Photographing method, electronic device and vehicle

Abstract

The present disclosure provides a photographing method, electronic device and vehicle, so as to solve the technical problems existing in related technologies of manually controlling the on-board camera to photograph the scenery along the way, resulting in missed shots and safety risks, and belongs to the field of image vehicle technology. The method comprises: during the driving of the vehicle, obtaining vehicle detection data through a vehicle detection device, the vehicle detection data at least including: the position of the vehicle; when there is an intersection between the point of interest at the vehicle position and a preset point of interest, calculating the distance value between each target point of interest in the intersection and the vehicle position; when the distance value meets the automatic shooting requirement, controlling the on-board camera to shoot. It can prevent passengers from forgetting to send instructions to the controller when they are immersed in appreciating the scenery, resulting in missed shots and safety risks, and prevent accidents caused by the driver's inattention when sending instructions to the controller, thereby reducing safety risks during vehicle driving.

Description

Technical Field

[0001] The present disclosure belongs to the field of image vehicle technology, and in particular relates to a photographing method, electronic equipment, and a vehicle. Background Art

[0002] When traveling by car and passing through a beautiful scenery, the driver or passengers usually want to capture the beautiful scenery outside the car, so they manually control the on-board camera to take pictures.

[0003] During the development of this invention, the inventors discovered that the existing technology has at least the following problems: Passengers, engrossed in admiring the scenery, often forget to control the onboard camera to capture the scene, resulting in the inability to capture the scenery along the way. Furthermore, if the driver manually controls the onboard camera to capture the scene, the need to adjust parameters such as lighting and angle can pose a safety risk, threatening the safety of the user's life and property. Summary of the Invention

[0004] Provided are a photographing method, electronic equipment, and vehicle to solve the technical problems in related technologies of manually controlling a vehicle-mounted camera to photograph scenery along the way, which may result in missed shots and safety risks.

[0005] In a first aspect, a method for taking photos is provided. The method comprises:

[0006] During the driving process of the vehicle, vehicle detection data is obtained through the vehicle detection equipment, and the vehicle detection data includes at least: vehicle position;

[0007] When there is an intersection between the interest point at the vehicle position and the preset interest point, the distance value between each target interest point in the intersection and the vehicle position is calculated;

[0008] When the distance value meets the automatic shooting requirement, the vehicle-mounted camera is controlled to shoot.

[0009] In a second aspect, an electronic device is provided. The electronic device includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the photographing method according to the first aspect.

[0010] In a third aspect, a readable storage medium is provided, which stores a program or instruction. When the program or instruction is executed by a processor, the steps of the photographing method of the first aspect are implemented.

[0011] In a fourth aspect, a vehicle is provided, comprising a processor configured to execute the photographing method of the first aspect.

[0012] One of the above technical solutions disclosed herein has the following beneficial effects:

[0013] The vehicle controller can obtain the vehicle detection data of the vehicle during driving in real time through the vehicle detection equipment, so that when the vehicle detection data includes at least the vehicle position, the controller can obtain the vehicle position in real time, so that when the vehicle passes by a preset point of interest with beautiful scenery that the driver or passenger wants to record, it can calculate whether there is an intersection between the point of interest at the vehicle position and the preset point of interest. When there is an intersection, the distance value between each target point of interest in the intersection and the vehicle position is calculated to determine whether the distance value meets the automatic shooting requirement. When the distance value meets the automatic shooting requirement, the on-board camera is controlled to automatically shoot. This can prevent passengers from forgetting to send instructions to the controller when they are immersed in enjoying the scenery, resulting in missing images of preset points of interest, and prevent accidents caused by the driver's inattention when sending instructions to the controller, thereby reducing safety risks during vehicle driving.

[0014] It should be understood that the contents described in this section are not intended to represent the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements.

[0016] Figure 1 This is a flowchart of the steps of a photographing method provided by an embodiment of the present disclosure;

[0017] Figure 2 is a flowchart of another photographing method provided by an embodiment of the present disclosure;

[0018] Figure 3 is an execution flow chart of a photographing method provided by an embodiment of the present disclosure;

[0019] Figure 4 is a flowchart of another photographing method provided by an embodiment of the present disclosure;

[0020] Figure 5 is an execution flow chart of another photographing method provided by an embodiment of the present disclosure;

[0021] Figure 6 is a flowchart of another photographing method provided by an embodiment of the present disclosure;

[0022] Figure 7 This is a structural block diagram of a photographing device provided by an embodiment of the present disclosure;

[0023] Figure 8This is a structural block diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0024] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0025] As used herein, the term "including" and its variations represent open inclusion, i.e., "including but not limited to." Unless otherwise stated, the term "or" means "and / or." The term "based on" means "based at least in part on." The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment." The term "another embodiment" means "at least one additional embodiment." The terms "first," "second," etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0026] As mentioned above, vehicles are typically equipped with onboard cameras, which allow users to capture scenes while driving, such as capturing scenery along the way. Currently, onboard cameras are typically triggered by the user's active and conscious triggering. While driving, users may not always be actively capturing photos, or they may be so focused on enjoying the scenery that they forget to trigger the camera. This can cause the camera to miss many beautiful moments. Furthermore, taking photos while the vehicle is in motion poses safety risks, threatening the safety of users' lives and property. Furthermore, the quality of photos taken while the vehicle is in motion can vary due to factors such as physical vibration (due to poor road conditions), lighting, and weather. This can result in some photos being of low quality, and the vehicle cannot automatically filter out low-quality photos, resulting in a lack of quality assurance for the photos obtained. This requires users to manually filter and sort the photos, which is time-consuming and provides a poor user experience.

[0027] Some mobile phone albums also have the function of automatic organization, but this automatic organization requires users to organize the group of photos through a preset program (such as downloading a certain software) after taking a group of photos. Since human intervention is required, this automatic organization is a passive organization, that is, the mobile phone cannot automatically filter and screen the images without human intervention after taking pictures.

[0028] To at least partially address one or more of the aforementioned and other potential issues, exemplary embodiments of the present disclosure provide a photography method, electronic device, and vehicle. In this solution, when a driver needs to take photos of scenes, such as scenery along the way, while driving, they may become so absorbed in the scenery that they forget to take photos, resulting in the driver failing to capture the scenery. This disclosure allows users to actively trigger onboard cameras (e.g., internal and external cameras) to capture photos while driving (e.g., triggering a specific camera to capture multiple photos at a time), allowing them to unconsciously capture photos of scenery along the way. Furthermore, by utilizing an aesthetics assessment model installed on the vehicle, the captured images are scored using a trained aesthetics assessment model, filtering out high-quality photos. For example, the optimal image (the one with the highest score) is selected after sorting, annotated with the current geographic location information, and recommended to the user for storage. In this solution, the vehicle controller can also automatically trigger photography based on geographic location information, such as points of interest (POIs), such as highway intersections and tourist attractions, to automatically select the optimal image, annotate it, and store it. In addition, the vehicle controller can also generate a photo record of the vehicle (for example, generating a travel record combining the vehicle's geographic trajectory and pictures) based on the stored annotated images in units of years.

[0029] Hereinafter, specific examples of this solution will be described in more detail with reference to the accompanying drawings.

[0030] Example 1

[0031] Figure 1 1 shows a flow chart of the steps of a photographing method provided by this embodiment. For example, the method 100 may be as follows: Figure 8 The electronic device 600 shown is executed by a processor 601, which may be a vehicle controller or a vehicle camera controller. It should be understood that the method 100 may also include additional blocks not shown and / or may omit the blocks shown, and the scope of the present disclosure is not limited in this respect.

[0032] In step 101, during the driving of a vehicle, vehicle detection data is acquired through a vehicle detection device, and the vehicle detection data includes at least: a vehicle position.

[0033] In the embodiment, the vehicle detection device can be a vehicle-mounted position device or a first camera set inside the vehicle. The specific method can be determined according to actual needs and is not limited here.

[0034] In an embodiment, while the vehicle is driving, the vehicle controller can obtain vehicle detection data in real time through the vehicle detection equipment. The obtained vehicle detection data may include: vehicle location, points of interest at the vehicle location, facial data inside the vehicle, etc.

[0035] For example, during the driving of the vehicle, the vehicle controller obtains the vehicle position from the onboard position device in real time.

[0036] In step 102 , when there is an intersection between the interest point at the vehicle position and the preset interest point, the distance value between each target interest point in the intersection and the vehicle position is calculated.

[0037] In an embodiment, a point of interest (POI) can be a scenic spot or a highway intersection; accordingly, a preset point of interest can be a scenic spot where the user needs to take a photo, or a highway intersection where the user needs to take a photo; and a target point of interest can be a scenic spot where the user needs to take a photo at the vehicle's position, or a highway intersection where the user needs to take a photo at the vehicle's position. The specific point of interest can be determined according to actual needs and is not limited here.

[0038] In an embodiment, after obtaining the vehicle position, the points of interest at the vehicle position are obtained through an electronic map or navigation system, and then it is detected whether there is an intersection between the points of interest at the vehicle position and the preset points of interest. When there is an intersection, the distance value between each target point of interest in the intersection and the vehicle position is calculated.

[0039] For example, Figure 2 As shown, after obtaining the vehicle position through the Global Positioning System (GPS), the points of interest in the POI list corresponding to the vehicle position are obtained through GPS, and the preset points of interest in the candidate POI list pre-stored by the user are obtained from the local memory. Then, it is detected whether there is an intersection between the points of interest at the vehicle position and the preset points of interest. When there is an intersection between the obtained POI list and the candidate POI list stored locally on the vehicle, the distance value between each target point of interest in the POI intersection and the vehicle position is calculated.

[0040] In step 103, when the distance value meets the automatic shooting requirement, the vehicle-mounted camera is controlled to shoot.

[0041] In an embodiment, the automatic shooting requirement can be used to determine whether the vehicle detection data meets the user's photography needs. For example, the user needs to take pictures at a preset point of interest, or the user needs to take pictures when the human eyes stay in a gaze direction for too long. The specific requirements can be determined based on actual needs and are not limited here.

[0042] In an embodiment, after obtaining the distance value between each target point of interest and the vehicle position, since the target point of interest is an interest point at the intersection of the point of interest at the vehicle position and the preset point of interest, the target point of interest is a preset point of interest, which meets the automatic shooting requirement of taking pictures at the preset point of interest. If the on-board camera can capture high-quality images within the distance threshold range, the on-board camera can be controlled to shoot when the distance value is within the distance threshold range.

[0043] For example, after obtaining the distance values ​​between each target point of interest and the vehicle position, the maximum distance value in the distance value is calculated. When the maximum distance value is less than the distance threshold, it is determined that all target points of interest are within the shooting range of the vehicle-mounted camera. At this time, the vehicle-mounted camera is controlled to automatically shoot at an interval time t, and a total of M images are taken. M is a positive integer, and t can be the default value of the vehicle-mounted camera (for example: 1 second) or the value set in the vehicle controller (for example: 3 seconds). The specific value can be determined according to actual needs and is not limited here.

[0044] This embodiment can obtain the vehicle detection data of the vehicle during driving in real time through the vehicle detection equipment, so that when the vehicle detection data includes at least the vehicle position, the controller can obtain the vehicle position in real time, so that when the vehicle passes by a preset point of interest with beautiful scenery that the driver or passenger wants to record, it can calculate whether there is an intersection between the point of interest at the vehicle position and the preset point of interest. When there is an intersection, the distance value between each target point of interest in the intersection and the vehicle position is calculated to determine whether the distance value meets the automatic shooting requirement. When the distance value meets the automatic shooting requirement, the on-board camera is controlled to automatically shoot. This can prevent passengers from forgetting to send instructions to the controller when they are immersed in enjoying the scenery, resulting in missing images of preset points of interest, and prevent accidents caused by the driver's inattention when sending instructions to the controller, thereby reducing safety risks during vehicle driving.

[0045] In step 104, the images captured by the vehicle-mounted camera are filtered and stored.

[0046] In an embodiment, after the vehicle-mounted camera takes a picture, an image list is obtained. The vehicle controller can filter out the images in the image list that are blurry, repeated, or unwanted by the user by deleting them, and then store the filtered images in a memory.

[0047] For example, the vehicle-mounted camera automatically takes pictures at an interval of t, taking a total of M images to obtain an image list containing M images. The vehicle controller can obtain the blurred A images in the image list through a preset image processing method, and then filter out the A images by deleting them, and finally store (MA) = B filtered images in the memory.

[0048] This embodiment can automatically complete the process of screening and storing images by screening and storing images taken by the vehicle-mounted camera, thereby avoiding the user from spending energy on screening and storing, saving the user time and energy.

[0049] This embodiment provides a photography method that uses vehicle detection equipment to obtain real-time vehicle detection data while the vehicle is in motion. When the vehicle detection data includes at least the vehicle's position, a controller can obtain the vehicle's position in real time. When the vehicle passes a preset point of interest with beautiful scenery that the driver or passenger wants to record, the controller can calculate whether there is an intersection between the point of interest at the vehicle's position and the preset point of interest. If there is an intersection, the controller calculates the distance between each target point of interest in the intersection and the vehicle's position to determine whether the distance meets the automatic photography requirement. If the distance meets the automatic photography requirement, the controller controls the vehicle's camera to automatically capture the image. This prevents passengers from forgetting to send commands to the controller while enjoying the scenery, potentially missing images of the preset point of interest. It also prevents accidents caused by the driver's inattention while sending commands to the controller, thereby reducing safety risks during vehicle operation. Furthermore, after the vehicle's camera automatically captures the image, the images captured by the camera are automatically filtered and stored, eliminating the need for the user to spend time and effort on filtering and storing the images, saving the user time and energy.

[0050] Example 2

[0051] Figure 3 1 shows a flowchart of the steps of a photographing method provided by an embodiment of the present disclosure. For example, method 200 may be performed as follows: Figure 8 The electronic device 600 shown is executed by a processor 601, which may be a vehicle controller or a vehicle camera controller. It should be understood that the method 200 may also include additional blocks not shown and / or may omit the blocks shown, and the scope of the present disclosure is not limited in this respect.

[0052] In step 201, the vehicle detection device includes: an on-board positioning device; while the vehicle is traveling, the vehicle position is obtained through the on-board positioning device.

[0053] In the embodiment, the vehicle-mounted location device is a device for obtaining vehicle coordinates, such as GPS, Geographic Information Service (GIS), BeiDou Navigation System, etc., which can be determined according to actual needs and is not limited here.

[0054] In an embodiment, the vehicle detection device includes an on-board position device. When the vehicle is traveling, the vehicle controller obtains the vehicle position in real time through the on-board position device.

[0055] For example, Figure 2 As shown, during the driving process of the vehicle, the vehicle controller obtains the longitude and latitude information in real time through GPS, and the vehicle position can be determined based on the longitude and latitude information.

[0056] In this embodiment, by setting up a vehicle detection device including an on-board positioning device, the vehicle position can be obtained in real time through the on-board positioning device during the vehicle's driving process, so that when the vehicle passes by a preset point of interest with beautiful scenery that the driver or passenger wants to record, the on-board camera can be controlled to automatically shoot. This can prevent passengers from forgetting to send instructions to the controller when they are immersed in enjoying the scenery, resulting in missing images of the preset points of interest, and prevent accidents caused by the driver's inattention when sending instructions to the controller, thereby reducing safety risks during vehicle driving.

[0057] In step 202 , when there is an intersection between the interest point at the vehicle position and the preset interest point, the distance value between each target interest point in the intersection and the vehicle position is calculated.

[0058] This step can be described with reference to the detailed description of step 102 and will not be repeated here.

[0059] In step 203 , the distance value includes a minimum distance value; when the minimum distance value is less than a distance threshold, the vehicle-mounted camera is controlled to take a photo.

[0060] In an embodiment, the distance value is the distance value between the target point of interest and the vehicle position. Since there can be at least one target point of interest, when there is one target point of interest, the minimum distance value refers to this distance value. When there are at least two target points of interest, the minimum distance value refers to the minimum value among the distance values. The specific distance value can be determined according to actual needs and is not limited here.

[0061] In an embodiment, the distance threshold may be a default value of the vehicle camera (eg, 500 meters) or a value set in the vehicle controller (eg, 1 kilometer). The specific value may be determined based on actual needs and is not limited here.

[0062] In an embodiment, after obtaining the distance values ​​between each target point of interest and the vehicle position, a minimum distance value in the distance value is determined by a mathematical method. When the minimum distance value is less than the distance threshold, the vehicle-mounted camera is controlled to automatically shoot at an interval time t, and a total of M images are taken.

[0063] For example, Figure 2As shown in the figure, after calculating the distance between each target point of interest in the intersection of POIs and the vehicle position, the POI in the intersection of POIs that is closest to the current vehicle position is selected. If the minimum value of this closest distance is less than the distance threshold Dist, the various on-board cameras outside the vehicle are automatically triggered to take photos at an interval t, and a total of M photos are taken. In this way, the vehicle position determined by longitude and latitude and the POI at the vehicle position can be actively triggered to take photos without relying on people.

[0064] This embodiment, by setting the distance value to include a minimum distance value, can refine the automatic shooting requirement to when the minimum distance value is less than a distance threshold. Thus, when the minimum distance value is less than the distance threshold, the vehicle control can control the on-board camera to automatically shoot, so as to prevent passengers from forgetting to send instructions to the controller and missing photos when they are immersed in enjoying the scenery. In addition, there are safety risks if users take photos with their mobile phones or cameras while the vehicle is driving, such as when the driver sends instructions to the controller but is not paying attention, resulting in an accident. This implementation can reduce the occurrence of such safety risks and protect the lives and property of users.

[0065] In step 204, the images captured by the vehicle-mounted camera are filtered and stored.

[0066] This step can be described with reference to the detailed description of step 104 and will not be repeated here.

[0067] Another photographing method provided by this embodiment is to set the vehicle detection equipment to include an on-board positioning equipment, so that the vehicle position can be obtained in real time through the on-board positioning equipment during the driving of the vehicle, so that when the vehicle passes by a preset point of interest with beautiful scenery that the driver or passenger wants to record, it can be calculated whether there is an intersection between the point of interest at the vehicle position and the preset point of interest. When there is an intersection, the distance value between each target point of interest and the vehicle position in the intersection is calculated to determine whether the distance value meets the automatic shooting requirement. By setting the distance value to include a minimum distance value, the automatic shooting requirement can be refined to the minimum distance value being less than the distance threshold, so that when the minimum distance value is less than the distance threshold, the vehicle control can control the on-board camera to automatically shoot, so as to prevent passengers from forgetting to send instructions to the controller when they are immersed in enjoying the scenery and thus missing photos, and to prevent accidents caused by the driver's inattention when sending instructions to the controller.

[0068] Example 3

[0069] Figure 4 1 shows a flowchart of the steps of a photographing method provided by an embodiment of the present disclosure. For example, method 300 may be as follows: Figure 8The electronic device 600 shown is executed by a processor 601, which may be a vehicle controller or a vehicle camera controller. It should be understood that the method 300 may also include additional blocks not shown and / or may omit the blocks shown, and the scope of the present disclosure is not limited in this respect.

[0070] In step 301, the vehicle detection equipment further includes: a first camera arranged inside the vehicle; the vehicle detection data further includes: facial data; while the vehicle is traveling, the facial data is obtained through the first camera.

[0071] In an embodiment, the first camera is a camera facing the interior of the vehicle, and is used to obtain facial data of users inside the vehicle to perform user face detection and eye tracking. Face detection may include detecting blinking frequency, concentration level, facial expression recognition, etc. For example: detecting whether the number of blinks reaches a threshold (2 times / 3 times) when the line of sight falls on a certain area; detecting whether the time without blinking exceeds a certain threshold T (attention concentration) when the line of sight falls on a certain area; judging whether the user wants to take a photo at this time by recognizing the user's expression; eye tracking is a technology that measures the gaze point of the human eye and the degree of movement relative to the head; the first camera can be a 360° panoramic camera set on the roof inside the vehicle, or it can be a camera set inside the four windows of the vehicle. The specific details can be determined according to actual needs and are not limited here.

[0072] In an embodiment, while the vehicle is driving, facial data of users inside the vehicle is acquired in real time through a first camera disposed inside the vehicle to perform face detection and line of sight tracking of the users.

[0073] For example, when the driver is driving the vehicle, the driver's facial data is acquired in real time through a first camera set inside the four windows of the vehicle to perform face detection and line of sight tracking of the driver.

[0074] In step 302, the gaze direction and the dwell time of the human eyes are extracted from the facial data.

[0075] In an embodiment, the gaze direction refers to the direction in which the user's eyes are looking, and the dwell time refers to the duration in which the user's eyes are looking in one direction.

[0076] In an embodiment, after acquiring the facial data, the vehicle controller may extract the gaze direction of the human eyes in the facial data and the duration of the human eyes staying in the gaze direction through an image processing algorithm.

[0077] For example, after obtaining the driver's facial data through the first camera set inside the four windows of the vehicle, the vehicle controller can segment the facial data through an image processing algorithm to obtain facial data, calculate the position of the eyeballs, determine the gaze direction of the human eye, and determine that the eyeball position remains unchanged for a period of time based on the changes in the eyeball position within a preset time period, and then determine this period of time as the human eye's stay time.

[0078] In step 303, when the gaze direction and the dwell time meet the automatic shooting requirements, the vehicle-mounted camera is controlled to shoot.

[0079] In an embodiment, after obtaining the gaze direction of the eye and the dwell time of the human eye, when the gaze direction and dwell time meet the automatic shooting requirements of the human eye in one gaze direction, the vehicle-mounted camera is controlled to automatically shoot at an interval time t, and a total of M images are taken.

[0080] For example, after obtaining the gaze direction and the dwell time of the eyes, when the gaze direction is any window area and the dwell time is too long, the vehicle-mounted camera is controlled to automatically shoot at an interval time t, and a total of M images are taken.

[0081] This embodiment, by providing a vehicle detection device including a first camera disposed inside the vehicle, can acquire facial data of users inside the vehicle in real time through the first camera while the vehicle is in motion, so as to perform facial detection and line of sight tracking of the user. After extracting the gaze direction and dwell time of the user's eyes from the facial data, if the gaze direction and dwell time meet the automatic shooting requirements, the vehicle control can control the onboard camera to automatically shoot, so as to prevent passengers from forgetting to send instructions to the controller while immersed in enjoying the scenery and thus missing a shot. This way, controlling the onboard camera shooting in a triggering manner of line of sight tracking can help users shoot without realizing it or forgetting to shoot, thereby enhancing the user's experience of taking pictures with the onboard camera.

[0082] Optionally, step 303 may include

[0083] The vehicle camera includes: a second camera arranged outside the vehicle; when the gaze direction stays in a preset area and the stay time is greater than a time threshold, the second camera is controlled to shoot.

[0084] In an embodiment, the second camera is a camera facing the outside of the vehicle and is used to capture images of points of interest. The second camera can be a 360° panoramic camera set on the roof outside the vehicle, or it can be a camera set outside the four windows of the vehicle. The specific camera can be determined according to actual needs and is not limited here.

[0085] In the embodiment, the preset area can be any one of the four windows, or the area of ​​the front windshield of the vehicle. The specific area can be determined according to actual needs and is not limited here.

[0086] In an embodiment, the time threshold may be a default value of the vehicle camera (eg, 30 seconds) or a value set in the vehicle controller (eg, 1 minute). The specific value may be determined based on actual needs and is not limited here.

[0087] In an embodiment, after obtaining the gaze direction of the eye and the dwell time of the human eye, when the gaze direction stays in a preset area and the dwell time is greater than a time threshold, the second camera set outside the vehicle is controlled to automatically shoot at an interval time t, and a total of M images are taken.

[0088] For example, Figure 5 As shown, the driver's line of sight is detected based on the facial data detected by the first camera. That is, the vehicle controller detects which part of the four windows the driver's line of sight falls on. When the vehicle controller detects that the driver's line of sight falls on a certain area of ​​any window area, the vehicle controller obtains the window area corresponding to the direction of the eye's gaze and continues to determine the duration of the eye's stay in this window area. If the stay time exceeds a certain time threshold T (for example, 30 seconds), the vehicle controller determines that the driver needs to capture the scene outside the window area. The data of the scene outside the window area is transmitted to the second camera used for shooting, triggering the second camera to capture the scene outside the window area at an interval t, for a total of M images. If the vehicle controller does not detect that the driver's line of sight falls on a certain area of ​​any window area, the first camera continues to detect the user's face to obtain facial data.

[0089] This embodiment sets the vehicle camera including a second camera set outside the vehicle, which can detect the user's line of sight based on the facial data detected by the first camera. When the vehicle controller detects that the gaze direction stays in a preset area and the stay time is greater than the time threshold, the vehicle control controls the on-board camera to automatically shoot, so as to prevent passengers from forgetting to send instructions to the controller when they are immersed in enjoying the scenery and missing photos.

[0090] In step 304, the images captured by the vehicle-mounted camera are filtered and stored.

[0091] This step can be described with reference to the detailed description of step 104 and will not be repeated here.

[0092] Another photo-taking method provided by this embodiment is to set a vehicle detection device including a first camera set inside the vehicle. During the driving of the vehicle, the facial data of the user inside the vehicle can be obtained in real time through the first camera to perform user face detection and line of sight tracking. By setting the vehicle camera to include a second camera set outside the vehicle, the user's line of sight can be detected based on the facial data detected by the first camera. When the vehicle controller detects that the gaze direction stays in a preset area and the stay time is greater than a time threshold, the vehicle control controls the on-board camera to automatically take pictures, so as to prevent passengers from forgetting to send instructions to the controller when they are immersed in enjoying the scenery and thus missing pictures.

[0093] Example 4

[0094] Figure 6 4 shows a flowchart of a method for taking a picture provided by an embodiment of the present disclosure. For example, method 400 may be performed as follows: Figure 8 The electronic device 600 shown is executed by a processor 601, which may be a vehicle controller or a vehicle camera controller. It should be understood that the method 400 may also include additional blocks not shown and / or may omit the blocks shown, and the scope of the present disclosure is not limited in this respect.

[0095] In step 401, a preset data set is obtained.

[0096] In the embodiment, the preset data set may be a data set created by a user or a data set downloaded from the Internet. The specific data set may be determined according to actual needs and is not limited here.

[0097] In an embodiment, the user uses a data set downloaded from the Internet as a preset data set.

[0098] For example, before the images captured by the vehicle-mounted camera are input into the aesthetics evaluation model, the data set downloaded by the user from the Internet is used as a preset data set.

[0099] In step 402, an aesthetic evaluation model is trained according to a preset data set to obtain a trained aesthetic evaluation model.

[0100] In one embodiment, an aesthetic evaluation model is used to determine the aesthetics of images in a preset input dataset. The aesthetic evaluation model is a deep learning-based convolutional neural network model. It is an image scoring model built based on the image aesthetics dataset and comprehensively considers factors such as color, tone, depth of field, and composition.

[0101] In an embodiment, images in a preset data set are input into an aesthetic evaluation model to obtain a probability distribution of the preset data set (e.g., 3 probability values ​​or 10 probability values), and the weighted sum of each probability value in the probability distribution is calculated to obtain the aesthetics.

[0102] For example, if the aesthetics evaluation model can output three probability values, the image in the preset data set is input into the aesthetics evaluation model to obtain a probability distribution consisting of three probability values, and the weighted sum of each probability value in the probability distribution is calculated to obtain the aesthetics of the image.

[0103] In step 403, the image is input into the trained aesthetic evaluation model to obtain the aesthetics of the image, and the clarity of the image is calculated using a preset image processing method.

[0104] In an embodiment, a preset image processing method is used to blur an image to compare the blurred image with the image to obtain the clarity of the image, such as reblur and peak signal-to-noise ratio (PSNR). The specific method can be determined according to actual needs and is not limited here.

[0105] In an embodiment, after the vehicle controller controls the on-board camera to take a picture, or after the user controls one of the on-board cameras placed at the four windows of the car for taking pictures of points of interest through a preset button to take a picture, the image taken by the on-board camera is input into a trained aesthetics evaluation model to obtain the aesthetics of the image, and the clarity of the image is calculated through secondary blurring to quickly obtain the clarity of the image.

[0106] For example, Figure 2 and Figure 5 As shown in the figure, the vehicle controller automatically triggers the onboard camera, or the user manually triggers the camera via a preset button. The camera automatically captures M images at intervals of t. After capturing a total of M images, the M images are fed into a trained aesthetics evaluation model for evaluation. The evaluation result is the aesthetics score assigned to the image data by the model. The aesthetics score can range from [0 to 1], with 0 being the lowest score and 1 being the highest. Manual triggering takes precedence over automatic triggering.

[0107] In step 404, a weighted sum is performed on the aesthetics and clarity of the image to obtain a score for the image.

[0108] In an embodiment, a weight is pre-set for both aesthetics and clarity. For example, the weight of aesthetics is 0.7, and the weight of clarity is 0.3, that is, the sum of the weights of aesthetics and clarity can be 1. The score range can be: [0, 1], with 0 being the lowest and 1 being the highest. The specific score can be determined according to actual needs and is not limited here.

[0109] In an embodiment, after obtaining the aesthetics and clarity of an image, a weighted sum is performed on the aesthetics and clarity of the image to obtain a score of the image.

[0110] For example, the weight of aesthetics is 0.7, the weight of clarity is 0.3, the aesthetics of the image is 7, the clarity of the image is 3, and the weighted sum of the aesthetics and clarity of the image is 0.58.

[0111] In step 405 , images with scores greater than a score threshold are taken as filtered images.

[0112] In an embodiment, the score threshold may be a default value of the vehicle camera (eg, 0.5) or a value set in the vehicle controller (eg, 0.6). The specific value may be determined based on actual needs and is not limited here.

[0113] In an embodiment, the vehicle controller may select images that meet a target score requirement as filtered images. For example, the vehicle controller selects images with scores greater than or equal to a threshold score as filtered images. If the output of step 405 is null, the process returns to the previous steps (e.g., 101-103, 201-203, or 301-303) of controlling the vehicle camera to capture images.

[0114] For example, Figure 2 As shown, when the weighted sum of the beauty and clarity of the image is obtained and the score of the image is greater than the score threshold Score, the images with scores less than the score threshold Score are deleted to complete the screening, and then the remaining high-quality images are used as the screened images.

[0115] In step 406 , the filtered images are annotated by vehicle location and stored.

[0116] In an embodiment, the vehicle controller inputs the vehicle location into the filtered image to display it in the filtered image, or names the filtered image based on the vehicle location to mark the filtered image, and then recommends the filtered image to the user. When the user selects the recommended image, the selected recommended image is stored; when the user does not select, all filtered images are stored.

[0117] For example, the vehicle controller can use the POI name, longitude and latitude at the current vehicle location to annotate and store the filtered image (for example: within the same day, under a single POI, if step 406 is executed successfully, the steps before controlling the vehicle camera to shoot and steps 401 to 405 will no longer be executed).

[0118] This embodiment obtains a preset data set and can train an aesthetics evaluation model based on the preset data set to obtain a trained aesthetics evaluation model. In this way, after the vehicle controller controls the on-board camera to shoot, the image can be input into the trained aesthetics evaluation model to obtain the aesthetics of the image. In this way, the captured images can be automatically screened using the aesthetics evaluation model, and higher-quality images can be recommended to users. The clarity of the image is calculated using a preset image processing method, and then the aesthetics and clarity of the image are weightedly summed to obtain the score of the image. In this way, images with scores less than the score threshold can be automatically deleted, and images with scores greater than the score threshold can be used as screened images, so that users do not have to spend energy on screening and storage, saving users time and energy.

[0119] Optionally, step 406 may include

[0120] Step 4061: When there are at least two filtered images, sort the scores of the filtered images from large to small, and select the first N images from the sorted images as recommended images to recommend to the user; where N is a positive integer.

[0121] In an embodiment, when there is only one filtered image, the filtered image can be directly recommended to the user; when there are at least two filtered images, the scores of the filtered images are sorted from large to small, and the top N images are selected from the sorted images as recommended images to the user.

[0122] Exemplarily, when there is only one filtered image, the filtered image is directly recommended to the user; when there are at least two filtered images, the scores of the filtered images are sorted from large to small, and the image with the largest score is selected and recommended to the user.

[0123] Step 4062: annotate and store the recommended image by the vehicle location; or, when the user selects a recommended image, annotate and store the selected recommended image by the vehicle location.

[0124] In an embodiment, when the user selects a recommended image, the selected recommended image is marked and stored; when the user does not select any recommended image, all filtered images are marked and stored.

[0125] For example, Figure 2 As shown, after the remaining high-quality images are selected as the filtered images, the filtered images or the filtered images with the largest scores are selected from the remaining high-quality filtered images for annotation and storage.

[0126] This embodiment automatically implements the labeling and storage functions by sorting the scores of the filtered images from large to small when there are at least two filtered images, and selecting the first N images from the sorted images as recommended images to recommend to the user; marking and storing the recommended images according to the vehicle position; or marking and storing the selected recommended images according to the vehicle position when the user selects the recommended images, so as to avoid the user having to spend energy on labeling and storing, thereby saving the user time and energy.

[0127] In step 407 , a photographic record of the vehicle is generated based on the stored annotated image at a preset time interval.

[0128] In an embodiment, the preset duration can be the default value of the vehicle camera (for example, 6 months) or the value set in the vehicle controller (for example, 1 year). The specific duration can be determined based on actual needs and is not limited here.

[0129] In an embodiment, at preset time intervals, the stored annotated image data is obtained from the local or cloud storage of the vehicle, and then a photo record of the vehicle is generated according to the POI name, longitude and latitude at the vehicle's location. The image and the POI at the geographic location and the longitude and latitude data can be combined to automatically generate a travel record centered on the vehicle's trajectory.

[0130] Exemplarily, in units of years, based on the stored labeled image data, a photographic record of the vehicle is generated as a vehicle travel record.

[0131] This embodiment generates a photo record of the vehicle based on the stored annotated images at preset time intervals. The photo record of the vehicle can be used as a travel photo of the vehicle trajectory. It can not only provide users with a stage-by-stage trajectory organization and summarization function, but also enhance the individual attributes of the vehicle and improve the stickiness between the vehicle and the user.

[0132] Another photography method provided by this embodiment obtains a preset data set and can train an aesthetics assessment model based on the preset data set to obtain a trained aesthetics assessment model. Thus, after the vehicle controller controls the onboard camera to capture, the image can be input into the trained aesthetics assessment model to obtain the image's aesthetics. The image's clarity is then calculated using a preset image processing method. A weighted summation of the image's aesthetics and clarity is then performed to obtain an image score. This automatically removes images with scores below a threshold and selects images with scores above the threshold as filtered images, eliminating the user's effort in filtering and storing them, saving the user time and effort. Furthermore, when there are at least two filtered images, the filtered images are sorted from highest to lowest scores, and the top N images from the sorted images are selected as recommended images and recommended to the user. The recommended images are annotated and stored based on the vehicle's location. Alternatively, when the user selects a recommended image, the selected recommended image is annotated and stored based on the vehicle's location. This automatic annotation and storage function eliminates the user's effort in annotation and storage, further saving the user's time and effort. In addition, by generating a photo record of the vehicle based on the stored annotated images at preset time intervals, the photo record of the vehicle can be used as a travel photo of the vehicle trajectory. This not only provides users with a stage-by-stage trajectory organization and summarization function, but also enhances the individual attributes of the vehicle and improves the stickiness between the vehicle and the user.

[0133] Example 5

[0134] Figure 7 The following is a block diagram of a photographing device provided by an embodiment of the present disclosure. The device 500 may be a third-party hardware device independent of the vehicle-mounted system, and the device 500 may include:

[0135] The acquisition module 501 is used to acquire vehicle detection data through a vehicle detection device during vehicle driving. The vehicle detection data at least includes: vehicle position.

[0136] The calculation module 502 is configured to calculate the distance between each target interest point in the intersection and the vehicle position when there is an intersection between the interest point at the vehicle position and the preset interest point.

[0137] The control module 503 is used to control the vehicle-mounted camera to take pictures when the distance value meets the automatic shooting requirement.

[0138] Optionally, the distance value includes a minimum distance value; the control module 503 is further configured to control the vehicle-mounted camera to take pictures when the minimum distance value is less than a distance threshold.

[0139] Optionally, the vehicle detection device includes: an on-board position device; and an acquisition module 501, further configured to acquire the vehicle position through the on-board position device while the vehicle is traveling.

[0140] Optionally, the vehicle detection equipment also includes: a first camera arranged inside the vehicle; the vehicle detection data also includes: facial data; the acquisition module 501 is also used to obtain facial data through the first camera during the vehicle driving process; extract the gaze direction and stay time of the human eyes in the facial data; the control module 503 is also used to control the vehicle-mounted camera to shoot when the gaze direction and stay time meet the automatic shooting requirements.

[0141] Optionally, the vehicle camera includes: a second camera arranged outside the vehicle; and a control module 503, further configured to control the second camera to shoot when the gaze direction stays in a preset area and the stay time is greater than a time threshold.

[0142] Optionally, the apparatus 500 may further include: a screening and storage module 504 for screening and storing images captured by the vehicle-mounted camera.

[0143] Optionally, the screening and storage module 504 is further used to input the image into a trained aesthetics evaluation model to obtain the aesthetics of the image, and calculate the clarity of the image through a preset image processing method; perform weighted summation on the aesthetics and clarity of the image to obtain the image score; use the image with a score greater than the score threshold as the screened image; and mark and store the screened image according to the vehicle position.

[0144] Optionally, the screening and storage module 504 is further used to sort the scores of the screened images from large to small when there are at least two screened images, and select the first N images from the sorted images as recommended images to recommend to the user; wherein N is a positive integer; the recommended images are marked and stored by the vehicle position; or, when the user selects a recommended image, the selected recommended image is marked and stored by the vehicle position.

[0145] Optionally, the apparatus 500 may further include: a generating module 505, configured to generate a photographic record of the vehicle based on the stored annotated images at predetermined intervals.

[0146] A photographing device provided in this embodiment can obtain vehicle detection data of the vehicle during driving in real time through vehicle detection equipment, so that when the vehicle detection data includes at least the vehicle position, the controller can obtain the vehicle position in real time, so that when the vehicle passes by a preset point of interest with beautiful scenery that the driver or passenger wants to record, it can calculate whether there is an intersection between the point of interest at the vehicle position and the preset point of interest. When there is an intersection, the distance value between each target point of interest in the intersection and the vehicle position is calculated to determine whether the distance value meets the automatic shooting requirement. When the distance value meets the automatic shooting requirement, the on-board camera is controlled to automatically shoot. This can prevent passengers from forgetting to send instructions to the controller when they are immersed in enjoying the scenery, resulting in missing images of preset points of interest, and prevent accidents caused by the driver's inattention when sending instructions to the controller, thereby reducing safety risks during vehicle driving.

[0147] Example 6

[0148] Figure 8 The following is a block diagram of an electronic device provided by an embodiment of the present disclosure. The electronic device 600 may be a third-party hardware device independent of the vehicle-mounted system. The electronic device 600 may include a processor 601, a memory 602, and a program or instruction stored in the memory 602 and executable by the processor 601. When executed by the processor 601, the program or instruction implements the steps of the above-described photographing method.

[0149] Optionally, the processor 601 is also used to obtain vehicle detection data through a vehicle detection device during vehicle driving, and the vehicle detection data includes at least: the vehicle position; when there is an intersection between the point of interest at the vehicle position and the preset point of interest, calculating the distance value between each target point of interest in the intersection and the vehicle position; when the distance value meets the automatic shooting requirements, controlling the vehicle-mounted camera to shoot.

[0150] Optionally, the distance value includes a minimum distance value; the processor 601 is further configured to control the vehicle-mounted camera to shoot when the minimum distance value is less than a distance threshold.

[0151] Optionally, the vehicle detection device includes: an on-board positioning device; and the processor 601 is further configured to obtain the vehicle position through the on-board positioning device while the vehicle is traveling.

[0152] Optionally, the vehicle detection equipment also includes: a first camera arranged inside the vehicle; the vehicle detection data also includes: facial data; the processor 601 is also used to obtain facial data through the first camera during the vehicle driving process; extract the gaze direction and stay time of the human eyes in the facial data; when the gaze direction and stay time meet the automatic shooting requirements, control the vehicle-mounted camera to shoot.

[0153] Optionally, the vehicle camera includes: a second camera arranged outside the vehicle; and the processor 601 is further used to control the second camera to shoot when the gaze direction stays in a preset area and the stay time is greater than a time threshold.

[0154] Optionally, the processor 601 is further used to filter images taken by the vehicle-mounted camera; and the memory 602 is further used to store the annotated images.

[0155] Optionally, the processor 601 is further used to input the image into a trained aesthetics evaluation model to obtain the aesthetics of the image, and calculate the clarity of the image through a preset image processing method; perform weighted summation on the aesthetics and clarity of the image to obtain the image score; use the image with a score greater than the score threshold as the filtered image; annotate the filtered image according to the vehicle position; and the memory 602 is further used to store the annotated image.

[0156] Optionally, the processor 601 is further used to, when there are at least two filtered images, sort the scores of the filtered images from large to small, and select the first N images from the sorted images as recommended images to recommend to the user; wherein N is a positive integer; mark and store the recommended images according to the vehicle position; or, when the user selects the recommended image, mark the selected recommended image according to the vehicle position; the memory 602 is also used to store the marked images.

[0157] Optionally, the processor 601 is further configured to generate a photographic record of the vehicle based on the stored annotated image at preset time intervals.

[0158] An electronic device provided by this embodiment can obtain vehicle detection data of the vehicle during driving in real time through a vehicle detection device, so that when the vehicle detection data includes at least the vehicle position, the controller can obtain the vehicle position in real time, so that when the vehicle passes by a preset point of interest with beautiful scenery that the driver or passenger wants to record, it can calculate whether there is an intersection between the point of interest at the vehicle position and the preset point of interest. When there is an intersection, the distance value between each target point of interest in the intersection and the vehicle position is calculated to determine whether the distance value meets the automatic shooting requirement. When the distance value meets the automatic shooting requirement, the on-board camera is controlled to automatically shoot. This can prevent passengers from forgetting to send instructions to the controller when they are immersed in enjoying the scenery, resulting in missing images of preset points of interest, and prevent accidents caused by the driver's inattention when sending instructions to the controller, thereby reducing safety risks during vehicle driving.

[0159] Example 7

[0160] This embodiment provides a readable storage medium, which stores a program or instruction. When the program or instruction is executed by a processor, the steps of the above-mentioned photographing method are implemented.

[0161] The present embodiment provides a readable storage medium, which can obtain vehicle detection data of the vehicle during driving in real time through vehicle detection equipment, so that when the vehicle detection data includes at least the vehicle position, the controller can obtain the vehicle position in real time, so that when the vehicle passes by a preset point of interest with beautiful scenery that the driver or passenger wants to record, it can calculate whether there is an intersection between the point of interest at the vehicle position and the preset point of interest. When there is an intersection, the distance value between each target point of interest in the intersection and the vehicle position is calculated to determine whether the distance value meets the automatic shooting requirement. When the distance value meets the automatic shooting requirement, the on-board camera is controlled to automatically shoot. This can prevent passengers from forgetting to send instructions to the controller when they are immersed in enjoying the scenery, resulting in missing images of preset points of interest, and prevent accidents caused by the driver's inattention when sending instructions to the controller, thereby reducing safety risks during vehicle driving.

[0162] Example 8

[0163] This embodiment provides a vehicle including a processor configured to execute the photographing method according to the first aspect.

[0164] A vehicle provided in this embodiment can obtain vehicle detection data of the vehicle during driving in real time through vehicle detection equipment, so that when the vehicle detection data includes at least the vehicle position, the controller can obtain the vehicle position in real time, so that when the vehicle passes by a preset point of interest with beautiful scenery that the driver or passenger wants to record, it can calculate whether there is an intersection between the point of interest at the vehicle position and the preset point of interest. When there is an intersection, the distance value between each target point of interest in the intersection and the vehicle position is calculated to determine whether the distance value meets the automatic shooting requirement. When the distance value meets the automatic shooting requirement, the on-board camera is controlled to automatically shoot. This can prevent passengers from forgetting to send instructions to the controller when they are immersed in enjoying the scenery, resulting in missing images of preset points of interest, and prevent accidents caused by the driver's inattention when sending instructions to the controller, thereby reducing safety risks during vehicle driving.

[0165] The present disclosure relates to methods, apparatuses, electronic devices, readable storage media, and / or computer program products, and vehicles. The computer program products may include computer-readable program instructions for executing various aspects of the present disclosure.

[0166] Computer-readable storage media can be a tangible device that can keep and store the instructions used by the instruction execution device.Computer-readable storage media can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device or any suitable combination thereof.More specific examples (non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, for example, a punch card or a convex structure in a groove having instructions stored thereon, and any suitable combination thereof.Computer-readable storage media used herein is not interpreted as a transient signal itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagated by waveguides or other transmission media (for example, light pulses by fiber optic cables), or electrical signals transmitted by wires.

[0167] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in the computer-readable storage medium in each computing / processing device.

[0168] The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, and conventional procedural programming languages ​​such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., utilizing an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions. The electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0169] Various aspects of the present disclosure are described herein with reference to flowcharts and / or block diagrams of methods, apparatus, and computer program products according to embodiments of the present disclosure. It should be understood that each block of the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer-readable program instructions.

[0170] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine such that when these instructions are executed by the processing unit of the computer or other programmable data processing device, a device is generated that implements the functions / actions specified in one or more blocks in the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium, where these instructions cause the computer, programmable data processing device, and / or other device to operate in a specific manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing various aspects of the functions / actions specified in one or more blocks in the flowchart and / or block diagram.

[0171] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more blocks in the flowchart and / or block diagram.

[0172] The flow charts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of a module, program segment or instruction includes one or more executable instructions for realizing the prescribed logical function. In some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart, can be implemented by a dedicated hardware-based system that performs the prescribed function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0173] While various embodiments of the present disclosure have been described above, the foregoing description is intended to be illustrative, non-exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is selected to best explain the principles of the embodiments, their practical applications, or technological improvements in the marketplace, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A photographing method, characterized in that: The method comprises: During the driving process of the vehicle, vehicle detection data is obtained through the vehicle detection equipment, and the vehicle detection data at least includes: vehicle position; When there is an intersection between the interest point at the vehicle position and the preset interest point, calculating the distance value between each target interest point in the intersection and the vehicle position; When the distance value meets the automatic shooting requirement, controlling the vehicle-mounted camera to shoot; The distance value includes a minimum distance value; when the minimum distance value is less than a distance threshold, controlling the vehicle-mounted camera to take a picture; The distance value includes a maximum distance value; when the maximum distance value is less than a distance threshold, controlling the vehicle-mounted camera to capture at least one image; Wherein, the vehicle detection device further includes: a first camera arranged inside the vehicle; the vehicle detection data further includes: facial data; The method of obtaining vehicle detection data by using a vehicle detection device during vehicle driving includes: While the vehicle is traveling, acquiring the facial data through the first camera; Extracting the gaze direction and dwell time of the human eyes from the facial data; When the gaze direction and the dwell time meet the automatic shooting requirements, controlling the vehicle-mounted camera to shoot; Alternatively, user face detection is performed on the facial data to obtain blinking frequency, concentration level, and facial expression, and when the blinking frequency, concentration level, or facial expression meets the automatic shooting requirements, the vehicle-mounted camera is controlled to shoot.

2. The method according to claim 1, characterized in that The vehicle detection equipment includes: a vehicle-mounted position device; The method of obtaining vehicle detection data by using a vehicle detection device during vehicle driving includes: During the driving of the vehicle, the vehicle position is acquired through the vehicle-mounted position device.

3. The method according to claim 1, characterized in that The vehicle camera includes: a second camera disposed outside the vehicle; When the gaze direction and the dwell time meet the automatic shooting requirements, controlling the vehicle-mounted camera to shoot includes: When the gaze direction stays in a preset area and the stay time is greater than a time threshold, the second camera is controlled to shoot.

4. The method according to claim 1, wherein After controlling the vehicle-mounted camera to shoot, the method further includes: The images captured by the vehicle-mounted camera are screened and stored.

5. The method according to claim 4, characterized in that The screening and storing of images captured by the vehicle-mounted camera includes: Inputting the image into a trained aesthetic evaluation model to obtain the aesthetics of the image, and calculating the clarity of the image using a preset image processing method; Performing a weighted summation on the aesthetics and clarity of the image to obtain a score for the image; The image with a score greater than the score threshold is used as a screened image; The filtered image is annotated and stored according to the vehicle position.

6. The method according to claim 5, characterized in that The marking and storing of the filtered image according to the vehicle position includes: When there are at least two filtered images, sorting the scores of the filtered images from large to small, and selecting the top N images from the sorted images as recommended images to recommend to the user; wherein N is a positive integer; The recommended image is marked and stored according to the vehicle position; or, when the user selects the recommended image, the selected recommended image is marked and stored according to the vehicle position.

7. The method according to claim 5, characterized in that After annotating and storing the filtered image according to the vehicle position, the method further includes: At preset intervals, a photo record of the vehicle is generated based on the stored annotated images.

8. An electronic device, characterized in that: The method comprises a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the photographing method according to any one of claims 1 to 7.

9. A vehicle, characterized in that: The device comprises a processor, wherein the processor is configured to execute the photographing method according to any one of claims 1 to 7.

Images