CN113743395A - Method, equipment and device for reading instrument - Google Patents
Method, equipment and device for reading instrument Download PDFInfo
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Abstract
The application provides a method, equipment and a device for reading an instrument; wherein the method comprises the following steps: acquiring image data of a dial plate of a monitored target instrument; applying a target meter reading identification algorithm to identify data results indicated by a target meter contained in the image data; and sending the image data and the data result to a destination address. In the embodiment of the application, the data result indicated by the instrument panel in the image data is automatically identified by acquiring the image data of the instrument panel, and the identification result is sent to the specified address, so that the instrument data is automatically read and reported, and compared with a manual meter reading mode in the prior art, the method has the positive effects of simplicity and high efficiency.
Description
Technical Field
The application relates to the technical field of image recognition processing, in particular to a method, equipment and a device for recognizing and reading an instrument.
Background
In some complicated industrial application environment, often can set up all kinds of instruments and meters and carry out the monitoring of environmental aspect etc. for example set up the manometer on liquid transport pipe way, gaseous transport pipe way, for example again, still can set up industrial electricity meter etc. in the mill, the reading of multiple instrument and meter if the mode of carrying out the meter reading through personnel along the transport pipe way walking is gone on, then can have the amount of labour great, and data report is untimely, goes out the mistake scheduling problem easily. For another example, in some instrument and meter detection scenarios, in order to detect the measurement accuracy of each meter, a worker needs to continuously simulate a test environment for testing, and needs to repeatedly read and analyze the detection data of the meter, and similarly, if a manual meter reading and recording manner is adopted in the scenario, it is difficult to simultaneously perform efficient and accurate detection on a large number of meters.
Disclosure of Invention
In view of the above, the present application provides a method, a module and a device for recognizing a reading of an instrument, so as to at least achieve the purpose of improving the reading efficiency of the instrument.
Specifically, the method is realized through the following technical scheme:
in a first aspect, an embodiment of the present application provides a method for reading a meter, where the method includes:
collecting image data of a monitored target instrument;
applying a target meter reading identification algorithm to identify data results indicated by a target meter contained in the image data;
and sending the image data and the data result to a destination address.
In a second aspect, an embodiment of the present application provides a reading identification device for a meter, where the device includes:
moving the carrier;
and, employ the above-mentioned method of the first aspect to carry on the reading of the instrument and read the image acquisition die set that the reading of the instrument discerns;
the image acquisition module is arranged on the movable carrier.
In a third aspect, an embodiment of the present application provides a reading device for a meter, where the device includes:
the image acquisition module is used for acquiring image data of the monitored target instrument;
the identification module is used for identifying a data result indicated by the target meter contained in the image data by applying a target meter reading identification algorithm;
and the pushing module is used for sending the image data and the data result to a destination address.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the image recognition method according to any one of the embodiments of the first aspect.
In a fifth aspect, embodiments of the present application provide a computer device, which includes at least a memory and a processor; the memory is connected with the processor through a communication bus and is used for storing computer instructions executable by the processor; the processor is configured to read computer instructions from the memory to implement the steps of the image recognition method according to any one of the embodiments of the first aspect.
The instrument reading method, the instrument reading equipment and the instrument reading device provided by the embodiment of the application directly acquire the image data of a monitored target instrument; according to the acquired image data, a target meter reading identification algorithm is applied to identify a data result indicated by a target meter contained in the image data; after the data result indicated by the instrument is identified, the acquired image data and the identified data result are sent to a destination address; in the embodiment of the application, the data result indicated by the instrument panel in the image data is automatically identified by acquiring the image data of the instrument panel, and the identification result is sent to the specified address, so that the instrument data is automatically read and reported, and compared with a manual meter reading mode in the prior art, the method has the positive effects of simplicity and high efficiency.
Drawings
FIG. 1 is a schematic diagram illustrating an application scenario of a method for reading an image meter according to an exemplary embodiment of the present application;
FIG. 2 is a flow chart diagram illustrating a method for reading a meter according to an exemplary embodiment of the present application;
FIG. 3 is a flow chart diagram illustrating another method of reading a meter according to an exemplary embodiment of the present application;
FIG. 4 is a schematic diagram of a single meter detection method based on SURF feature matching as shown in an exemplary embodiment of the present application;
FIG. 5 is a schematic view of a meter reading identification device shown in an exemplary embodiment of the present application;
FIG. 6 is a schematic diagram illustrating a structure of a reading identification device of a meter according to an exemplary embodiment of the present application;
fig. 7 is a schematic structural diagram of a computer device according to an exemplary embodiment of the present application.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
In consideration of the problems that in the prior art, in some complex industrial application environments and instrument and meter test scenes, if various meters are read and recorded in a manual meter reading mode, the labor capacity is large, the data is not reported timely and the like. Therefore, the application provides a method, equipment and a device for reading a meter.
FIG. 1 is a schematic view of an application scenario of a meter reading method according to an exemplary embodiment of the present application; referring to fig. 1, in this embodiment, the image capturing module 10 is configured to capture image data of a monitored instrument panel 20, automatically identify a data result indicated by the instrument panel according to the captured image data, and push the captured image data and the obtained data result to a server 30 with an http address specified by a user.
All table body discernment in this application, reading identification algorithm all integrate inside the image acquisition module, have realized end side perception, end side calculation. Moreover, the image acquisition module provided by the application is used as an edge end, has the characteristic of being close to a data source, and performs data processing, prediction and analysis on the image acquisition module, so that the transmission time delay and energy consumption of the system are reduced.
FIG. 2 is a flow chart diagram illustrating a method for reading a meter according to an exemplary embodiment of the present application; referring to fig. 2, the method is applied to the image capturing module, and the method includes the following steps S100 to S104:
s100, the image acquisition module acquires image data of a dial plate of the monitored target instrument.
In this embodiment, the image acquisition module shoots the dial plate of monitored target instrument, and the triggering mode of shooing can be multiple, for example manual control triggers to shoot, also can regularly trigger automatically and shoot.
And S102, identifying a data result indicated by the target meter contained in the image data by applying a target meter reading identification algorithm.
In a possible embodiment of the present application, the image capturing module is provided with a browser client, and a user can log in the browser client to perform operations such as basic parameter configuration and recognition algorithm management on the image capturing module; such as adding a recognition algorithm, deleting a recognition algorithm, or replacing and upgrading a recognition algorithm. Besides, a plurality of digital table identification algorithms and a plurality of pointer table identification algorithms are arranged in the image acquisition module.
In this embodiment, the user can set up the current acquiescent instrument detection mode of image acquisition module at the customer end, is to the instrument of specific type to know and read, still general can to the instrument of different grade type to know and read.
FIG. 3 is a flow chart diagram illustrating another method of reading a meter according to an exemplary embodiment of the present application; referring to fig. 3, in this embodiment, before the step S102, the method further includes the following step S101:
s101, judging whether the current working mode is in a mode for identifying a table body of a specified type;
if yes, the step S102 specifically includes the following steps S1021 to S1022:
and S1021, positioning the target meter from the image data by applying a meter body detection algorithm matched with the meter body of the specified type.
And S1022, identifying the data result indicated by the target meter by applying an identification algorithm matched with the table body of the specified type.
In this embodiment, the meter body detection algorithm is a single target detection algorithm, and if the image acquisition module is in a mode of reading data of a specific type of meter, the image acquisition module locates a target meter from image data by using a specified meter body detection algorithm after acquiring an image, and then identifies a data result currently indicated by the target meter by using a specified identification algorithm.
If not, the step S102 specifically includes the following steps S1021 '-S1023':
s1021', a general meter body type recognition algorithm is loaded, and the general meter body type recognition algorithm is applied to recognize the meter body type and the meter position of the target meter contained in the image data.
S1022', determining a meter reading identification algorithm matched with the target meter according to the meter body type of the target meter.
S1023', after the meter position is determined, the data result indicated by the target meter is identified by applying the meter reading identification algorithm.
The general table body type recognition algorithm is a multi-target detection algorithm, is a multi-target detection algorithm and is obtained by performing model training by taking a CenterNet network as a basic framework.
Furthermore, in the embodiment of the application, a user can set the working mode of the image acquisition device in advance, and in the process of reading the data result of the instrument panel, if the user sets the type of the watch body to be identified in advance, the image acquisition device carries out the detection of the instrument panel according to the type of the watch body specified by the user and the identification algorithm of the type of the watch body.
Furthermore, in an embodiment of the present application, before the applying the target meter reading identification algorithm identifies the data result indicated by the target meter included in the image data, the method further includes the following steps a10-a 20:
step A10, receiving configuration information sent by a client; the configuration information is generated by the client in response to the operation that the user selects the type of the monitored meter in the browser.
The user configures the working mode of the image acquisition module at the client, and the user can select a meter body detection algorithm and a meter reading identification algorithm to be executed by the image acquisition module according to the type of the meter to be detected.
Step A20, setting the current working mode as the mode for identifying the table body of the appointed type based on the configuration information.
In an embodiment of the present application, in the step S1021, locating the target meter from the image data by applying a meter body detection algorithm adapted to the meter body type includes the following steps:
s1021', a SURF feature-based template matching method is applied to positioning the meter body, and the target meter is positioned from the image data.
In the embodiment of the application, for single instrument detection, the SURF-feature-based template matching method is adopted for surface body positioning, the method is general for all instrument types, the process of training a detection model independently for each instrument type can be avoided, and the workload of algorithm modeling is greatly reduced.
Referring to fig. 4, in the embodiment, in the process of detecting a single table body, the table body is located by the template matching method of SURF features, for example, SURF feature points are extracted from a template map of a meter to be detected, and feature factors are extracted as reference criteria. When the designated instrument is detected, the image acquisition module firstly takes a picture of the target instrument, captures an image, extracts SURF characteristic points and characteristic factors from the image, performs characteristic matching on the SURF characteristic points and the characteristic factors as well as the SURF characteristic points and the characteristic factors in the reference standard, calculates the transformation relation among the characteristic matching points and finally obtains the position of the target instrument (the instrument to be detected) in the image.
In an embodiment of the present application, in the instrument reading process, if the target instrument is an LCD digital meter, the identifying a data result indicated by the target instrument includes the following steps B10-B60:
and step B10, inputting the image data into a Yolov5m network structure which is trained in advance, and obtaining the position coordinates of each character on the instrument panel in the image.
And step B20, obtaining the maximum height of the single character through calculation and comparison as the maximum height interval threshold value max _ height of the single-row number.
And step B30, obtaining the maximum coordinate value ymax and the minimum coordinate value ymin of the Y direction of all the characters through calculation and comparison.
Step B40, obtain the number n of character rows int ((ymax-ymin)// max _ height).
And step B50, dividing a plurality of lines of grids at intervals of (ymax-ymin)/n in the Y-axis direction.
And step B60, respectively determining which central points of the characters in each line of grid fall in the area, and sequencing the characters from small to large according to the abscissa x _ center of the central points to obtain the complete reading of the last line of characters.
The Yolov5m network structure is obtained by training a multi-target detection model by taking characters { "0", "1", "2", "3" "4", "5", "6", "7", "8", "9", "} as 11 categories, and the network input size is as follows: 640*640.
FIG. 5 is a schematic view of a meter reading identification device shown in an exemplary embodiment of the present application; referring to fig. 5, an embodiment of the present application provides a reading identification device 400 for a meter, including:
the image acquisition module 10 is used for carrying out reading identification on the instrument by the method;
and a mobile carrier 40;
the image capturing module 10 is mounted on the movable carrier 40.
In this embodiment, the mobile carrier may be a polling car, and the image acquisition module may be fixed to the polling car to identify and read the instrument along a transportation pipeline, a power line, or the like; or, in another possible embodiment of this application, foretell removal carrier also can be unmanned aerial vehicle, is fixed in the image acquisition module on unmanned aerial vehicle, also can realize identifying reading to the instrument that sets up on specific position or high altitude high-voltage line, electric power tower etc..
In an optional embodiment, in order to solve the problem of poor image acquisition quality under dark light and no light conditions, the camera of the image acquisition module is integrated with the infrared light supplement module.
FIG. 6 is a schematic diagram illustrating a structure of a reading identification device of a meter according to an exemplary embodiment of the present application; referring to fig. 6, the apparatus includes:
the acquisition module 501 is used for acquiring image data of a monitored target instrument;
an identification module 502, configured to apply a target meter reading identification algorithm to identify a data result indicated by a target meter included in the image data;
a sending module 503, configured to send the image data and the data result to a destination address.
Optionally, the apparatus further includes:
the judging module is used for judging whether the current working mode is in a mode of identifying the table body of the specified type;
the identification module 502 is specifically configured to:
loading a table body detection algorithm corresponding to the table body of the specified type, and positioning the target instrument from the image data;
and after the target instrument is positioned, identifying the data result indicated by the target instrument by applying an identification algorithm corresponding to the table body type.
Optionally, the identifying module 502 is specifically configured to:
loading a general meter body type identification algorithm, and identifying the meter body type and the meter position of a target meter contained in the image data by applying the general meter body type identification algorithm;
determining a meter reading identification algorithm matched with the target meter according to the meter body type of the target meter;
and after the meter position is determined, identifying the data result indicated by the target meter by applying the meter reading identification algorithm.
Optionally, the apparatus further includes:
the receiving module is used for receiving the configuration information sent by the client; the configuration information is generated by the client end in response to the operation that a user selects the type of the monitored meter;
and the setting module is used for setting the current working mode as a mode for identifying the table body of the specified type based on the configuration information.
Optionally, the identification module is further configured to:
and loading the table body single table body detection algorithm of the specified type, performing table body detection by using a template matching method based on SURF characteristics, and positioning the target instrument from the image data.
Optionally, the identification module is further configured to:
inputting image data into a previously trained Yolov5m network structure to obtain position coordinates of each character on a dashboard in an image;
obtaining the maximum height of a single character through calculation and comparison, wherein the maximum height is used as the maximum height interval threshold value max _ height of a single row of numbers;
obtaining the maximum coordinate value ymax and the minimum coordinate value ymin of all the characters in the Y direction through calculation and comparison;
obtaining the number n of character rows int ((ymax-ymin)// max _ height);
dividing a plurality of lines of grids at intervals in the Y-axis direction according to (ymax-ymin)/n;
respectively determining which central points of the characters in each line of grids fall in the area, and sequencing the characters from small to large according to the abscissa x _ center of the central points to obtain the complete reading of the last line of characters;
the Yolov5m network structure is obtained by training a multi-target detection model by taking characters { "0", "1", "2", "3" "4", "5", "6", "7", "8", "9", "} as 11 categories, and the network input size is as follows: 640*640.
Optionally, the general table type recognition algorithm is a multi-target detection algorithm and is obtained by performing model training with a centret network as a basic architecture.
An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the steps of the image recognition method according to any one of the above embodiments.
Fig. 6 is a schematic structural diagram of a computer device according to an embodiment of the present application. Referring to fig. 6, the computer device 600 includes at least a memory 602 and a processor 601; the memory 602 is connected to the processor 601 through a communication bus 603, and is used for storing computer instructions executable by the processor 601; the processor 601 is configured to read computer instructions from the memory 602 to implement the steps of the method for reading a meter according to any of the above embodiments.
The implementation process of the functions and actions of each unit in the above device is specifically described in the implementation process of the corresponding step in the above method, and is not described herein again.
For the device embodiments, since they substantially correspond to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the application. One of ordinary skill in the art can understand and implement it without inventive effort.
Embodiments of the subject matter and the functional operations described in this specification can be implemented in: digital electronic circuitry, tangibly embodied computer software or firmware, computer hardware including the structures disclosed in this specification and their structural equivalents, or a combination of one or more of them. Embodiments of the subject matter described in this specification can be implemented as one or more computer programs, i.e., one or more modules of computer program instructions, encoded on a tangible, non-transitory program carrier for execution by, or to control the operation of, data processing apparatus. Alternatively or additionally, the program instructions may be encoded on an artificially generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal, that is generated to encode and transmit information to suitable receiver apparatus for execution by the data processing apparatus. The computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of one or more of them.
The processes and logic flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform corresponding functions by operating on input data and generating output. The processes and logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit).
Computers suitable for executing computer programs include, for example, general and/or special purpose microprocessors, or any other type of central processing unit. Generally, a central processing unit will receive instructions and data from a read-only memory and/or a random access memory. The basic components of a computer include a central processing unit for implementing or executing instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks. However, a computer does not necessarily have such a device.
Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices (e.g., EPROM, EEPROM, and flash memory devices), magnetic disks (e.g., an internal hard disk or a removable disk), magneto-optical disks, and CD ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.
While this specification contains many specific implementation details, these should not be construed as limitations on the scope of any invention or of what may be claimed, but rather as descriptions of features specific to particular embodiments of particular inventions. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. In other instances, features described in connection with one embodiment may be implemented as discrete components or in any suitable subcombination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination.
Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In some cases, multitasking and parallel processing may be advantageous. Moreover, the separation of various system modules and components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.
Thus, particular embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve desirable results. Further, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some implementations, multitasking and parallel processing may be advantageous.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the scope of protection of the present application.
Claims (10)
1. A method of reading a meter, the method comprising:
acquiring image data of a dial plate of a monitored target instrument;
applying a target meter reading identification algorithm to identify data results indicated by a target meter contained in the image data;
and sending the image data and the data result to a destination address.
2. The method of claim 1, wherein prior to the applying a target meter reading identification algorithm identifying the data result indicated by the target meter, the method further comprises:
judging whether the current working mode is in a mode for identifying the table body of the specified type;
if yes, the identifying a data result indicated by the target meter contained in the image data by applying a target meter reading identification algorithm includes:
loading a table body detection algorithm corresponding to the table body of the specified type, and positioning the target instrument from the image data;
and after the target instrument is positioned, identifying the data result indicated by the target instrument by applying an identification algorithm corresponding to the table body type.
3. The method of claim 2, wherein if not, the applying a target meter reading identification algorithm to identify a data result indicated by a target meter contained in the image data comprises:
loading a general meter body type identification algorithm, and identifying the meter body type and the meter position of a target meter contained in the image data by applying the general meter body type identification algorithm;
determining a meter reading identification algorithm matched with the target meter according to the meter body type of the target meter;
and after the meter position is determined, identifying the data result indicated by the target meter by applying the meter reading identification algorithm.
4. The method of claim 2, prior to the applying a target meter reading identification algorithm to identify a data result indicated by a target meter contained in the image data, the method further comprising:
receiving configuration information sent by a client; the configuration information is generated by the client end in response to the operation that a user selects the type of the monitored meter;
and setting the current working mode as a mode for identifying the table body of the specified type based on the configuration information.
5. The method of claim 2, wherein said loading a table body detection algorithm corresponding to the table body of the specified type to locate the target meter from the image data comprises:
and loading the table body single table body detection algorithm of the specified type, performing table body detection by using a template matching method based on SURF characteristics, and positioning the target instrument from the image data.
6. The method of claim 2 or 3, wherein if the target meter is an LCD digital meter, the identifying the data result indicated by the target meter comprises:
inputting image data into a previously trained Yolov5m network structure to obtain position coordinates of each character on a dashboard in an image;
obtaining the maximum height of a single character through calculation and comparison, wherein the maximum height is used as the maximum height interval threshold value max _ height of a single row of numbers;
obtaining the maximum coordinate value ymax and the minimum coordinate value ymin of all the characters in the Y direction through calculation and comparison;
obtaining the number n of character rows int ((ymax-ymin)// max _ height);
dividing a plurality of lines of grids at intervals in the Y-axis direction according to (ymax-ymin)/n;
respectively determining which central points of the characters in each line of grids fall in the area, and sequencing the characters from small to large according to the abscissa x _ center of the central points to obtain the complete reading of the last line of characters;
the Yolov5m network structure is obtained by training a multi-target detection model by taking characters { "0", "1", "2", "3" "4", "5", "6", "7", "8", "9", "} as 11 categories, and the network input size is as follows: 640*640.
7. The method of claim 3, wherein the common table type recognition algorithm is a multi-target detection algorithm and is obtained by model training using a CenterNet network as an infrastructure.
8. A reading identification device for a meter, the device comprising:
an image acquisition module for identifying the reading of the meter by applying the method of any one of claims 1 to 7;
and, moving the carrier;
wherein, the image acquisition module is installed on the mobile carrier.
9. An apparatus for recognizing a reading of a meter, the apparatus comprising:
the acquisition module is used for acquiring image data of the monitored target instrument;
the identification module is used for identifying a data result indicated by the target meter contained in the image data by applying a target meter reading identification algorithm;
and the sending module is used for sending the image data and the data result to a destination address.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for recognizing an image according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111010264.1A CN113743395A (en) | 2021-08-31 | 2021-08-31 | Method, equipment and device for reading instrument |
Applications Claiming Priority (1)
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