CN113408501A - Oil field park detection method and system based on computer vision - Google Patents
Oil field park detection method and system based on computer vision Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 51
- 238000012544 monitoring process Methods 0.000 claims abstract description 79
- 238000000034 method Methods 0.000 claims abstract description 21
- 238000013507 mapping Methods 0.000 claims abstract description 11
- 239000007788 liquid Substances 0.000 claims description 30
- 238000012015 optical character recognition Methods 0.000 claims description 9
- 230000006399 behavior Effects 0.000 claims description 6
- 238000013145 classification model Methods 0.000 claims description 6
- 238000004590 computer program Methods 0.000 claims description 6
- 206010033799 Paralysis Diseases 0.000 claims description 3
- 238000004891 communication Methods 0.000 claims description 3
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- 230000004931 aggregating effect Effects 0.000 description 1
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Abstract
The invention discloses a computer vision-based oil field park detection method and system, relating to the technical field of oil field park detection, wherein the method comprises the following steps: the multiple cloud platforms carrying the cameras respectively move to the specified positions according to the preset tracks to monitor the detection objects; adjusting the monitoring area of each camera, and establishing a mapping relation between a three-dimensional coordinate system and the monitoring area of each camera; manually comparing the picture screenshots of the cameras, identifying and marking overlapped monitoring areas, and storing the non-overlapped monitoring areas; and judging the people in the non-coincident monitoring area to enter or exit, and performing face recognition. And each camera is mapped into a three-dimensional coordinate, so that a user can conveniently master the dynamic state of each camera in the park in real time. By marking the overlapped monitoring area, a person is prevented from appearing in the pictures of a plurality of cameras at the same time. Whether the person enters or exits can be judged according to the moving direction of the human body and whether the person crosses the marked tripwire.
Description
Technical Field
The invention relates to the technical field of oilfield park detection, in particular to an oilfield park detection method and system based on computer vision.
Background
The industrial park is a special regional environment created for promoting the development of a certain industry, is an important space gathering form for regional economic development and industrial adjustment and upgrading, and is responsible for gathering innovative resources, cultivating emerging industries, promoting urbanization construction and other important missions. The industrial park can effectively create the gathering power, and the development of the associated industry is driven by sharing resources and overcoming external negative effects, so that the formation of industrial clusters is effectively promoted.
Among the prior art, the oil field garden adopts artifical mode discernment people to enter and the condition of each equipment, and detection efficiency is low, and wastes time and energy very much.
Disclosure of Invention
In order to overcome the above problems or at least partially solve the above problems, embodiments of the present invention provide a method and a system for detecting an oilfield park based on computer vision, so as to improve detection efficiency.
The embodiment of the invention is realized by the following steps:
in a first aspect, an embodiment of the present invention provides an oilfield park detection method based on computer vision, which includes receiving a motion instruction, and monitoring a detection object by a plurality of holders carrying cameras respectively moving to specified positions according to preset tracks;
adjusting the monitoring area of each camera, and establishing a mapping relation between a three-dimensional coordinate system and the monitoring area of each camera;
manually comparing the picture screenshots of the cameras, identifying and marking overlapped monitoring areas, and storing the non-overlapped monitoring areas;
and judging the people in the non-coincident monitoring area to enter or exit, and performing face recognition.
Based on the first aspect, in some embodiments of the present invention, the monitoring the detection object includes:
identifying a pressure gauge and a thermometer through an HR model detection pointer key point to obtain pressure data and temperature data;
carrying out liquid level meter identification on the liquid level meter through a LineNet detection liquid level line to obtain liquid level data;
using a classification model to identify the knife switch to obtain the type of the knife switch;
and identifying the flow meter based on OCR identification to obtain flow data.
Based on the first aspect, in some embodiments of the invention, the method further comprises performing behavior recognition on people in the monitoring areas which are not coincident.
Based on the first aspect, in some embodiments of the invention, the behavior recognition includes:
whether the personnel smoke or not, whether the telephone is called or not, whether the safety helmet is worn or not, whether the mask is worn or not and whether the patient is paralyzed or not are identified.
Based on the first aspect, in some embodiments of the invention, a method of identifying whether a person smokes comprises:
and inputting the screenshot of the camera into a heatmap model for recognition.
Based on the first aspect, in some embodiments of the present invention, the method for face recognition includes:
capturing human faces at an entrance and an exit of a park, judging the entrance or the exit through a human face recognition algorithm, adding human face information of entering personnel into a real-time park personnel database, and deleting the exiting personnel from the real-time park personnel database;
the camera captures a face through a face recognition algorithm, a face sequence with a certain length is established according to the face captured by tracking, a compliant face is added into the sequence, a face is obtained from the sequence through the face recognition algorithm, face recognition is carried out, and information is obtained.
In a second aspect, an embodiment of the present invention provides an oilfield park detection system based on computer vision, including:
the monitoring module is used for receiving a motion instruction, and the multiple cloud platforms carrying the cameras respectively move to the specified positions according to the preset tracks to monitor the detection object;
the establishing module is used for adjusting the monitoring area of each camera and establishing a mapping relation between a three-dimensional coordinate system and the monitoring area of each camera;
the comparison module is used for manually comparing the picture screenshots of the cameras, identifying and marking overlapped monitoring areas and storing the non-overlapped monitoring areas;
and the face recognition module is used for judging the entrance or the exit of people in the non-coincident monitoring area and carrying out face recognition.
According to a second aspect, in some embodiments of the invention, the monitoring module comprises
The pressure and temperature identification submodule is used for identifying the pressure gauge and the thermometer through the HR model detection pointer key point to obtain pressure data and temperature data;
the liquid level identification submodule is used for carrying out liquid level meter identification on the liquid level meter through a LineNet detection liquid level line to obtain liquid level data;
the disconnecting link identification submodule is used for identifying the disconnecting link by using the classification model to acquire the type of the disconnecting link;
and the flow identification submodule is used for identifying the flow meter based on OCR (optical character recognition) to acquire flow data.
In a third aspect, an embodiment of the present invention provides an electronic device, including:
at least one processor, at least one memory, and a data bus; wherein:
the processor and the memory complete mutual communication through the data bus; the memory stores program instructions executable by the processor, and the processor calls the program instructions to execute the method.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, which stores a computer program, and the computer program causes the computer to execute the method described above.
The embodiment of the invention at least has the following advantages or beneficial effects:
receiving a motion instruction, and respectively monitoring a detection object by a plurality of cloud platforms carrying cameras according to preset tracks when the cloud platforms move to specified positions; in this step, the cloud platform is used for the stabilizer of camera, plays balanced and stabilizing action, and the cloud platform can fixed cloud platform, also can be electronic cloud platform, and the cloud platform can rotate about and can rotate from top to bottom again, is convenient for adjust the control area. Adjusting the monitoring area of each camera, and establishing a mapping relation between a three-dimensional coordinate system and the monitoring area of each camera; in the step, camera parameters are determined, three-dimensional coordinates are established based on the terrain of the garden, and the cameras are mapped into the three-dimensional coordinates, so that a user can conveniently master the dynamic state of the cameras in the garden in real time. Manually comparing the picture screenshots of the cameras, identifying and marking overlapped monitoring areas, and storing the non-overlapped monitoring areas; in the step, by marking the overlapped monitoring area, a person is prevented from appearing in the pictures of a plurality of cameras at the same time, and the camera can be prevented from repeatedly calculating the same person. And judging the people in the non-coincident monitoring area to enter or exit, and performing face recognition. In this step, whether a person enters or exits can be judged according to the moving direction of the human body and whether the person crosses a demarcated tripwire.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a flow chart of one embodiment of a computer vision based oilfield park detection method of the present invention;
FIG. 2 is a block diagram of an embodiment of an oilfield park detection system based on computer vision of the present invention;
fig. 3 is a block diagram of an electronic device according to the present invention.
Icon: 1. a monitoring module; 2. establishing a module; 3. a comparison module; 4. a face recognition module; 5. a processor; 6. a memory; 7. a data bus.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. 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 invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the embodiments provided in the present application, it should be understood that the disclosed system may be implemented in other ways. The system embodiments are merely illustrative, and for example, the block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems and computer program products according to various embodiments of the present application. In this regard, each block in the block diagrams may represent a module, 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 and/or flowchart illustration, and combinations of blocks in the block diagrams and/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.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device, which may be a personal computer, a server, or a network device, to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
In the description of the embodiments of the present invention, "a plurality" represents at least 2.
In the description of the embodiments of the present invention, it should be further noted that unless otherwise explicitly stated or limited, the terms "disposed" and "connected" should be interpreted broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Examples
Referring to fig. 1, in a first aspect, an embodiment of the present invention provides a computer vision-based oilfield park detection method, which includes
S1, receiving a motion instruction, and enabling a plurality of cloud platforms carrying cameras to respectively move to specified positions according to preset tracks to monitor the detection object;
in this step, for example, when the detection object is an instrument, the instrument can be used for detection, and the instrument detection is performed periodically, for example, 1 time in 1 hour, and 1 time of inspection is within 1 minute. The holder is used for the stabilizer of camera, plays balanced and stabilizing action, and the holder can fixed cloud platform, also can be electronic cloud platform, and the cloud platform can be rotatory about and can rotate from top to bottom again, is convenient for adjust monitoring area.
S2, adjusting the monitoring area of each camera and establishing the mapping relation between the three-dimensional coordinate system and the monitoring area of each camera;
in the step, camera parameters are determined by camera area calibration, three-dimensional coordinates are established according to the terrain of the garden, and each camera is mapped into the three-dimensional coordinates, so that a user can conveniently master the dynamic information of each camera in the garden in real time.
S3, manually comparing the picture screenshots of the cameras, identifying and marking overlapped monitoring areas, and storing the non-overlapped monitoring areas;
in the step, by marking the overlapped monitoring area, a person is prevented from appearing in the pictures of a plurality of cameras at the same time, and the camera can be prevented from repeatedly calculating the same person.
And S4, judging the entrance or the exit of people in the non-coincident monitoring area, and performing face recognition.
In this step, whether a person enters or exits can be judged according to the moving direction of the human body and whether the person crosses a demarcated tripwire. The face recognition method comprises the following steps: the identity card reader acquires information to construct a face database, a face gate/training system acquires face information from a face acquired by an algorithm, the face information is matched with identity card information, and the face information in the PersonInfo is updated to be a current face; real-time face recognition, establishing a real-time campus personnel database, capturing faces at an entrance and an exit, and judging whether the faces enter or exit through an algorithm. And adding the face information of the entering personnel to the real-time park personnel database, and deleting the exiting personnel from the real-time park personnel database. The monitoring camera captures a face through an algorithm, tracks the captured face, establishes a face sequence with a certain length, and adds a compliant face into the sequence. And acquiring a face from the sequence through an algorithm, and performing face recognition to acquire information.
In some embodiments of the present invention, the monitoring the detection object includes:
identifying a pressure gauge and a thermometer through an HR model detection pointer key point to obtain pressure data and temperature data;
the oil field park uses a pressure gauge to measure data such as oil pressure, and the oil pressure is used for analyzing the liquid supply capacity of an oil well. Various equipment and materials in the park have the requirement of adapting to the temperature, and various temperatures need to be measured in real time to ensure the stability of the park. And the prior art is time-consuming and labor-consuming through manual identification of the pressure gauge and the thermometer. In the step, the camera identifies pressure data and temperature data and transmits the data to the upper computer, so that the working efficiency is high.
Carrying out liquid level meter identification on the liquid level meter through a LineNet detection liquid level line to obtain liquid level data;
the oil field park adopts the level gauge to carry out real-time supervision to the height of liquid or material in the container, and through the artificial identification level gauge among the prior art. In the step, the camera identifies liquid level data and transmits the data to the upper computer.
Using a classification model to identify the knife switch to obtain the type of the knife switch;
and similarly, identifying the type of the disconnecting link by adopting a camera.
And identifying the flow meter based on OCR identification to obtain flow data.
Similarly, the camera is adopted to identify the flow data.
Based on the first aspect, in some embodiments of the invention, the method further comprises performing behavior recognition on people in the monitoring areas which are not coincident. The behavior recognition includes: whether the personnel smoke or not, whether the telephone is called or not, whether the safety helmet is worn or not, whether the mask is worn or not and whether the patient is paralyzed or not are identified.
Illustratively, the method of identifying whether a person is smoking comprises:
the method includes inputting a screenshot of a camera into a heatmap model for recognition, simply aggregating a large amount of data through a heatmap, and using a progressive color band to express elegantly, wherein the final effect is generally superior to direct display of discrete points, and the density degree or frequency of spatial data can be intuitively displayed.
Based on the first aspect, in some embodiments of the present invention, the method for face recognition includes:
capturing human faces at an entrance and an exit of a park, judging the entrance or the exit through a human face recognition algorithm, adding human face information of entering personnel into a real-time park personnel database, and deleting the exiting personnel from the real-time park personnel database;
the camera captures a face through a face recognition algorithm, a face sequence with a certain length is established according to the face captured by tracking, a compliant face is added into the sequence, a face is obtained from the sequence through the face recognition algorithm, face recognition is carried out, and information is obtained.
Referring to fig. 2, in a second aspect, an embodiment of the present invention provides an oilfield park detection system based on computer vision, including:
the monitoring module 1 is used for receiving a motion instruction, and a plurality of cloud platforms carrying cameras respectively move to an appointed position according to a preset track to monitor a detection object;
the establishing module 2 is used for adjusting the monitoring area of each camera and establishing a mapping relation between a three-dimensional coordinate system and the monitoring area of each camera;
the comparison module 3 is used for manually comparing the picture screenshots of the cameras, identifying and marking overlapped monitoring areas and storing the overlapped monitoring areas;
and the face recognition module 4 is used for judging the entrance or the exit of people in the non-coincident monitoring area and carrying out face recognition.
According to a second aspect, in some embodiments of the present invention, the monitoring module 1 comprises
The pressure and temperature identification submodule is used for identifying the pressure gauge and the thermometer through the HR model detection pointer key point to obtain pressure data and temperature data;
the liquid level identification submodule is used for carrying out liquid level meter identification on the liquid level meter through a LineNet detection liquid level line to obtain liquid level data;
the disconnecting link identification submodule is used for identifying the disconnecting link by using the classification model to acquire the type of the disconnecting link;
and the flow identification submodule is used for identifying the flow meter based on OCR (optical character recognition) to acquire flow data.
Referring to fig. 3, in a third aspect, an embodiment of the invention provides an electronic device, including: at least one processor 5, at least one memory 6 and a data bus 7; wherein: the processor 5 and the memory 6 complete communication with each other through the data bus 7; the memory 6 stores program instructions executable by the processor 5, and the processor 5 calls the program instructions to execute the method, for example, to: receiving a motion instruction, and respectively monitoring a detection object by a plurality of cloud platforms carrying cameras according to preset tracks when the cloud platforms move to specified positions; adjusting the monitoring area of each camera, and establishing a mapping relation between a three-dimensional coordinate system and the monitoring area of each camera; manually comparing the picture screenshots of the cameras, identifying and marking overlapped monitoring areas, and storing the non-overlapped monitoring areas; and judging the people in the non-coincident monitoring area to enter or exit, and performing face recognition.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, which stores a computer program, and the computer program causes the computer to execute the method described above. For example, performing: receiving a motion instruction, and respectively monitoring a detection object by a plurality of cloud platforms carrying cameras according to preset tracks when the cloud platforms move to specified positions; adjusting the monitoring area of each camera, and establishing a mapping relation between a three-dimensional coordinate system and the monitoring area of each camera; manually comparing the picture screenshots of the cameras, identifying and marking overlapped monitoring areas, and storing the non-overlapped monitoring areas; and judging the people in the non-coincident monitoring area to enter or exit, and performing face recognition.
In summary, embodiments of the present invention provide a method and a system for detecting an oilfield park based on computer vision. The method comprises the steps that by receiving a motion instruction, a plurality of cloud platforms carrying cameras respectively move to specified positions according to preset tracks to monitor a detection object; in this step, the cloud platform is used for the stabilizer of camera, plays balanced and stabilizing action, and the cloud platform can fixed cloud platform, also can be electronic cloud platform, and the cloud platform can rotate about and can rotate from top to bottom again, is convenient for adjust the control area. Adjusting the monitoring area of each camera, and establishing a mapping relation between a three-dimensional coordinate system and the monitoring area of each camera; in the step, camera parameters are determined, three-dimensional coordinates are established based on the terrain of the garden, and the cameras are mapped into the three-dimensional coordinates, so that a user can conveniently master the dynamic state of the cameras in the garden in real time. Manually comparing the picture screenshots of the cameras, identifying and marking overlapped monitoring areas, and storing the non-overlapped monitoring areas; in the step, by marking the overlapped monitoring area, a person is prevented from appearing in the pictures of a plurality of cameras at the same time, and the camera can be prevented from repeatedly calculating the same person. And judging the people in the non-coincident monitoring area to enter or exit, and performing face recognition. In this step, whether a person enters or exits can be judged according to the moving direction of the human body and whether the person crosses a demarcated tripwire.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
1. An oilfield park detection method based on computer vision, comprising:
receiving a motion instruction, and respectively monitoring a detection object by a plurality of cloud platforms carrying cameras according to preset tracks when the cloud platforms move to specified positions;
adjusting the monitoring area of each camera, and establishing a mapping relation between a three-dimensional coordinate system and the monitoring area of each camera;
manually comparing the picture screenshots of the cameras, identifying and marking overlapped monitoring areas, and storing the non-overlapped monitoring areas;
and judging the people in the non-coincident monitoring area to enter or exit, and performing face recognition.
2. The computer vision-based oilfield park detection method according to claim 1, wherein the monitoring of the detection object comprises:
identifying a pressure gauge and a thermometer through an HR model detection pointer key point to obtain pressure data and temperature data;
carrying out liquid level meter identification on the liquid level meter through a LineNet detection liquid level line to obtain liquid level data;
using a classification model to identify the knife switch to obtain the type of the knife switch;
and identifying the flow meter based on OCR identification to obtain flow data.
3. The computer vision-based oilfield park detection method of claim 2, further comprising performing behavior recognition on people in the misaligned monitoring area.
4. The computer vision-based oilfield park detection method of claim 3, wherein the behavior recognition comprises:
whether the personnel smoke or not, whether the telephone is called or not, whether the safety helmet is worn or not, whether the mask is worn or not and whether the patient is paralyzed or not are identified.
5. The computer vision-based oilfield park detection method of claim 4, wherein the method for identifying whether a person smokes comprises:
and inputting the screenshot of the camera into a heatmap model for recognition.
6. The computer vision-based oilfield park detection method according to claim 1, wherein the face recognition method comprises:
capturing human faces at an entrance and an exit of a park, judging the entrance or the exit through a human face recognition algorithm, adding human face information of entering personnel into a real-time park personnel database, and deleting the exiting personnel from the real-time park personnel database;
the camera captures a face through a face recognition algorithm, a face sequence with a certain length is established according to the face captured by tracking, a compliant face is added into the sequence, a face is obtained from the sequence through the face recognition algorithm, face recognition is carried out, and information is obtained.
7. An oilfield park detection system based on computer vision, comprising:
the monitoring module is used for receiving a motion instruction, and the multiple cloud platforms carrying the cameras respectively move to the specified positions according to the preset tracks to monitor the detection object;
the establishing module is used for adjusting the monitoring area of each camera and establishing a mapping relation between a three-dimensional coordinate system and the monitoring area of each camera;
the comparison module is used for manually comparing the picture screenshots of the cameras, identifying and marking overlapped monitoring areas and storing the non-overlapped monitoring areas;
and the face recognition module is used for judging the entrance or the exit of people in the non-coincident monitoring area and carrying out face recognition.
8. The computer vision-based oilfield park detection system of claim 7, wherein the monitoring module comprises
The pressure and temperature identification submodule is used for identifying the pressure gauge and the thermometer through the HR model detection pointer key point to obtain pressure data and temperature data;
the liquid level identification submodule is used for carrying out liquid level meter identification on the liquid level meter through a LineNet detection liquid level line to obtain liquid level data;
the disconnecting link identification submodule is used for identifying the disconnecting link by using the classification model to acquire the type of the disconnecting link;
and the flow identification submodule is used for identifying the flow meter based on OCR (optical character recognition) to acquire flow data.
9. An electronic device, comprising:
at least one processor, at least one memory, and a data bus; wherein:
the processor and the memory complete mutual communication through the data bus; the memory stores program instructions executable by the processor, the processor calling the program instructions to perform the method of any of claims 1 to 6.
10. A non-transitory computer-readable storage medium storing a computer program that causes a computer to perform the method according to any one of claims 1 to 6.
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