CN113188465A - Drilling hole depth identification method and device based on video learning - Google Patents
Drilling hole depth identification method and device based on video learning Download PDFInfo
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- G—PHYSICS
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- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/22—Measuring arrangements characterised by the use of optical techniques for measuring depth
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
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Abstract
The invention discloses a drilling hole depth identification method and device based on video learning. Wherein, the method comprises the following steps: acquiring lifting rod video data; identifying data of the top and the bottom of the drill rod according to the lifting rod video data; calculating the drilling depth according to the data of the top and the bottom of the drill rod; and outputting the drilling depth. The invention solves the technical problems that in the prior art, the length of each drill rod needs to be manually measured one by one in the drilling depth measuring process, the measuring process is complicated, the efficiency is low, and errors are easy to occur when the number of the measuring rods is large.
Description
Technical Field
The invention relates to the field of machine vision, in particular to a drilling hole depth identification method and device based on video learning.
Background
In geological drilling, the depth of a drill hole is an important index for judging the drilling quality, and the stratum can be accurately and comprehensively ascertained only when the drill hole reaches the design depth, so that a scientific basis is provided for basic design. At present, the drilling depth is generally obtained by manually measuring drill rods and accumulating the drill rods one by one, the workload is high, and in the measuring process, a drilling machine cannot move, so that the drilling work is stopped, and the drilling progress is influenced.
The main problems existing in the current manual measurement of the hole depth are as follows:
1. the length of each drill rod needs to be manually measured one by one, the measuring process is complicated, the efficiency is low, and errors are easy to occur when the number of the measuring rods is large;
2. measuring the hole depth, the drilling machine must be stopped and not moved in position, causing interference with the drilling process (this interference can have a more significant impact on the drilling progress when the hole depth in the drilling process is to be obtained rather than the final hole depth);
3. after the drilling depth is manually measured, the drilling depth needs to be manually input and uploaded to a geological exploration management system, which wastes time and labor.
To the above-mentioned problem that exists of present manual measurement hole depth, this patent provides one set of software and equipment based on probing shadoof video identification study, main solution:
1. measuring the interference problem of the hole depth to the drilling process;
2. accuracy and efficiency of hole depth measurement;
3. and automatically uploading the measured hole depth to an exploration management system.
Disclosure of Invention
The embodiment of the invention provides a drilling hole depth identification method and device based on video learning, and at least solves the technical problems that in the drilling depth measurement process in the prior art, the length of each drilling rod needs to be manually measured one by one, the measurement process is complicated, the efficiency is low, and errors are prone to occurring when the number of the measuring rods is large.
According to an aspect of the embodiments of the present invention, there is provided a method for identifying a depth of a drilled hole based on video learning, including: acquiring lifting rod video data; identifying data of the top and the bottom of the drill rod according to the lifting rod video data; calculating the drilling depth according to the data of the top and the bottom of the drill rod; and outputting the drilling depth.
Optionally, before the obtaining the lifter video data, the method further includes: and acquiring shooting position information.
Optionally, the calculating the drilling depth according to the data of the top and the bottom of the drill rod comprises: calculating the length of the drill rod according to the data of the top and the bottom of the drill rod; acquiring the number data of the drill rods; and calculating to generate the drilling depth according to the length of the drill rod and the number of the drill rods.
Optionally, after the outputting the drilling depth, the method further includes: uploading the drilling depth to a server.
According to another aspect of the embodiments of the present invention, there is also provided a drilling hole depth recognition apparatus based on video learning, including: the acquisition module is used for acquiring the lifting rod video data; the identification module is used for identifying data of the top and the bottom of the drill rod according to the lifting rod video data; the calculation module is used for calculating the drilling depth according to the data of the top and the bottom of the drill rod; and the output module is used for outputting the drilling depth.
Optionally, the apparatus further comprises: the acquisition module is also used for acquiring shooting position information.
Optionally, the calculation module includes: the first calculation unit is used for calculating the length of the drill rod according to the data of the top and the bottom of the drill rod; the acquisition unit is used for acquiring the number data of the drill rods; and the second calculation unit is used for calculating and generating the drilling depth according to the length of the drill rod and the number of the drill rods.
Optionally, the apparatus further comprises: and the uploading module is used for uploading the drilling depth to a server.
According to another aspect of the embodiments of the present invention, there is also provided a non-volatile storage medium including a stored program, wherein the program controls an apparatus in which the non-volatile storage medium is located to execute a method for identifying a borehole depth based on video learning.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including a processor and a memory; the memory is stored with computer readable instructions, and the processor is used for executing the computer readable instructions, wherein the computer readable instructions execute a method for identifying the depth of a drilled hole based on video learning.
In the embodiment of the invention, the method comprises the steps of acquiring lifter video data; identifying data of the top and the bottom of the drill rod according to the lifting rod video data; calculating the drilling depth according to the data of the top and the bottom of the drill rod; will the mode that drilling depth carries out output has solved among the prior art in drilling depth measurement process, needs the length of each drilling rod of manual measurement one by one, and the measurement process is loaded down with trivial details, and is inefficient, easily takes place wrong technical problem when measuring the pole number many.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a flow chart of a method for identifying a borehole depth based on video learning according to an embodiment of the present invention;
fig. 2 is a block diagram of a drilling hole depth recognition apparatus based on video learning according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a pixel coordinate system and an image coordinate system of a method for identifying a borehole depth based on video learning according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a hole depth recognition method of a drill hole depth recognition method based on video learning according to an embodiment of the present invention;
fig. 5 is a schematic view of binocular imaging of a borehole depth recognition method based on video learning according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, 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 only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In accordance with an embodiment of the present invention, there is provided a method embodiment of a method for drill hole depth recognition based on video learning, it is noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions and that, although a logical order is illustrated in the flowchart, in some cases, the steps illustrated or described may be performed in an order different than here.
Example one
Fig. 1 is a flowchart of a method for identifying a borehole depth based on video learning according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
and step S102, acquiring the lifting rod video data.
Specifically, in order to calculate the drilling depth by acquiring the video of the related drilling detection device, the embodiment of the invention firstly needs to acquire the video data of the lifting rod, wherein the acquisition of the video data of the lifting rod can be realized by shooting the lifting rod device through the image or video acquisition equipment of the robot, so that the video data of the completion of various actions of the lifting rod in various time periods can be obtained, and the video data is used for the identification and analysis of the subsequent lifting rod part, and finally the depth data of the detected drilling is determined.
It should be noted that after the lifter video data is acquired in the embodiment of the present invention, the acquired video data needs to be preprocessed, the preprocessing may be noise reduction processing to increase identifiability of the video data and remove interference data in the video data, and each frame of image has higher definition and identifiability through the image noise reduction processing, so that the subsequent image identification and calculation are facilitated.
Optionally, before the obtaining the lifter video data, the method further includes: and acquiring shooting position information.
Specifically, in order to enable the bar-lifting video data to be more accurate and reasonable, the embodiment of the invention needs to place the robot at a position with the drilling equipment as the center and the radius of 5-10 meters, and the robot placement principle is as follows: (1) the complete lifting rod process and the lifting rod platform can be clearly seen at the placing position; (2) the sun cannot be photographed directly, and the phenomenon of overexposure is generated. (3) The robot's video capture device elevation angle cannot be greater than 20 degrees.
And step S104, identifying data of the top and the bottom of the drill rod according to the lifting rod video data.
Specifically, identifying the top and bottom of the drill pipe: the process is based on a recognition algorithm of deep learning, the top and the bottom of the drill rod are searched from the whole image, time is consumed, and error recognition is easy to occur, so that the drilling equipment is firstly positioned from an original image src, the drilling equipment is intercepted as an ROI (region of interest), and then the top and the bottom of the drill rod are recognized and positioned. The specific method comprises the following steps: (1) positioning the drilling equipment: the method can automatically identify the drilling equipment database through deep learning, but the diversity of shooting positions and targets requires deep learning network hierarchy and more learning parameters, and the ideal effect can be achieved only when the training samples are sufficient. Therefore, the shot borehole image is subjected to mirroring, amplification, reduction, rotation, background updating and the like, and the training sample is expanded. Traversing and searching based on a window moving mode is low in efficiency, so that window screening is firstly carried out through the characteristics of drilling equipment, and the identification efficiency is further improved. (2) And (3) positioning the top and the bottom of the drill rod, intercepting the window obtained in the step (1), carrying out normalization operation, and then carrying out identification and positioning on the top and the bottom of the drill rod according to the training process and the prediction process in the step (1).
And S106, calculating the drilling depth according to the data of the top and the bottom of the drill rod.
Optionally, the calculating the drilling depth according to the data of the top and the bottom of the drill rod comprises: calculating the length of the drill rod according to the data of the top and the bottom of the drill rod; acquiring the number data of the drill rods; and calculating to generate the drilling depth according to the length of the drill rod and the number of the drill rods.
Specifically, after the data of the top and the bottom of the drill rod are acquired in the embodiment of the present invention, the length and the number of the drill rod need to be calculated and identified according to the data of the top and the bottom of the drill rod, and the obtained data is further calculated and processed to obtain a final drilling depth value.
In addition, the binocular camera is calibrated before the robot leaves a factory, internal parameters fx, fy, cx and cy of the camera, an external parameter rotation matrix R and a translation matrix T are obtained, and the camera can be corrected through the two parameters to form a parallax map. The position of the drill rod in the image and the pixel coordinates of the top and the bottom of the drill rod are obtained from the embodiment, coordinate conversion is carried out through parameter transformation to obtain coordinate values of the top and the bottom of the drill rod in a world coordinate system, the length of the drill rod is obtained according to a coordinate distance formula, and namely, the point in the image coordinate system is mapped with the position in an actual space. The robot recognizes and calculates the length of the drill rod, and needs to be converted and calculated by four coordinate systems, namely a pixel coordinate system, an image coordinate system, a camera coordinate system and a world coordinate system. The pixel coordinate system and the image coordinate system are shown in fig. 3 and 4. The pixel coordinate system takes the upper left corner O0 of the image as an origin, and horizontal and vertical coordinates u and v respectively represent the column number and the row number of the pixel point in the image; the origin of the image coordinate system is the intersection O1 of the optical axis of the camera and the image plane, generally the center of the image plane, also referred to as the principal point of the image, with the x-axis parallel to the u-axis and the y-axis parallel to the v-axis. Let the coordinates of O1 in the pixel coordinate system be (U0, V0), and dx and dy be the physical dimensions of the unit pixel on the horizontal axis and the vertical axis, the two coordinate systems have the following relationship:
expressed as a homogeneous matrix:
the inverse relationship is as follows:
as shown in the imaging principle of the camera in FIG. 5, Oc is the optical center of the camera, ZC is the optical axis of the camera, the intersection point of the optical axis and the image is O1, the coordinate system Oc-XcYcZc is the coordinate system of the camera, Ow-XwYwZw is the world coordinate system, and the distance between OcO1 is the focal length f of the camera. The formula for converting from the camera coordinate system to the image coordinate system is as follows:
expressed as follows with a homogeneous matrix (where s is the scale factor and f is the focal length):
the transformation relationship between the camera coordinate system and the world coordinate system is as follows:
wherein R is an orthogonal matrix of 3 x 3, which is a rotation matrix, and T is a matrix of 3 x 1, which is a translation matrix.
Wherein, the three-dimensional coordinates of the objects in the actual scene can be determined by binocular stereo vision technology. As shown in the schematic diagram of binocular stereopsis in fig. 5, OL and OR are the optical centers of the left and right cameras, and their optical axes and their respective imaging planes are shown. Assuming that the internal and external parameters of the two cameras are identical, the focal length is f, the distance between the optical centers (base line) is B, the two cameras are on the same plane, and the Y coordinates of the cameras to their projection centers are equal. The imaging points of the spatial point p (x, y, z) on the two cameras at the same time are Pleft and Pright respectively. Therefore, after the actual coordinate value is obtained, the actual length value, namely the length of the drill rod, can be obtained according to a distance formula between two points and the like:
wherein: xh1, yh1, zh1 are the relative positions of the top of the drill rod and the camera, xh2, yh2, zh2 are the relative positions of the bottom of the drill rod and the camera, and Hs1 is the actual length of the drill rod.
It should be noted that, the position of the top of the drill rod in the image can be obtained from the above embodiment by identifying the number of the drill rods, and according to the actual rod lifting process, the position is a process that the position is from the lower part to the upper part of the image, and the corresponding value is changed from large to small and then from small to large from the upper part to the lower part, so that each rod lifting process obtains a trough, and finally, the number of the rods is obtained by counting the number of the troughs. The lifting process of the active rod is not changed after the active rod is changed from small to large, and the active rod can be judged according to the characteristic.
In addition, the drilling depth is calculated by summing the rod length values of the lifting rod each time to obtain the total lifting rod length and adding the lifting amount Hy of the driving rod, namely the hole depth Kd;
wherein i is 1,2,3, … n;
and S108, outputting the drilling depth.
Optionally, after the outputting the drilling depth, the method further includes: uploading the drilling depth to a server.
Specifically, after the drilling depth is acquired, the drilling depth value needs to be output to a display terminal, so that a user can check the drilling depth value in real time, the drilling depth value can be transmitted to a cloud server through a remote transmission protocol, and the server can store and analyze the drilling depth value in real time.
Through above-mentioned embodiment, solved among the prior art in drilling depth measurement process, need the length of each drilling rod of manual measurement one by one, the measurement process is loaded down with trivial details, and is inefficient, easily takes place wrong technical problem when measuring the pole number is many.
Example two
Fig. 2 is a block diagram of a drilling hole depth recognition apparatus based on video learning according to an embodiment of the present invention, as shown in fig. 2, the apparatus includes:
and the obtaining module 20 is used for obtaining the lifter video data.
Specifically, in order to calculate the drilling depth by acquiring the video of the related drilling detection device, the embodiment of the invention firstly needs to acquire the video data of the lifting rod, wherein the acquisition of the video data of the lifting rod can be realized by shooting the lifting rod device through the image or video acquisition equipment of the robot, so that the video data of the completion of various actions of the lifting rod in various time periods can be obtained, and the video data is used for the identification and analysis of the subsequent lifting rod part, and finally the depth data of the detected drilling is determined.
It should be noted that after the lifter video data is acquired in the embodiment of the present invention, the acquired video data needs to be preprocessed, the preprocessing may be noise reduction processing to increase identifiability of the video data and remove interference data in the video data, and each frame of image has higher definition and identifiability through the image noise reduction processing, so that the subsequent image identification and calculation are facilitated.
Optionally, the apparatus further comprises: the acquisition module is also used for acquiring shooting position information.
Specifically, in order to enable the bar-lifting video data to be more accurate and reasonable, the embodiment of the invention needs to place the robot at a position with the drilling equipment as the center and the radius of 5-10 meters, and the robot placement principle is as follows: (1) the complete lifting rod process and the lifting rod platform can be clearly seen at the placing position; (2) the sun cannot be photographed directly, and the phenomenon of overexposure is generated. (3) The robot's video capture device elevation angle cannot be greater than 20 degrees.
And the identification module 22 is used for identifying the data of the top and the bottom of the drill rod according to the lifting rod video data.
Specifically, identifying the top and bottom of the drill pipe: the process is based on a recognition algorithm of deep learning, the top and the bottom of the drill rod are searched from the whole image, time is consumed, and error recognition is easy to occur, so that the drilling equipment is firstly positioned from an original image src, the drilling equipment is intercepted as an ROI (region of interest), and then the top and the bottom of the drill rod are recognized and positioned. The specific method comprises the following steps: (1) positioning the drilling equipment: the method can automatically identify the drilling equipment database through deep learning, but the diversity of shooting positions and targets requires deep learning network hierarchy and more learning parameters, and the ideal effect can be achieved only when the training samples are sufficient. Therefore, the shot borehole image is subjected to mirroring, amplification, reduction, rotation, background updating and the like, and the training sample is expanded. Traversing and searching based on a window moving mode is low in efficiency, so that window screening is firstly carried out through the characteristics of drilling equipment, and the identification efficiency is further improved. (2) And (3) positioning the top and the bottom of the drill rod, intercepting the window obtained in the step (1), carrying out normalization operation, and then carrying out identification and positioning on the top and the bottom of the drill rod according to the training process and the prediction process in the step (1).
And the calculation module 24 is used for calculating the drilling depth according to the data of the top and the bottom of the drill rod.
Optionally, the calculation module includes: the first calculation unit is used for calculating the length of the drill rod according to the data of the top and the bottom of the drill rod; the acquisition unit is used for acquiring the number data of the drill rods; and the second calculation unit is used for calculating and generating the drilling depth according to the length of the drill rod and the number of the drill rods.
Specifically, after the data of the top and the bottom of the drill rod are acquired in the embodiment of the present invention, the length and the number of the drill rod need to be calculated and identified according to the data of the top and the bottom of the drill rod, and the obtained data is further calculated and processed to obtain a final drilling depth value.
In addition, the binocular camera is calibrated before the robot leaves a factory, internal parameters fx, fy, cx and cy of the camera, an external parameter rotation matrix R and a translation matrix T are obtained, and the camera can be corrected through the two parameters to form a parallax map. The position of the drill rod in the image and the pixel coordinates of the top and the bottom of the drill rod are obtained from the embodiment, coordinate conversion is carried out through parameter transformation to obtain coordinate values of the top and the bottom of the drill rod in a world coordinate system, the length of the drill rod is obtained according to a coordinate distance formula, and namely, the point in the image coordinate system is mapped with the position in an actual space. The robot recognizes and calculates the length of the drill rod, and needs to be converted and calculated by four coordinate systems, namely a pixel coordinate system, an image coordinate system, a camera coordinate system and a world coordinate system. The pixel coordinate system and the image coordinate system are shown in fig. 3 and 4. The pixel coordinate system takes the upper left corner O0 of the image as an origin, and horizontal and vertical coordinates u and v respectively represent the column number and the row number of the pixel point in the image; the origin of the image coordinate system is the intersection O1 of the optical axis of the camera and the image plane, generally the center of the image plane, also referred to as the principal point of the image, with the x-axis parallel to the u-axis and the y-axis parallel to the v-axis. Let the coordinates of O1 in the pixel coordinate system be (U0, V0), and dx and dy be the physical dimensions of the unit pixel on the horizontal axis and the vertical axis, the two coordinate systems have the following relationship:
expressed as a homogeneous matrix:
the inverse relationship is as follows:
as shown in the imaging principle of the camera in FIG. 5, Oc is the optical center of the camera, ZC is the optical axis of the camera, the intersection point of the optical axis and the image is O1, the coordinate system Oc-XcYcZc is the coordinate system of the camera, Ow-XwYwZw is the world coordinate system, and the distance between OcO1 is the focal length f of the camera. The formula for converting from the camera coordinate system to the image coordinate system is as follows:
expressed as follows with a homogeneous matrix (where s is the scale factor and f is the focal length):
the transformation relationship between the camera coordinate system and the world coordinate system is as follows:
wherein R is an orthogonal matrix of 3 x 3, which is a rotation matrix, and T is a matrix of 3 x 1, which is a translation matrix.
Wherein, the three-dimensional coordinates of the objects in the actual scene can be determined by binocular stereo vision technology. As shown in the schematic diagram of binocular stereopsis in fig. 5, OL and OR are the optical centers of the left and right cameras, and their optical axes and their respective imaging planes are shown. Assuming that the internal and external parameters of the two cameras are identical, the focal length is f, the distance between the optical centers (base line) is B, the two cameras are on the same plane, and the Y coordinates of the cameras to their projection centers are equal. The imaging points of the spatial point p (x, y, z) on the two cameras at the same time are Pleft and Pright respectively. Therefore, after the actual coordinate value is obtained, the actual length value, namely the length of the drill rod, can be obtained according to a distance formula between two points and the like:
wherein: xh1, yh1, zh1 are the relative positions of the top of the drill rod and the camera, xh2, yh2, zh2 are the relative positions of the bottom of the drill rod and the camera, and Hs1 is the actual length of the drill rod.
It should be noted that, the position of the top of the drill rod in the image can be obtained from the above embodiment by identifying the number of the drill rods, and according to the actual rod lifting process, the position is a process that the position is from the lower part to the upper part of the image, and the corresponding value is changed from large to small and then from small to large from the upper part to the lower part, so that each rod lifting process obtains a trough, and finally, the number of the rods is obtained by counting the number of the troughs. The lifting process of the active rod is not changed after the active rod is changed from small to large, and the active rod can be judged according to the characteristic.
In addition, the drilling depth is calculated by summing the rod length values of the lifting rod each time to obtain the total lifting rod length and adding the lifting amount Hy of the driving rod, namely the hole depth Kd;
wherein i is 1,2,3, … n;
and the output module 26 is used for outputting the drilling depth.
Optionally, the apparatus further comprises: and the uploading module is used for uploading the drilling depth to a server.
Specifically, after the drilling depth is acquired, the drilling depth value needs to be output to a display terminal, so that a user can check the drilling depth value in real time, the drilling depth value can be transmitted to a cloud server through a remote transmission protocol, and the server can store and analyze the drilling depth value in real time.
According to another aspect of the embodiments of the present invention, there is also provided a non-volatile storage medium including a stored program, wherein the program controls an apparatus in which the non-volatile storage medium is located to execute a method for identifying a borehole depth based on video learning.
Specifically, the method comprises the following steps: acquiring lifting rod video data; identifying data of the top and the bottom of the drill rod according to the lifting rod video data; calculating the drilling depth according to the data of the top and the bottom of the drill rod; and outputting the drilling depth.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including a processor and a memory; the memory is stored with computer readable instructions, and the processor is used for executing the computer readable instructions, wherein the computer readable instructions execute a method for identifying the depth of a drilled hole based on video learning.
Specifically, the method comprises the following steps: acquiring lifting rod video data; identifying data of the top and the bottom of the drill rod according to the lifting rod video data; calculating the drilling depth according to the data of the top and the bottom of the drill rod; and outputting the drilling depth.
Through above-mentioned embodiment, solved among the prior art in drilling depth measurement process, need the length of each drilling rod of manual measurement one by one, the measurement process is loaded down with trivial details, and is inefficient, easily takes place wrong technical problem when measuring the pole number is many.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
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 units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit 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 invention may be embodied in the form of a software product, which is stored in a storage medium and includes 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 invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A drilling hole depth identification method based on video learning is characterized by comprising the following steps:
acquiring lifting rod video data;
identifying data of the top and the bottom of the drill rod according to the lifting rod video data;
calculating the drilling depth according to the data of the top and the bottom of the drill rod;
and outputting the drilling depth.
2. The method of claim 1, wherein prior to said obtaining the lifter video data, the method further comprises:
and acquiring shooting position information.
3. The method of claim 1, wherein calculating a borehole depth from the drill pipe top and bottom data comprises:
calculating the length of the drill rod according to the data of the top and the bottom of the drill rod;
acquiring the number data of the drill rods;
and calculating to generate the drilling depth according to the length of the drill rod and the number of the drill rods.
4. The method of claim 1, wherein after said outputting the borehole depth, the method further comprises:
uploading the drilling depth to a server.
5. A drilling hole depth recognition device based on video learning is characterized by comprising:
the acquisition module is used for acquiring the lifting rod video data;
the identification module is used for identifying data of the top and the bottom of the drill rod according to the lifting rod video data;
the calculation module is used for calculating the drilling depth according to the data of the top and the bottom of the drill rod;
and the output module is used for outputting the drilling depth.
6. The apparatus of claim 5, further comprising:
the acquisition module is also used for acquiring shooting position information.
7. The apparatus of claim 5, wherein the computing module comprises:
the first calculation unit is used for calculating the length of the drill rod according to the data of the top and the bottom of the drill rod;
the acquisition unit is used for acquiring the number data of the drill rods;
and the second calculation unit is used for calculating and generating the drilling depth according to the length of the drill rod and the number of the drill rods.
8. The apparatus of claim 5, further comprising:
and the uploading module is used for uploading the drilling depth to a server.
9. A non-volatile storage medium, comprising a stored program, wherein the program, when executed, controls an apparatus in which the non-volatile storage medium is located to perform the method of any one of claims 1 to 4.
10. An electronic device comprising a processor and a memory; the memory has stored therein computer readable instructions for execution by the processor, wherein the computer readable instructions when executed perform the method of any one of claims 1 to 4.
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