Vehicle weight information determination method, device and equipment, automobile and storage medium

Abstract

The embodiment of the invention provides a vehicle weight information determination method and device, equipment, an automobile and a storage medium, and relates to the technical field of vehicles. The method comprises the following steps: controlling a vehicle-mounted camera device to collect at least one target image of an environment in which a vehicle is located in response to the detection that the vehicle is located in a weighing scene; wherein the target image is an image including target equipment, and the target equipment is equipment displaying weight information of the vehicle; and processing the target image, and determining the weight information of the vehicle. The method is used for achieving the effects of automatically obtaining the weight information of the vehicle and reducing the weighing cost.

Description

Technical Field

[0001] This application relates to the technical field of vehicles, and in particular, to a method, apparatus, device, vehicle, and storage medium for determining vehicle weight information. Background Art

[0002] In scenarios such as logistics transportation and vehicle management, the weight information of a vehicle is a key parameter. Accurate weight data not only helps optimize transportation efficiency but also improves the safety and compliance of vehicle operation.

[0003] Traditional vehicle weighing usually relies on fixed weighbridges or on-vehicle weighing devices. Such solutions generally require the vehicle to drive to a specific location, and the driver also needs to manually record the weight data. The execution process is often cumbersome, increases the risk of human error, and the overall weighing cost is relatively high, making it difficult to be widely applied.

[0004] Therefore, how to quickly, accurately, and at low cost obtain the weight information of a vehicle remains an urgent problem to be solved currently. Summary of the Invention

[0005] Embodiments of this application provide a method, apparatus, device, vehicle, and storage medium for determining vehicle weight information, so as to achieve the effect of quickly, accurately, and at low cost obtaining the weight information of a vehicle.

[0006] In a first aspect, embodiments of this application provide a method for determining vehicle weight information, the method including:

[0007] In response to detecting that the vehicle is in a weighing scenario, controlling an in-vehicle camera device to collect at least one target image of the environment where the vehicle is located; wherein, the target image is an image including a target device, and the target device is a device that displays the weight information of the vehicle;

[0008] Processing the target image to determine the weight information of the vehicle.

[0009] In a possible implementation manner, the processing the target image to determine the weight information of the vehicle includes:

[0010] Identifying the target image and cropping the image of the target device in the target image;

[0011] Performing orthodontic processing on the image of the target device to obtain an orthodontic target device image;

[0012] Identifying the orthodontic target device image through optical character recognition technology to obtain the weight information of the vehicle.

[0013] In a possible implementation, identifying the target device image after orthodontics through optical character recognition technology to obtain the weight information of the vehicle includes:

[0014] Identifying the target device image after orthodontics through optical character recognition technology to find the target character; wherein, the target character is a character related to the weight information;

[0015] Searching for numerical information within a preset range of the target character;

[0016] Determining the weight information of the vehicle according to the numerical information.

[0017] In a possible implementation, the determining the weight information of the vehicle according to the numerical information includes:

[0018] Comparing the numerical information with a preset reference value, and determining that the numerical information closest to the preset reference value is the weight information of the vehicle.

[0019] In a possible implementation, when there are multiple target images, after obtaining the weight information of the vehicle, the method further includes:

[0020] Determining the difference between the weight information of each vehicle;

[0021] Eliminating the abnormal weight information with a difference greater than a preset difference, and determining the average value of the remaining weight information.

[0022] In a possible implementation, the detecting that the vehicle is in a weighing scenario includes:

[0023] When it is determined that the vehicle is in a preset low-speed mode, controlling the on-vehicle camera device to collect an image of the current moment of the environment where the vehicle is located;

[0024] Identifying the current moment image, and if it is determined that the current moment image includes a target character, determining that the vehicle is in a weighing scenario; wherein, the target character is a character related to the weight information.

[0025] In a possible implementation, the determining that the vehicle is in a preset low-speed mode includes:

[0026] Controlling the on-vehicle camera device to continuously collect at least two adjacent moment images of the environment where the vehicle is located;

[0027] If it is determined that the similarity between the adjacent moment images is greater than a preset threshold, determining that the vehicle is in a preset low-speed mode.

[0028] In a possible implementation, the detecting that the vehicle is in a weighing scenario includes:

[0029] Control the in-vehicle camera device to continuously collect real-time images of the vehicle's surrounding environment;

[0030] Identify the real scene in the real-time image. If it is determined that the real scene is a preset target scene, it is determined that the vehicle is in a weighing scene; wherein, the preset target scene is a scene where vehicle weighing is performed and the weight information of the vehicle is displayed.

[0031] In a possible implementation manner, the controlling the in-vehicle camera device to collect at least one target image of the vehicle's surrounding environment includes:

[0032] Locate the target device in the vehicle's surrounding environment;

[0033] Control the in-vehicle camera device to perform shooting processing on the target device to obtain at least one target image.

[0034] In a possible implementation manner, the locating the target device in the vehicle's surrounding environment includes:

[0035] Detect a second wireless communication element in the vehicle's surrounding environment through a first wireless communication element on the vehicle;

[0036] Read the identification information of the second wireless communication element, and determine the target device according to the identification information.

[0037] In a possible implementation manner, the locating the target device in the vehicle's surrounding environment includes:

[0038] Determine that the device that emits a specific sound wave signal in the vehicle's surrounding environment is the target device.

[0039] In a possible implementation manner, the method further includes:

[0040] Save the weight information of the vehicle in a target format; wherein, the target format is a format including the time information and / or location information for collecting the target image.

[0041] In a possible implementation manner, the method further includes:

[0042] If it is determined that within the time period between two consecutively saved weight information of the vehicle, the parking duration of the vehicle is less than or equal to a preset duration, and the difference between the two weights is less than or equal to a preset value, then determine the average value of the two weight information of the vehicle.

[0043] In a second aspect, an embodiment of the present application provides a device for determining vehicle weight information, and the device includes:

[0044] A processing unit, configured to control an in-vehicle imaging device to capture at least one target image of the environment where the vehicle is located in response to detecting that the vehicle is in a weighing scenario; wherein, the target image is an image including a target device, and the target device is a device displaying the weight information of the vehicle;

[0045] A determining unit, configured to process the target image to determine the weight information of the vehicle.

[0046] In a third aspect, an embodiment of the present application provides an electronic device, which includes: a memory and a processor;

[0047] The memory stores computer-executable instructions;

[0048] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the first aspect and / or various possible implementation manners of the first aspect as described above.

[0049] In a fourth aspect, an embodiment of the present application provides an automobile, which includes the electronic device as described in the third aspect.

[0050] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, they are used to implement the first aspect and / or various possible implementation manners of the first aspect as described above.

[0051] In a sixth aspect, an embodiment of the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the first aspect and / or various possible implementation manners of the first aspect as described above.

[0052] In the method, device, equipment, automobile and storage medium for determining vehicle weight information provided by the embodiments of the present application, the method includes: controlling an in-vehicle imaging device to capture at least one target image of the environment where the vehicle is located in response to detecting that the vehicle is in a weighing scenario; wherein, the target image is an image including a target device, and the target device is a device displaying the weight information of the vehicle; processing the target image to determine the weight information of the vehicle. Through the in-vehicle imaging device and image processing technology, the present application can automatically obtain the weight information of the vehicle, no longer requiring a self-provided weighing device, which not only reduces the weighing cost, but also eliminates the need for manual reading and input of weighing data. This automated process not only improves efficiency but also reduces the possibility of human errors, and can realize automatic monitoring and management of vehicle weight in various application scenarios. Description of the Drawings

[0053] The accompanying drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0054] Figure 1 It is a schematic flow chart of a method for determining vehicle weight information provided by an embodiment of the present application;

[0055] Figure 2 It is a schematic view of the field of view of a side-mounted camera provided by an embodiment of the present application;

[0056] Figure 3 It is a schematic view of a target image provided by an embodiment of the present application;

[0057] Figure 4 It is a schematic flow chart of another method for determining vehicle weight information provided by an embodiment of the present application;

[0058] Figure 5 It is a schematic flow chart of yet another method for determining vehicle weight information provided by an embodiment of the present application;

[0059] Figure 6 It is a schematic structural diagram of a device for determining vehicle weight information provided by an embodiment of the present application;

[0060] Figure 7 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0061] Through the above accompanying drawings, the clear embodiments of the present application have been shown, and there will be more detailed descriptions hereinafter. These drawings and text descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. Detailed Description of the Embodiments

[0062] Here, the exemplary embodiments will be described in detail, and the examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0063] In logistics transportation and vehicle management, accurately obtaining the weight information of vehicles is very important. The weight information can be used not only for the braking strategy management and self-state estimation of the vehicle itself, but also for weight fuel analysis, etc. Accurate weight data not only helps to optimize transportation efficiency, but also improves the safety and compliance of vehicle operation.

[0064] In some scenarios, vehicle weighing is completed by the platform scales fixed at transportation centers or weighing stations. In this method, usually the vehicle needs to drive to the location where the platform scale is located for weighing. The weighing result is displayed on the display screen of the platform scale system for the operator, and then the operator records the relevant weighing data. Its execution process is often rather cumbersome. Especially in high-traffic scenarios, it is also prone to causing traffic congestion. In addition, when the platform scale system is not networked with the fleet management system, the staff also needs to manually record the weight information, which also increases the risk of data errors caused by humans. Moreover, the cost of platform scale weighing is relatively high, making it difficult to be widely applied on a large scale.

[0065] In other scenarios, weighing is completed by on-vehicle weighing devices. In this method, in order to improve the weighing accuracy, it is necessary to customize the appropriate installation positions of on-vehicle weighing devices for each different type of vehicle. Moreover, the manufacturing cost of on-vehicle weighing devices is relatively high, and they also need to be calibrated regularly. High costs are required both in the installation and use processes. The weighing accuracy is also easily affected by driving environmental conditions, and the practicality is not high enough.

[0066] To solve the above existing problems, the embodiments of the present application provide a method for determining vehicle weight information. Considering that in many weighing scenarios, the weighing information of the vehicle will be displayed on the display screen. For example, before a vehicle enters the highway section, the weighing system of the highway section will weigh the vehicle entering the highway and display the weighing information on the display screen to determine whether the vehicle is overweight. Another example is that when using a platform scale for weighing, the weighing result will also be displayed on the display screen of the platform scale system. Therefore, the present application proposes a solution for determining the vehicle weight information by identifying the weight information on these display screens. Based on the solution of the present application, since on-vehicle camera devices are already installed on the vehicle, there is no need to increase additional equipment costs, nor is it necessary to use additional weighing devices, and the vehicle weight information can be determined, greatly reducing the weighing cost and ensuring the weighing accuracy.

[0067] The following uses specific embodiments to elaborate in detail on the technical solution of the present application and how the technical solution of the present application solves the above technical problems. These several specific embodiments below can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0068] It should be noted that the execution subject of the method for determining vehicle weight information provided by the embodiments of the present application can be a device for determining vehicle weight information. This device for determining vehicle weight information can be deployed in the processor for data processing on the vehicle, or can be deployed on a remote control device (such as a fleet management system, a logistics transportation center system, etc.). The embodiments of the present application do not make any restrictions.

[0069] Understandably, when the vehicle weight information determination device is deployed on the vehicle, after completing data processing to determine the vehicle's weight information, it can also send the vehicle's weight information to a remote control device so that the remote control device can perform data analysis and management based on the vehicle's weight information. Among them, deploying the vehicle weight information determination device on the vehicle and having the vehicle itself complete data processing can not only reduce data transmission costs but also improve the overall data processing efficiency.

[0070] If the vehicle weight information determination device is deployed on the remote control device, the vehicle needs to send the captured target image to the remote control device, and then the remote control device completes the data processing process. This method can reduce the data processing pressure on the vehicle itself.

[0071] In practical applications, according to actual needs, the vehicle weight information determination device can be deployed on the vehicle or the remote control device, and the embodiments of the present application do not make restrictions.

[0072] Figure 1 It is a schematic flowchart of a method for determining vehicle weight information provided by an embodiment of the present application. As Figure 1 shown, the method for determining vehicle weight information provided by the embodiments of the present application may include:

[0073] S101. In response to detecting that the vehicle is in a weighing scenario, control an in-vehicle camera device to collect at least one target image of the environment where the vehicle is located; wherein, the target image is an image including a target device, and the target device is a device that displays the vehicle's weight information.

[0074] Exemplarily, based on the solution of the embodiment of the present application, to obtain the vehicle's weight information, first, an image containing the vehicle's weight information needs to be obtained. Understandably, when the vehicle is in a weighing scenario, weighing is performed to obtain the weight information. Therefore, when it is detected that the vehicle is in a weighing scenario, the in-vehicle camera device on the vehicle can be controlled to collect at least one target image of the environment where the vehicle is located.

[0075] Among them, the in-vehicle camera device is a camera device pre-installed on the vehicle. For example, it may include a side-mounted camera device, a front-mounted camera device, etc., and the embodiments of the present application do not make restrictions. The viewing angle and position of the camera should be carefully designed to ensure that the target image can be clearly captured. The target image collected by the in-vehicle camera device should include the target device, and the vehicle's weight information will be displayed on the target device. The target device can be a display screen, a monitor, a projector, etc. with an information display function, and the embodiments of the present application do not make restrictions. In practical applications, the target device can be the display screen of a weighbridge system, the display screen showing the vehicle weight at a highway toll station, the factory display screen at a logistics transportation center, etc.

[0076] Exemplarily,Figure 2 This is a schematic view of the field of view of a side-mounted camera provided by an embodiment of the present application. As Figure 2 shown, when the imaging device is located on the left side of the vehicle, it can collect environmental images of the left side of the vehicle. When the target device is located on the left side of the vehicle, the target device will be included in the images collected by the imaging device. Similarly, it can be understood that when the target device is located on the right side or the front side of the vehicle, the target device will also be included in the images collected by the imaging device located on the right side or the front side of the vehicle, so as to collect target images.

[0077] In practical applications, the in-vehicle imaging device on the left side, or the right side, or the front side can be determined to be selected to collect target images according to the actual position of the target device. Of course, if the in-vehicle imaging device is a panoramic imaging device and can collect target devices located in different orientations, the imaging device can also be directly selected to complete the collection of target images, and the embodiments of the present application do not make restrictions.

[0078] It should be noted that the embodiments of the present application do not make restrictions on how to detect whether the vehicle is in a weighing scenario. For example, it can be determined whether the vehicle is in a weighing scenario by judging the geographical location to determine whether the vehicle has entered a known weighing station, or by detecting with a sensor whether the vehicle has stopped on a weighing platform, etc.

[0079] Optionally, in a possible embodiment, detecting that the vehicle is in a weighing scenario may include:

[0080] S1. When it is determined that the vehicle is in a preset low-speed mode, control the in-vehicle imaging device to collect an image of the current moment of the environment where the vehicle is located;

[0081] S2. Identify the image of the current moment. If it is determined that the target character is included in the image of the current moment, it is determined that the vehicle is in a weighing scenario; wherein, the target character is a character related to weight information.

[0082] Exemplarily, when weighing a vehicle, generally the vehicle is required to be in a low-speed driving / stopped state. Therefore, when judging whether the vehicle is in a weighing scenario, it can be first determined whether the vehicle is in a preset low-speed mode. If so, then control the in-vehicle imaging device to collect an image of the current moment of the environment where the vehicle is located.

[0083] Among them, the low-speed mode can be obtained through the vehicle speed sensor or the in-vehicle computer, and is usually set within a low-speed range (for example, below 5 km / h) to indicate that the vehicle may be entering or has entered the weighing area.

[0084] Exemplarily, once it is determined that the vehicle is in the low-speed mode, the on-vehicle camera device can be directly activated to control the on-vehicle camera device to collect the current moment image of the environment where the vehicle is located, and process the collected current moment image, such as using Optical Character Recognition (OCR) technology to extract character information and determine whether the target character is included in the image. If characters related to weight information such as "weight", "vehicle weight", "total weight", "overweight", "heavy", "kg", "ton", "ton" etc. are recognized in the image, it can be considered that the vehicle is located in the weighing scenario.

[0085] Through vehicle speed detection and image recognition, the environment scenario where the vehicle is located can be recognized faster and more accurately, which can effectively detect whether the vehicle is located in the weighing scenario and prepare for the subsequent acquisition and processing of weight information.

[0086] Optionally, in a possible embodiment, determining that the vehicle is in the preset low-speed mode may include:

[0087] S11. Control the on-vehicle camera device to continuously collect at least two adjacent moment images of the environment where the vehicle is located;

[0088] S12. If it is determined that the similarity between the adjacent moment images is greater than the preset threshold, determine that the vehicle is in the preset low-speed mode.

[0089] Exemplarily, it can be determined whether the vehicle is in the preset low-speed mode through the camera device on the side of the vehicle or the camera device in the front of the vehicle. When the vehicle is in the low-speed mode, the images collected by the on-vehicle camera device do not change particularly much. Therefore, the on-vehicle camera device can be controlled to continuously collect at least two adjacent moment images of the environment where the vehicle is located, and image recognition technology can be used to calculate the similarity between them. If the similarity is greater than the preset threshold, it indicates that the environment where the vehicle is located has not changed significantly, and the vehicle should be in the low-speed / stop state. At this time, it can be considered that the vehicle is in the preset low-speed mode.

[0090] When determining whether the vehicle is in the preset low-speed mode through the on-vehicle camera device, there is no need to increase additional equipment costs, and the environment where the vehicle is located can be recognized quickly and accurately. Furthermore, the timing of controlling the on-vehicle camera device to collect the current moment image of the environment where the vehicle is located can be accurately controlled, reducing the amount of data processing while also facilitating the subsequent quick recognition of the weighing scenario.

[0091] Optionally, in another possible embodiment, detecting that the vehicle is located in the weighing scenario may also include:

[0092] S10. Control the on-vehicle camera device to continuously collect real-time images of the environment where the vehicle is located;

[0093] S20. Identify the real scene in the real-time image. If it is determined that the real scene is a preset target scene, it is determined that the vehicle is in the weighing scene; wherein, the preset target scene is a scene where vehicle weighing is performed and the weight information of the vehicle is displayed.

[0094] Exemplarily, in practical applications, it is also possible to identify the real scene in the image collected by the on-vehicle camera device to determine whether the vehicle is in the weighing scene. Since the vehicle may be moving, it is necessary to control the on-vehicle camera device to continuously collect real-time images of the vehicle's surrounding environment at a certain frequency. After the image is collected, it is also necessary to process the collected image in real time to quickly identify the scene and make corresponding judgments. For example, computer vision techniques such as Convolutional Neural Networks (CNN) in deep learning models can be used to identify specific environmental features, and then feature extraction and matching algorithms are used to match the features in the real-time image with the features of the preset target scene. If the features of the identified real scene match the features of the preset target scene, and vehicle weighing is performed and the weight information of the vehicle is displayed, it is considered that the vehicle is in the weighing scene.

[0095] Through continuous image acquisition and advanced scene recognition techniques, efficient and reliable scene detection capabilities can be provided, enabling real-time detection and confirmation of whether the vehicle is in the weighing scene during the vehicle's movement.

[0096] Exemplarily, in the embodiment of the present application, when it is detected that the vehicle is in the weighing scene, the on-vehicle camera device is controlled to collect at least one target image of the vehicle's surrounding environment for subsequent acquisition of the vehicle's weight information.

[0097] Optionally, in a possible embodiment, controlling the on-vehicle camera device to collect at least one target image of the vehicle's surrounding environment may include:

[0098] S100. Locate the target device in the vehicle's surrounding environment;

[0099] S200. Control the on-vehicle camera device to take pictures of the target device to obtain at least one target image.

[0100] Exemplarily, since the target image needs to include the target device, before controlling the vehicle-mounted camera device to take a picture, the position of the target device can be determined first. For example, sensors on the vehicle (such as radar, lidar, ultrasonic sensors, etc.) can be used to help locate the target device. These sensors can provide distance and azimuth information about the surrounding objects in the environment where the vehicle is located, which helps to identify the position of the target device. After determining the azimuth of the target device, the parameters such as the angle, focal length, and exposure of the vehicle-mounted camera device can be automatically adjusted to ensure that the target image containing the target device can be clearly captured.

[0101] By first locating the target device in the environment where the vehicle is located and then taking pictures, it can be ensured that the captured images all include the target device, improving the quality of the target image.

[0102] Optionally, to improve the quality of the captured target image, after taking the picture, the quality of the target image can also be checked to determine the clarity and integrity of the image. If the image quality is not good, the vehicle-mounted camera device can be controlled to take a re-picture, or if multiple target images are taken, the images with low quality can also be directly excluded. The embodiments of the present application do not make any restrictions.

[0103] Optionally, in a possible embodiment, locating the target device in the environment where the vehicle is located may include:

[0104] S01. Detect a second wireless communication element in the environment where the vehicle is located through a first wireless communication element on the vehicle;

[0105] S02. Read the identification information of the second wireless communication element, and determine the target device according to the identification information.

[0106] Exemplarily, the target device can be located through wireless communication technologies such as Wi-Fi, Bluetooth, Zigbee, Near Field Communication (NFC), 4G, 5G, 6G, Vehicle-to-Everything (V2X), etc.

[0107] For example, a wireless communication element can be configured on a vehicle. As the first wireless communication element, it can scan and detect surrounding wireless signals, and use the wireless communication elements that the first wireless communication element can scan as the second wireless communication elements. Then, by measuring the received signal strength, the distance and position of the scanned second wireless communication elements can be estimated. Generally, the stronger the signal strength, the closer the distance. Further, by reading the identification information (such as MAC address, Universally Unique Identifier (UUID), etc.) of the scanned second wireless communication elements, the target device can be identified.

[0108] By configuring the first wireless communication element on the vehicle, other wireless communication elements in the vehicle environment can be quickly and effectively detected and identified, so as to determine the target device, which is convenient for subsequent shooting of the target image.

[0109] Optionally, in another possible embodiment, locating the target device in the environment where the vehicle is located may also include: determining that the device that emits a specific sound wave signal in the environment where the vehicle is located is the target device.

[0110] Exemplarily, if the target device is configured with the function of emitting a specific sound wave, a sound wave sensor (such as a microphone array, etc.) can be installed on the vehicle to detect and receive the sound wave signals in the environment where the vehicle is located. The sound wave sensor continuously monitors the sound wave signals in the vehicle's surrounding environment, and uses filtering techniques (such as band-pass filters, etc.) to filter out irrelevant background noise, only retaining signals with specific frequencies or characteristics. Then, features such as frequency, amplitude, and phase are extracted from the received sound wave signals to identify the source of the signal. Then, pattern recognition algorithms or machine learning models, etc., are used to match the extracted signal features with the predefined specific sound wave signal features. After determining the position and characteristics of the signal source, the target device that emits a specific sound wave signal in the environment where the vehicle is located can be found.

[0111] Combining sound wave signal processing and positioning technologies can provide accurate device identification and positioning capabilities in a complex acoustic environment, thereby effectively detecting and identifying the target device that emits a specific sound wave signal in the vehicle environment.

[0112] By first locating the target device in the environment where the vehicle is located, and then controlling the on-vehicle camera device to perform shooting processing on the target device at a certain frequency, a more accurate target image can be obtained, ensuring that the images captured by the on-vehicle camera device all include the target device, which is beneficial for subsequent faster and more accurate identification of the vehicle's weight information.

[0113] In addition, it should be noted that the number of target images collected in the embodiments of the present application is not limited either. For example, the vehicle-mounted imaging device can be controlled to continuously collect target images for a preset duration (such as 3 minutes) at a specific frequency; the vehicle-mounted imaging device can also be controlled to end image collection after collecting N (for example, 10) target images; image collection can also be ended after accurate vehicle weight information is recognized (such as the weight information of the vehicle recognized from multiple consecutive target images is the same); and so on, which is not limited in the embodiments of the present application.

[0114] S102. Process the target image to determine the weight information of the vehicle.

[0115] Exemplarily, after the target image is collected, the image needs to be processed to extract the weight information of the vehicle from the target image. Among them, the image processing process may include technologies such as image recognition, text recognition, and optical character recognition, which are not limited in the embodiments of the present application.

[0116] Optionally, in a possible embodiment, processing the target image to determine the weight information of the vehicle may include:

[0117] S001. Recognize the target image and intercept the image of the target device in the target image;

[0118] S002. Perform orthodontic processing on the image of the target device to obtain the orthodontic-processed image of the target device;

[0119] S003. Recognize the orthodontic-processed image of the target device through optical character recognition technology to obtain the weight information of the vehicle.

[0120] Exemplarily, computer vision technologies such as edge detection, shape recognition, color filtering, or deep learning models (such as convolutional neural networks, etc.) can be used to recognize the target device in the target image. When the target device is recognized, image segmentation algorithms such as threshold segmentation are used to segment the image to intercept the area displaying the weight information and obtain the image of the target device. Due to factors such as the angle and distance of the vehicle-mounted imaging device, the intercepted image of the target device may have perspective distortion. Therefore, perspective transformation technology can be further used to perform orthodontic processing on the image of the target device to make the text, numbers, etc. in the image present as a front view, ensure that the text or numbers in the image are horizontally aligned, and improve the accuracy of subsequent OCR recognition. Finally, OCR technology is used to extract text information from the orthodontic-processed image to obtain the weight information of the vehicle. Among them, the OCR software can recognize the characters in the image and convert them into an editable text format, and then extract the weight information of the vehicle from the OCR result. Usually, the weight information is displayed in digital form. Therefore, the target characters can be recognized first, and then the corresponding numerical value can be found near the target characters to obtain the weight information of the vehicle.

[0121] Optionally, in order to improve the recognition accuracy, after finding the corresponding value, it is also possible to verify whether the extracted information is reasonable, for example, by checking the number format and range. In particular, when there are multiple feature characters + reasonable continuous numerical values, the weight information of the vehicle can be comprehensively determined through other information of the vehicle such as vehicle type and use, so as to improve the recognition accuracy.

[0122] Optionally, in a possible embodiment, step S003, identifying the orthodontic target device image through optical character recognition technology to obtain the weight information of the vehicle, may include:

[0123] S0031, identifying the orthodontic target device image through optical character recognition technology to find the target character; wherein, the target character is a character related to the weight information;

[0124] S0032, searching for numerical information within a preset range of the target character;

[0125] S0033, determining the weight information of the vehicle according to the numerical information.

[0126] Exemplarily, the target character being a character related to the weight information may include one or more of "weight", "vehicle weight", "gross weight", "overweight", "weight", "kg", "ton", "ton", etc. When using OCR technology to identify the orthodontic target device image and search for the target character, the image can be first converted into a grayscale image to simplify data processing; then a filter (such as median filtering) can be used to remove the noise in the image to improve the recognition accuracy; and a threshold method can be used to convert the grayscale image into a black-and-white image for easy character segmentation and recognition; finally, the character contours in the black-and-white image can be recognized, adjacent characters can be separated, and the edge features of the characters can be recognized, and the shape, structure features and texture features of the characters, such as strokes, intersection points, etc., can be analyzed, and the extracted character features can be compared with the character templates of the predefined target characters to find the most matching character, and then the recognized characters can be combined into a complete text to find the target character.

[0127] Among them, the preset range refers to a specific area near the recognized target character. Within this area, there may be numerical values directly related to the weight information. The embodiments of the present application do not make specific range limitations. For example, the preset range can be the right area, left area, etc. in the same horizontal direction as the target character. Within this preset range, further recognition can be performed to extract numerical information including numbers. By judging the reasonableness of these numerical information, the weight information of the vehicle can be finally determined.

[0128] Optionally, in a possible embodiment, step S0033, determining the weight information of the vehicle according to the numerical information, may include: comparing the numerical information with a preset reference value, and determining the numerical information closest to the preset reference value as the weight information of the vehicle.

[0129] It can be understood that among the numerical information found in the image, in addition to the weight information of the vehicle, there may also be license plate numbers, the number of axles, etc. These information may also be presented by numbers. Therefore, it is necessary to further judge the rationality of these numerical information.

[0130] Exemplarily, the preset reference value may be set based on prior knowledge or historical data, representing a reasonable vehicle weight range or the known weight of a specific vehicle. The preset reference value may be a specific value or a value range. For example, the typical weight range of a certain type of vehicle may be 1000 to 3000 kilograms, or the known weight of a specific vehicle is 1500 kilograms, or the historical known weight of the vehicle at the previous moment is 2000 kilograms; and so on.

[0131] Compare the numerical information found within the preset range of the target character with the corresponding preset reference value in sequence, calculate the difference between each extracted value and the reference value, and the rationality of the numerical information can be judged. Finally, the numerical information closest to the preset reference value can be selected as the weight information of the vehicle.

[0132] For example, if the net weight of the vehicle is set as the preset reference value, and its value is 1500 kilograms, then the actual weight information of the vehicle should be at least greater than or equal to 1500 kg. Among the numerical information found within the preset range of the target character, at least the numerical information with a value greater than or equal to 1500 should be selected as the weight information of the vehicle.

[0133] The preset reference value can effectively filter out the noise or mis-identified values in the recognition process, thereby improving the robustness and accuracy of the vehicle weight information determination system. Exemplarily, Figure 3 A schematic diagram of a target image provided by an embodiment of the present application. As Figure 3 shown, in the target image 30, in addition to the target device 31, there may also be a bracket 32 of the target device 31 and other environmental information such as clouds 33, etc. To improve the data processing efficiency, the target image 30 can be recognized first, and the image of the target device 31 can be cropped from the target image 30, and then, the image of the target device 31 is orthodontically processed and character recognition processed to obtain the weight information of the vehicle.

[0134] In addition, in some possible examples, preprocessing can also be performed on the acquired target image. For example, filtering techniques can be used to remove noise in the image to improve the clarity and contrast of the image; for another example, adjusting the brightness, contrast, sharpness, etc. of the image for image enhancement to ensure that the information on the display device is clearly visible; and so on, which are not limited in the embodiments of the present application. By preprocessing the target image, the weight information of the vehicle can be determined faster and more accurately.

[0135] Optionally, in a possible embodiment, when there are multiple target images, after obtaining the weight information of the vehicle, the method of the embodiments of the present application may further include:

[0136] S0001. Determine the difference between the weight information of each vehicle;

[0137] S0002. Eliminate the abnormal weight information with a difference greater than the preset difference, and determine the average value of the remaining weight information.

[0138] Exemplarily, in order to improve the accuracy of the vehicle weight information, multiple target images can be acquired from different perspectives in the same weighing scenario. When processing multiple target images to obtain the weight information of the vehicle, situations where the weight information is inconsistent may occur due to various reasons such as image quality, light changes, equipment reading fluctuations, etc. Therefore, when there are multiple acquired target images, in order to improve the reliability and accuracy of the data, after separately performing recognition processing on each target image to obtain the vehicle weight information in each target image, the difference between the weight information of each vehicle can be determined, and it can be judged whether each difference is greater than the preset difference. Eliminate the abnormal weight information with a larger difference among them, and then calculate the average value of the remaining weight information after eliminating the outliers, and use the calculated average value as the final vehicle weight information, so as to provide a more stable and accurate vehicle weight information.

[0139] Through difference judgment, abnormal readings caused by various reasons can be effectively filtered out, thereby improving the accuracy and reliability of the vehicle weight information. This method is particularly suitable for scenarios that require high-precision weight measurement, such as logistics management, vehicle load monitoring, etc.

[0140] The method for determining vehicle weight information provided by the embodiments of the present application includes: when it is detected that the vehicle is in a weighing scenario, controlling an in-vehicle camera device to collect at least one target image of the environment where the vehicle is located; where the target image is an image including a target device, and the target device is a device that displays the weight information of the vehicle; processing the target image to determine the weight information of the vehicle. In the embodiments of the present application, by using the in-vehicle camera device and image processing technology, the weight information of the vehicle can be automatically obtained, and there is no need to prepare a weighing device by oneself. This not only reduces the weighing cost, but also eliminates the need for manual reading and input of weighing data. This automated process not only improves efficiency but also reduces the possibility of human errors, and can realize automatic monitoring and management of vehicle weight in various application scenarios.

[0141] Exemplarily, Figure 4 is a schematic flowchart of another method for determining vehicle weight information provided by the embodiments of the present application. As Figure 4 shown, the method for determining vehicle weight information provided by the embodiments of the present application may include:

[0142] S401. Control the in-vehicle camera device to continuously collect at least two adjacent moment images of the environment where the vehicle is located.

[0143] S402. Determine whether the similarity between the adjacent moment images is greater than a preset threshold.

[0144] If so, execute step S403; if not, continue to execute step S401.

[0145] S403. Control the in-vehicle camera device to collect the current moment image of the environment where the vehicle is located.

[0146] S404. Identify the current moment image and determine whether the current moment image includes a target character.

[0147] If so, execute step S405; if not, execute step S403.

[0148] S405. Control the in-vehicle camera device to collect at least one target image of the environment where the vehicle is located.

[0149] Where the target image is an image including a target device, and the target device is a device that displays the weight information of the vehicle.

[0150] S406. Identify the target image and intercept the image of the target device in the target image.

[0151] S407. Perform orthodontic processing on the image of the target device to obtain the orthodontic target device image.

[0152] S408. Through optical character recognition technology, identify the orthodontic target device image to obtain the weight information of the vehicle.

[0153] S409. Determine the difference between the weight information of each vehicle, and eliminate the abnormal weight information whose difference is greater than the preset difference.

[0154] S410. Calculate the average value of the remaining weight information, and use the average value as the final vehicle weight information.

[0155] It should be noted that the specific implementation of the above steps in this embodiment can refer to the specific description of other embodiments, which will not be elaborated here. In determining the vehicle weight information, the above partial or all steps may be included, and the embodiments of the present application do not make restrictions.

[0156] S411. Save the final vehicle weight information in the target format.

[0157] Wherein, the target format is a format including the time information and / or location information of collecting the target image.

[0158] Exemplarily, in practical applications, vehicle weighing may be completed at different times and different locations. In order to facilitate the subsequent management of vehicle weight data, when recording the vehicle weight information, the time information and / or location information of collecting the target image may be recorded simultaneously, so as to facilitate subsequent tracking, analysis and verification.

[0159] Among them, the time information helps to track the data collection time point, which is convenient for subsequent time series analysis or event association. When collecting the target image, the time stamp can be automatically generated and recorded through the system clock, so as to obtain the time information. The location information is very useful for logistics management, geographical analysis and anomaly detection (such as whether the vehicle is weighed at the predetermined location, etc.). The geographical location information at the time of collecting the target image can be recorded through the Global Positioning System (GPS), Global Navigation Satellite System (GNSS) or other positioning systems equipped on the vehicle or weighing device.

[0160] After calculating the final vehicle weight information, record the vehicle weight information, the time information and / or location information of collecting the target image in a table or other way in the local database or send it to the remote control device for saving, which can provide more comprehensive and useful data support for the subsequent, so as to meet various business requirements and analysis requirements.

[0161] The method for determining vehicle weight information provided by the embodiments of the present application utilizes on-vehicle camera devices and image processing technology to automatically obtain the vehicle weight information without the need to prepare weighing equipment on one's own. This not only reduces the weighing cost but also eliminates the need for manual reading and input of weighing data. This automated process not only improves efficiency but also reduces the possibility of human errors, and can achieve automatic monitoring and management of vehicle weight in various application scenarios.

[0162] Exemplarily, Figure 5 is a schematic flowchart of another method for determining vehicle weight information provided by the embodiments of the present application. As Figure 5 shown, the method for determining vehicle weight information provided by the embodiments of the present application may include:

[0163] S501. Control the on-vehicle camera device to continuously collect real-time images of the vehicle's environment.

[0164] S502. Identify the real scene in the real-time image and determine whether the real scene is a preset target scene.

[0165] Among them, the preset target scene is a scene where vehicle weighing is performed and the vehicle's weight information is displayed.

[0166] If so, execute step S503; if not, continue to execute step S501.

[0167] S503. Control the on-vehicle camera device to collect at least one target image of the vehicle's environment.

[0168] Among them, the target image is an image including a target device, and the target device is a device that displays the vehicle's weight information.

[0169] S504. Identify the target image and intercept the image of the target device in the target image.

[0170] S505. Perform orthodontic processing on the image of the target device to obtain the orthodontic target device image.

[0171] S506. Through optical character recognition technology, recognize the orthodontic target device image to obtain the vehicle's weight information.

[0172] S507. Determine the difference between the weight information of each vehicle, and eliminate abnormal weight information whose difference is greater than the preset difference.

[0173] S508. Calculate the average value of the remaining weight information, and use the average value as the final vehicle weight information.

[0174] S509. Save the final vehicle weight information in the target format.

[0175] Among them, the target format is a format including the time information and / or location information of the acquired target image.

[0176] It should be noted that the specific implementation of the above steps in this embodiment can refer to the specific description of other embodiments, and will not be elaborated here. In the determination of vehicle weight information, some or all of the above steps may be included, and the embodiments of the present application do not make restrictions.

[0177] The method for determining vehicle weight information provided by the embodiments of the present application uses on-vehicle camera devices and image processing technologies, and can automatically obtain vehicle weight information without the need to prepare weighing equipment separately. This not only reduces the weighing cost, but also eliminates the need for manual reading and input of weighing data. This automated process not only improves efficiency, but also reduces the possibility of human errors, and can realize automatic monitoring and management of vehicle weights in various application scenarios.

[0178] Optionally, on the basis of any of the above embodiments, in a possible embodiment, if it is determined that within the time period between the weight information of two continuously saved vehicles, the parking duration of the vehicle is less than or equal to a preset duration, and the weight difference between the two is less than or equal to a preset value, then the average value of the weight information of the two vehicles is determined.

[0179] Exemplarily, after continuously saving the weight information of vehicles at multiple different times and different locations, for this weight information, further data processing can also be performed according to actual needs. For example, for a pair of toll stations, when it is recognized that during the process of a vehicle traveling between the pair of toll stations, there is an operation mode of parking - driving - parking, and the weighing results are only recorded when entering and leaving the toll stations respectively, if there is not much difference between the two weight information, then the two weight information can be averaged to determine the weight information of the vehicle when traveling on this section of the highway.

[0180] For another example, when a weight information is recorded when a vehicle exits the highway, and then a weight information obtained by weighing with a weighbridge is recorded. If the vehicle does not stop for a long time between exiting the highway and reaching the location of the weighbridge, and there is no significant difference in weight between the two, then they can also be averaged, otherwise, weight averaging is not performed.

[0181] By identifying the vehicle weight information at different times and different locations, and thus determining whether to perform averaging, more accurate vehicle weight information can be obtained, which is extremely crucial in fleet management and logistics transportation, and can avoid situations such as loss of goods on the vehicle and replacement of goods, and better realize vehicle transportation management.

[0182] The following is an embodiment of the device of the present application, which can be used to execute the method embodiment of the present application. For the details not disclosed in the embodiment of the device of the present application, please refer to the method embodiment of the present application.

[0183] Figure 6 This is a schematic structural diagram of a device for determining vehicle weight information provided by an embodiment of the present application. As Figure 6 shown, the device 60 for determining vehicle weight information provided in this embodiment includes a processing unit 601 and a determination unit 602.

[0184] Among them, the processing unit 601 is configured to control an in-vehicle camera device to collect at least one target image of the environment where the vehicle is located in response to detecting that the vehicle is in a weighing scenario; wherein, the target image is an image including a target device, and the target device is a device that displays the weight information of the vehicle;

[0185] The determination unit 602 is configured to process the target image and determine the weight information of the vehicle.

[0186] The device provided in this embodiment can execute the method provided in the above method embodiment, and its implementation principle and technical effects are similar, and will not be elaborated here in this embodiment.

[0187] Based on the above device embodiment, in some possible examples, the determination unit 602 is specifically configured to:

[0188] Identify the target image and intercept the image of the target device in the target image;

[0189] Perform orthodontic processing on the image of the target device to obtain the orthodontic target device image;

[0190] Identify the orthodontic target device image through optical character recognition technology to obtain the weight information of the vehicle.

[0191] Based on the above device embodiment, in some possible examples, the determination unit 602 is specifically configured to:

[0192] Identify the orthodontic target device image through optical character recognition technology to find the target character; wherein, the target character is a character related to the weight information;

[0193] Search for numerical information within the preset range of the target character;

[0194] Determine the weight information of the vehicle according to the numerical information.

[0195] Based on the above device embodiment, in some possible examples, the determination unit 602 is specifically configured to:

[0196] Compare the numerical information with a preset reference value, and determine that the numerical information closest to the preset reference value is the weight information of the vehicle.

[0197] Based on the above device embodiments, in some possible examples, when there are multiple target images, after obtaining the weight information of the vehicle, the determination unit 602 is further configured to:

[0198] Determine the difference between the weight information of each vehicle;

[0199] Eliminate abnormal weight information with a difference greater than a preset difference, and determine the average value of the remaining weight information.

[0200] Based on the above device embodiments, in some possible examples, the processing unit 601 is specifically configured to:

[0201] When it is determined that the vehicle is in a preset low-speed mode, control the on-vehicle camera device to collect an image of the current moment of the environment where the vehicle is located;

[0202] Identify the image of the current moment. If it is determined that the target character is included in the image of the current moment, it is determined that the vehicle is located in a weighing scenario; wherein, the target character is a character related to the weight information.

[0203] Based on the above device embodiments, in some possible examples, the processing unit 601 is specifically configured to:

[0204] Control the on-vehicle camera device to continuously collect at least two adjacent moment images of the environment where the vehicle is located;

[0205] If it is determined that the similarity between the adjacent moment images is greater than a preset threshold, it is determined that the vehicle is in a preset low-speed mode.

[0206] Based on the above device embodiments, in some possible examples, the processing unit 601 is specifically configured to:

[0207] Control the on-vehicle camera device to continuously collect real-time images of the environment where the vehicle is located;

[0208] Identify the real scene in the real-time image. If it is determined that the real scene is a preset target scene, it is determined that the vehicle is located in a weighing scenario; wherein, the preset target scene is a scene where vehicle weighing is performed and the weight information of the vehicle is displayed.

[0209] Based on the above device embodiments, in some possible examples, the processing unit 601 is specifically configured to:

[0210] Locate the target device in the environment where the vehicle is located;

[0211] Control the on-vehicle camera device to perform shooting processing on the target device to obtain at least one target image.

[0212] Based on the above device embodiments, in some possible examples, the processing unit 601 is specifically configured to:

[0213] Detect a second wireless communication element in the environment where the vehicle is located through a first wireless communication element on the vehicle;

[0214] Read the identification information of the second wireless communication element, and determine the target device according to the identification information.

[0215] Based on the above device embodiment, in some possible examples, the processing unit 601 is specifically configured to:

[0216] Determine that the device that emits a specific sound wave signal in the environment where the vehicle is located is the target device.

[0217] Based on the above device embodiment, in some possible examples, the determination unit 602 is further specifically configured to:

[0218] Save the weight information of the vehicle in a target format; wherein, the target format is a format including the time information and / or location information for collecting the target image.

[0219] Based on the above device embodiment, in some possible examples, the determination unit 602 is further specifically configured to:

[0220] If it is determined that within the time period between the weight information of two consecutively saved vehicles, the parking duration of the vehicle is less than or equal to a preset duration, and the difference in their weights is less than or equal to a preset value, then determine the average value of the weight information of the two vehicles.

[0221] The device provided in this embodiment can be used to execute the method of the above embodiment, and its implementation principle and technical effects are similar, which will not be elaborated here.

[0222] It should be noted that it should be understood that the division of each module of the above device is only a logical function division. In actual implementation, it can be fully or partially integrated into a physical entity, or physically separated. And these modules can all be implemented in the form of software called by a processing element; they can also all be implemented in the form of hardware; or some modules can be implemented in the form of software called by a processing element, and some modules can be implemented in the form of hardware. In addition, it can also be stored in the memory of the above device in the form of program code, and called and executed by a certain processing element of the above device to perform the functions of the above data processing module. The implementation of other modules is similar. In addition, these modules can be fully or partially integrated together or independently implemented. Here, the processing element can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each of the above modules can be completed by the integrated logic circuit in the processor element or the instruction in the form of software.

[0223] Figure 7 This is a schematic structural diagram of an electronic device provided by an embodiment of the present application. AsFigure 7 As shown in the figure, the electronic device 70 provided in this embodiment includes: at least one processor 701 and a memory 702. Optionally, the device 70 further includes a communication component 703. Among them, the processor 701, the memory 702, and the communication component 703 are connected through a bus 704.

[0224] In the specific implementation process, at least one processor 701 executes the computer-executable instructions stored in the memory 702, so that at least one processor 701 executes the above-mentioned method.

[0225] For the specific implementation process of the processor 701, reference can be made to the above method embodiment, and its implementation principle and technical effect are similar, so they will not be elaborated here in this embodiment.

[0226] In the above embodiment, it should be understood that the processor may be a central processing unit (English: Central Processing Unit, abbreviated as: CPU), or other general-purpose processors, digital signal processors (English: Digital Signal Processor, abbreviated as: DSP), application specific integrated circuits (English: Application Specific Integrated Circuit, abbreviated as: ASIC), etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the invention can be directly embodied as being executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

[0227] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (Non-volatile Memory, NVM), such as at least one disk memory.

[0228] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0229] This embodiment of the present application also provides an automobile, which includes the electronic device as described above.

[0230] The present application also provides a computer program product, including a computer program which, when executed by a processor, implements the above-mentioned method.

[0231] The present application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-mentioned method.

[0232] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk or an optical disc. The readable storage medium can be any available medium accessible by a general-purpose or special-purpose computer.

[0233] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist as discrete components in a device.

[0234] The division of units is merely a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be an indirect coupling or communication connection through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0235] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0236] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0237] 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 may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs, etc., all kinds of media that can store program codes.

[0238] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps including the above method embodiments; and the aforementioned storage medium includes: ROMs, RAMs, magnetic disks, or optical discs, etc., all kinds of media that can store program codes.

[0239] Finally, it should be noted that: After considering the specification and practicing the invention disclosed herein, those skilled in the art will readily think of other implementation manners of the present invention. The present invention is intended to cover any variations, uses, or adaptations of the present invention, which follow the general principles of the present invention and include the common general knowledge or conventional technical means in the technical field not disclosed by the present invention. It is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. A method for determining vehicle weight information, characterized in that The method includes: In response to detecting that the vehicle is in a weighing scenario, controlling an in-vehicle camera device to collect at least one target image of the environment where the vehicle is located; wherein, the target image is an image including a target device, and the target device is a device that displays the weight information of the vehicle; Processing the target image to determine the weight information of the vehicle.

2. The method according to claim 1, wherein The processing the target image to determine the weight information of the vehicle includes: Identifying the target image and cropping the image of the target device in the target image; Performing orthodontic processing on the image of the target device to obtain an orthodontic-processed target device image; Identifying the orthodontic-processed target device image through optical character recognition technology to obtain the weight information of the vehicle.

3. The method according to claim 2, wherein The identifying the orthodontic-processed target device image through optical character recognition technology to obtain the weight information of the vehicle includes: Identifying the orthodontic-processed target device image through optical character recognition technology to find target characters; wherein, the target characters are characters related to weight information; Searching for numerical information within a preset range of the target characters; Determining the weight information of the vehicle according to the numerical information.

4. The method according to claim 3, wherein The determining the weight information of the vehicle according to the numerical information includes: comparing the numerical information with a preset reference value, and determining the numerical information closest to the preset reference value as the weight information of the vehicle.

5. The method according to claim 2, wherein When there are multiple target images, after obtaining the weight information of the vehicle, the method further includes: Determining the difference between the weight information of each vehicle; Eliminating abnormal weight information with a difference greater than a preset difference, and determining the average value of the remaining weight information.

6. The method according to claim 1, wherein The detecting that the vehicle is in a weighing scenario includes: In the case of determining that the vehicle is in a preset low-speed mode, controlling the in-vehicle camera device to collect an image of the current moment of the environment where the vehicle is located; Identifying the image of the current moment, and if it is determined that the image of the current moment includes target characters, determining that the vehicle is in a weighing scenario; wherein, the target characters are characters related to weight information.

7. The method according to claim 6, wherein The determining that the vehicle is in a preset low-speed mode includes: Controlling the in-vehicle camera device to continuously collect at least two adjacent moment images of the environment where the vehicle is located; If it is determined that the similarity between the adjacent moment images is greater than a preset threshold, determining that the vehicle is in a preset low-speed mode.

8. The method according to claim 1, characterized in that, The detecting that the vehicle is in a weighing scenario includes: Controlling the in-vehicle camera device to continuously collect real-time images of the environment where the vehicle is located; Identifying the real scene in the real-time image, and if it is determined that the real scene is a preset target scene, determining that the vehicle is in a weighing scenario; wherein, the preset target scene is a scene where vehicle weighing is performed and the weight information of the vehicle is displayed.

9. The method according to claim 1, wherein The controlling the in-vehicle camera device to collect at least one target image of the environment where the vehicle is located includes: Locating a target device in the environment where the vehicle is located; Controlling the in-vehicle camera device to perform a shooting process on the target device to obtain at least one target image.

10. The method according to claim 9, wherein The locating a target device in the environment where the vehicle is located includes: Detect a second wireless communication element in the environment where the vehicle is located through a first wireless communication element on the vehicle; Read the identification information of the second wireless communication element, and determine a target device according to the identification information.

11. The method according to claim 9, wherein Locating the target device in the environment where the vehicle is located includes: Determine that the device that emits a specific sound wave signal in the environment where the vehicle is located is the target device.

12. The method according to any one of claims 1-11, characterized in that, The method further includes: Save the weight information of the vehicle in a target format; wherein, the target format is a format including the time information and / or location information of collecting the target image.

13. The method according to claim 12, wherein The method further includes: If it is determined that within the time period between two consecutively saved weight information of the vehicle, the parking duration of the vehicle is less than or equal to a preset duration, and the difference between the two weights is less than or equal to a preset value, then determine the average value of the two weight information of the vehicle.

14. A device for determining vehicle weight information, characterized in that, The device includes: A processing unit, configured to control an in-vehicle imaging device to collect at least one target image of the environment where the vehicle is located in response to detecting that the vehicle is in a weighing scenario; wherein, the target image is an image including a target device, and the target device is a device that displays the weight information of the vehicle; A determining unit, configured to process the target image and determine the weight information of the vehicle.

15. An electronic device, characterized in that, The electronic device includes: a memory, a processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes the method according to any one of claims 1-13.

16. An automobile, characterized in that, The vehicle includes the electronic device according to claim 15.

17. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method according to any one of claims 1-13.

18. A computer program product, characterized in that, Including a computer program, which when executed by a processor implements the method according to any one of claims 1-13.

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