CN114494826A - Multi-water-gauge water level identification method and system, electronic equipment and storable medium - Google Patents
Multi-water-gauge water level identification method and system, electronic equipment and storable medium Download PDFInfo
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Abstract
The application provides a multi-water-gauge water level identification method, electronic equipment and a storable medium, and belongs to the technical field of data processing. The method comprises the following steps: acquiring environment images of a plurality of water gauges through a set camera; inputting the environment image into a pre-trained target detection model to obtain a target image carrying a prediction position frame of a plurality of water gauges; screening out the target image by using an image processing method, and reserving a target water gauge at a boundary with a water area and a predicted position frame thereof; inputting the target image after the image science processing into a pre-trained image segmentation model, and extracting the total number of pixel points corresponding to the target water gauge from the target image; and determining a water level value of the target water gauge according to preset configuration information corresponding to the target water gauge and the total number of pixel points corresponding to the target water gauge, wherein the configuration information comprises the number of pixel points corresponding to the unit scale value of the water gauge and the elevation of the water gauge. The present application aims to improve the efficiency of water level supervision.
Description
Technical Field
The embodiment of the application relates to the technical field of data processing, in particular to a multi-water-gauge water level identification method, a multi-water-gauge water level identification system, electronic equipment and a storage medium.
Background
Under the water conservancy scene, the detection and the early warning of water level are the important ring of water conservancy safety, especially under present environment, weather variation is unusual, can effectual prevention flood disaster protection safety such as agricultural, citizen to the control of water level.
The condition that generally can have a plurality of water gauges in the water level scene to guarantee to all can accomplish accurate discernment when different water levels, generally use the manual work to carry out the reading mostly, but the method of adopting artifical reading needs artifical supervision that lasts, and night reading can receive the influence of illumination factor, causes the reading difficulty, and the change of the unable water level of supervising at all times of artifical reading leads to the efficiency of supervision not high.
Disclosure of Invention
The embodiment of the application provides a multi-water-gauge water level identification method, electronic equipment and a storable medium, and aims to improve the efficiency of water level supervision.
In a first aspect, an embodiment of the present application provides a method for identifying water levels of multiple water levels, where the method includes:
acquiring environment images of a plurality of water gauges through a set camera;
inputting the environment image into a pre-trained target detection model to obtain a target image carrying the predicted position frames of the plurality of water gauges, wherein the target detection model is obtained by training based on a plurality of environment image samples, and the environment image samples are provided with the water gauges for marking the predicted position frames;
screening the target image by using an image processing method, and reserving a target water gauge at a boundary with a water area and a predicted position frame thereof;
inputting the target image after the image processing into a pre-trained image segmentation model, and extracting the total number of pixel points corresponding to the target water gauge from the target image, wherein the image segmentation model is obtained by training a plurality of environment image samples which are output based on the target detection model and carry a prediction position frame of the water gauge sample;
and determining the water level value of the target water gauge according to preset configuration information corresponding to the target water gauge and the total number of pixel points corresponding to the target water gauge, wherein the configuration information comprises the number of pixel points corresponding to the unit scale value of the water gauge and the elevation of the water gauge.
Optionally, the environmental image of a plurality of water gauges is obtained through the camera that sets up, include:
acquiring video data acquired by a set camera;
and at regular time intervals, performing frame extraction on the video data to obtain the environment images of the plurality of water gauges.
Optionally, when the target detection model is trained, the method further includes:
and acquiring a plurality of environment image samples under different illumination and/or climate environments as input, and training the target detection model.
Optionally, screening out the target image by using an image processing method, and reserving a target water gauge at a boundary with a water area and a predicted position frame thereof, including:
respectively carrying out edge identification on the plurality of water gauges carrying the predicted position frame in the target image, and judging whether the plurality of water gauges are in junction with the water area or not according to the result of the edge identification;
and deleting the water gauge image which does not have a boundary with the water area, and reserving the target water gauge which has the boundary with the water area and the predicted position frame thereof.
In a second aspect, an embodiment of the present application provides a multi-level water level identification system, which includes:
the acquisition module is used for acquiring environment images of a plurality of water gauges through the arranged camera;
the first processing module is used for inputting the environment image into a pre-trained target detection model to obtain a target image carrying the predicted position frames of the plurality of water gauges, wherein the target detection model is obtained by training based on a plurality of environment image samples, and the environment image samples are provided with the water gauges for marking the predicted position frames;
the second processing module is used for screening out the target image by using an image processing method and reserving a target water gauge at a boundary with a water area and a predicted position frame thereof;
the third processing module is used for inputting the target image after the image science processing into a pre-trained image segmentation model and extracting the total number of pixel points corresponding to the target water gauge from the target image, wherein the image segmentation model is obtained by training a plurality of environment image samples which are output based on the target detection model and carry a prediction position frame of the water gauge sample;
and the result determining module is used for determining the water level value of the target water gauge according to preset configuration information corresponding to the target water gauge and the total number of pixel points corresponding to the target water gauge, wherein the configuration information comprises the number of the pixel points corresponding to the unit scale value of the water gauge and the elevation of the water gauge.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement the multi-level water level identification method according to the first aspect of the embodiment.
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 multi-level water level identification method according to the first aspect of the embodiment.
Has the advantages that:
the method comprises the steps of firstly obtaining environment images of a plurality of water gauges through a set camera, inputting the environment images into a pre-trained target detection model to obtain target images carrying predicted position frames of the water gauges, then performing imaging processing on the target images, reserving a target water gauge at a junction with a water level and the predicted position frame of the target water gauge, inputting the target images after the imaging processing into a pre-trained image segmentation model, extracting the total number of pixel points corresponding to the target water gauge from the target images, aiming at preset configuration information of the target water gauge, wherein the configuration information comprises the number of the pixel points corresponding to the unit scale value of the water gauge and the elevation of the water gauge, and determining the water level value of the target water gauge according to the number of the pixel points corresponding to the unit scale value of the water gauge and the elevation of the water gauge.
According to the method, through the target detection model and the image segmentation model, respective water level values of the water gauges can be determined according to the acquired environment image, and compared with manual reading, the method has the effect of improving the working efficiency, so that the change of the water level can be timely and efficiently monitored.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments of the present application will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive exercise.
FIG. 1 is a flow chart illustrating the steps of a multi-level water level identification method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an output of a target detection model according to an embodiment of the present application;
FIG. 3 is a schematic diagram of an output of an image segmentation model according to an embodiment of the present application;
fig. 4 is a functional block diagram of a multi-level water level identification system according to an embodiment of the present application.
Detailed Description
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 the present application
Some, but not all embodiments are claimed. 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.
Referring to fig. 1, a flowchart illustrating steps of a multi-level water level identification method in an embodiment of the present invention is shown, and as shown in fig. 1, the method may specifically include the following steps:
s101, acquiring environment images of a plurality of water gauges through the arranged cameras.
In the practical application process, the camera is arranged at a position where water level monitoring is needed, the camera can collect a plurality of water gauges, and then the water gauges needing to determine water level values can be obtained from the plurality of water gauges.
After the video data acquired by the set camera is acquired, the video data is subjected to frame extraction to obtain environment images of a plurality of water gauges, the video data can be subjected to frame extraction at regular time intervals, the water level numerical value of the water gauge is identified by frame extraction at the regular time intervals, the change rule of the water level in the fixed time intervals can be embodied, and the length of the regular time intervals can be set in a user-defined mode.
S102, inputting the environment image into a pre-trained target detection model to obtain a target image carrying the predicted position frames of the plurality of water gauges, wherein the target detection model is obtained by training based on a plurality of environment image samples, and the environment image samples are provided with the water gauges for marking the predicted position frames.
Referring to fig. 2, a schematic diagram of an output of a target detection model according to an embodiment of the present application is shown, in the diagram, a solid rectangle represents a water gauge, and a dotted rectangle represents a prediction position frame corresponding to each water gauge, for example, in fig. 2, an environment image obtained by frame extraction is input into the target detection model, the target detection model can identify a plurality of water gauges in the environment image, and the plurality of water gauges in the target image output by the target detection model carry the prediction position frames corresponding to each other, so that the plurality of water gauges can be processed subsequently.
The target detection model is obtained based on training of a plurality of environment image samples, the environment image samples are provided with water gauges for marking and predicting position frames, in order to improve the detection effect of the target detection model, a plurality of environment image samples under different illumination and/or climatic environments can be obtained as input to train the target detection model, and then the target monitoring model can be applied to different environments, for example, environment samples in the day, at night, in cloudy days and in different seasons are obtained.
S103, screening the target image by using an image processing method, and reserving a target water gauge at a boundary with a water area and a predicted position frame of the target water gauge.
Because the target image comprises a plurality of water gauges, the positions of the water gauges are different, and some water gauges may not have junctions with the water area, that is, some water gauges may not measure the water level and are regarded as invalid measurement data. In order to save resources, the water gauge images without water level detection are screened out, only the images of the target water gauges at the boundary with the water area and the predicted position frames of the target water gauges are reserved, and the number of the target water gauges can be one or more.
In one possible embodiment, the screening out the target image by using an image processing method, and reserving the target water gauge at the boundary with the water area and the predicted position frame thereof comprises:
and respectively carrying out edge identification on the plurality of water gauges carrying the predicted position frame in the target image, and judging whether the plurality of water gauges are in junction with the water area or not according to the result of the edge identification.
And deleting the water gauge image which does not have a boundary with the water area, and reserving the target water gauge which has the boundary with the water area and the predicted position frame thereof.
The method comprises the steps of respectively carrying out edge identification on a plurality of water gauges in a target image output by a target detection model, judging whether the bottom edges of the water gauges have junctions with a water area after obtaining the edges of the water gauges and an environment, deleting the water gauge image without the junctions with the water area, reserving the target water gauge with the junction with the water area and a prediction position frame thereof, screening out invalid water gauges with measured data, further processing the water gauges with valid measured data to obtain a water level value, saving data processing cost and increasing the speed of obtaining a data processing result.
Usually, can have a plurality of water gauge posts to same waters, insert the position of putting the different degree of depth in the waters to the convenience all can be accurate when different water levels look over the water level, but the water level numerical value of a plurality of water gauge actual measurements should be unanimous, and the same scale value is on same water flat line in the water gauge that lies in different degree of depth positions.
For example, as shown in fig. 2, three water gauges A, B, C are sequentially arranged from the center of the water area to the bank, wherein the range of the water gauge a may be 10-30, the range of the water gauge B may be 20-40, the range of the water gauge C may be 30-50, and when the water surface and the water gauges a and B have a junction, the water level values measured by the two water gauges are the same.
In one embodiment, the water level value of the water gauge located at the farthest position on the offshore side can be calculated by selecting a target water gauge according to the positions of the water gauges sequentially arranged, for example, the water level value of the water gauge located at the farthest position on the offshore side is calculated preferentially, and as the water level rises, the water gauge located at a point closer to the shore side is read after the water surface is submerged by the water gauge located at the farthest position on the offshore side. After the camera is set, the arrangement mode of the water gauges in the acquired image is unchanged, and if the left side of the image is the side far away from the bank, the water gauge at the boundary between the leftmost side and the water area can be used as a target water gauge.
And S104, inputting the target image after the imaging processing into a pre-trained image segmentation model, and extracting the total number of pixel points corresponding to the target water gauge from the target image, wherein the image segmentation model is obtained by training a plurality of environment image samples which are output based on the target detection model and carry a prediction position frame of the water gauge sample.
Referring to fig. 3, a schematic diagram of an output of an image segmentation model provided in this embodiment of the present application is shown, where a lattice portion in the diagram represents an image segmentation result of a target water gauge, and a slash portion represents an image segmentation result of a non-water gauge, and as shown in fig. 3, a target image after image processing is input into the image segmentation model, the image segmentation model is obtained by training a plurality of environment image samples, which are output based on a target detection model and carry a predicted position frame of a water gauge sample, and the image segmentation model can perform image segmentation on the target water gauge carrying the predicted position frame in the target image, so as to obtain an accurate total number of pixels of the target water gauge, and if there are a plurality of target water gauges, the image segmentation model can obtain a total number of pixels corresponding to each of the plurality of target water gauges.
S105, determining a water level value of the target water gauge according to preset configuration information corresponding to the target water gauge and the total number of pixel points corresponding to the target water gauge, wherein the configuration information comprises the number of the pixel points corresponding to the unit scale value of the water gauge and the elevation of the water gauge.
For a certain camera, each water gauge in the shooting range of the camera is provided with corresponding configuration information, and the configuration information comprises the number of pixel points corresponding to the unit scale value of the water gauge and the elevation of the water gauge.
Under the condition that the number of pixel points corresponding to the unit scale value of the target water gauge and the elevation of the target water gauge are known, the total number of the pixel points of the target water gauge obtained according to the image segmentation model is divided by the number of the pixel points corresponding to the unit scale value of one water gauge, the value of the target water gauge above the water surface can be obtained, and the value of the target water gauge above the water surface is subtracted from the elevation of the target water gauge, so that the water level value of the target water gauge can be obtained.
If adjust the focus etc. of camera, only need to the pixel quantity that water gauge unit scale interval corresponds and the elevation of water gauge reset can.
The method comprises the steps of firstly obtaining environment images of a plurality of water gauges through a set camera, inputting the environment images into a pre-trained target detection model to obtain target images carrying predicted position frames of the water gauges, then carrying out image processing on the target images, reserving a target water gauge with a boundary with a water level and the predicted position frame of the target water gauge, inputting the target images after the image processing into a pre-trained image segmentation model, extracting the total number of pixel points corresponding to the target water gauge from the target images, aiming at preset configuration information of the target water gauge, wherein the configuration information comprises the number of the pixel points corresponding to a unit scale value of the water gauge and the elevation of the water gauge, and determining the water level value of the target water gauge according to the number of the pixel points corresponding to the unit scale value of the water gauge and the elevation of the water gauge.
The application has at least the following beneficial effects:
1. through the target detection model and the image segmentation model, respective water level values of the water gauges can be determined according to the acquired environment image, and compared with manual reading, the water level detection method has the effect of improving the working efficiency, so that the change of the water level can be monitored timely and efficiently.
2. The method screens the images of the water gauge without the junction between the edge and the water area through an imaging processing method, so that the water gauge images of effective measurement data are processed, and the effect of saving data processing cost is achieved.
3. This application passes through the water gauge in the target detection model discernment environment image, does not need the position of artifical configuration water gauge, has the effect that improves water level monitoring efficiency.
Referring to fig. 4, a functional module diagram of a multi-level water level identification system provided by an embodiment of the present application is shown, the system includes:
the acquisition module 100 is used for acquiring environment images of a plurality of water gauges through the arranged camera;
a first processing module 200, configured to input the environment image into a pre-trained target detection model to obtain a target image carrying predicted position frames of the multiple water gauges, where the target detection model is obtained by training based on multiple environment image samples, and the environment image samples include the water gauges labeled with the predicted position frames;
the second processing module 300 is configured to screen out the target image by using an imaging processing method, and reserve a target water gauge at a boundary with a water area and a predicted position frame thereof;
a third processing module 400, configured to input the target image after the image processing into a pre-trained image segmentation model, and extract a total number of pixels corresponding to the target water gauge from the target image, where the image segmentation model is obtained by training a plurality of environment image samples, which are output based on the target detection model and carry a predicted position frame of a water gauge sample;
the result determining module 500 is configured to determine a water level value of the target water gauge according to preset configuration information corresponding to the target water gauge and a total number of pixels corresponding to the target water gauge, where the configuration information includes a number of pixels corresponding to a unit scale value of the water gauge and an elevation of the water gauge.
Optionally, the acquisition module comprises:
the video acquisition unit is used for acquiring video data acquired by the set camera;
and the image acquisition unit is used for performing frame extraction on the video data at a calibration time interval to obtain the environment images of the plurality of water gauges.
Optionally, the system further comprises:
and the multi-sample acquisition module is used for acquiring a plurality of environment image samples under different illumination and/or climate environments as input and training the target detection model.
Optionally, the second processing module includes:
the identification unit is used for respectively carrying out edge identification on the plurality of water gauges carrying the predicted position frame in the target image and judging whether the plurality of water gauges are in junction with the water area or not according to the result of the edge identification;
and the screening unit is used for deleting the water gauge image which does not have a boundary with the water area, and reserving the target water gauge which has the boundary with the water area and the predicted position frame thereof.
The embodiment of the application also provides electronic equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the computer program to realize the multi-water-gauge water level identification method.
Embodiments of the present application further provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method for identifying water levels of multiple water levels according to the embodiments is implemented.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
As will be appreciated by one of skill in the art, embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the true scope of the embodiments of the application.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
The principle and the implementation of the present application are explained herein by applying specific examples, and the above description of the embodiments is only used to help understand the method and the core idea of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (7)
1. A method for multi-level water level identification, the method comprising:
acquiring environment images of a plurality of water gauges through a set camera;
inputting the environment image into a pre-trained target detection model to obtain a target image carrying the predicted position frames of the plurality of water gauges, wherein the target detection model is obtained by training based on a plurality of environment image samples, and the environment image samples are provided with the water gauges for marking the predicted position frames;
screening out the target image by using an image processing method, and reserving a target water gauge at a boundary with a water area and a prediction position frame thereof;
inputting the target image after the image processing into a pre-trained image segmentation model, and extracting the total number of pixel points corresponding to the target water gauge from the target image, wherein the image segmentation model is obtained by training a plurality of environment image samples which are output based on the target detection model and carry a prediction position frame of the water gauge sample;
and determining the water level value of the target water gauge according to preset configuration information corresponding to the target water gauge and the total number of pixel points corresponding to the target water gauge, wherein the configuration information comprises the number of pixel points corresponding to the unit scale value of the water gauge and the elevation of the water gauge.
2. The method of claim 1, wherein acquiring the environmental images of the plurality of water gauges via the arranged cameras comprises:
acquiring video data acquired by a set camera;
and at regular time intervals, performing frame extraction on the video data to obtain the environment images of the plurality of water gauges.
3. The method of claim 1, wherein in training the object detection model, further comprising:
and acquiring a plurality of environment image samples under different illumination and/or climate environments as input, and training the target detection model.
4. The method of any one of claims 1-3, wherein the screening out the target image by using an image processing method, and reserving the target water gauge at the boundary with the water area and the predicted position frame thereof comprises:
respectively carrying out edge identification on the plurality of water gauges carrying the predicted position frame in the target image, and judging whether the plurality of water gauges are in junction with the water area or not according to the result of the edge identification;
and deleting the water gauge image which does not have a boundary with the water area, and reserving the target water gauge which has the boundary with the water area and the predicted position frame thereof.
5. A multi-level water level identification system, the system comprising:
the acquisition module is used for acquiring environment images of a plurality of water gauges through the arranged camera;
the first processing module is used for inputting the environment image into a pre-trained target detection model to obtain a target image carrying the predicted position frames of the plurality of water gauges, wherein the target detection model is obtained by training based on a plurality of environment image samples, and the environment image samples are provided with the water gauges for marking the predicted position frames;
the second processing module is used for screening out the target image by using an image processing method and reserving a target water gauge at a boundary with a water area and a predicted position frame thereof;
the third processing module is used for inputting the target image after the image science processing into a pre-trained image segmentation model and extracting the total number of pixel points corresponding to the target water gauge from the target image, wherein the image segmentation model is obtained by training a plurality of environment image samples which are output based on the target detection model and carry a prediction position frame of the water gauge sample;
and the result determining module is used for determining the water level value of the target water gauge according to preset configuration information corresponding to the target water gauge and the total number of pixel points corresponding to the target water gauge, wherein the configuration information comprises the number of the pixel points corresponding to the unit scale value of the water gauge and the elevation of the water gauge.
6. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 4 when executing the computer program.
7. A computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the multi-level water level identification method of any one of claims 1 to 4.
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| CN116129430A (en) * | 2023-01-28 | 2023-05-16 | 武汉大水云科技有限公司 | Self-adaptive environment water level identification method, device and equipment |
| CN116668830A (en) * | 2023-05-19 | 2023-08-29 | 哈尔滨四福科技有限公司 | Method, system, equipment and medium for setting preset point of water level observation camera |
| CN117994797A (en) * | 2024-04-02 | 2024-05-07 | 杭州海康威视数字技术股份有限公司 | Water gauge reading method and device, storage medium and electronic equipment |
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