CN114494633B - Filling and digging data processing method and device, computer equipment and storage medium - Google Patents
Filling and digging data processing method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The present disclosure provides a fill-cut data processing method, apparatus, computer device and storage medium, the method comprising: capturing image data of the filling and excavating body, acquiring feature point information in the image data, processing the image data according to the feature point information to obtain image data to be marked, generating a ground surface model according to the image data to be marked, and optimizing a preset geological model according to the ground surface model to obtain a target geological model. Through the method and the device, the adaptability and the reasonability of the obtained target geological model to the excavated filling body can be effectively improved while the automation degree of the target geological model establishing process can be greatly improved, so that the objectivity and the accuracy of the characteristic data of the excavated filling body obtained based on the target geological model can be effectively improved.
Description
Technical Field
The disclosure relates to the technical field of coal mining, in particular to a filling and digging data processing method and device, computer equipment and a storage medium.
Background
The processing of cut fill (e.g., strip mine, earthwork) data involves a number of application scenarios, such as strip mine mining, land development consolidation, engineering construction, and so forth. The accuracy of the processing results of the fill volume data can have a direct impact on the cost accuracy and objectivity of the project.
The related art measurement method collects single-point data, and the processing method of the filling and excavating body data comprises a square grid method, a triangular grid method, a section method and the like.
Under the modes, the measuring and calculating efficiency and the measuring and calculating accuracy of the large-volume filling and excavating body with complex terrain are low, and the terrain and the landform of the filling and excavating body cannot be accurately reflected.
Disclosure of Invention
The present disclosure is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, the purpose of the present disclosure is to provide a filling and digging data processing method, device, computer equipment and storage medium, so that the degree of automation of the target geological model creation process can be greatly improved, and meanwhile, the adaptability and rationality of the obtained target geological model for the filling body can be effectively improved, thereby effectively improving the objectivity and accuracy of the filling body characteristic data obtained based on the target geological model.
The filling and digging data processing method provided by the embodiment of the first aspect of the disclosure comprises the following steps: capturing image data of the infill; acquiring feature point information in image data; processing the image data according to the characteristic point information to obtain image data to be marked; generating a ground surface model according to the image data to be marked, wherein the ground surface model comprises: geological classification information associated with the infill; and optimizing the preset geological model according to the earth surface model to obtain a target geological model, wherein the target geological model is used for determining the characteristic data of the filling and digging body.
According to the filling and digging data processing method provided by the embodiment of the first aspect of the disclosure, the image data of the filling and digging body is captured, the feature point information in the image data is obtained, the image data is processed according to the feature point information, the image data to be marked is obtained, the earth surface model is generated according to the image data to be marked, the preset geological model is optimized according to the earth surface model, and the target geological model is obtained, wherein the target geological model is used for determining the feature data of the filling and digging body, so that the automation degree of the creation process of the target geological model can be greatly improved, the adaptability and the rationality of the obtained target geological model for the filling and digging body are effectively improved, and the objectivity and the accuracy of the feature data of the filling and digging body obtained based on the target geological model are effectively improved.
The filling and digging data processing device provided by the embodiment of the second aspect of the disclosure comprises: the capture module is used for capturing image data of the filling and digging body; the first acquisition module is used for acquiring feature point information in the image data; the first processing module is used for processing the image data according to the characteristic point information to obtain image data to be marked; the generation module is used for generating a ground surface model according to the image data to be marked, wherein the ground surface model comprises: geological classification information associated with the infill; and the second processing module is used for optimizing the preset geological model according to the earth surface model to obtain a target geological model, wherein the target geological model is used for determining the characteristic data of the filling and digging body.
The filling and digging data processing device provided by the embodiment of the second aspect of the disclosure acquires feature point information in image data by capturing image data of a filling and digging body, processes the image data according to the feature point information to obtain image data to be marked, generates a ground surface model according to the image data to be marked, and optimizes a preset geological model according to the ground surface model to obtain a target geological model.
An embodiment of a third aspect of the present disclosure provides a computer device, including: the system comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the filling and digging data processing method as set forth in the embodiment of the first aspect of the disclosure.
A fourth aspect of the present disclosure provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the fill-and-dig data processing method as set forth in the first aspect of the present disclosure.
An embodiment of a fifth aspect of the present disclosure provides a computer program product, which when executed by an instruction processor in the computer program product, performs the method for processing fill-and-dig data as set forth in the embodiment of the first aspect of the present disclosure.
Additional aspects and advantages of the disclosure will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the disclosure.
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The foregoing and/or additional aspects and advantages of the present disclosure will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic flowchart of a fill-and-dig data processing method according to an embodiment of the disclosure;
fig. 2 is a schematic flowchart of a fill-and-dig data processing method according to another embodiment of the disclosure;
fig. 3 is a schematic flowchart of a fill-and-dig data processing method according to another embodiment of the disclosure;
FIG. 4 is a schematic flow chart of computing feature data according to an embodiment of the present disclosure;
FIG. 5 is a schematic illustration of determining a surface feature classification boundary in an aerial photographic image in accordance with an embodiment of the present disclosure;
FIG. 6 is a schematic diagram illustrating the determination of a feature classification boundary in a ground rephotograph image according to an embodiment of the disclosure;
fig. 7 is a schematic structural diagram of a fill-and-dig data processing apparatus according to an embodiment of the disclosure;
fig. 8 is a schematic structural diagram of a cut-and-fill data processing apparatus according to another embodiment of the present disclosure;
FIG. 9 illustrates a block diagram of an exemplary computer device suitable for use to implement embodiments of the present disclosure.
Detailed Description
Reference will now be made in detail to the embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of illustrating the present disclosure and should not be construed as limiting the same. On the contrary, the embodiments of the disclosure include all changes, modifications and equivalents coming within the spirit and terms of the claims appended hereto.
Fig. 1 is a schematic flow chart of a fill-and-dig data processing method according to an embodiment of the disclosure.
It should be noted that the execution main body of the filling and digging data processing method of the embodiment is a filling and digging data processing device, the device may be implemented by software and/or hardware, the device may be configured in a computer device, and the computer device may include, but is not limited to, a terminal, a server, and the like.
As shown in fig. 1, the fill-and-dig data processing method includes:
s101: image data of the infill is captured.
The filling body is the volume of earth and stones filled from the original ground to the surface part of the roadbed when the surface of the roadbed is higher than the original ground; the digging body is used for digging part of soil and stone from the original ground to the surface of the roadbed when the surface of the roadbed is lower than the original ground; the term "infill and excavation" may be used to refer broadly to a construction area having infill and/or excavation, such as an open pit coal mine, a road and bridge work, and is not limited thereto.
In the embodiment of the present disclosure, the image data of the cut and fill object may be captured in a manner of aerial photography by an unmanned aerial vehicle or ground supplementary photography, which is not limited to this.
In the embodiment of the disclosure, by capturing the image data of the filling body, reliable data support can be provided for the subsequent process of creating the earth surface model, and the adaptability and the reasonability of the obtained target geological model to the filling body can be effectively improved.
S102: feature point information in the image data is acquired.
The feature point may refer to a control point and/or any other point having a certain feature in the image data, which is not limited herein. The feature point information may be used to describe relevant information of the feature points obtained from the image, such as relative positions between the feature points, latitude and longitude information, and the like, which is not limited in this respect.
In the embodiment of the present disclosure, the feature point information in the image data may be obtained by inputting the image data into a pre-trained feature point information detection model to obtain the feature point information in the image data, and transmitting the obtained feature point information to the execution main body of the embodiment of the present disclosure, or a third-party feature point information detection device may obtain the feature point information in the image data from the image data and transmit the feature point information to the execution main body of the embodiment of the present disclosure, which is not limited herein.
That is to say, in the embodiment of the present disclosure, after the image data of the filling body is captured, the feature point information in the image data may be acquired, so as to screen the related information in the image data, remove redundant information that does not help much in the process of creating the earth surface model, and greatly improve the effectiveness of the obtained feature point information.
S103: and processing the image data according to the characteristic point information to obtain image data to be marked.
The image data to be marked refers to image data processed by the feature point information, and the data to be marked can be used for generating a ground surface model subsequently.
In the embodiment of the present disclosure, the processing of the image data according to the feature point information may be to identify and remove a non-terrestrial body in the image data according to the feature point information, or may also be any other possible optimization processing process, which is not limited to this.
S104: generating a ground surface model according to the image data to be marked, wherein the ground surface model comprises: geological classification information associated with the infill.
The surface model refers to a model of the surface of the filling body obtained according to the image data to be marked, and the surface model may include structure information, geological classification information, and the like of the surface of the filling body, which is not limited herein.
The geological classification information refers to the type of geology (such as soil texture, rock, etc.) in the filling body, and the corresponding quantity and distribution range, and other related information. The geological classification information related to the cut filler may be information that can be used to determine earth and stone feature data in the cut filler among the geological classification information.
It can be understood that a filling body may include a plurality of soil types and/or rock types, and different soil types and/or rock types may cause differences in the calculation process of the feature data of the filling body due to different characteristics, so that the embodiment of the disclosure, by generating the surface model with the geological classification information, facilitates the subsequent calculation process of the feature data of the corresponding filling body according to the geological classification information, thereby effectively improving the accuracy of the obtained feature data of the filling body.
In the embodiment of the present disclosure, a surface model is generated according to image data to be marked, the image data to be marked may be input into a pre-trained surface model generator to obtain the surface model, and the obtained surface model is transmitted to an execution subject of the embodiment of the present disclosure, or an engineering method may be adopted to generate a surface model according to the image data to be marked, which is not limited to this.
S105: and optimizing the preset geological model according to the earth surface model to obtain a target geological model, wherein the target geological model is used for determining the characteristic data of the filling and digging body.
The preset geological model is obtained by modeling drilling points, fault lines, known probe points, geophysical prospecting data and time dimension data related to the filling body, or a communication link between an execution main body and a big data processing server in the embodiment of the disclosure may be established in advance, and the preset geological model is requested from the big data processing server, which is not limited to this.
The target geological model is a geological model obtained by optimizing a preset geological model through an earth surface model, and can be used for determining characteristic data of the filling and excavating body.
The feature data of the filling-digging body may refer to geological classification information of the filling-digging body, filling-digging amount and position information corresponding to each classification, and the like, and is not limited thereto.
In the embodiment of the present disclosure, the preset geological model is optimized according to the earth surface model to obtain the target geological model, and the preset geological model may obtain relevant data required in the modeling process from the earth surface model to perform modeling to obtain the target geological model, or may perform optimization on the preset geological model according to the earth surface model by any other possible manner to obtain the target geological model, which is not limited to this.
In the embodiment, the image data of the filling and excavating body is captured, the characteristic point information in the image data is obtained, the image data is processed according to the characteristic point information to obtain the image data to be marked, the earth surface model is generated according to the image data to be marked, and the preset geological model is optimized according to the earth surface model to obtain the target geological model.
Fig. 2 is a schematic flow chart of a fill-and-dig data processing method according to another embodiment of the disclosure.
As shown in fig. 2, the fill-and-dig data processing method includes:
s201: a plurality of control points are deployed in the infill.
In the embodiment of the present disclosure, the number of the control points may be one or more, and the control points may be one or a combination of one or more of triangular points, guide lines, level points, astronomical points, and the like, which is not limited herein.
Therefore, when a plurality of control points are deployed in the filling and digging body, effective reference basis can be provided for subsequent acquisition of feature point information, and meanwhile, the working efficiency of the feature point information acquisition process can be effectively improved.
S202: image data of the infill is captured.
For the description of S202, reference may be made to the foregoing embodiments, and details are not repeated herein.
S203: and extracting the reference point characteristics and the characteristics of each control point in the image data based on an aerial triangulation method and a difference calculation method, and taking the reference point characteristics and the characteristics of each control point as characteristic point information.
The aerial triangulation method is a measuring method for encrypting control points indoors according to a small number of field control points in stereo photogrammetry to obtain the elevation and the plane position of the encrypted points. In the embodiment of the present disclosure, the aerial triangulation method may refer to a simulated aerial triangulation method, an analytic aerial triangulation method, and the like, which is not limited herein.
The adjustment, i.e. the measurement adjustment, refers to a theory and a calculation method for processing various observed results by using the principle of least square method, and can be used for eliminating the contradiction between the observed values so as to obtain a result with higher reliability and evaluate the accuracy of the measurement result. It can be understood that in any measurement process, if redundant observation exists, the problem of adjustment occurs with a high probability, and the reliability of the obtained feature point information can be effectively improved by adopting an adjustment calculation method in the embodiment of the disclosure.
The reference point may be a point in the image that has a larger color difference from the surrounding area, for example, a boundary line between two objects or a point in the same object that is different from other parts, which is not limited herein. The reference point characteristics may be used to describe the number, position, and other characteristics of the reference point, which is not limited herein.
In the embodiment of the present disclosure, the characteristic of the control point may refer to a spatial position of the control point in the excavation body, longitude and latitude data of the control point, and the like, which is not limited herein.
That is to say, the embodiment of the present disclosure may deploy a plurality of control points in the filling and excavating body in advance, after capturing the image data of the filling and excavating body, extract the reference point features and the features of each control point in the image data based on an aerial triangulation method and a adjustment calculation method, and use the reference point features and the features of each control point as the feature point information, thereby, when deploying a plurality of control points in the filling and excavating body, providing an effective reference basis for obtaining the feature point information, and simultaneously, effectively improving the work efficiency of the feature point information obtaining process, and then extract the reference point features and the features of each control point in the image data based on the aerial triangulation method and the adjustment calculation method, and use the reference point features and the features of each control point as the feature point information, and effectively improving the accuracy and reliability of the obtained feature point information.
S204: and processing the image data according to the characteristic point information to obtain image data to be marked.
For the description of S204, reference may be made to the foregoing embodiments specifically, and details are not repeated here.
S205: and acquiring multispectral image data of the filling and digging body.
The multispectral image is an image including many bands, and may be three bands (for example, a color image) or more than three bands, which is not limited thereto. Each band is a gray scale image that represents the brightness of the scene based on the sensitivity of the sensor used to create the band.
In the embodiment of the present disclosure, the acquiring of the multispectral image data of the filling and digging body may be acquiring the multispectral image data of the filling and digging body when capturing the image data of the filling and digging body, or may be acquiring the multispectral image data of the filling and digging body by using a photographing device at any other time point, which is not limited to this.
S206: and re-marking the feature classification range and the feature classification characteristics in the image data to be marked according to the multispectral image data to obtain target image data.
The surface feature classification refers to a method for classifying pixels in a similar brightness range of a remote sensing image by using a statistical method through a computer, and can also be called computer automatic identification. The feature classification range may refer to a region in the image data to be marked, where feature classification is required. The feature classification features may refer to spectral features, spatial features, temporal features, and the like, and are expressed in the form of gray level changes on the image, different features of the features are different, and the appearance forms on the image are also different, so that different categories can be distinguished according to the changes and differences on the image.
The target image data refers to image data obtained after the image data to be marked is processed again through multispectral image data.
It can be understood that in the multispectral image data, the gray level expression forms of different types of surface features may have differences, and therefore, the surface feature classification range and the surface feature classification features in the image data to be labeled are labeled again according to the multispectral image data, so that the obtained target image data can effectively represent geological classification information related to the filling body.
S207: and generating a ground surface model according to the target image data.
In the embodiment of the disclosure, when the earth surface model is generated based on the target image data, the obtained earth surface model can accurately represent the geological classification information in the image data to be marked because the target image data can effectively represent the geological classification information related to the filling and excavating body.
That is to say, after the image data to be marked is obtained, the multispectral image data of the filling and excavating body can be obtained, the ground feature classification range and the ground feature classification characteristics in the image data to be marked are marked again according to the multispectral image data to obtain target image data, and then the ground surface model is generated according to the target image data.
S208: determining a reference surface model to which a preset geological model relates, wherein the reference surface model comprises: and obtaining reference geological classification information related to the filling and digging body based on the preset geological model.
The reference earth model is an earth model obtained in advance based on the preset geological model and the related information of the filling body.
The reference geological classification information refers to geological classification information related to the cut filler included in the reference surface model.
Optionally, in some embodiments, the preset geological model is a four-dimensional + multi-parameter geological model, and thus, the preset geological model can flexibly configure a plurality of data sources according to an application scenario, and the applicability of the preset geological model can be effectively improved.
Of course, in some embodiments, the preset geological model may also be any other geological model that may be applicable to the embodiments of the present disclosure, and is not limited thereto.
S209: and optimizing the reference earth surface model according to the earth surface model to obtain a target geological model.
It can be understood that the earth surface model and the reference earth surface model have relevance, the two models are obtained by the filling body at different stages, and when the reference earth surface model is optimized according to the earth surface model, the target earth surface model can effectively combine geological classification information and reference geological classification information corresponding to the two stages, and the influence of errors possibly existing in the earth surface model on the target earth surface model can be effectively reduced.
That is to say, after the earth surface model is obtained, the reference earth surface model related to the preset geological model can be determined, and then the reference earth surface model is optimized according to the earth surface model to obtain the target geological model, so that when the reference earth surface model is combined with the earth surface model to optimize the reference earth surface model to obtain the target geological model, the target geological model can effectively combine the geological classification information and the reference geological classification information corresponding to the two stages, and the influence of errors possibly existing in the earth surface model on the target geological model can be effectively reduced.
In the embodiment, when a plurality of control points are deployed in the cut filler, effective reference basis can be provided for obtaining characteristic point information, the working efficiency of the characteristic point information obtaining process can be effectively improved, then the reference point characteristics and the characteristics of each control point in image data are extracted based on an aerial triangulation method and a difference calculation method, the reference point characteristics and the characteristics of each control point are used as characteristic point information, the accuracy and the reliability of the obtained characteristic point information can be effectively improved, after the image data to be marked are obtained, the multispectral image data of the cut filler is obtained, the ground feature classification range and the ground feature classification characteristics in the image data to be marked are marked again according to the multispectral image data to obtain target image data, then a ground surface model is generated according to the target image data, and therefore, the obtained ground surface model can accurately represent the geological classification information in the image data to be marked, the method can be adapted to different application scenes, the clarity and the flexibility of geological classification information carried in the earth surface model can be effectively improved, the reference earth surface model is optimized by combining the earth surface model based on the reference earth surface model to obtain the target geological model, the geological classification information and the reference geological classification information corresponding to two stages can be effectively combined with the target geological model, the influence of errors possibly existing in the earth surface model on the target geological model can be effectively reduced, when the four-dimensional + multi-parameter geological model is taken as the preset geological model, the preset geological model can flexibly configure a plurality of data sources according to the application scenes, and the applicability of the preset geological model can be effectively improved.
Fig. 3 is a flowchart illustrating a cut-and-fill data processing method according to another embodiment of the disclosure.
As shown in fig. 3, the fill-and-dig data processing method includes:
s301: image data of the infill is captured.
S302: feature point information in the image data is acquired.
S303: and processing the image data according to the characteristic point information to obtain image data to be marked.
S304: and acquiring multispectral image data of the filling and digging body.
S305: and re-marking the ground feature classification range and the ground feature classification characteristics in the image data to be marked according to the multispectral image data to obtain target image data.
For the description of S301 to S305, reference may be made to the above embodiments, which are not described herein again.
S306: and acquiring geological classification information according to the target image data.
It can be understood that the target image data is obtained by re-labeling the ground feature classification range and the ground feature classification features in the image data to be labeled according to the multispectral image data, and therefore in the embodiment of the disclosure, geological classification information (for example, distribution conditions of various geological categories in the target image data) can be obtained according to the target image data, so as to facilitate subsequent determination of rock classification boundary lines.
S307: and according to the geological classification information, performing surface texture filling on the initial surface model to determine a rock classification boundary line.
The initial surface model may be a surface model of the filling-up body obtained through the image data to be marked.
The surface texture refers to texture features expressed by different geological types in the initial surface model.
In some embodiments, the rock classification boundary line may refer to a boundary line between adjacent different rock types, or may also refer to a boundary line between adjacent rock types and soil properties, which is not limited herein.
Therefore, the rock classification boundary line can accurately represent the distribution conditions of different geologies in the filling body.
S308: and generating geological classification information related to the filling and digging body according to the geological classification information and the rock classification boundary line.
In the embodiment of the disclosure, after the rock classification boundary line is determined, the geological classification information related to the filling and digging body is generated according to the geological classification information (such as the volumes and densities corresponding to a plurality of geological categories) and the rock classification boundary line, so that the practicability of the obtained geological classification information related to the filling and digging body can be effectively improved.
S309: and marking the initial earth surface model by adopting geological classification information related to the filling and digging body to obtain the earth surface model.
In the embodiment of the disclosure, after the geological classification information related to the filling-up body is obtained, the geological classification information related to the filling-up body is adopted to mark the initial earth surface model, so that the obtained earth surface model can effectively represent the geological classification information related to the filling-up body, and a reliable basis is provided for subsequently determining the target geological model.
That is to say, after the target image data is obtained, according to the target image data, the geological classification information may be obtained, according to the geological classification information, the surface texture filling may be performed on the initial surface model to determine the rock classification boundary line, according to the geological classification information and the rock classification boundary line, the geological classification information related to the filling-and-digging body may be generated, and the geological classification information related to the filling-and-digging body may be adopted to perform the labeling processing on the initial surface model to obtain the surface model.
S310: determining a reference surface model to which a preset geological model relates, wherein the reference surface model comprises: and obtaining reference geological classification information related to the filling and digging body based on the preset geological model.
For the description of S310, reference may be made to the foregoing embodiments, which are not described herein again.
S311: and performing Boolean operation on the reference geological classification information and the geological classification information to form a sub geological body model and an overall model of sub rock types.
The boolean operations refer to a logic derivation method of digital symbolization, including union, intersection, subtraction, and the like. Boolean operation is introduced in the graphic processing operation, so that a simple basic graphic combination can generate a new form, and the Boolean operation is developed from two-dimensional Boolean operation to three-dimensional graphic Boolean operation.
The sub-geological body model refers to a plurality of corresponding geological models established according to a plurality of rock types of the filling and digging body. The overall model can be a geological model which is formed by combining all the sub geological body models and can characterize the overall characteristics of the filling body.
It can be understood that there may be differences in the calculation process of the earth and stone square characteristic data corresponding to different rock types, and the embodiment of the present disclosure may facilitate the subsequent calculation process of the earth and stone square characteristic data of various rock types according to the characteristics of different rock types in combination with the corresponding sub-geologic body models by forming the sub-geologic body models and the overall model of the sub-rock types.
S312: and taking the sub geological body model and the overall model of the sub rock types as target geological models.
In the embodiment of the disclosure, after the sub-geological body model and the overall model of the sub-rock type are obtained, the sub-geological body model and the overall model of the sub-rock type are used as the target geological model, so that the target geological model can be suitable for the personalized earth and rock square characteristic data calculation process, and the practicability of the target geological model is effectively improved.
That is to say, after the reference earth surface model related to the preset geological model is determined, boolean operations can be performed on the reference geological classification information and the geological classification information to form sub-geological body models and overall models of sub-rock types, and the sub-geological body models and the overall models of the sub-rock types are used as target geological models.
S313: and determining characteristic data of the earthwork related to the filling and digging body according to the target geological model and the geological classification information.
The characteristic data may refer to the volume of earth and rock corresponding to each rock type in the filling and excavating body.
That is to say, after the target geological model is obtained, the feature data of the earthwork related to the filling and excavating body can be determined according to the target geological model and the geological classification information, so that the accuracy of the obtained feature data can be ensured, and the intelligence degree of the feature data calculation process can be effectively improved.
For example, fig. 4 is a schematic flow chart of calculating feature data according to an embodiment of the disclosure, as shown in fig. 4, after a close-range photogrammetry project is created for a filling body, a plurality of control points may be deployed in the filling body according to an application scene, after the filling body is subjected to unmanned aerial vehicle aerial photography or ground supplementary photography, the acquired image data is uploaded to the close-range photogrammetry project and is archived, a serial number configured by an European Petroleum Surveying Group (EPSG) corresponding to a coordinate System used for a project modeling result is automatically determined according to Global Positioning System (GPS) tag data carried by a photo, so as to obtain a close-range oblique image with a GPS tag, and the close-range oblique image may be processed by using a pre-configured serial number, including but not limited to feature point extraction, control point extraction, and the like, The method comprises the steps of aerial triangulation, control point identification, adjustment calculation and the like, and is based on a multi-modal image (visible light + multi-spectrum) semantic segmentation and geometric reconstruction technology of an artificial intelligence technology, so that artificial classification and/or intelligent automatic classification are realized, land object boundaries are determined, so that land irrelevant objects such as construction site shrubs, engineering equipment, personnel and the like are removed according to the land object classification result, a land triangle network model is generated, then the land object classification range and characteristics are marked again by combining the multi-spectral image, land surface textures are filled (manually filled or intelligently and automatically filled) to determine rock classification boundary lines, a land surface model A (the land surface model obtained in the last stage can be a land surface model B) with classification information is generated, the land surface model and the classification information are led into a four-dimensional + multi-parameter geological model, and the classification information can be reversely acted on the four-dimensional + multi-parameter geological model, it is corrected. In the four-dimensional + multi-parameter geological model, the current earth surface model A and the last earth surface model B can be subjected to Boolean operation to form a sub-geological body model and an overall model of sub-rock types, and corresponding earth and rock volume calculation is carried out.
For example, fig. 5 is a schematic diagram illustrating determination of a ground feature classification boundary in an aerial image according to an embodiment of the present disclosure, and as shown in fig. 5, the embodiment of the present disclosure may determine non-terrain objects such as multiple houses in the aerial image based on a multi-modal image (visible light + multi-spectrum) semantic segmentation and geometric reconstruction technology of an artificial intelligence technology, and label the non-terrain objects according to outlines of the non-terrain objects, so as to determine a boundary between the multiple houses and the ground in the aerial image.
Of course, in some embodiments, as shown in fig. 6, fig. 6 is a schematic diagram illustrating the determination of the classification boundary of the ground feature in the ground rephotograph image according to the embodiments of the present disclosure, and non-terrestrial bodies such as motorcycles may also be determined in the ground rephotograph image and marked, so as to facilitate the subsequent operations related to removing the non-terrestrial bodies.
In the embodiment, after target image data is obtained, geological classification information is obtained according to the target image data, surface texture filling is carried out on an initial surface model according to the geological classification information to determine rock classification boundary lines, geological classification information related to filling bodies is generated according to the geological classification information and the rock classification boundary lines, the initial surface model is marked by the geological classification information related to the filling bodies to obtain a surface model, the obtained surface model can effectively represent the geological classification information related to the filling bodies, reliable basis is provided for subsequently determining the target geological model, logic rigor of the filling and digging data processing process is effectively improved, Boolean operation is carried out on the reference geological classification information and the geological classification information after a reference surface model related to a preset geological model is determined, the method comprises the steps of forming a sub-geological body model and an overall model of a sub-rock type, taking the sub-geological body model and the overall model of the sub-rock type as target geological models, effectively improving the practicability of the obtained target geological models, enabling a user to select different sub-geological body models according to the rock types to perform corresponding filling and digging data processing, effectively improving the accuracy of processing results of the filling and digging data, determining feature data of earthwork related to a filling and digging body according to the target geological models and geological classification information after the target geological models are obtained, and effectively improving the intelligence degree of the feature data calculation process while ensuring the accuracy of the obtained feature data.
Fig. 7 is a schematic structural diagram of a fill-and-dig data processing apparatus according to an embodiment of the disclosure.
As shown, the cut and fill data processing apparatus 70 includes:
a capturing module 701, configured to capture image data of a filling body;
a first obtaining module 702, configured to obtain feature point information in image data;
the first processing module 703 is configured to process the image data according to the feature point information to obtain image data to be marked;
a generating module 704, configured to generate a surface model according to the image data to be marked, where the surface model includes: geological classification information associated with the infill;
the second processing module 705 is configured to perform optimization processing on the preset geological model according to the earth surface model to obtain a target geological model, where the target geological model is used to determine feature data of the filling and excavating body.
In some embodiments of the present disclosure, as shown in fig. 8, fig. 8 is a schematic structural diagram of a fill-and-dig data processing apparatus according to another embodiment of the present disclosure, where the fill-and-dig data processing apparatus 70 further includes:
a second obtaining module 706, configured to obtain multispectral image data of the cut-and-fill object;
the third processing module 707 is configured to re-label the feature classification range and the feature classification characteristic in the image data to be labeled according to the multispectral image data to obtain target image data;
the generating module 704 is specifically configured to:
and generating a ground surface model according to the target image data.
In some embodiments of the present disclosure, the cut-and-fill data processing apparatus 70 further includes:
a fourth processing module 708 for deploying a plurality of control points in the excavation;
the first obtaining module 702 is specifically configured to:
and extracting the reference point characteristics and the characteristics of each control point in the image data based on an aerial triangulation method and a difference calculation method, and taking the reference point characteristics and the characteristics of each control point as characteristic point information.
In some embodiments of the present disclosure, the method includes the steps of presetting a geological model, which is obtained by modeling a drilling point, a fault line, a known probe point, geophysical data and time dimension data related to a filling body;
the second processing module 705 includes:
a determining sub-module 7051, configured to determine a reference surface model related to the preset geological model, where the reference surface model includes: obtaining reference geological classification information related to the cut-in body based on a preset geological model;
and the processing submodule 7052 is configured to perform optimization processing on the reference surface model according to the surface model to obtain the target geological model.
In some embodiments of the present disclosure, processing submodule 7052 is specifically configured to:
performing Boolean operation on the reference geological classification information and the geological classification information to form a sub geological body model and an overall model of sub rock types;
and taking the sub geological body model and the overall model of the sub rock types as target geological models.
In some embodiments of the present disclosure, the generating module 704 is further configured to:
acquiring geological classification information according to target image data;
according to the geological classification information, performing surface texture filling on the initial surface model to determine a rock classification boundary line;
generating geological classification information related to the filling-up body according to the geological classification information and the rock classification boundary line;
and marking the initial earth surface model by adopting geological classification information related to the filling and digging body to obtain the earth surface model.
In some embodiments of the present disclosure, the fill and dig data processing apparatus 70 further includes:
the determining module 709 is configured to determine feature data of an earth and rock cube related to the filling and excavating body according to the target geological model and the geological classification information.
In some embodiments of the disclosure, it is characterized in that the preset geological model is a four-dimensional + multi-parameter geological model.
It should be noted that the explanation of the filling and digging data processing method is also applicable to the filling and digging data processing device of the present embodiment, and is not repeated herein.
In the embodiment, the image data of the filling and digging body is captured, the feature point information in the image data is obtained, the image data is processed according to the feature point information to obtain the image data to be marked, the earth surface model is generated according to the image data to be marked, the preset geological model is optimized according to the earth surface model to obtain the target geological model, therefore, the degree of automation of the process of creating the target geological model can be greatly improved, meanwhile, the adaptability and the reasonability of the obtained target geological model for the filling and digging body are effectively improved, and the objectivity and the accuracy of the characteristic data of the filling and digging body obtained based on the target geological model are effectively improved.
FIG. 9 illustrates a block diagram of an exemplary computer device suitable for use in implementing embodiments of the present disclosure. The computer device 12 shown in fig. 9 is only an example and should not bring any limitations to the functionality or scope of use of the embodiments of the present disclosure.
As shown in FIG. 9, computer device 12 is in the form of a general purpose computing device. The components of computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
Although not shown in FIG. 9, a disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a compact disk read Only memory (CD-ROM), a digital versatile disk read Only memory (DVD-ROM), or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the disclosure.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally perform the functions and/or methodologies of the embodiments described in this disclosure.
The processing unit 16 executes various functional applications and fill and dig data processing by running a program stored in the system memory 28, for example, implementing the fill and dig data processing method mentioned in the foregoing embodiment.
In order to achieve the above embodiments, the present disclosure also proposes a non-transitory computer readable storage medium on which a computer program is stored, which when executed by a processor, implements the fill and dig data processing method as proposed by the foregoing embodiments of the present disclosure.
In order to implement the foregoing embodiments, the present disclosure further provides a computer program product, which when executed by an instruction processor in the computer program product, executes the filling and digging data processing method as set forth in the foregoing embodiments of the present disclosure.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice in the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
It should be noted that, in the description of the present disclosure, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present disclosure, "a plurality" means two or more unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present disclosure includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present disclosure.
It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following technologies, which are well known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried out in the method of implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and the program, when executed, includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present disclosure may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a separate product, may also be stored in a computer-readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present disclosure have been shown and described above, it will be understood that the above embodiments are exemplary and not to be construed as limiting the present disclosure, and that changes, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present disclosure.
Claims (7)
1. A fill-and-dig data processing method is characterized by comprising the following steps:
capturing image data of the infill;
acquiring feature point information in the image data;
processing the image data according to the characteristic point information to obtain image data to be marked;
generating a surface model according to the image data to be marked, wherein the surface model comprises: geological classification information associated with the pack;
optimizing a preset geological model according to the earth surface model to obtain a target geological model, wherein the target geological model is used for determining characteristic data of the filling and digging body;
further comprising:
acquiring multispectral image data of the filling and digging body;
re-marking the feature classification range and the feature classification characteristics in the image data to be marked according to the multispectral image data to obtain target image data;
wherein, according to the image data to be marked, generating a surface model, comprising:
generating the earth surface model according to the target image data;
generating a surface model according to the image data to be marked, wherein the surface model comprises: geological classification information associated with the pack, comprising:
acquiring geological classification information according to the target image data;
according to the geological classification information, performing surface texture filling on the initial surface model to determine a rock classification boundary line;
generating geological classification information related to the filling-up body according to the geological classification information and the rock classification boundary line;
marking the initial earth surface model by adopting the geological classification information related to the filling and digging body to obtain the earth surface model;
the preset geological model is obtained by modeling drilling points, fault lines, known probe points, geophysical prospecting data and time dimension data which are related to the filling body;
the method for optimizing the preset geological model according to the earth surface model to obtain the target geological model comprises the following steps:
determining a reference surface model to which the preset geological model relates, wherein the reference surface model comprises: obtaining reference geological classification information related to the filling and digging body based on the preset geological model;
and optimizing the reference earth surface model according to the earth surface model to obtain the target geological model.
2. The method of claim 1, prior to said capturing image data of a infill, further comprising:
deploying a plurality of control points in the cut-fill body;
wherein the acquiring of the feature point information in the image data includes:
and extracting reference point features and features of the control points in the image data based on an aerial triangulation method and a adjustment calculation method, and taking the reference point features and the features of the control points as the feature point information.
3. The method of claim 1, wherein said optimizing said reference surface model from said surface model to obtain said target geological model comprises:
performing Boolean operation on the reference geological classification information and the geological classification information to form a sub-geological body model and a general model of sub-rock types;
and taking the sub geological body model and the overall model of the sub rock types as the target geological model.
4. The method of claim 1, further comprising:
and determining characteristic data of earthwork related to the filling and digging body according to the target geological model and the geological classification information.
5. The method of any one of claims 1-4, wherein the predetermined geological model is a four-dimensional + multi-parameter geological model.
6. A fill and dig data processing apparatus, comprising:
the capture module is used for capturing image data of the filling body;
the first acquisition module is used for acquiring feature point information in the image data;
the first processing module is used for processing the image data according to the characteristic point information to obtain image data to be marked;
a generating module, configured to generate a surface model according to the image data to be marked, where the surface model includes: geological classification information associated with the pack;
the second processing module is used for optimizing a preset geological model according to the earth surface model to obtain a target geological model, wherein the target geological model is used for determining characteristic data of the filling and digging body;
the generation module further comprises: acquiring multispectral image data of the filling and digging body;
re-marking the feature classification range and the feature classification characteristics in the image data to be marked according to the multispectral image data to obtain target image data;
wherein, according to the image data to be marked, generating a surface model, comprising:
generating the earth surface model according to the target image data;
generating a surface model according to the image data to be marked, wherein the surface model comprises: geological classification information associated with the pack, comprising:
acquiring geological classification information according to the target image data;
according to the geological classification information, performing surface texture filling on the initial surface model to determine a rock classification boundary line;
generating geological classification information related to the filling body according to the geological classification information and the rock classification boundary line;
marking the initial earth surface model by adopting the geological classification information related to the filling and digging body to obtain the earth surface model;
the second processing module further comprises: the preset geological model is obtained by modeling drilling points, fault lines, known detection points, geophysical prospecting data and time dimension data which are related to the filling body;
the method for optimizing the preset geological model according to the earth surface model to obtain the target geological model comprises the following steps:
determining a reference surface model to which the preset geological model relates, wherein the reference surface model comprises: obtaining reference geological classification information related to the filling and digging body based on the preset geological model;
and optimizing the reference earth surface model according to the earth surface model to obtain the target geological model.
7. A computer device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
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