Drilling hole wall image splicing and multi-attribute data synchronous display method and device

Abstract

The invention discloses a drill hole wall image splicing and multi-attribute data synchronous display method and device, and the method comprises the steps: carrying out the graying of an obtained expanded image of a drill hole wall image, and obtaining the gray value of each line of the expanded image of the drill hole wall image; according to a preset gray threshold value, cutting and noise reduction are carried out on the expanded borehole wall image, and each cut picture is sequentially spliced according to a sequence to form a target borehole wall expanded image; the method comprises the following steps: acquiring an initial data set of wave velocity and experimental data, reading and extracting by using Python to obtain array form data, and drawing a broken line graph by using the array form data through a plot function; the formats of the target drilled hole wall unfolding image and the experimental data broken line graph are converted into a preset picture format, and the spliced hole wall image and the experimental data image are synchronously displayed through a rolling area assembly and an event binding mechanism.

Description

Technical Field

[0001] This application relates to the field of engineering geological exploration technology, and more specifically, to a method and apparatus for stitching borehole wall images and synchronously displaying multi-attribute data. Background Technology

[0002] Engineering geological surveys, such as borehole television and borehole acoustic testing, are effective means of directly obtaining engineering geological information about the rock mass surrounding the borehole. The borehole wall images and surrounding rock wave velocities obtained from in-situ borehole tests are important parameters for assessing the quality of the underground rock mass. After drilling, laboratory geotechnical experiments are used to obtain data such as density and compressive strength. These data, along with borehole wall unfolding diagrams and rock wave velocities obtained from borehole tests, are then manually identified and interpreted. Finally, relevant technical personnel conduct comprehensive analysis to determine the quality of the underground rock mass and other key geological characteristics. However, poor spatial alignment, low contrast, and incomplete information reflection among the individual test data can affect the efficiency and accuracy of the comprehensive analysis.

[0003] Currently, borehole testing in the field of engineering geological exploration suffers from problems such as high labor costs, low efficiency, and insufficient digitalization and intelligentization. Conducting research on information technology for underground rock mass engineering geology, and achieving standardized integration of multi-attribute borehole data, can effectively improve the accuracy and quality of geological exploration, free up human resources, increase work efficiency, and reduce exploration costs. Therefore, how to visualize borehole in-situ test data and experimental data, and achieve integrated and synchronized display of multi-attribute visualized data, is of great significance for overall analysis, basic design, and construction management in engineering geological exploration. Summary of the Invention

[0004] To address at least one deficiency or improvement need in the existing technology, this invention provides a method and apparatus for stitching borehole wall images and synchronously displaying multi-attribute data. This solves the problems of poor spatial alignment of test data and incomplete information reflection in existing borehole tests in the field of engineering geological exploration, which leads to low comprehensive analysis efficiency and accuracy. It improves the data processing efficiency and analysis accuracy in engineering geological exploration and provides a more reliable basis for the quality assessment and feature identification of underground rock masses.

[0005] To achieve the above objectives, according to a first aspect of the present invention, a method for stitching borehole wall images and synchronously displaying multi-attribute data is provided. The method includes: performing grayscale processing on the acquired expanded borehole wall image to obtain the grayscale value of each row of the expanded borehole wall image; cropping and denoising the expanded borehole wall image according to a preset grayscale threshold; stitching each cropped image sequentially to form a target expanded borehole wall image; acquiring an initial dataset of wave velocity and experimental data; using Python to read and extract array-type data; plotting the array-type data as a line graph using the plot function; converting the format of the target expanded borehole wall image and the experimental data line graph into a predetermined image format; and synchronously displaying the stitched borehole wall image and experimental data image using a scrolling area component and an event binding mechanism.

[0006] In an exemplary embodiment, the step of cropping and denoising the expanded borehole wall image based on a preset grayscale threshold, and then sequentially stitching together each cropped image to form the target expanded borehole wall image, includes: determining a preset grayscale threshold using the grayscale histogram of the expanded borehole wall image; determining the cropping position of the image based on the preset grayscale threshold; and cropping the image. The specific formula for calculating the cropping position based on the preset grayscale threshold is as follows:

[0007] in, Indicates the image position in the original image. This represents the sum of the grayscale values ​​of the pixels in each row. To preset the grayscale threshold, This is the cropped image.

[0008] In one exemplary embodiment, after plotting the array-based data into a line graph using the plot function, the method further includes: performing noise reduction processing on the plotted line graph to obtain the height of the current initial experimental data line graph. The final height of the aligned line chart of experimental data is: The formula for calculating the final height is as follows:

[0009] in, This represents the final height of the line graph of the experimental data. This is the proportionality coefficient. The height of the line graph of the initial experimental data.

[0010] In an exemplary embodiment, converting the format of the target borehole wall unfolded image and the experimental data line graph into a predetermined image format includes: converting the format of the target borehole wall unfolded image and the experimental data line graph by swapping the red and blue channels of the images respectively; converting the BGR format to the RGB format to generate the corresponding QImage format image.

[0011] In one exemplary embodiment, the synchronous display of the stitched hole wall image and experimental data image through a scrolling area component and an event binding mechanism includes: displaying the image using a QLabel and placing the QLabel in a QScrollArea container; placing each QScrollArea area in the same interface and arranging them using a QVBoxLayout layout, with the width of each QScrollArea area set to the image width.

[0012] In one exemplary embodiment, the synchronous display of the stitched hole wall image and experimental data image through a scrolling area component and an event binding mechanism includes: binding scroll bar events to synchronize the scrolling effects of multiple scrolling areas; installing an event filter to listen for scrolling events; using a signal and slot mechanism to bind the scrolling signal of the scroll bar to the corresponding slot function; and triggering other scroll bars to scroll with the same scroll displacement when any one scroll bar scrolls.

[0013] According to a second aspect of the present invention, a borehole wall image stitching and multi-attribute data synchronous display device is also provided, comprising: an acquisition unit, used to perform grayscale processing on the acquired borehole wall image unfolded image to obtain the grayscale value of each row of the borehole wall image unfolded image; a stitching unit, used to crop and denoise the borehole wall image unfolded image according to a preset grayscale threshold, and stitch each cropped image sequentially to form a target borehole wall unfolded image; a drawing unit, used to acquire an initial data set of wave velocity and experimental data, use Python to read and extract array-type data, and use the plot function to draw a line graph of the array-type data; and a display unit, used to convert the format of the target borehole wall unfolded image and the experimental data line graph into a predetermined image format, and synchronously display the stitched borehole wall image and experimental data image through a scrolling area component and an event binding mechanism.

[0014] According to a third aspect of the present invention, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer program, wherein the computer program is configured to execute the above-described method for stitching borehole wall images and synchronously displaying multi-attribute data when running.

[0015] According to a fourth aspect of the present invention, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-described method for stitching borehole wall images and synchronously displaying multi-attribute data through the computer program.

[0016] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: (1) This invention provides a method for stitching borehole wall images and synchronously displaying multi-attribute data. By using data standardization and spatial alignment technology, it solves the problems of scattered data sources and inconsistent formats in traditional data. Test data from different sources can be accurately aligned in the same coordinate system and fused through a unified platform, resulting in higher data contrast, more comprehensive information, and greatly improving the usability and analytical value of the data.

[0017] (2) Improve analysis efficiency and decision accuracy: Based on the fusion technology of multi-source data, various information such as borehole images, rock wave velocity, and geotechnical test data can be integrated on a single platform, avoiding the tediousness and errors in the traditional manual analysis process, thereby improving the timeliness and accuracy of decision-making.

[0018] (3) Reduce costs and improve work efficiency: By realizing a digital and intelligent geological exploration process, not only can manual intervention be reduced and more labor resources be released, but the exploration cycle can also be greatly shortened. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart illustrating an optional method for stitching borehole wall images and synchronously displaying multi-attribute data, provided in an embodiment of this application; Figure 2 A flowchart illustrating another optional method for stitching borehole wall images and synchronously displaying multi-attribute data provided in an embodiment of this application; Figure 3 This application provides an optional image grayscale value illustration. Figure 4 An optional grayscale threshold selection grayscale histogram is provided for embodiments of this application; Figure 5 This is a schematic diagram of an optional image noise reduction method provided in an embodiment of this application; Figure 6 This is a schematic diagram illustrating an optional cutting and splicing method provided for an embodiment of this application; Figure 7 An optional final result display diagram provided for an embodiment of this application; Figure 8 A schematic diagram of an optional borehole wall image stitching and multi-attribute data synchronous display device provided in an embodiment of this application; Figure 9 This is a schematic diagram of an optional electronic device provided in an embodiment of this application. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0022] The terms "first," "second," "third," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0023] According to one aspect of the embodiments of this application, a method for stitching together borehole wall images and synchronously displaying multi-attribute data is provided. The following is in conjunction with... Figure 1 This application describes a method for stitching borehole wall images and synchronously displaying multi-attribute data, as provided in an embodiment of the present application.

[0024] Figure 1 This is a flowchart illustrating an optional method for stitching borehole wall images and synchronously displaying multi-attribute data, as provided in an embodiment of this application. Figure 1 As shown, the process of this method may include the following steps: S102, perform grayscale processing on the acquired borehole wall image unfolded image to obtain the grayscale value of each row of the borehole wall image unfolded image; S104, the borehole wall image unfolded image is cropped and denoised according to the preset grayscale threshold, and each cropped image is stitched together in order to form the target borehole wall unfolded image. S106: Obtain the initial dataset of wave velocity and experimental data, use Python to read and extract the data in array form, and use the plot function to draw a line graph of the array data. S108, convert the target borehole wall unfolded image and experimental data line graph format into a predetermined image format, and synchronously display the stitched borehole wall image and experimental data image through a scrolling area component and event binding mechanism.

[0025] The method for stitching borehole wall images and synchronously displaying multi-attribute data provided in this application embodiment is applicable to engineering geological exploration scenarios. The borehole test data comes from various sources and has significant differences in data format and spatial coordinates. For example, it can be multi-source data such as borehole wall images, rock mass wave velocity, and geotechnical test data.

[0026] It should be noted that the borehole data acquisition involved in this embodiment can be carried out by using a borehole television imaging device to take real-time pictures of the specific conditions of the rock mass deep underground and transmit the pictures to the ground receiving end through optical fiber. Wave velocity data is obtained by on-site wave velocity testing, and experimental data is obtained by outdoor and indoor experiments.

[0027] Furthermore, combined Figure 1 and Figure 2 As shown, the main implementation process of the borehole wall image stitching and multi-attribute data synchronous display method provided in this embodiment is as follows: After the drilling tools have drilled, a borehole television imager is inserted into the hole to obtain the required borehole images and transmit them to the ground.

[0028] An algorithm was written using the Python platform to determine the cropping position for each hole wall unfolded image according to the grayscale threshold, and then crop it. A loop algorithm was used to determine the size of the image after stitching, create a blank image area, and stitch it sequentially. Black and white edges were detected in the stitched image to remove noise areas and determine the final hole wall unfolded image. Import wave velocity and experimental data, and use the Matplotlib library to write the corresponding algorithm to draw two-dimensional line graphs. Set the titles, horizontal and vertical axis data, legends, and font sizes for the line graphs. After plotting, perform the same noise region detection and removal on each line graph, determine the scaling factor between the developed borehole wall and the line graph, and enlarge the line graph size to match the developed borehole wall size according to the scaling factor. Figure 1 To maintain depth alignment.

[0029] Understandably, the predefined image format can be QImage, and the scrolling area component can be QscrollArea. Furthermore, the borehole wall unfolding diagram and various data line charts are in array format. Using PyQt5's corresponding algorithm, the red and blue channels are converted to QImage format, and each image is displayed using a QLabel, placed within a QscrollArea area defined in the PyQt5 UI. When the image size is too large, a scrolling viewing effect can be achieved. The scrollbar of each image's QscrollArea area is bound, so when any image triggers a scrolling event, the other images scroll synchronously and consistently. Ultimately, this achieves an integrated display of the stitched borehole wall unfolding diagram and the visualized test data, synchronously reflecting detailed information from various parts of the borehole.

[0030] Through steps S102 to S108, the acquired borehole wall image unfolded is processed into grayscale to obtain the grayscale value of each row of the unfolded borehole wall image; the unfolded borehole wall image is cropped and denoised according to a preset grayscale threshold, and each cropped image is stitched together in sequence to form the target borehole wall unfolded image; the initial data set of wave velocity and experimental data is obtained, and the array data is read and extracted using Python, and a line graph is plotted using the plot function; the format of the target borehole wall unfolded image and the experimental data line graph are converted to a predetermined image format, and the stitched borehole wall image and experimental data image are displayed synchronously through a scrolling area component and an event binding mechanism, thereby improving the data processing efficiency and analysis accuracy in engineering geological exploration, and providing a more reliable basis for the quality assessment and feature identification of underground rock masses.

[0031] In an exemplary embodiment, the step of cropping and denoising the expanded image of the borehole wall according to a preset grayscale threshold, and then sequentially stitching together each cropped image to form the target expanded image of the borehole wall includes: S11, determine a preset grayscale threshold by unfolding the grayscale histogram of the borehole wall image, determine the cropping position of the image based on the preset grayscale threshold, and crop the image. S12, the calculation formula for determining the cropping position of the image based on a preset grayscale threshold is as follows:

[0032] in, Indicates the image position in the original image. This represents the sum of the grayscale values ​​of the pixels in each row. To preset the grayscale threshold, This is the cropped image.

[0033] Optionally, before cropping the image, it is necessary to obtain the unfolded image of the borehole wall, wave velocity, and experimental data. The unfolded image of the borehole wall is then converted to grayscale to obtain the grayscale value of each row of the image. Based on a reasonable grayscale threshold, the image is cropped and denoised to remove noise. The effective content of the unfolded image of the borehole wall is retained and stitched together to form a complete unfolded image of the borehole wall.

[0034] Combination Figures 3 to 6 As shown, each borehole wall unfolded image is processed into a grayscale image, converting the color image to a grayscale image. The grayscale values ​​are calculated by weighting the RGB (red, green, blue) channels, using the following formula:

[0035] R, G, and B are the intensity values ​​of the red, green, and blue components of a pixel, respectively, and are typically integers between 0 and 255 (for 8-bit color depth). Gray is the calculated grayscale value, which ranges from [0, 255].

[0036] Therefore, the expression for the sum of gray values ​​in each row is: , where Gray(x) is the sum of gray values ​​in x rows, i is the number of pixels in each row, and Grayi is the gray value of the i-th pixel in x rows.

[0037] Furthermore, the optimal gray-level threshold is selected using the image's gray-level histogram. Determine the cropping location of the image and crop the image accordingly.

[0038] The method for determining this is: the grayscale value range of the image. [0, 255], calculate the image grayscale histogram , which represents the frequency of occurrence of each grayscale value.

[0039] The expression for the total grayscale mean of an image is: ,in, Represents grayscale value frequency, It is the overall mean of the image.

[0040] Standard deviation : ,in, Standard deviation Let be the grayscale value of the i-th row. It is the overall mean of the image.

[0041] The formula for determining the range is: ; .

[0042] Each cropped image is stitched together sequentially to obtain the final borehole wall unfolded image height H. The stitched borehole wall unfolded image is then subjected to vertical black and white noise region detection to remove invalid black and white edges, retaining the valid parts of the borehole wall unfolded image to form the final borehole wall unfolded image.

[0043] In this embodiment, a reasonable grayscale threshold is calculated based on the grayscale curve histogram to determine the cropping position, which also serves to isolate some noise areas.

[0044] In one exemplary embodiment, after plotting the array-based data into a line chart using the plot function, the method further includes: S21, first perform noise reduction processing on the drawn line graph to obtain the height of the current initial experimental data line graph. ; S22, the final height of the aligned experimental data line graph is The formula for calculating the final height is as follows:

[0045] in, This represents the final height of the line graph of the experimental data. This is the proportionality coefficient. The height of the line graph of the initial experimental data.

[0046] In this embodiment, for example, the Matplotlib library in Python is used to read indoor and outdoor collected data stored in Excel spreadsheets and TXT files, and the one-dimensional array is visualized in two dimensions to obtain a line graph of the experimental data. It should be noted that the Matplotlib library is a plotting tool in Python similar to Matlab, supporting cross-platform operation. It draws 2D images based on NumPy and ndarray arrays, is simple to use, has clear and easy-to-understand code, and the visualization results can be manually edited, resulting in good processing effects.

[0047] Then, the initial dataset of wave velocity and experimental data was obtained. The pandas library of Python was used to read the wave velocity and experimental data and extract key information. The read data was processed in the form of an array. The plot function of Matplotlib was used to draw a line chart. Based on the read data, the depth was used as the vertical axis and the data was used as the horizontal axis. The title, legend, scale labels and other information in the chart were set.

[0048] The drawn line chart is first subjected to noise reduction processing, and the image is converted to grayscale. First, black and white regions are detected horizontally, and then vertical regions are detected, removing rows and columns with grayscale values ​​of 0 or 255 from the image's grayscale curve. This yields the height of the line chart for the current experimental data. ; In the visualization of experimental data, wave velocity and depth information need to be precisely aligned with the borehole wall unfolding diagram. The height of the line graph of the experimental data is set to [value missing]. The height of the stitched image of the borehole wall unfolded is The proportionality coefficient between them can be calculated using the following formula:

[0049] Therefore, the final height of the line graph of the experimental data is , The expression is:

[0050] in, This represents the final height of the line graph of the experimental data. This is the proportionality coefficient. The height of the line graph of the initial experimental data.

[0051] In one exemplary embodiment, converting the format of the target borehole wall unfolded image and the experimental data line graph into a predetermined image format includes: S31, Convert the format of the target borehole wall unfolded image and the experimental data line graph, and swap the red and blue channels of the images respectively; S32 converts the BGR format to RGB format and generates the corresponding QImage format image.

[0052] In this embodiment, since the images are displayed using PyQt5, the image format must be QImage. Therefore, it is necessary to convert the borehole wall unfolded diagram and the experimental data line graph to QImage format. For example, the borehole wall unfolded diagram and the experimental data line graph are format converted by swapping the red and blue channels of the images, converting the BGR format to RGB format, and generating a QImage format image that meets the requirements of PyQt5.

[0053] OpenCV was used to read the experimental data line graphs and the stitched borehole wall unfolded images, which were then read as BGR format images. The pixel values ​​of the images were... Where x and y represent pixel positions. The channel indices are represented as (0: blue channel, 1: green channel, 2: red channel), therefore, the loaded image data is a three-dimensional array: , in, Image height, This represents the image width.

[0054] The conversion channel transforms the BGR format to RGB format. The formula for rearranging pixel values ​​is as follows:

[0055] in, This indicates the mapping relationship from BGR to RGB.

[0056] The construction of QImage requires obtaining the image's dimensions and data: the image's width ( ),high( ) directly corresponds to the size of the pixel matrix. For a three-channel RGB image, the number of bytes occupied by each row ( )for: Here, the number of channels is selected as 3.

[0057] PyQt5's QImage class supports various image formats, among which Format_RGB888 is suitable for RGB images, with each pixel occupying 3 bytes. The formula for constructing a QImage format image is:

[0058] in, For image data, Image width, Image height, The number of bytes per line.

[0059] In one exemplary embodiment, the synchronous display of the stitched hole wall image and experimental data image through a scrolling area component and an event binding mechanism includes: S41, Use QLabel to display the image, and place the QLabel in a QScrollArea container; S42 places each QScrollArea area in the same interface and arranges them using QVBoxLayout. The width of each QScrollArea area is set to the width of the image.

[0060] In the embodiments of this application, such as Figure 7 As shown, the stitched hole wall image and experimental data image are displayed using QScrollArea (i.e., the scroll area component). When the size of the image or data image is too large, a scroll bar is used to enable image viewing. An event binding mechanism is used to synchronize the scroll bar, thereby achieving synchronized display of the image and data.

[0061] For example, when displaying an image using a QLabel, place the QLabel within a QScrollArea container. This container allows the content to be scrolled out of its display area using scrollbars. Place each QScrollArea area within the same interface and arrange them using a QVBoxLayout layout, setting the width of each QScrollArea area to [value missing]. Numerically, it is equal to the image width. The expression is:

[0062] The height of each QScrollArea area is kept consistent and is set to follow the height of the main window.

[0063] This embodiment integrates multi-attribute data from boreholes and displays them synchronously on the same interface, making the acquisition of borehole information more accurate and the feedback more intuitive.

[0064] In one exemplary embodiment, the synchronous display of the stitched hole wall image and experimental data image through a scrolling area component and an event binding mechanism includes: S51, bind scroll bar events to synchronize the scrolling effects of multiple scroll areas, and install event filters to listen for scroll events; S52 uses the signal and slot mechanism to bind the scroll bar's scroll signal to the corresponding slot function; S53, when any one scroll bar is scrolling, it triggers other scroll bars to scroll with the same scroll displacement.

[0065] In this embodiment, when the image is too large, scroll bar events are bound to achieve synchronized scrolling of multiple scrolling areas. An event filter is installed to listen for scrolling events. When one scroll bar changes, the other scroll bars also change accordingly.

[0066] By binding scrollbars with slot functions and signals, the scrolling of any one scrollbar triggers the scrolling of the other scrollbars, with consistent scroll displacement. The synchronous scrolling formula is as follows:

[0067] in, , , These represent the vertical displacement of the scroll bar for each scrolling area.

[0068] This embodiment enables the integrated display of multi-attribute data after the spliced ​​borehole wall unfolding diagram and test data visualization, synchronously reflecting detailed information from all parts of the borehole.

[0069] According to another aspect of the embodiments of this application, a synchronous display device is also provided for implementing the above-described method for synchronous display of borehole wall image stitching and multi-attribute data. Figure 8 This is a schematic diagram of an optional borehole wall image stitching and multi-attribute data synchronous display device according to an embodiment of this application, as shown below. Figure 8 As shown, the device may include: The acquisition unit 802 is used to perform grayscale processing on the acquired borehole wall image unfolded image to obtain the grayscale value of each row of the borehole wall image unfolded image. The stitching unit 804 is used to crop and reduce noise of the borehole wall image unfolded image according to a preset grayscale threshold, and stitch each cropped image sequentially to form the target borehole wall unfolded image. Plotting unit 806 is used to obtain the initial dataset of wave velocity and experimental data. Python is used to read and extract the data in array form, and the plot function is used to plot the array data into a line graph. Display unit 808 is used to convert the unfolded image of the target borehole wall and the line graph of experimental data into a predetermined image format, and to synchronously display the stitched borehole wall image and experimental data image through a scrolling area component and an event binding mechanism.

[0070] It should be noted that the acquisition unit 802 in this embodiment can be used to perform the above step S102, the splicing unit 804 in this embodiment can be used to perform the above step S104, the drawing unit 806 in this embodiment can be used to perform the above step S106, and the display unit 808 in this embodiment can be used to perform the above step S108.

[0071] The above modules perform grayscale processing on the acquired borehole wall image unfolded image to obtain the grayscale value of each row of the unfolded borehole wall image; the unfolded borehole wall image is cropped and denoised according to a preset grayscale threshold, and each cropped image is stitched together in sequence to form the target borehole wall unfolded image; the initial data set of wave velocity and experimental data is obtained, and Python is used to read and extract the data in array form, and the array form data is plotted into a line graph using the plot function; the format of the target borehole wall unfolded image and the experimental data line graph are converted to a predetermined image format, and the stitched borehole wall image and experimental data image are displayed synchronously through a scrolling area component and event binding mechanism, which improves the data processing efficiency and analysis accuracy in engineering geological exploration, and provides a more reliable basis for the quality assessment and feature identification of underground rock masses.

[0072] In an exemplary embodiment, the stitching unit includes: a cropping module, configured to determine a preset grayscale threshold using a grayscale histogram of an image unfolded from a borehole wall image, determine a cropping position for the image based on the preset grayscale threshold, and crop the image; and a determining module, configured to use a specific formula for calculating the cropping position based on the preset grayscale threshold.

[0073] in, Indicates the image position in the original image. This represents the sum of the grayscale values ​​of the pixels in each row. To preset the grayscale threshold, This is the cropped image.

[0074] In one exemplary embodiment, the apparatus further includes: a noise reduction unit, configured to first perform noise reduction processing on the drawn line graph to obtain the height of the current initial experimental data line graph. Alignment cells, used to determine the final height of the aligned line graph of experimental data. The formula for calculating the final height is as follows:

[0075] in, This represents the final height of the line graph of the experimental data. This is the proportionality coefficient. The height of the line graph of the initial experimental data.

[0076] In an exemplary embodiment, the display unit includes: a conversion module for converting the format of the target borehole wall unfolded image and the experimental data line graph, and swapping the red and blue channels of the images respectively; and a generation module for converting the BGR format to the RGB format to generate the corresponding QImage format image.

[0077] In an exemplary embodiment, the display unit includes: a display module for displaying an image using a QLabel and placing the QLabel in a QScrollArea container; and an arrangement module for placing each QScrollArea area in the same interface and arranging them using a QVBoxLayout layout, wherein the width of each QScrollArea area is set to the image width.

[0078] In an exemplary embodiment, the display unit includes: a first binding module for binding scroll bar events to synchronize the scrolling effects of multiple scrolling areas and installing an event filter to listen for scrolling events; a second binding module for using a signal and slot mechanism to bind the scrolling signal of the scroll bar to the corresponding slot function; and a scrolling module for triggering other scroll bars to scroll with the same scroll displacement when any one scroll bar scrolls.

[0079] It should be noted that the examples and scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in the above embodiments. It should be noted that the above modules, as part of the device, can run in a hardware environment and can be implemented by software or hardware. The hardware environment includes a network environment.

[0080] According to another aspect of the embodiments of this application, a storage medium is also provided. Optionally, in this embodiment, the storage medium can be used to execute the program code of any of the above-described methods for stitching borehole wall images and synchronously displaying multi-attribute data in the embodiments of this application.

[0081] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: S1, perform grayscale processing on the acquired borehole wall image unfolded image to obtain the grayscale value of each row of the borehole wall image unfolded image; S2, the borehole wall image is cropped and denoised according to the preset grayscale threshold, and each cropped image is stitched together in order to form the target borehole wall image. S3: Obtain the initial dataset of wave velocity and experimental data, use Python to read and extract the data in array form, and use the plot function to draw a line graph of the array data. S4 converts the target borehole wall unfolded image and experimental data line graph into a predetermined image format, and synchronously displays the stitched borehole wall image and experimental data image through a scrolling area component and event binding mechanism.

[0082] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments, and will not be repeated in this embodiment.

[0083] The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0084] According to another aspect of the embodiments of this application, an electronic device is also provided for implementing the above-described method for stitching borehole wall images and synchronously displaying multi-attribute data. The electronic device may be a server, a terminal, or a combination thereof.

[0085] Figure 9 This is a schematic diagram of the structure of an optional electronic device according to an embodiment of this application, such as... Figure 9 As shown, it includes a processor 902, a communication interface 904, a memory 906, and a communication bus 908. The processor 902, communication interface 904, and memory 906 communicate with each other via the communication bus 908. Memory 906 is used to store computer programs; When processor 902 executes a computer program stored in memory 906, it performs the following steps: S1, perform grayscale processing on the acquired borehole wall image unfolded image to obtain the grayscale value of each row of the borehole wall image unfolded image; S2, the borehole wall image is cropped and denoised according to the preset grayscale threshold, and each cropped image is stitched together in order to form the target borehole wall image. S3: Obtain the initial dataset of wave velocity and experimental data, use Python to read and extract the data in array form, and use the plot function to draw a line graph of the array data. S4 converts the target borehole wall unfolded image and experimental data line graph into a predetermined image format, and synchronously displays the stitched borehole wall image and experimental data image through a scrolling area component and event binding mechanism.

[0086] Optionally, the communication bus can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. This communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 9 The symbol is represented by a single thick line, but this does not indicate that there is only one bus or one type of bus. The communication interface is used for communication between the aforementioned electronic device and other devices.

[0087] The memory may include RAM, or non-volatile memory, such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0088] As an example, the memory 906 described above may include, but is not limited to, the acquisition unit 802, the stitching unit 804, the drawing unit 806, and the display unit 808 from the borehole wall image stitching and multi-attribute data synchronous display device described above. Furthermore, it may include, but is not limited to, other module units from the borehole wall image stitching and multi-attribute data synchronous display device described above, which will not be elaborated upon in this example.

[0089] The processors mentioned above can be general-purpose processors, including but not limited to: CPU (Central Processing Unit), NP (Network Processor), etc.; they can also be DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0090] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments, and will not be repeated here.

[0091] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0092] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0093] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0094] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0095] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0096] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0097] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0098] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of embodiments of this disclosure upon considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

[0099] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0100] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for stitching together borehole wall images and synchronously displaying multi-attribute data, characterized in that, include: The acquired borehole wall image is unfolded and then converted to grayscale to obtain the grayscale value of each row of the unfolded borehole wall image. The borehole wall image is cropped and denoised according to a preset grayscale threshold. The cropped images are then stitched together in sequence to form the target borehole wall image. The initial dataset of wave velocity and experimental data was obtained, and Python was used to read and extract the data into array form. The plot function was then used to draw a line graph of the array data. The target borehole wall unfolded image and experimental data line graph are converted into a predetermined image format, and the stitched borehole wall image and experimental data image are displayed synchronously through a scrolling area component and an event binding mechanism.

2. The method for stitching borehole wall images and synchronously displaying multi-attribute data as described in claim 1, characterized in that, The step of cropping and denoising the expanded image of the borehole wall based on a preset grayscale threshold, and then stitching together each cropped image in sequence to form the target expanded image of the borehole wall includes: A preset grayscale threshold is determined by unfolding the grayscale histogram of the borehole wall image, and the cropping position of the image is determined based on the preset grayscale threshold, and the image is cropped. The specific formula for calculating the cropping position of the image based on a preset grayscale threshold is as follows: in, Indicates the image position in the original image. This represents the sum of the grayscale values ​​of the pixels in each row. To preset the grayscale threshold, This is the cropped image.

3. The method for stitching borehole wall images and synchronously displaying multi-attribute data as described in claim 1, characterized in that, After plotting the array-based data into a line chart using the plot function, the method further includes: The plotted line chart is first subjected to noise reduction processing to obtain the height of the line chart of the current initial experimental data. ; The final height of the aligned experimental data line chart is The final height calculation formula is as follows: in, This represents the final height of the line graph of the experimental data. This is the proportionality coefficient. The height of the line graph of the initial experimental data.

4. The method for stitching borehole wall images and synchronously displaying multi-attribute data as described in claim 1, characterized in that, The process of converting the unfolded image of the target borehole wall and the line graph of experimental data into a predetermined image format includes: The format of the unfolded image of the target borehole wall and the line graph of experimental data were converted, and the red and blue channels of the images were swapped respectively. Convert the BGR format to RGB format to generate the corresponding QImage format image.

5. The method for stitching borehole wall images and synchronously displaying multi-attribute data as described in claim 1, characterized in that, The synchronous display of the stitched hole wall image and experimental data image through a scrolling area component and an event binding mechanism includes: Use QLabel to display the image, and place the QLabel inside a QScrollArea container; Place each QScrollArea area in the same interface and arrange them using QVBoxLayout. Set the width of each QScrollArea area to the width of the image.

6. The method for stitching borehole wall images and synchronously displaying multi-attribute data as described in claim 1, characterized in that, The synchronous display of the stitched hole wall image and experimental data image through a scrolling area component and an event binding mechanism includes: Bind scrollbar events to synchronize the scrolling effects of multiple scroll areas, and install event filters to listen for scroll events; By using the signal and slot mechanism, the scroll signal of the scroll bar is bound to the corresponding slot function; When any one scroll bar is scrolled, it triggers the other scroll bars to scroll as well, with the same scroll displacement.

7. A device for stitching together borehole wall images and synchronously displaying multi-attribute data, characterized in that, include: The acquisition unit is used to perform grayscale processing on the acquired borehole wall image unfolded image to obtain the grayscale value of each row of the borehole wall image unfolded image. The stitching unit is used to crop and reduce noise of the borehole wall image unfolded according to a preset grayscale threshold, and stitch each cropped image sequentially to form the target borehole wall unfolded image. The plotting unit is used to obtain the initial dataset of wave velocity and experimental data. Python is used to read and extract the data in array form, and the plot function is used to plot the array data into a line graph. The display unit is used to convert the unfolded image of the target borehole wall and the line graph of experimental data into a predetermined image format, and synchronously display the stitched borehole wall image and experimental data image through a scrolling area component and an event binding mechanism.

8. The borehole wall image stitching and multi-attribute data synchronous display device as described in claim 7, characterized in that, The splicing unit includes: The cropping module is used to determine a preset grayscale threshold by unfolding the grayscale histogram of the borehole wall image, determine the cropping position of the image based on the preset grayscale threshold, and crop the image. The determination module, specifically the formula for calculating the cropping position of the image based on a preset grayscale threshold, is as follows: in, Indicates the image position in the original image. This represents the sum of the grayscale values ​​of the pixels in each row. To preset the grayscale threshold, This is the cropped image.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method of any one of claims 1 to 6.

10. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method of any one of claims 1 to 6 through the computer program.

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