embodiment obtains the vehicle driving image captured by the target dashcam through the target applet, and then further identifies the vehicle driving image to determine whether the vehicle driving image contains the target object, so that in subsequent steps, if the vehicle driving image contains the target object, the vehicle driving image can be displayed based on the target object.

[0112] In one specific implementation, refer to Figure 3 As shown, step 303 involves recognizing the vehicle driving image to determine whether it contains a target object. This may include the following steps 407-408:

[0113] 407. Input the vehicle driving image into the trained target prediction model, and output the target confidence score of each object in the vehicle driving image as belonging to the target object through the target prediction model;

[0114] 408. Based on the target confidence level, determine whether the vehicle driving image contains the target object.

[0115] The objects in a vehicle driving image are pedestrians and objects surrounding the target vehicle during its movement. These objects can include vehicles, pedestrians, road signs, trees, road barriers, etc. Target confidence is the probability that each object in the vehicle driving image belongs to the target object. For example, if the target object is a vehicle, the target confidence is the probability that each object in the vehicle driving image belongs to the vehicle. The target prediction model can predict the target confidence of each object in the vehicle driving image as belonging to the target object. The target prediction model is trained on a pre-acquired training sample set using a preset network model. This preset network model can be a deep learning model or a machine learning model, such as Convolutional Neural Networks (CNN) or De-Convolutional Networks (DN).

[0116] In one embodiment, the pre-acquired training sample set includes several training images and the true confidence scores of each object in each training image belonging to the target object. Accordingly, the training process of the target prediction model includes: inputting several training images into a preset network model; outputting the predicted confidence scores of each object in each training image belonging to the target object through the preset network model; determining a loss value based on the predicted confidence scores, true confidence scores, and the loss function of the preset network model; when the loss value does not meet a preset condition, correcting the model parameters of the preset network model according to a preset parameter learning rate, and continuing to execute the steps of inputting several training images into the preset network model and outputting the predicted confidence scores of each object in each training image belonging to the target object through the preset network model, until the loss value meets the preset condition. The preset condition for the loss value to meet the preset condition can be that the loss value is less than a preset first threshold, or the difference between two consecutive loss values ​​is less than a preset second threshold.

[0117] After acquiring vehicle driving images captured by a target dashcam via a target app, the computer device further inputs these images into a target prediction model. The model outputs a target confidence score for each object in the driving image, indicating that it belongs to the target object. This target confidence score is then compared to a confidence threshold, and objects in the driving image with a target confidence score greater than the threshold are identified as target objects. This embodiment, based on a target prediction model, determines whether a vehicle driving image contains a target object, thereby improving the display speed of the driving image.

[0118] For example, when the target object is a vehicle, the vehicle driving image is input into the target prediction model. The target prediction model outputs the target confidence score that each object in the vehicle driving image belongs to a vehicle. Then, based on the target confidence score and a confidence threshold, it is determined whether the vehicle driving image contains a vehicle. Similarly, when the target object is a pedestrian, the vehicle driving image is input into the target prediction model. The target prediction model outputs the target confidence score that each object in the vehicle driving image belongs to a pedestrian. Then, based on the target confidence score and a confidence threshold, it is determined whether the vehicle driving image contains a pedestrian. Furthermore, when the target objects are both vehicles and pedestrians, the vehicle driving image can be input into a first prediction model and a second prediction model, respectively. The first prediction model outputs a first confidence score that each object in the vehicle driving image belongs to a vehicle, and the second prediction model outputs a second confidence score that each object in the vehicle driving image belongs to a pedestrian. Then, based on the first and second confidence scores, it is determined whether the vehicle driving image contains both vehicles and pedestrians.

[0119] 304. When a target object is contained in the vehicle driving image, the target display ratio of the vehicle driving image is determined according to the target object.

[0120] The target display ratio is the display ratio of the target vehicle driving image. The target display ratio is relative to the default size of the vehicle driving image displayed by the computer device. When displaying the default-sized vehicle driving image, the target display ratio is 100%. When the vehicle driving image is reduced in size, the target display ratio is less than 100%, and when the vehicle driving image is enlarged, the target display ratio is greater than 100%. In this embodiment, when it is determined that the vehicle driving image contains a target object, the target display ratio of the vehicle driving image is determined based on the target object, so that the vehicle driving image can be displayed based on the target display ratio in subsequent steps.

[0121] In one specific implementation, refer to Figure 3 As shown, step 304, which determines the target display ratio of the vehicle driving image based on the target object, may include the following steps 409-410, as detailed below:

[0122] 409. Obtain the pixel coordinates and object type of the target object;

[0123] 410. Determine the target display ratio of the vehicle driving image based on pixel coordinates and object type.

[0124] Pixel coordinates are the coordinates of the target object in the vehicle driving image. The pixel coordinates of the target object can be the coordinates of the center point of the target object in the vehicle driving image, or the coordinates of other points of the target object in the vehicle driving image. The object type is the type to which the target object belongs; for example, the target object can be a pedestrian, a vehicle, etc. In this embodiment, when determining the target display ratio of the vehicle driving image based on the target object, the pixel coordinates and object type of the target object are first obtained, and then the target display ratio of the vehicle driving image is determined based on the pixel coordinates and object type.

[0125] In one specific embodiment, determining the target display ratio of the vehicle driving image in step 410 based on pixel coordinates and object type may include the following steps 501-502, as detailed below:

[0126] 501. Determine the distance information between the target object and the target vehicle based on pixel coordinates;

[0127] 502. Based on distance information and object type, determine the target display ratio of the vehicle driving image.

[0128] The distance information refers to the distance between the target object and the target vehicle. For example, if the target object is another vehicle, the distance information is the distance between that other vehicle and the target vehicle. It should be noted that when the vehicle driving image contains multiple target objects, the distance between the target object and the target vehicle can be the average of the distances between the multiple target objects and the target vehicle, or it can be the minimum distance among the multiple distances. For example, if the vehicle driving image includes a vehicle and a pedestrian, and the distance between the vehicle and the target vehicle is 5m, and the distance between the pedestrian and the target vehicle is 9m, then the distance between the target object and the target vehicle can be 5m or 7m. Considering that the closer the target object is to the target vehicle, the greater the possibility of a traffic accident, to improve user driving safety, this embodiment determines the target display ratio of the vehicle driving image based on pixel coordinates and object type. First, it determines the distance information between the target object and the target vehicle based on pixel coordinates, and then it determines the target display ratio of the vehicle driving image based on the distance information and object type.

[0129] In one specific embodiment, determining the distance information between the target object and the target vehicle based on pixel coordinates in step 501 may include the following steps 601-602, as detailed below:

[0130] 601. Perform coordinate transformation on the pixel coordinates to obtain the target coordinates of the target object. The target coordinates are the three-dimensional coordinates of the target object in the target vehicle coordinate system.

[0131] 602. Based on the target coordinates, determine the distance information between the target object and the target vehicle.

[0132] The target coordinates are the three-dimensional coordinates of the target object in the target vehicle coordinate system. They can be obtained by transforming pixel coordinates using a pre-determined transformation relationship between the camera coordinates of the target dashcam and the target vehicle coordinate system. In this embodiment, the camera of the target dashcam can be pre-calibrated to obtain the transformation relationship between the camera coordinates and the target vehicle coordinate system. The camera calibration method can employ existing traditional camera calibration methods, active vision camera calibration methods, camera self-calibration methods, etc. When determining the distance information between the target object and the target vehicle based on the pixel coordinates, the pixel coordinates can first be transformed according to the transformation relationship between the camera coordinates and the target vehicle coordinate system to obtain the target coordinates of the target object. Then, based on the target coordinates, the distance information between the target object and the target vehicle can be determined.

[0133] In one specific embodiment, determining the target display ratio of the vehicle driving image in step 502 based on distance information and object type may include the following steps 603-604, as detailed below:

[0134] 603. Determine the display scale range of the vehicle driving image based on the object type;

[0135] 604. Based on distance information and display scale range, determine the target display scale of the vehicle driving image.

[0136] The display ratio range refers to the range within which the target display ratio of the vehicle driving image falls. In this embodiment, different display ratio ranges are pre-set for vehicle driving images containing different object types. For example, the display ratio range for vehicle driving images containing both vehicles and pedestrians is 150%–180%, while the display ratio range for vehicle driving images containing only vehicles is 120%–150%. When determining the target display ratio of the vehicle driving image based on distance information and object type, the display ratio range can be determined first based on the object type, and then the target display ratio can be determined based on the distance information and the display ratio range. For example, if the object type is vehicles and pedestrians, and the distance information is 2m, the display ratio range of the vehicle driving image is first determined to be 150%–180% based on the object type, and then the target display ratio corresponding to the distance information of 2m within the display ratio range of 150%–180% is determined to be 170%.

[0137] 305. Display the vehicle driving image based on the target display ratio.

[0138] After determining the target display ratio of the vehicle driving image in this embodiment, the vehicle driving image can be displayed based on the target display ratio. For example, when the target object includes both vehicles and pedestrians, and the distance between the target object and the target vehicle is 2m, the vehicle driving image is displayed at a 170% display ratio. When the target object only includes vehicles, and the distance between the target object and the target vehicle is 5m, the vehicle driving image is displayed at a 130% display ratio. By adjusting the display ratio of the vehicle driving image in real time, the user can be alerted to surrounding vehicles and pedestrians, helping the user to drive safely. To better implement the image display method in this embodiment, based on the image display method, this embodiment also provides an image display device, such as... Figure 4 As shown, the image display 700 includes:

[0139] Information acquisition unit 701 is used to acquire vehicle driving information of target vehicle, acquire risk score of target vehicle based on vehicle driving information, and trigger the opening of target applet if the risk score meets target conditions;

[0140] The image acquisition unit 702 is used to open the target applet if the risk score meets the target conditions, and acquire vehicle driving images captured by the target dashcam through the target applet, wherein the target dashcam is installed on the target vehicle;

[0141] Image recognition unit 703 is used to recognize the vehicle driving image and determine whether the vehicle driving image contains a target object;

[0142] The ratio determination unit 704 is used to determine the target display ratio of the vehicle driving image based on the target object when the vehicle driving image contains a target object.

[0143] The image display unit 705 is used to display the vehicle driving image based on the target display ratio.

[0144] In this embodiment, vehicle driving images captured by the target dashcam are obtained through the target mini-program. The vehicle driving images can be quickly viewed and played without downloading a dedicated APP. The target mini-program is automatically opened based on the vehicle driving information, and the display ratio of the vehicle driving images is adjusted according to the target objects contained in the vehicle driving images, which can improve the display effect of the vehicle driving images and help users drive safely.

[0145] In some embodiments of this application, the image display 700 further includes:

[0146] The request retrieval unit is used to retrieve hotspot connection requests;

[0147] The message sending unit is configured to send a request message for requesting hotspot connection to the target dashcam according to the hotspot connection request;

[0148] A message receiving unit is used to receive hotspot information returned by the target dashcam based on the request message;

[0149] A hotspot connection unit is used to connect to the wireless network hotspot of the target dashcam based on the hotspot information.

[0150] In some embodiments of this application, the vehicle driving information includes vehicle speed, vehicle location, and driver information, and the information acquisition unit 701 is specifically used for:

[0151] A risk score is determined based on the vehicle's speed, location, and driver information.

[0152] In some embodiments of this application, the image acquisition unit 702 is specifically used for:

[0153] The risk score is compared with a preset risk threshold. When the risk score is greater than the risk threshold, the target mini-program is activated.

[0154] In some embodiments of this application, the image recognition unit 703 is specifically used for:

[0155] The vehicle driving image is input into a trained target prediction model, and the target prediction model outputs the target confidence score of each object in the vehicle driving image belonging to the target object.

[0156] Based on the target confidence level, determine whether the vehicle driving image contains a target object.

[0157] In some embodiments of this application, the ratio determination unit 704 is specifically used for:

[0158] Obtain the pixel coordinates of the target object and the object type of the target object;

[0159] Based on the pixel coordinates and the object type, the target display ratio of the vehicle driving image is determined.

[0160] In some embodiments of this application, the ratio determination unit 704 is further configured to:

[0161] Based on the pixel coordinates, the distance information between the target object and the target vehicle is determined;

[0162] Based on the distance information and the object type, the target display ratio of the vehicle driving image is determined.

[0163] In some embodiments of this application, the ratio determination unit 704 is further configured to:

[0164] The pixel coordinates are transformed to obtain the target coordinates of the target object, where the target coordinates are the three-dimensional coordinates of the target object in the target vehicle coordinate system.

[0165] Based on the target coordinates, the distance information between the target object and the target vehicle is determined.

[0166] In some embodiments of this application, the ratio determination unit 704 is further configured to:

[0167] Based on the object type, determine the display ratio range of the vehicle driving image;

[0168] Based on the distance information and the display ratio range, the target display ratio of the vehicle driving image is determined.

[0169] This application also provides a computer device that integrates any of the image display devices provided in this application, the computer device comprising:

[0170] One or more processors;

[0171] Memory; and

[0172] One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor in the steps of the image display method described in any of the above-described embodiments of the image display method.

[0173] This application also provides a computer device that integrates any of the image display devices provided in this application. For example... Figure 5 As shown, it illustrates a structural schematic diagram of the computer device involved in the embodiments of this application, specifically:

[0174] The computer device may include components such as a processor 901 with one or more processing cores, a memory 902 with one or more computer-readable storage media, a power supply 903, and an input unit 904. Those skilled in the art will understand that... Figure 5 The computer device structure shown does not constitute a limitation on the computer device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein:

[0175] The processor 901 is the control center of the computer device. It connects various parts of the computer device via various interfaces and lines, and performs various functions and processes data by running or executing software programs and / or modules stored in the memory 902, and by calling data stored in the memory 902, thereby providing overall monitoring of the computer device. Optionally, the processor 901 may include one or more processing cores; preferably, the processor 901 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 901.

[0176] The memory 902 can be used to store software programs and modules. The processor 901 executes various functional applications and data processing by running the software programs and modules stored in the memory 902. The memory 902 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 902 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 902 may also include a memory controller to provide the processor 901 with access to the memory 902.

[0177] The computer device also includes a power supply 903 that supplies power to the various components. Preferably, the power supply 903 can be logically connected to the processor 901 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 903 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0178] The computer device may also include an input unit 904, which can be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0179] Although not shown, the computer device may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 901 in the computer device loads the executable files corresponding to the processes of one or more application programs into the memory 902 according to the following instructions, and the processor 901 runs the application programs stored in the memory 902 to realize various functions, as follows:

[0180] Obtain the vehicle driving information of the target vehicle, obtain the risk score of the target vehicle based on the vehicle driving information, and trigger the opening of the target mini-program if the risk score meets the target conditions;

[0181] If the risk score meets the target conditions, the target mini-program is activated, and the vehicle driving image captured by the target dashcam is obtained through the target mini-program. The target dashcam is installed on the target vehicle.

[0182] The vehicle driving image is identified to determine whether the vehicle driving image contains a target object;

[0183] When the vehicle driving image contains a target object, the target display ratio of the vehicle driving image is determined based on the target object;

[0184] The vehicle driving image is displayed based on the target display ratio.

[0185] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0186] Therefore, embodiments of this application provide a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), a magnetic disk, or an optical disk, etc. A computer program is stored thereon, which is loaded by a processor to execute the steps in any of the image display methods provided in embodiments of this application. For example, the computer program loaded by the processor can execute the following steps:

[0187] Obtain the vehicle driving information of the target vehicle, obtain the risk score of the target vehicle based on the vehicle driving information, and trigger the opening of the target mini-program if the risk score meets the target conditions;

[0188] If the risk score meets the target conditions, the target mini-program is activated, and the vehicle driving image captured by the target dashcam is obtained through the target mini-program. The target dashcam is installed on the target vehicle.

[0189] The vehicle driving image is identified to determine whether the vehicle driving image contains a target object;

[0190] When the vehicle driving image contains a target object, the target display ratio of the vehicle driving image is determined based on the target object;

[0191] The vehicle driving image is displayed based on the target display ratio.

[0192] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the detailed descriptions of other embodiments above, which will not be repeated here.

[0193] In practice, each of the above units or structures can be implemented as an independent entity or can be arbitrarily combined to be implemented as the same or several entities. For the specific implementation of each of the above units or structures, please refer to the previous method embodiments, which will not be repeated here.

[0194] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0195] The above provides a detailed description of an image display method, apparatus, and storage medium provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. An image display method, characterized in that, The image display method includes: Obtain the vehicle driving information of the target vehicle, obtain the risk score of the target vehicle based on the vehicle driving information, and trigger the opening of the target mini-program if the risk score meets the target conditions; If the risk score meets the target conditions, the target mini-program is activated, and the vehicle driving image captured by the target dashcam is obtained through the target mini-program. The target dashcam is installed on the target vehicle. The vehicle driving image is identified to determine whether the vehicle driving image contains a target object; When the vehicle driving image contains a target object, the target display ratio of the vehicle driving image is determined based on the target object; The vehicle driving image is displayed based on the target display ratio; The risk score is used to characterize the likelihood of a target vehicle being involved in a traffic accident. The vehicle driving information includes vehicle speed, vehicle location, and driver information. Obtaining the risk score based on the vehicle driving information includes: A risk score is determined based on the vehicle's speed, location, and driver information. If the risk score meets the target conditions, the target mini-program is activated, including: The risk score is compared with a preset risk threshold. When the risk score is greater than the risk threshold, the target mini-program is activated.

2. The image display method according to claim 1, characterized in that, Before obtaining the vehicle driving information of the target vehicle, the method includes: Get hotspot connection requests; Based on the hotspot connection request, a request message for requesting a hotspot connection is sent to the target dashcam; Receive hotspot information returned by the target dashcam based on the request message; Based on the hotspot information, connect to the wireless network hotspot of the target dashcam.

3. The image display method according to claim 1, characterized in that, The step of identifying the vehicle driving image and determining whether the vehicle driving image contains a target object includes: The vehicle driving image is input into a trained target prediction model, and the target prediction model outputs the target confidence score of each object in the vehicle driving image belonging to the target object. Based on the target confidence level, determine whether the vehicle driving image contains a target object.

4. The image display method according to claim 1, characterized in that, Determining the target display ratio of the vehicle driving image based on the target object includes: Obtain the pixel coordinates of the target object and the object type of the target object; Based on the pixel coordinates and the object type, the target display ratio of the vehicle driving image is determined.

5. The image display method according to claim 4, characterized in that, Determining the target display ratio of the vehicle driving image based on the pixel coordinates and the object type includes: Based on the pixel coordinates, the distance information between the target object and the target vehicle is determined; Based on the distance information and the object type, the target display ratio of the vehicle driving image is determined.

6. The image display method according to claim 5, characterized in that, Determining the distance information between the target object and the target vehicle based on the pixel coordinates includes: The pixel coordinates are transformed to obtain the target coordinates of the target object, where the target coordinates are the three-dimensional coordinates of the target object in the target vehicle coordinate system. Based on the target coordinates, the distance information between the target object and the target vehicle is determined.

7. The image display method according to claim 5, characterized in that, Determining the target display ratio of the vehicle driving image based on the distance information and the object type includes: Based on the object type, determine the display ratio range of the vehicle driving image; Based on the distance information and the display ratio range, the target display ratio of the vehicle driving image is determined.

8. An image display device, characterized in that, The image display device includes: The information acquisition unit is used to acquire the vehicle driving information of the target vehicle, and to acquire the risk score of the target vehicle based on the vehicle driving information. The risk score can trigger the opening of the target applet if the target conditions are met. An image acquisition unit is used to, if the risk score meets the target conditions, open the target mini-program and acquire vehicle driving images captured by the target dashcam through the target mini-program, wherein the target dashcam is installed on the target vehicle; An image recognition unit is used to recognize the vehicle driving image and determine whether the vehicle driving image contains a target object; A ratio determination unit is used to determine the target display ratio of the vehicle driving image based on the target object when the vehicle driving image contains a target object. An image display unit is used to display the vehicle driving image based on the target display ratio; The risk score is used to characterize the likelihood of the target vehicle being involved in a traffic accident. The vehicle driving information includes vehicle speed, vehicle location, and driver information. The information acquisition unit is also used to determine a risk score based on the vehicle's driving speed, the vehicle's driving location, and the driver's information; The image acquisition unit is also used to compare the risk score with a preset risk threshold, and when the risk score is greater than the risk threshold, to open the target mini-program.

9. A computer-readable storage medium, characterized in that, It stores a computer program, which is loaded by a processor to perform the steps of the image display method according to any one of claims 1 to 7.

Images