CN112699862B - Image data processing method, device, equipment and storage medium - Google Patents
Image data processing method, device, equipment and storage medium Download PDFInfo
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- CN112699862B CN112699862B CN202110316575.4A CN202110316575A CN112699862B CN 112699862 B CN112699862 B CN 112699862B CN 202110316575 A CN202110316575 A CN 202110316575A CN 112699862 B CN112699862 B CN 112699862B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/005—General purpose rendering architectures
Abstract
The application discloses an image data processing method, an image data processing device, image data processing equipment and a storage medium. The method comprises the following steps: responding to a trigger message sent by a user, and determining the vehicle type in an image frame shot by a camera by adopting a vehicle type recognition algorithm; determining a vehicle rendering model corresponding to the vehicle type according to the vehicle type and a preset corresponding relation between the vehicle type and the vehicle rendering model; and generating and displaying an auxiliary driving image frame according to the vehicle rendering model. According to the method and the device, the image data are processed, the rendering model is used for replacing the image frame shot in real time, the image of the rendering model is simple, the color is single, many details are omitted, the attention of a user is improved, the phenomenon that the user distracts from the details of the image which are irrelevant and interferes with driving is avoided, and the user is helped to drive a vehicle better.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to an image data processing method, apparatus, device, and storage medium.
Background
The camera of vehicle gathers the image data in the place ahead and sends for intelligent on-vehicle networking terminal, and among the prior art, intelligent on-vehicle networking terminal is the simple image that reflects the road in the place ahead in real time, does not handle image data, and the user is when watching the picture, is probably attracted by some useful irrelevant factors, for example, the colour of preceding vehicle, picture on the car etc. and influence the user and notice useful information.
Disclosure of Invention
A primary object of the present application is to provide an image data processing method, apparatus, device, and storage medium to solve the above-mentioned problems.
In order to achieve the above object, according to an aspect of the present application, there is provided an image data processing method including:
an image data processing method, comprising:
responding to a trigger message sent by a user, and determining the vehicle type in an image frame shot by a camera by adopting a vehicle type recognition algorithm;
determining a vehicle rendering model corresponding to the vehicle type according to the vehicle type and a preset corresponding relation between the vehicle type and the vehicle rendering model;
and generating and displaying an auxiliary driving image frame according to the vehicle rendering model.
In one embodiment, the method further comprises: judging whether the spacing distance between the user vehicle and the front nearest vehicle is smaller than a preset threshold value or not;
if so, selecting a vehicle rendering model with a tail display warning lamp for the nearest vehicle from a rendering model library.
In one embodiment, if the separation distance is less than a predetermined threshold, the method further comprises: emitting a second color light wave by the vehicle in the driving assistance image frame;
if the separation distance is greater than or equal to a predetermined threshold, the vehicle emits a first color light wave in the driving assistance image frame.
In one embodiment, the method further comprises: if a pedestrian is detected in front of the user vehicle in the image frames shot by the camera, displaying a rendering model of the pedestrian in the auxiliary driving image frames; and the rendering model of the user vehicle emits red light waves and emits warning sounds.
In one embodiment, the method further comprises: and if the animal in front of the user vehicle is detected in the image frame shot by the camera, displaying an animal rendering model in the auxiliary driving image frame.
In one embodiment, the method further comprises: and if a traffic accident in front of the user vehicle is detected in the image frames shot by the camera, displaying a rendering model of the traffic accident in the auxiliary driving image frames.
In one embodiment, the method further comprises: if two people are detected in the image frame shot by the camera;
calculating a distance between the two persons in the image frames taken by the camera,
if the distance is less than a predetermined threshold;
a character rendering model is displayed instead of the two persons in the assistant driving image frame.
According to a second aspect of the embodiments of the present invention, there is also provided an image data processing apparatus including:
the vehicle type determining module is used for responding to a trigger message sent by a user and determining the type of a vehicle in an image frame shot by the camera by adopting a vehicle type recognition algorithm;
the rendering model determining module is used for determining a vehicle rendering model corresponding to the vehicle type according to the vehicle type and a preset corresponding relation between the vehicle type and the vehicle rendering model;
and the image frame generating module is used for generating and displaying the auxiliary driving image frame according to the vehicle rendering model.
In one embodiment, the rendering model determining module is further configured to determine whether a separation distance between the user vehicle and a nearest vehicle ahead is less than a predetermined threshold;
if so, selecting a vehicle rendering model with a tail display warning lamp for the nearest vehicle from a rendering model library.
In one embodiment, the image frame generation module is further configured to emit a second color light wave by the vehicle in the driving assistance image frame if the separation distance is less than a predetermined threshold;
if the separation distance is greater than or equal to a predetermined threshold, the vehicle emits a first color light wave in the driving assistance image frame.
In one embodiment, the image frame generation module is further configured to display a rendering model of a pedestrian in the driving assistance image frame if the pedestrian is detected in front of the user vehicle in the image frame captured by the camera; and the rendering model of the user vehicle emits red light waves and emits warning sounds.
In one embodiment, the image frame generation module is further configured to display an animal rendering model in the driving assistance image frame if an animal is detected in front of the user vehicle in the image frame captured by the camera.
In one embodiment, the image frame generation module is further configured to display a rendering model of a traffic accident in the driving assistance image frame if the traffic accident is detected in front of the user vehicle in the image frames captured by the camera.
In one embodiment, the image frame generation module is further configured to, if two persons are detected in the image frame captured by the camera;
calculating a distance between the two persons in the image frames taken by the camera,
if the distance is less than a predetermined threshold;
a character rendering model is displayed instead of the two persons in the assistant driving image frame.
According to a third aspect of an embodiment of the present invention, an embodiment of the present application further proposes an image data processing apparatus including: at least one processor and at least one memory;
the memory is to store one or more program instructions;
the processor is configured to execute one or more program instructions to perform the method of any one of the above.
According to a fourth aspect of the embodiments of the present invention, the embodiments of the present application also propose a computer-readable storage medium having one or more program instructions embodied therein, the one or more program instructions being configured to be executed to perform the method according to any one of the above-mentioned methods.
The image rendering method and the device replace the image frames shot in real time with the rendering model, the image rendering model is simple in image and single in color, many details are omitted, attention of a user is improved, the user is prevented from being distracted to the irrelevant image details, and driving safety is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, serve to provide a further understanding of the application and to enable other features, objects, and advantages of the application to be more apparent. The drawings and their description illustrate the embodiments of the invention and do not limit it. In the drawings:
FIG. 1 is a flow chart of a method of image data processing according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of an image data processing apparatus according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an image data processing apparatus according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
The present application proposes an image data processing method, which refers to a flow chart of an image data processing method based on intelligent traffic shown in fig. 1; the method comprises the following steps:
step S102, responding to a trigger message sent by a user, and determining the vehicle type in an image frame shot by a camera by adopting a vehicle type recognition algorithm;
specifically, when a user wants to start a current monitoring screen, the user can click a trigger start button to display an image frame for driving assistance on a display interface of the intelligent vehicle-mounted internet terminal in the vehicle. The camera shoots an image in front of the vehicle, generates an image frame and sends the image frame to the intelligent vehicle-mounted internet terminal. For the image frames, a vehicle type identification algorithm may be employed to identify the type of vehicle in the image. The vehicle types include, but are not limited to, cars, buses, trucks, bicycles, among others.
Step S104, determining a vehicle rendering model corresponding to the vehicle type according to the vehicle type and a preset corresponding relation between the vehicle type and the vehicle rendering model;
wherein the rendering model omits much unnecessary detail compared to the actual image. Such as colors, patterns, letters, etc., of the surface of the vehicle body. The user can concentrate on watching the rendering model, and unnecessary factors are avoided to distract the user.
Specifically, rendering models of various types of vehicles are stored in the vehicle rendering model library. For each vehicle type, at least one rendering model is included. Taking a family car as an example, a rendering model of the car is used for replacing display regardless of the appearance, brand and characters of the car.
And S106, generating and displaying an auxiliary driving image frame according to the vehicle rendering model.
Specifically, according to the relative position relationship in the image frames shot by the camera, in the driving assistance image frames, the rendering models are set by still keeping the position relationship.
In some embodiments, a map display image frame sent by a background server is received and displayed;
and in the map display image frame, displaying a vehicle icon and a reference icon which take the user vehicle as a center and take a preset distance as a radius range. The reference icon includes: an icon of a traffic accident for indicating occurrence of the traffic accident; displaying a traffic police icon for indicating that a traffic police is present; and displaying a no-pass icon for indicating no-pass.
To enhance the warning effect, in some embodiments, it is determined whether the user vehicle is spaced less than a predetermined threshold from a nearest vehicle in front; if the front vehicle is smaller than the preset threshold value, selecting a vehicle rendering model with a tail display warning lamp for the front vehicle from a rendering model library.
When the distance between the user vehicle and the nearest vehicle in front is determined, an infrared distance measurement method can be adopted for measurement. Or the distance between the vehicle and the front vehicle can be calculated by adopting the image frame of the camera and utilizing an image frame distance algorithm.
The threshold may be 1 meter, or may be other values, and is not limited specifically.
A large number of models are stored in the rendering model library, and for vehicles of the same type, the models are multiple and comprise models with red lamps arranged at the tail parts. The red light can remind the user to pay attention to safety.
In some embodiments, if the separation distance is less than a predetermined threshold, the vehicle emits a first color light wave in the assisted driving image frame; if the separation distance is greater than or equal to a predetermined threshold, the vehicle emits a second color light wave in the assisted driving image frame. Wherein the first color may be red and the second color may be white. The predetermined threshold may be 1 meter. And is not particularly limited.
In some embodiments, if a pedestrian is detected in front of the user vehicle in an image frame captured by a camera, displaying a rendering model of the pedestrian in the driving assistance image frame; and the rendering model of the user vehicle emits red light waves and emits warning sounds.
Specifically, a human rendering model is also set in the rendering model library, and if a pedestrian is detected in the image frame, the pedestrian rendering model is called.
In some embodiments, the vehicle speed is displayed on the driving assistance image frame; displaying a weather icon, a temperature and a sharing button on the map display image frame.
In some embodiments, if a traffic accident is detected in front of the user vehicle in image frames taken by a camera, a rendered model of the traffic accident is displayed in the driving assistance image frames.
The method comprises the steps of collecting a large number of traffic accident images, extracting the characteristics of the traffic accident images, carrying out learning training through a machine learning algorithm, and determining whether a traffic accident occurs in image frames shot by a camera through a trained model.
The traffic accident rendering model can be a traffic accident model of a two-vehicle collision model; an accident model of collision between a person and a car can be established; and a traffic accident model of the collision of the bicycle and people can be established. And calling different types of traffic accident rendering models according to specific conditions.
In some embodiments, if an animal is detected in front of the user vehicle in image frames taken by a camera, a rendered model of the animal is displayed in the driving assistance image frames.
Specifically, the animal rendering model can be relatively rough to be established, and is not necessarily particularly similar to a real object. That is, the animal rendering model cannot distinguish whether a cat is a dog, but is determined to be an animal.
In some embodiments, if multiple people are detected in an image frame; calculating the distance between any two adjacent people in the image frame, if the distance between any two people is less than a preset threshold value; the positions of the plurality of persons in the assistant driving image frame are displayed with a character rendering model instead of the plurality of persons.
Specifically, a target detection algorithm may be employed to calculate the horizontal distance between the center points of each person's marker box.
Wherein the threshold value may be 0.5 meter. The setting can be flexibly set, and the application is not limited. According to the method, the rendering model of one person is used for replacing two persons close to the rendering model, so that the method is suitable for a scene that the two persons run in parallel, or a scene that an adult leads a child to walk on the roadside. Therefore, resources occupied by the auxiliary driving image frame can be saved.
In some embodiments, an alert prompt may be issued.
The prompt information may also be a voice prompt, for example, the intelligent vehicle-mounted internet terminal sends "please notice, there is a pedestrian in front"; "Please note, there is a vehicle in front". Particularly, when a pedestrian exists in the front, the attention of a user driving a vehicle is more needed, so the application divides the category of the target three-dimensional object into two categories, if the pedestrian is the first category, the user needs to pay special attention, because the pedestrian occupies a smaller area on a display screen compared with a vehicle, and the user may neglect the existence of the pedestrian, therefore, when the target three-dimensional object is the pedestrian, the attention of the user is more needed.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
According to a second aspect of the embodiment of the present invention, the embodiment of the present application further provides an image data processing apparatus, referring to a schematic structural diagram of an image data processing apparatus shown in fig. 2; the device includes:
the vehicle type determining module 21 is configured to determine a vehicle type in an image frame captured by the camera by using a vehicle type recognition algorithm in response to a trigger message sent by a user;
the rendering model determining module 22 is configured to determine a vehicle rendering model corresponding to the vehicle type according to the vehicle type and a preset correspondence between the vehicle type and the vehicle rendering model;
and the image frame generating module 23 is configured to generate and display an auxiliary driving image frame according to the vehicle rendering model.
In one embodiment, the rendering model determining module 22 is further configured to determine whether the separation distance between the user vehicle and the nearest vehicle in front is less than a predetermined threshold;
if so, selecting a vehicle rendering model with a tail display warning lamp for the nearest vehicle from a rendering model library.
In one embodiment, the image frame generation module 23 is further configured to emit a second color light wave from the vehicle in the driving assistance image frame if the separation distance is less than a predetermined threshold;
if the separation distance is greater than or equal to a predetermined threshold, the vehicle emits a first color light wave in the driving assistance image frame.
In one embodiment, the image frame generation module 23 is further configured to display a rendering model of a pedestrian in the driving assistance image frame if the pedestrian is detected in front of the user vehicle in the image frame captured by the camera; and the rendering model of the user vehicle emits red light waves and emits warning sounds.
In one embodiment, the image frame generation module 23 is further configured to display an animal rendering model in the driving assistance image frame if an animal is detected in front of the user vehicle in the image frame captured by the camera.
In one embodiment, the image frame generating module 23 is further configured to display a rendering model of a traffic accident in the driving assistance image frame if the traffic accident is detected in front of the user vehicle in the image frames captured by the camera.
In one embodiment, the image frame generation module 23 is further configured to, if two persons are detected in the image frame captured by the camera;
calculating a distance between the two persons in the image frames taken by the camera,
if the distance is less than a predetermined threshold;
a character rendering model is displayed instead of the two persons in the assistant driving image frame.
According to a third aspect of the embodiments of the present invention, an embodiment of the present application further provides an image data processing apparatus, which is shown in fig. 3 for a schematic structural diagram of the image data processing apparatus; the apparatus comprises: at least one processor 31 and at least one memory 32;
the memory 32 is for storing one or more program instructions;
the processor 31 is configured to execute one or more program instructions to perform the steps of any of the above methods.
In an embodiment of the invention, the processor may be an integrated circuit chip having signal processing capability. The Processor may be a general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete Gate or transistor logic device, discrete hardware component.
The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The processor reads the information in the storage medium and completes the steps of the method in combination with the hardware.
The storage medium may be a memory, for example, which may be volatile memory or nonvolatile memory, or which may include both volatile and nonvolatile memory.
The nonvolatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory.
The volatile Memory may be a Random Access Memory (RAM) which serves as an external cache. By way of example and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), SLDRAM (SLDRAM), and Direct Rambus RAM (DRRAM).
The storage media described in connection with the embodiments of the invention are intended to comprise, without being limited to, these and any other suitable types of memory.
Those skilled in the art will appreciate that the functionality described in the present invention may be implemented in a combination of hardware and software in one or more of the examples described above. When software is applied, the corresponding functionality may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
The above-mentioned embodiments, objects, technical solutions and advantages of the present invention are further described in detail, it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made on the basis of the technical solutions of the present invention should be included in the scope of the present invention.
Claims (4)
1. An image data processing method characterized by comprising:
responding to a trigger message sent by a user, and determining the vehicle type in an image frame shot by a camera by adopting a vehicle type recognition algorithm;
determining a vehicle rendering model corresponding to the vehicle type according to the vehicle type and a preset corresponding relation between the vehicle type and the vehicle rendering model;
compared with the actual vehicle image, the vehicle rendering model omits the color, pattern and characters on the surface of the vehicle body;
generating and displaying an auxiliary driving image frame according to the vehicle rendering model;
judging whether the spacing distance between the user vehicle and the nearest vehicle in front is smaller than a preset threshold value or not;
if so, selecting a vehicle rendering model with a tail display warning lamp for the nearest vehicle from a rendering model library;
if the separation distance is less than a predetermined threshold, the method further comprises: emitting a second color light wave by the vehicle in the driving assistance image frame;
if the separation distance is greater than or equal to a predetermined threshold value, the vehicle emits a first color light wave in the auxiliary driving image frame;
if a pedestrian is detected in front of the user vehicle in the image frames shot by the camera, displaying a rendering model of the pedestrian in the auxiliary driving image frames; the rendering model of the user vehicle emits red light waves and emits warning sounds;
if an animal in front of the user vehicle is detected in an image frame shot by a camera, displaying an animal rendering model in the auxiliary driving image frame;
if a traffic accident in front of the user vehicle is detected in an image frame shot by a camera, displaying a rendering model of the traffic accident in the auxiliary driving image frame;
if two people are detected in the image frame shot by the camera;
calculating a distance between the two persons in the image frames taken by the camera,
if the distance is less than a predetermined threshold;
a character rendering model is displayed instead of the two persons in the assistant driving image frame.
2. An image data processing apparatus characterized by comprising:
the vehicle type determining module is used for responding to a trigger message sent by a user and determining the type of a vehicle in an image frame shot by the camera by adopting a vehicle type recognition algorithm;
the rendering model determining module is used for determining a vehicle rendering model corresponding to the vehicle type according to the vehicle type and a preset corresponding relation between the vehicle type and the vehicle rendering model;
compared with the actual vehicle image, the vehicle rendering model is added, so that the color, the pattern and the characters of the surface of the vehicle body are omitted;
the image frame generating module is used for generating and displaying an auxiliary driving image frame according to the vehicle rendering model;
the rendering model determining module is further used for judging whether the spacing distance between the user vehicle and the front nearest vehicle is smaller than a preset threshold value;
if so, selecting a vehicle rendering model with a tail display warning lamp for the nearest vehicle from a rendering model library;
the image frame generation module is further used for emitting a second color light wave by the vehicle in the auxiliary driving image frame if the spacing distance is smaller than a preset threshold value;
if the separation distance is greater than or equal to a predetermined threshold value, the vehicle emits a first color light wave in the auxiliary driving image frame;
the image frame generation module is further used for displaying a rendering model of the pedestrian in the auxiliary driving image frame if the pedestrian is detected in front of the user vehicle in the image frame shot by the camera; the rendering model of the user vehicle emits red light waves and emits warning sounds;
the image frame generating module is further used for displaying an animal rendering model in the auxiliary driving image frame if an animal in front of the user vehicle is detected in the image frame shot by the camera;
the image frame generating module is further used for displaying a rendering model of the traffic accident in the auxiliary driving image frame if the traffic accident in front of the user vehicle is detected in the image frame shot by the camera;
the image frame generation module is also used for detecting that two persons exist in the image frame shot by the camera;
calculating a distance between the two persons in the image frames taken by the camera,
if the distance is less than a predetermined threshold;
a character rendering model is displayed instead of the two persons in the assistant driving image frame.
3. An image data processing apparatus characterized by comprising: at least one processor and at least one memory;
the memory is to store one or more program instructions;
the processor, configured to execute one or more program instructions to perform the method of claim 1.
4. A computer-readable storage medium having one or more program instructions embodied therein for being executed by the method of claim 1.
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| CN113590980B (en) * | 2021-07-20 | 2024-03-29 | 北京地平线机器人技术研发有限公司 | Method for training neural network, method and device for predicting track |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101187978A (en) * | 2006-11-21 | 2008-05-28 | 哈曼贝克自动系统股份有限公司 | Method and system for presenting video images |
| CN109690558A (en) * | 2016-08-09 | 2019-04-26 | 康诺特电子有限公司 | Method, driver assistance system and the motor vehicles of driver's driving maneuver vehicle for auxiliary maneuvering vehicle |
| CN111881958A (en) * | 2020-07-17 | 2020-11-03 | 上海东普信息科技有限公司 | License plate classification recognition method, device, equipment and storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7493202B2 (en) * | 2004-11-12 | 2009-02-17 | Takata Corporation | Vehicle safety control system by image processing |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101187978A (en) * | 2006-11-21 | 2008-05-28 | 哈曼贝克自动系统股份有限公司 | Method and system for presenting video images |
| CN109690558A (en) * | 2016-08-09 | 2019-04-26 | 康诺特电子有限公司 | Method, driver assistance system and the motor vehicles of driver's driving maneuver vehicle for auxiliary maneuvering vehicle |
| CN111881958A (en) * | 2020-07-17 | 2020-11-03 | 上海东普信息科技有限公司 | License plate classification recognition method, device, equipment and storage medium |
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