CN113312941A - Method and device for monitoring instrument panel - Google Patents
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Abstract
The invention discloses a method and a device for monitoring an instrument panel, and relates to the technical field of warehouse logistics. The main technical scheme of the method comprises the following steps: acquiring an image to be identified, wherein the image to be identified is an image containing a dashboard; determining a target graph of the image to be recognized from the image to be recognized; and if the preset direction of the pointer of the instrument panel is identified from the target graph, warning. The embodiment automatically monitors the instrument panel and frees workers from the operation of instrument panel monitoring.
Description
Technical Field
The invention relates to the technical field of warehouse logistics, in particular to a method and a device for monitoring an instrument panel.
Background
The meter is a device for measuring various physical quantities, material compositions, physical parameters, or the like, and the instrument panel is used for displaying the physical quantities, material compositions, physical parameters, or the like.
In the field of warehouse logistics, the environment of a warehouse is important for storing articles, the environment of the warehouse is generally measured through an instrument, an instrument panel is checked manually at regular intervals, and when the pointing direction of a pointer of the instrument panel is abnormal, an alarm is manually sent.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:
due to manual participation, the automation degree of monitoring is low, and the working intensity of workers is high.
Disclosure of Invention
In view of this, the present invention provides a method and an apparatus for monitoring an instrument panel, which can automatically monitor the instrument panel and release workers from the monitoring of the instrument panel.
To achieve the above object, according to an aspect of an embodiment of the present invention, a method of monitoring an instrument panel is provided.
The method for monitoring the instrument panel comprises the following steps:
acquiring an image to be identified, wherein the image to be identified is an image containing a dashboard;
determining a target graph of the image to be recognized from the image to be recognized;
and if the preset direction of the pointer of the instrument panel is identified from the target graph, warning.
In one embodiment, determining a target pattern of the image to be recognized from the image to be recognized includes:
carrying out image segmentation on the image to be identified to obtain at least one graph;
acquiring a pattern recognition model matched with the instrument panel;
and selecting a target graph of the image to be recognized from the at least one graph by adopting the graph recognition model.
In one embodiment, selecting a target pattern of the image to be recognized from the at least one pattern using the pattern recognition model includes:
identifying each graph in the at least one graph by adopting the graph identification model;
and if the pattern recognition model recognizes one pattern from the at least one pattern, selecting the recognized pattern as a target pattern of the image to be recognized.
In one embodiment, the warning if the preset pointing direction of the pointer of the dashboard is recognized from the target graph includes:
acquiring a pointing identification model of a pointer matched with the instrument panel;
if the pointing identification model of the pointer identifies the preset pointing of the pointer of the instrument panel from the target graph, acquiring a parameter value, a parameter type and an identifier of the instrument panel which are matched with the preset pointing;
and splicing the parameter type, the parameter value and the mark of the instrument panel into warning information, and sending the warning information.
In one embodiment, the method for creating the pointing recognition model of the pointer comprises the following steps:
acquiring an image containing a preset direction of a pointer of the instrument panel;
and training a neural network model by adopting the preset-pointing image containing the pointer of the instrument panel to obtain a pointing recognition model of the pointer.
In one embodiment, acquiring an image to be recognized includes:
acquiring a video stream from an image acquisition device; the video stream is obtained by the image acquisition equipment acquiring the images of the instrument panel;
and intercepting the image of the video stream according to a preset time interval to obtain at least one frame of image, and taking each frame of image as the image to be identified.
To achieve the above object, according to another aspect of an embodiment of the present invention, there is provided an apparatus for monitoring an instrument panel.
The device for monitoring the instrument panel of the embodiment of the invention comprises:
the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring an image to be identified, and the image to be identified is an image containing a dashboard;
the first processing unit is used for determining a target graph of the image to be recognized from the image to be recognized;
and the second processing unit is used for warning if the preset direction of the pointer of the instrument panel is identified from the target graph.
In one embodiment, the first processing unit is to:
carrying out image segmentation on the image to be identified to obtain at least one graph;
acquiring a pattern recognition model matched with the instrument panel;
and selecting a target graph of the image to be recognized from the at least one graph by adopting the graph recognition model.
In one embodiment, the first processing unit is to:
identifying each graph in the at least one graph by adopting the graph identification model;
and if the pattern recognition model recognizes one pattern from the at least one pattern, selecting the recognized pattern as a target pattern of the image to be recognized.
In one embodiment, the second processing unit is configured to:
acquiring a pointing identification model of a pointer matched with the instrument panel;
if the pointing identification model of the pointer identifies the preset pointing of the pointer of the instrument panel from the target graph, acquiring a parameter value, a parameter type and an identifier of the instrument panel which are matched with the preset pointing;
and splicing the parameter type, the parameter value and the mark of the instrument panel into warning information, and sending the warning information.
In one embodiment, the second processing unit is configured to:
acquiring an image containing a preset direction of a pointer of the instrument panel;
and training a neural network model by adopting the preset-pointing image containing the pointer of the instrument panel to obtain a pointing recognition model of the pointer.
In one embodiment, the obtaining unit is configured to:
acquiring a video stream from an image acquisition device; the video stream is obtained by the image acquisition equipment acquiring the images of the instrument panel;
and intercepting the image of the video stream according to a preset time interval to obtain at least one frame of image, and taking each frame of image as the image to be identified.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a system for monitoring an instrument panel.
The system for monitoring the instrument panel comprises a server and image acquisition equipment; the server is used for acquiring an image to be identified, wherein the image to be identified is an image containing a dashboard; determining a target graph of the image to be recognized from the image to be recognized; and if the preset direction of the pointer of the instrument panel is identified from the target graph, warning.
To achieve the above object, according to still another aspect of an embodiment of the present invention, there is provided an electronic apparatus.
An electronic device of an embodiment of the present invention includes: one or more processors; the storage device is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method for monitoring the instrument panel provided by the embodiment of the invention.
To achieve the above object, according to still another aspect of an embodiment of the present invention, there is provided a computer-readable medium.
A computer-readable medium of an embodiment of the present invention stores thereon a computer program, and the computer program, when executed by a processor, implements the method for monitoring a dashboard provided by an embodiment of the present invention.
One embodiment of the above invention has the following advantages or benefits: acquiring an image to be identified, wherein the image to be identified is an image containing a dashboard; determining a target graph of the image to be recognized from the image to be recognized; and if the preset direction of the pointer of the instrument panel is identified from the target graph, warning. The instrument panel monitoring process is free of manual participation, automatic instrument panel monitoring is carried out through image recognition, and workers are released from monitoring work.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a schematic diagram of a main flow of a method of monitoring a dashboard, according to an embodiment of the invention;
FIG. 2 is an application scenario of a method of monitoring a dashboard, according to an embodiment of the invention;
FIG. 3 is an application scenario of a method of monitoring a dashboard, according to another embodiment of the present invention;
FIG. 4 is a schematic diagram of the main elements of an apparatus for monitoring a dashboard in accordance with an embodiment of the present invention;
FIG. 5 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 6 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
In order to solve the problems in the prior art, an embodiment of the present invention provides a method for monitoring an instrument panel, where as shown in fig. 1, the method includes:
step S101, an image to be identified is obtained, wherein the image to be identified is an image containing a dashboard.
In this step, in implementation, as shown in fig. 2, the camera captures an image of the dashboard to obtain an image to be recognized. The camera sends the image to be recognized to a server to which the embodiment of the present invention is applied.
Or, the camera shoots the instrument panel to obtain a video stream; the camera sends the video stream to a server applied to the embodiment of the invention. The server applied in the embodiment of the invention intercepts the images of the video stream according to the preset time interval to obtain at least one frame of image, and each frame of image is taken as the image to be identified.
The meter may be a thermometer, a hygrometer, an electronic scale, or the like. The instrument panel of the thermometer is used for displaying temperature, the instrument panel of the hygrometer is used for displaying humidity, and the instrument panel of the electronic scale is used for displaying weight.
And S102, determining a target graph of the image to be recognized from the image to be recognized.
In this step, it should be noted that the specific implementation of this step is described in detail below, and is not described herein again. In addition, the shape of the target pattern of the image to be recognized is the same as the shape of the dashboard.
And step S103, if the preset direction of the pointer of the instrument panel is identified from the target graph, warning.
In this step, it should be noted that the specific implementation of this step is described in detail below, and is not described herein again.
It should be understood that any pointer type instrument panel can be automatically monitored according to the method provided by the embodiment of the invention. The idea of the embodiment of the invention is as follows: and determining a target graph of the image to be recognized, wherein the target graph is a part of the image to be recognized and comprises an instrument panel, and if the pointing direction of a pointer of the instrument panel in the target graph is the same as the preset pointing direction of the pointer of the instrument panel, warning is given, so that the instrument panel is automatically monitored through an image recognition technology.
This embodiment is illustrated below in a specific example:
the camera collects images of the instrument panel to obtain a video stream; the camera sends the video stream and the pre-configured identification of the camera to a server applied in the embodiment of the invention.
The server receives the video stream and the identification of the camera, and the camera and the instrument panel have a one-to-one correspondence relationship, so that the image recognition model matched with the instrument panel and the pointing recognition model of the pointer matched with the instrument panel can be obtained through the identification of the camera.
The server intercepts images of the video stream according to a preset time interval to obtain at least one frame of image, and each frame of image is used as an image to be identified.
The server carries out image segmentation on an image to be recognized to obtain at least one graph; and selecting a target graph of the image to be recognized from the at least one graph by adopting a graph recognition model.
If the pointing identification model of the pointer identifies the preset pointing of the pointer of the instrument panel from the target graph, the server acquires a parameter value, a parameter type and an identifier of the instrument panel which are matched with the preset pointing; and splicing the parameter type, the parameter value and the mark of the instrument panel into warning information, and sending the warning information.
In the embodiment of the present invention, determining the target pattern of the image to be recognized from the image to be recognized includes:
carrying out image segmentation on the image to be identified to obtain at least one graph;
acquiring a pattern recognition model matched with the instrument panel;
and selecting a target graph of the image to be recognized from the at least one graph by adopting the graph recognition model.
In this embodiment, in specific implementation, the image to be recognized is segmented by using the existing image segmentation technology to obtain at least one graph.
A shape of the dashboard matches a pattern recognition model. Specifically, a pattern recognition model matching the shape of the dashboard is obtained. Therefore, the pattern recognition model matching the circular-shaped instrument panel is not the same pattern recognition model as the pattern recognition model matching the square-shaped instrument panel; among them, the instrument panel having a circular shape is different only in shape from the instrument panel having a square shape.
Creating a pattern recognition model matched with the instrument panel according to the following method: acquiring a graph with the same shape as the instrument panel; and training a neural network model by using a pattern with the same shape as the instrument panel to obtain a pattern recognition model matched with the instrument panel.
In the embodiment, image segmentation is carried out on an image to be recognized to obtain at least one graph; acquiring a pattern recognition model matched with an instrument panel; and selecting a target graph of the image to be recognized from the at least one graph by adopting a graph recognition model. The instrument panel monitoring process is free of manual participation, and automatic instrument panel monitoring is carried out through image recognition.
In an embodiment of the present invention, selecting a target graph of the image to be recognized from the at least one graph by using the graph recognition model includes:
identifying each graph in the at least one graph by adopting the graph identification model;
and if the pattern recognition model recognizes one pattern from the at least one pattern, selecting the recognized pattern as a target pattern of the image to be recognized.
In this embodiment, it should be noted that only the target pattern can be recognized by the pattern recognition model, and any pattern other than the target pattern in the at least one pattern cannot be recognized by the pattern recognition model.
In an embodiment of the present invention, if the preset direction of the pointer of the dashboard is recognized from the target graph, the warning includes:
acquiring a pointing identification model of a pointer matched with the instrument panel;
if the pointing identification model of the pointer identifies the preset pointing of the pointer of the instrument panel from the target graph, acquiring a parameter value, a parameter type and an identifier of the instrument panel which are matched with the preset pointing;
and splicing the parameter type, the parameter value and the mark of the instrument panel into warning information, and sending the warning information.
In this embodiment, in specific implementation, if a plurality of warehouses all have image acquisition devices and instrument panels, the parameter types, the parameter values, the identifiers of the instrument panels and the identifiers of the warehouses where the instrument panels are located are spliced into warning information. The parameter types include weight, temperature, humidity, or volume, etc.
And sending warning information according to the address matched with the preset direction, and preventing by related personnel through the warning information.
The preset direction, the parameter value matched with the preset direction, the parameter type matched with the preset direction and the identifier of the instrument panel matched with the preset direction are stored in the database in a matching mode in advance, and therefore the parameter value, the parameter type and the identifier of the instrument panel matched with the preset direction are obtained from the database through the preset direction.
The following describes the parameter values and parameter types matching the preset pointers by a specific example: and if the temperature of the warehouse reaches 40 ℃, warning, wherein the pointer direction 40 of an instrument panel of the thermometer is a preset direction, the parameter value matched with the preset direction is 40, and the parameter type matched with the preset direction is the temperature.
It should be noted that the preset direction of the pointer of the instrument panel, and the parameter value and the parameter type matched with the preset direction can be set according to the requirements, so that the customization requirements are met, and the application range is wide.
In the embodiment, a pointing identification model of a pointer matched with a dashboard is obtained; if the pointing identification model of the pointer identifies the preset pointing of the pointer of the instrument panel from the target graph, acquiring a parameter value, a parameter type and an identifier of the instrument panel which are matched with the preset pointing; and splicing the parameter type, the parameter value and the mark of the instrument panel into warning information, and sending the warning information. The instrument panel is automatically monitored through image recognition, workers are released from monitoring, high equipment is not required to be added, automatic monitoring is completed, and the cost required by automatic monitoring is further reduced.
In the embodiment of the present invention, a method for creating a pointer-oriented recognition model includes:
acquiring an image containing a preset direction of a pointer of the instrument panel;
and training a neural network model by adopting the preset-pointing image containing the pointer of the instrument panel to obtain a pointing recognition model of the pointer.
In this embodiment, in implementation, a camera is used to capture an instrument panel to which the pointer is pointing in a preset direction, so as to obtain an image containing the preset direction of the pointer of the instrument panel.
In the embodiment of the present invention, acquiring an image to be recognized includes:
acquiring a video stream from an image acquisition device; the video stream is obtained by the image acquisition equipment acquiring the images of the instrument panel;
and intercepting the image of the video stream according to a preset time interval to obtain at least one frame of image, and taking each frame of image as the image to be identified.
In this embodiment, the image capturing device may be a camera and the image capturing mode may be photographing.
In specific implementation, a camera in the warehouse shoots an instrument panel in the warehouse to obtain a video stream. The camera sends the video stream to a server applied to the embodiment of the invention.
The preset time interval may be set according to requirements, for example, 5 seconds.
The method comprises the steps of adopting the existing image interception technology, carrying out image interception on a video stream according to a preset time interval, and obtaining at least one frame of image.
It should be noted that, when each of the plurality of warehouses has a camera and a dashboard, the camera sends the video stream, the identifier of the warehouse, the identifier of the camera, and the identifier of the dashboard to the server applied in the embodiment of the present invention. The identification of the warehouse is used for assembling warning information, so that a warehouse responsible person can quickly lock the problem warehouse through the identification of the warehouse in the warning information. The identification of the camera is used for uniformly processing the video stream collected by the camera so as to increase the monitoring accuracy.
In this embodiment, a video stream is acquired from an image capture device; the video stream is obtained by the image acquisition equipment acquiring the images of the instrument panel; and intercepting the image of the video stream according to a preset time interval to obtain at least one frame of image, and taking each frame of image as the image to be identified. The automatic monitoring of the instrument panel can be realized through the image acquisition equipment, the cost of the image acquisition equipment is low, and the cost required by the automatic monitoring is further reduced.
With the development of the industry, more and more articles need to be transported to a warehouse for temporary storage after being produced. Wherein, the warehousing process includes: and placing the articles into the material frame, and carrying the material frame to a specified shelf of a warehouse to finish warehousing the articles. Of course, after warehousing, operations such as inventory of articles, sorting of articles, and ex-warehouse of articles are also required. The environment of the warehouse is important for the storage of the items, and is typically measured by a meter and the dashboard is manually monitored. Or, the instrument is modified to add communication and intelligent chips to realize automatic monitoring of the instrument panel, but the monitoring cost is high.
The embodiment of the invention can be applied to the scenes, and realizes automatic monitoring and early warning of the instrument panel by acquiring the image of the instrument panel and the image recognition technology on the premise of not changing the instruments in the warehouse, thereby reducing the monitoring cost.
A method for monitoring an instrument panel according to another embodiment of the present invention is described below with reference to a specific example.
It should be noted that, as shown in fig. 3, in the warehouse (X is the identifier of the warehouse), a Webcam (Webcam-1 is the identifier of the camera) is arranged, and an angle of the Webcam is adjusted, so that the Webcam can accurately acquire a video stream of an instrument panel (Dashboard-1 is the identifier of the Dashboard) of an electronic scale (an electronic scale is an instrument) in the warehouse, and configure context parameters of the Webcam, where the context parameters include the identifier (i.e., X) of the warehouse where the Dashboard is located, the identifier (i.e., Webcam-1) of the camera, the identifier (i.e., Dashboard-1) of the Dashboard, a push address (i.e., Server-1) of the video stream, local network connection authentication parameters, and the like. In addition, the identification of the instrument panel may be the model number of the instrument or the number of the instrument, etc.
And matching and storing the Dashboard-1 and a pattern recognition model matched with the Dashboard-1 into a database, wherein the shape of a Dashboard of the electronic scale is circular and the border is black, and the pattern recognition model is used for recognizing the pattern which is circular and the border is black.
Matching and storing the pointer to 30 (namely the first preset pointer), Webcam-1, X, Dashboard-1, 30KG, weight and the notification address of 30KG in a database; matching and storing the pointer to 60 (namely the second preset pointer), Webcam-1, X, Dashboard-1, 60KG, weight and the notification address of 60KG in a database; and matching and storing the pointer to 90 (namely the third preset pointer), Webcam-1, X, Dashboard-1, 90KG, weight and the notification address of 90KG in the database.
The method comprises the following steps:
the Webcam-1 in the warehouse collects a video stream Streaming1 of a Dashboard-1 of an electronic scale in the warehouse, and sends the video stream Streaming1, the Webcam-1, the X and the Dashboard-1 to a Server (i.e. the Server-1) through a local network (the local network mode comprises Wifi, 4G or 5G, and the network protocol of the local network can be RTSP) and a public network through context parameters.
The server receives the video streams Streaming1, Webcam-1, X and Dashboard-1.
The server intercepts images of the video stream Streaming1 every 5 seconds to obtain at least one frame of image, and each frame of image is taken as an image-x to be identified.
The server carries out image segmentation on the image-x to be recognized to obtain at least one graph; and acquiring a pattern recognition model matched with the Dashboard-1, and selecting a target pattern of the image-x to be recognized from at least one pattern by adopting the pattern recognition model matched with the Dashboard-1. The shape of the target graph is circular, and the frame is black.
If at least one of the figures does not include a figure having a circular shape and a black frame, the process is terminated.
The server trains a neural network model by adopting a first preset-pointing image containing a pointer of an instrument panel to obtain a first recognition model; training a neural network model by using a second preset-pointing image containing a pointer of an instrument panel to obtain a second recognition model; and training the neural network model by adopting a third preset pointed image containing a pointer of the instrument panel to obtain a third recognition model. And the first recognition model, the second recognition model and the third recognition model are all pointing recognition models of pointers. The method comprises the steps of respectively adopting a first recognition model, a second recognition model and a third recognition model to recognize a target graph, if a first preset direction of a pointer of a Dashboard is recognized from the target graph, obtaining a parameter value (namely 30KG), a parameter type (namely weight), an identifier (namely X) of a warehouse where the Dashboard is located and an identifier (namely Dashboard-1) of the Dashboard which are matched and stored with the first preset direction, and splicing the weight, 30KG, Dashboard-1 and X into warning information.
It should be noted that, if the second recognition model is used to recognize the second preset direction of the pointer of the instrument panel from the target graph, the parameter value (i.e. 60KG), the parameter type (i.e. weight), the identifier (i.e. X) of the warehouse where the instrument panel is located, and the identifier (i.e. Dashboard-1) of the instrument panel, which are stored in matching with the second preset direction, are obtained, and the weight, 60KG, Dashboard-1, and X are assembled into the warning information.
If the third preset direction of the pointer of the instrument panel is recognized from the target graph by adopting the third recognition model, the parameter value (namely 90KG), the parameter type (namely weight), the identifier (namely X) of the warehouse where the instrument panel is located and the identifier (namely Dashboard-1) of the instrument panel which are matched and stored with the third preset direction are obtained, and the weight, the 90KG, the Dashboard-1 and the X are spliced into the warning information.
In addition, if the target pattern of the image to be recognized can be recognized, only one of the first recognition model, the second recognition model and the third recognition model can be used for recognition.
The server sends the warning information to the service system through the private network according to the notification address of 30 KG.
And the service system (for example, a supply chain financing service system) acquires standard values (the standard value is the weight of the goods matched with the identification of the warehouse and the identification of the instrument panel when the goods are put in the warehouse) according to the identification of the warehouse, the identification of the instrument panel and the weight in the warning information, and if the standard value is not the same as the standard value, the service system informs a responsible person of the warehouse to prevent the goods in the warehouse from being lost more seriously.
It should be noted that, the alarm information may have different processing modes, for example, when the parameter value in the alarm information is 30KG, only the warehouse responsible person is notified, and when the parameter value in the alarm information is 60KG, the warehouse responsible person and the enterprise responsible person are notified.
In order to solve the problems in the prior art, an embodiment of the present invention provides an apparatus for monitoring an instrument panel, as shown in fig. 4, the apparatus includes:
the acquiring unit 401 is configured to acquire an image to be recognized, where the image to be recognized is an image including a dashboard.
A first processing unit 402, configured to determine a target pattern of the image to be recognized from the image to be recognized.
A second processing unit 403, configured to warn if the preset direction of the pointer of the dashboard is recognized from the target graph.
In this embodiment of the present invention, the first processing unit 402 is configured to:
carrying out image segmentation on the image to be identified to obtain at least one graph;
acquiring a pattern recognition model matched with the instrument panel;
and selecting a target graph of the image to be recognized from the at least one graph by adopting the graph recognition model.
In this embodiment of the present invention, the first processing unit 402 is configured to:
identifying each graph in the at least one graph by adopting the graph identification model;
and if the pattern recognition model recognizes one pattern from the at least one pattern, selecting the recognized pattern as a target pattern of the image to be recognized.
In this embodiment of the present invention, the second processing unit 403 is configured to:
acquiring a pointing identification model of a pointer matched with the instrument panel;
if the pointing identification model of the pointer identifies the preset pointing of the pointer of the instrument panel from the target graph, acquiring a parameter value, a parameter type and an identifier of the instrument panel which are matched with the preset pointing;
and splicing the parameter type, the parameter value and the mark of the instrument panel into warning information, and sending the warning information.
In this embodiment of the present invention, the second processing unit 403 is configured to:
acquiring an image containing a preset direction of a pointer of the instrument panel;
and training a neural network model by adopting the preset-pointing image containing the pointer of the instrument panel to obtain a pointing recognition model of the pointer.
In this embodiment of the present invention, the obtaining unit 401 is configured to:
acquiring a video stream from an image acquisition device; the video stream is obtained by the image acquisition equipment acquiring the images of the instrument panel;
and intercepting the image of the video stream according to a preset time interval to obtain at least one frame of image, and taking each frame of image as the image to be identified.
It should be understood that the functions performed by the components of the device for monitoring an instrument panel according to the embodiment of the present invention have been described in detail in the method for monitoring an instrument panel according to the above embodiment, and are not described herein again.
In order to solve the problems in the prior art, an embodiment of the present invention provides a system for monitoring an instrument panel, where the system includes a server and an image capture device.
The server is used for acquiring an image to be identified, wherein the image to be identified is an image containing a dashboard; determining a target graph of the image to be recognized from the image to be recognized; and if the preset direction of the pointer of the instrument panel is identified from the target graph, warning.
And the image acquisition equipment is used for acquiring images of the instrument panel to obtain a video stream and sending the video stream to the server.
In this embodiment, the server may be a cloud server.
The server acquires an image to be identified, and the method comprises the following steps: receiving a video stream sent by image acquisition equipment, carrying out image interception on the video stream according to a preset time interval to obtain at least one frame of image, and taking each frame of image as the image to be identified.
The specific implementation of the server is the same as that of the embodiment shown in fig. 4, and is not described herein again.
Fig. 5 illustrates an exemplary system architecture 500 to which the method of monitoring a dashboard or the apparatus for monitoring a dashboard of embodiments of the present invention may be applied.
As shown in fig. 5, the system architecture 500 may include terminal devices 501, 502, 503, a network 504, and a server 505. The network 504 serves to provide a medium for communication links between the terminal devices 501, 502, 503 and the server 505. Network 504 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 501, 502, 503 to interact with a server 505 over a network 504 to receive or send messages or the like. The terminal devices 501, 502, 503 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 501, 502, 503 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 505 may be a server providing various services, such as a background management server (for example only) providing support for shopping websites browsed by users using the terminal devices 501, 502, 503. The backend management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (for example, target push information, product information — just an example) to the terminal device.
It should be noted that the method for monitoring a dashboard provided by the embodiment of the present invention is generally performed by the server 505, and accordingly, the apparatus for monitoring a dashboard is generally disposed in the server 505.
It should be understood that the number of terminal devices, networks, and servers in fig. 5 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 6, a block diagram of a computer system 600 suitable for use with a terminal device implementing an embodiment of the invention is shown. The terminal device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the system 600 are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 601.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a unit, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present invention may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, a first processing unit, and a second processing unit. The names of the units do not form a limitation to the units themselves in some cases, and for example, the first processing unit may also be described as a "unit that determines a target pattern of the image to be recognized from the image to be recognized".
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: acquiring an image to be identified, wherein the image to be identified is an image containing a dashboard; determining a target graph of the image to be recognized from the image to be recognized; and if the preset direction of the pointer of the instrument panel is identified from the target graph, warning.
According to the technical scheme of the embodiment of the invention, the image to be identified is obtained, and the image to be identified is an image containing a dashboard; determining a target graph of the image to be recognized from the image to be recognized; and if the preset direction of the pointer of the instrument panel is identified from the target graph, warning. The instrument panel monitoring process is free of manual participation, automatic instrument panel monitoring is carried out through image recognition, and workers are released from monitoring work.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method of monitoring an instrument panel, comprising:
acquiring an image to be identified, wherein the image to be identified is an image containing a dashboard;
determining a target graph of the image to be recognized from the image to be recognized;
and if the preset direction of the pointer of the instrument panel is identified from the target graph, warning.
2. The method according to claim 1, wherein determining the target pattern of the image to be recognized from the image to be recognized comprises:
carrying out image segmentation on the image to be identified to obtain at least one graph;
acquiring a pattern recognition model matched with the instrument panel;
and selecting a target graph of the image to be recognized from the at least one graph by adopting the graph recognition model.
3. The method of claim 2, wherein selecting a target pattern of the image to be recognized from the at least one pattern using the pattern recognition model comprises:
identifying each graph in the at least one graph by adopting the graph identification model;
and if the pattern recognition model recognizes one pattern from the at least one pattern, selecting the recognized pattern as a target pattern of the image to be recognized.
4. The method of claim 1, wherein alerting if a preset orientation of a pointer of the dashboard is identified from the target graphic comprises:
acquiring a pointing identification model of a pointer matched with the instrument panel;
if the pointing identification model of the pointer identifies the preset pointing of the pointer of the instrument panel from the target graph, acquiring a parameter value, a parameter type and an identifier of the instrument panel which are matched with the preset pointing;
and splicing the parameter type, the parameter value and the mark of the instrument panel into warning information, and sending the warning information.
5. The method of claim 4, wherein the creating of the identification model by the pointer comprises:
acquiring an image containing a preset direction of a pointer of the instrument panel;
and training a neural network model by adopting the preset-pointing image containing the pointer of the instrument panel to obtain a pointing recognition model of the pointer.
6. The method of claim 1, wherein acquiring the image to be identified comprises:
acquiring a video stream from an image acquisition device; the video stream is obtained by the image acquisition equipment acquiring the images of the instrument panel;
and intercepting the image of the video stream according to a preset time interval to obtain at least one frame of image, and taking each frame of image as the image to be identified.
7. An apparatus for monitoring an instrument panel, comprising:
the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring an image to be identified, and the image to be identified is an image containing a dashboard;
the first processing unit is used for determining a target graph of the image to be recognized from the image to be recognized;
and the second processing unit is used for warning if the preset direction of the pointer of the instrument panel is identified from the target graph.
8. A system for monitoring a dashboard, comprising a server and an image capture device, the server comprising the apparatus for monitoring a dashboard of claim 7.
9. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-6.
10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-6.
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