CN116303859A - QGIS-based high-precision map automatic quality inspection system and method - Google Patents

Abstract

The invention provides a QGIS-based high-precision map automatic quality inspection system and a QGIS-based high-precision map automatic quality inspection method, wherein the QGIS-based high-precision map automatic quality inspection system comprises the following steps: the data acquisition module transmits the original data to the data rendering module, the original data comprises vector data related to a road, the QGIS in the data rendering module performs data rendering display and QT visualization operation, and then the rendered image data is sent to the data processing module for processing. The data processing module comprises a data display module which performs rendering display on the high-precision map data based on the QGIS; the data editing module performs geometric modification and attribute editing on the vector data; the data quality inspection module performs geometric topology inspection and attribute information inspection on the vector data; the data repairing module is used for repairing the problems in the data in batches; the data conversion module is used for converting data formats; the data segmentation module cuts data in a large range, and further task allocation is achieved. The invention improves the production and quality inspection efficiency of the high-precision map and reduces the production cost of the high-precision map.

Description

QGIS-based high-precision map automatic quality inspection system and method

technical field

The present invention relates to the technical field of high-precision map processing, in particular to a QGIS-based automatic quality inspection system and method for high-precision maps.

Background technique

Compared with ordinary maps, high-precision maps provide higher-precision and richer map information, mainly for autonomous driving. For high-precision maps, maps that have higher requirements for fineness or richness than ordinary SD maps are often called high-precision maps. For example, the ADAS map used in assisted driving has a relative accuracy of 1m and an absolute accuracy of 5m. It is sometimes called a high-precision map.

The high-precision map data produced through surveying and mapping collection and automatic generation algorithms still has unavoidable accuracy problems, such as sensor errors, inaccurate vehicle pose estimation, road conditions, and algorithm errors. Manual intervention and repair is required, and traditional manual inspection and repair has problems such as time-consuming and easy to miss.

Therefore, there is an urgent need in the market for a high-precision map automatic quality inspection system and method based on QGIS that can improve high-precision map quality inspection and production efficiency.

Contents of the invention

Aiming at the defects in the prior art, the object of the present invention is to provide a QGIS-based automatic quality inspection system and method for high-precision maps.

In a first aspect, the present invention provides a QGIS-based high-precision map automatic quality inspection system, including: a data acquisition module, a data rendering module and a data processing module;

The data acquisition module transmits the original data to the data rendering module, the original data includes road-related vector data, the QGIS in the data rendering module performs data rendering and display and the QT performs visualization operations, and then the rendered image data is sent to the data processing module for further processing.

The data processing module includes a data display module, a data editing module, a data quality inspection module, a data repair module, a data conversion module and a data segmentation module;

The data display module renders and displays the high-precision map data based on QGIS; the data editing module performs geometric modification and attribute editing on the vector data; the data quality inspection module performs geometric topology inspection and attribute information inspection on the vector data; The data repair module is used for automatic batch repair of errors detected by the data quality inspection module; the data conversion module is used for conversion between data formats; the data segmentation module is used for large-scale data cutting, and then realizes task allocation.

Preferably, the raw data also includes high-precision map data, protobuf data and road picture data;

The high-precision map data includes road-related point cloud data;

The protobuf data includes data for transmission;

The road picture data includes a road picture including time stamp information, and the road picture and point cloud data can be associated through the time stamp.

Preferably, the data display module performs visual color matching according to different layers and attribute information on the high-precision map display, and binds and displays the road real-scene picture and track point data, including vector data loading, raster data loading, and protobuf file reading Conversion loading, road boundary line data pnt_types analysis and trajectory viewing module.

Preferably, the data quality inspection module is used to perform quality inspection on the produced high-precision map data. The QGIS-based topology checker can perform quality inspections between multiple layers, including geometric direction inspection, duplicate ID inspection, and suspension point inspection. , geometric duplication check, zigzag line check, upstream-downstream relationship check and road boundary line ID check.

Preferably, the geometric direction check is used to check the line direction of the road centerline hd_center and the road line hd_boundary layer, and when the two lines are connected at the beginning or end and the angle between the two lines is greater than 120°, it indicates the direction of the two lines mistake;

The duplicate ID check is used to check whether there is a duplicate value in the id attribute value of the vector layer by traversing the elements, if so, then check whether the corresponding vector layer is duplicated, and delete one of the duplicated layers; if not, then pass the inspection ;

The hanging point check is used to check the vector line layer, including a single layer hanging point check and a multi-layer hanging point check, and the multi-layer hanging point check indexes all the end points of the input multiple layers Check, where the hanging point is when the head end point or tail end point of a line is not connected with other line end points, then it is determined that the end point is a hanging point;

The geometric duplication check is used to check the geometric elements of the vector layer, including single-layer inspection and multi-layer inspection, and the multi-layer geometric duplication check traverses all layer elements to establish a geometric index to judge geometric duplication;

The checking of the upstream and downstream relationship determines the correctness of the corresponding two attribute values through the geometric topology relationship;

The road boundary line ID check finds the left and right boundaries of each line in the road centerline hd_center through the spatial topology relationship, and judges whether the boundary id is the attribute value of left_bid and right_bid.

Preferably, the data repair module adopts specific repair methods for batch repairs for different errors, including short-distance suspension point repair, invalid geometry repair, duplicate ID repair, and jagged line repair;

The short-distance suspension point repair adsorbs the two suspension points so that the two lines are connected, and then completes the repair of the suspension points whose distance is smaller than the threshold.

Preferably, the data conversion module performs format conversion and block processing for point cloud data with a large amount of data;

The format conversion includes converting road point cloud data into block tif data, converting point cloud range original data into multiple shp files for loading, and converting shp point data with elevation into las point cloud data format.

Preferably, the data segmentation module is used to divide the vector layer into multiple layers according to a specified range or a specified area element.

In a second aspect, the present invention provides a QGIS-based automatic quality inspection method for high-precision maps, including:

Data acquisition step: loading raw data, which includes road-related vector data;

Data rendering step: using QGIS to perform data rendering display and analysis on the data, and using QT to develop the interface view so as to perform visual operation;

Data detection step: perform geometric modification and attribute editing on the rendered vector data, and perform geometric topology inspection and attribute information inspection on the vector data to obtain corresponding detection results;

Data repairing step: automatic batch repairing of errors in the detection results.

Preferably, it also includes a data conversion step: performing format conversion and block processing on the point cloud data with a large amount of data, for data loading and processing;

The format conversion includes converting the road point cloud data into block tif data, converting the point cloud range original data into multiple shp files for loading, and converting the shp point cloud data with elevation into a common point cloud data format ;

It also includes a data segmentation step: dividing the vector layer into multiple layers according to the specified range or the specified area features.

Compared with the prior art, the present invention has the following beneficial effects:

The present invention is based on the high-precision map automatic quality inspection system and method developed by QGIS, and realizes fast visual color matching of high-precision maps, conversion of high-precision map data, fast editing of high-precision map data, rapid quality inspection and repair of common problems in high-precision map data, The function of comparing and viewing high-precision maps and real-world maps improves the efficiency of high-precision map production and quality inspection, and reduces the production cost of high-precision maps.

Description of drawings

Other characteristics, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

Fig. 1 is a schematic structural diagram of the high-precision map automatic quality inspection system based on QGIS of the present invention.

Fig. 2 is a schematic workflow diagram of the QGIS-based automatic quality inspection method for high-precision maps of the present invention.

Fig. 3 is a schematic diagram of the comparison effect before and after repairing the short-distance suspension point in the present invention.

Fig. 4 is a schematic diagram of the comparison effect before and after repairing the zigzag line in the present invention.

Detailed ways

The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

Embodiment one

A QGIS-based automatic quality inspection system for high-precision maps provided by the present invention, as shown in FIG. 1 , includes: a data acquisition module, a data rendering module and a data processing module. The data acquisition module transmits the original data to the data rendering module, the original data includes road-related vector data, QGIS in the data rendering module performs data rendering and display and QT performs visualization operations, and then the rendered image data is sent to the data processing module in further processing. Specifically, the original data also includes high-precision map data, protobuf data and road picture data. High-precision map data includes road-related point cloud data, protobuf data includes data for transmission, and road image data includes road images containing time stamp information, and the road images and point cloud data can be associated through time stamps. In the data rendering module, considering that the processing speed of c++ is fast, it has great advantages in spatial data analysis and processing, so it can be developed with c++.

The data processing module includes a data display module, a data editing module, a data quality inspection module, a data repair module, a data conversion module and a data segmentation module. Among them, the data display module renders and displays the high-precision map data based on QGIS. The data editing module performs geometric modification and attribute editing on vector data. The data quality inspection module performs geometric topology inspection and attribute information inspection on vector data. The data repair module is used to automatically repair errors detected by the data quality inspection module in batches. The data conversion module is used for conversion between data formats. The data segmentation module is used for large-scale data segmentation to realize task allocation.

Specifically, the data display module performs visual color matching according to different layers and attribute information on the high-precision map display, and binds the road real-scene picture with the track point data, including vector data loading, raster data loading, and protobuf file reading Conversion loading, road boundary line data pnt_types analysis and trajectory viewing module. At the same time, the visualization and color matching of the high-precision map data that conforms to the specifications, as well as the realization of binding and displaying the real road pictures and track point data can facilitate data editing and modification.

Furthermore, for non-high-precision map vector data, the default style is used for loading and rendering. For high-precision map vector data, qml style files are configured separately for different types of data. When QGIS renders, the layer will be rendered in the specified style. Among them, different types of data include road centerline (hd_center), road boundary line (hd_boundary), stop line (hd_stop), signal light (hd_signal), road arrow (hd_arrow), road surface (hd_road) and intersection (hd_crossroad). When loading raster data, the layer is placed at the bottom by default for loading and displaying, so as to avoid occluding the vector data. Protobuf is a binary data exchange format. The present invention can read protobuf files of hdmap and pointmap data types, wherein hdmap mainly stores high-precision map road data, including road centerline, road boundary line, stop line, signal light , road arrows, road surfaces, intersections and their topological relationships, pointmap mainly stores the road point cloud data collected by the collection vehicle. Use the protobuf library to read the information in it, and use the GDAL library to write it into the corresponding vector file, load and render it into QGIS through the specified style, and store the parsed vector in the same level directory, and read the protobuf file next time , it will give priority to judging whether the parsed file already exists, and if so, use it directly. Protobuf files are stored in bin format, among which the protobuf files starting with "hd" will be parsed as hdmap data types, and finally seven vector files will be generated: hd_center, hd_boundary, hd_stop, hd_signal, hd_arrow, hd_road, hd_crossroad, and other protobuf files will be pointmap Data type analysis, generate a point type vector file.

The pnt_type attribute value of the road boundary line (hd_boundary) stores the type of each point on the line, representing the type of lane line, such as white solid line, white dashed line, yellow solid line, yellow dashed line, etc. The storage method is stored at intervals in the form of point quantity and type to compress the field value size. When parsing pnt_types, first judge whether the number of points stored in pnt_types is consistent with the number of points on the line, discard the excess part, and supplement the missing part with 0, split the line data according to the point type, and finally generate the hd_boundary_types file for displaying lane lines type.

The data editing module is used to modify the attributes and geometric information of the layer, and has a large optimization in the multi-element editing and attribute display interface. Specifically, the element selection of the present invention includes two methods of frame selection and polygon selection. The frame selection is to draw a rectangular frame by pressing and holding the left mouse button, and the polygon selection is to draw a polygon frame by clicking the left mouse button. Finally, the rectangular frame or polygon will be highlighted. The elements in the box, and the attribute information is displayed in the editing tool UI interface. At this point, the attribute information can be edited directly. For example, flip line segments, break line segments, move line segments, merge line segments, etc.

The data quality inspection module is used to perform quality inspection on the produced high-precision map data. The QGIS-based topology checker can perform quality inspections between multiple layers, including geometric direction inspection, duplicate ID inspection, suspension point inspection, and geometric repetition. Inspection, jagged line inspection, upstream and downstream relationship inspection and road boundary line ID inspection. At the same time, the detected error information is displayed on the panel of the quality inspection module, and the error location can be located according to the specific error information.

Specifically, the geometric direction check is used to check the line direction of the road centerline hd_center and road line hd_boundary layers. When the two lines are connected at the beginning or end and the angle between the two lines is greater than 120°, it means that the direction of the two lines is wrong. Duplicate ID check is used to check whether the id attribute value of the vector layer has duplicate values by traversing the elements. If so, check whether the corresponding vector layer is duplicated, and delete one of the duplicated layers; if not, pass the check. The hanging point check is used to check the vector line layer, including the single layer hanging point check and the multi-layer hanging point check. The multi-layer hanging point check indexes all the end points of the input multiple layers for checking, Among them, the hanging point is when the head end point or tail end point of a line is not connected with other line end points, then the end point is determined to be a hanging point. The geometric duplication check is used to check the geometric elements of the vector layer, including single-layer checking and multi-layer checking. The multi-layer geometric duplication checking traverses all layer elements and establishes geometric indexes to judge geometric duplication. The jagged line check checks the geometric elements of the vector line layer. When the angle between the lines in a line element exceeds a certain threshold, the line will be judged as a jagged line. The upstream and downstream relationship check determines the correctness of the corresponding two attribute values through the geometric topology relationship. The road boundary line ID check is mainly aimed at the hd_center (road centerline) and hd_boundary (road boundary) layers of the high-precision map. The hd_center layer has left_bid and right_bid attribute fields, which represent the left and right boundaries of the road centerline respectively. It includes finding the left and right boundaries of each line in the road centerline hd_center through the spatial topology relationship, and judging whether the boundary id is the attribute value of left_bid and right_bid.

The data repair module adopts specific repair methods for batch repairs for different errors, including short-distance suspension point repair, invalid geometry repair, duplicate ID repair, and jagged line repair. Specifically, as shown in Figure 3, the left figure shows that the small error in the layer production process leads to a small distance between the hanging points, and the right figure shows that the two hanging points are absorbed by the close hanging point repair so that the two lines are connected, and then Complete the repair of hanging points whose distance is less than the threshold. As shown in Figure 4, the left picture is the jagged line checked by the quality inspection module, and the right picture is the rendering of the jagged line repaired by the present invention. For duplicate ID repair, it traverses the vector elements to obtain the attribute value of the ID field, and judges whether there are duplicate values. For duplicate values, it is renumbered to the maximum ID value of the current layer plus one. Invalid geometry repair is mainly used to repair empty geometric elements, and directly delete such elements.

The data conversion module performs format conversion and block processing for point cloud data with a large amount of data. Format conversion includes converting road point cloud data into block t if data, converting point cloud range raw data into multiple shp files for loading, and converting shp point data with elevation into las point cloud data format.

Specifically, the pointmap point cloud is the binary point cloud data stored and transmitted by protobuf. For the pointmap point cloud data with a large amount of data, the data can be converted into block tif data and displayed in QGIS. During the conversion process, first Calculate the boundary range of pointmap point cloud data, divide the file according to the size of the range, convert the data into tif data and specify the row and column numbers at the end of the generated file name, and finally generate an index file for management. When loading and displaying the divided tif file, read the index file and display the tif image according to the current canvas range of QGIS to realize dynamic loading. When the amount of point cloud data is too large, it cannot be directly converted into one shp file for loading and displaying. The data conversion module can convert the original data of the point cloud range into multiple shp files for loading.

The data segmentation module is used to divide the vector layer into multiple layers according to the specified range or specified area features. In the process of high-precision map quality inspection, a large area is divided into multiple small areas and handed over to different quality inspectors for simultaneous quality inspection to improve efficiency.

Specifically, for example, to perform layer segmentation according to a specified range, first select the layer to be segmented and the specified segmentation range, and then perform segmentation processing. During segmentation, the elements to be segmented within the segmented range are stored in the first database, and the elements located outside the range are stored in the first database. The elements to be divided are stored in the second database. Another example is to divide the layer by area features, that is, divide the layer to be divided into multiple blocks according to the features in a certain area layer. First, select the area layer to be split. When splitting, create an empty folder according to the fid of each area element of the area layer to be segmented. The elements to be divided located in the corresponding area element will be imported into the corresponding folder. The features to be split in the area features will be discarded.

Embodiment two

A kind of high-precision map automatic quality inspection method based on QGIS provided by the present invention, as shown in Figure 2, includes:

Data acquisition step: loading raw data, which includes road-related vector data, high-precision map data, protobuf data and road picture data. Specifically, high-precision map data includes road-related point cloud data, protobuf data includes data for transmission, and road image data includes road images containing time stamp information, and the road images and point cloud data can be associated through time stamps .

Data rendering step: use QGIS to perform data rendering, display and analysis on the data, and use QT to develop the interface view for visual operation.

Data detection step: perform geometric modification and attribute editing on the rendered vector data, and perform geometric topology inspection and attribute information inspection on the vector data to obtain corresponding detection results. Specifically, the geometric topology check and attribute information check include geometric direction check, duplicate ID check, suspension point check, geometric duplicate check, zigzag line check, upstream-downstream relationship check, and road boundary line ID check. At the same time, the detected error information is displayed on the panel of the quality inspection module, and the error location can be located according to the specific error information. The splitting process includes splitting the vector layer into multiple layers according to a specified range or a specified area element.

Furthermore, in the process of high-precision map quality inspection, reference through real-scene photos will greatly improve the accuracy of quality inspection. Binding and displaying the track points of the data collection vehicle with the real-scene photos taken can make it more convenient for quality inspection personnel to compare quality. check. In points (point cloud layer), the label attribute records the point type, the point data with label=10 is the track point data, the timestamp attribute records the time stamp when the collection vehicle passed the point, and the name of the real-scene picture taken by the collection vehicle also contains time stamp information. When viewing the track, first select the point layer where the track point is located, and the system will fit the track line according to the timestamp of the track point, or use the existing track line, and finally select the road real picture directory for timestamp matching. That is to say, when checking the track, first select the track line to be viewed, and then select the track points on the track line to view the road real-scene picture matching. The specific implementation steps include: first, establish a relationship index between the real road picture and the time stamp; then select the track point, and judge whether it is a track point on the current track line; then, obtain the time stamp of the track point, and blur with the time stamp of the real road picture Match to obtain the real picture of the road near the current track point; finally, display the picture.

Data repairing step: automatic batch repairing of errors in the detection results. Said fixes include close hanging point fixes, invalid geometry fixes, duplicate ID fixes, jagged line fixes. Specifically, the short-distance suspension point repair includes absorbing two suspension points through the short-distance suspension point repair so that the two lines are connected, and then completing the repair of the suspension points whose distance is less than a threshold. For duplicate ID repair, it traverses the vector elements to obtain the attribute value of the ID field, and judges whether there are duplicate values. For duplicate values, it is renumbered to the maximum ID value of the current layer plus one. Invalid geometry repair is mainly used to repair empty geometric elements, and directly delete such elements.

A QGIS-based automatic quality inspection method for high-precision maps provided by the present invention also includes a data conversion step and a data segmentation step. Wherein, the data conversion step includes performing format conversion and block processing on large amount of point cloud data for data loading and processing. Format conversion includes converting road point cloud data into block tif data, converting point cloud range raw data into multiple shp files for loading, and converting shp point cloud data with elevation into a common point cloud data format. The data segmentation step includes dividing the vector layer into multiple layers according to the specified range or the specified area features.

Those skilled in the art know that, in addition to realizing the system, device and each module thereof provided by the present invention in a purely computer-readable program code mode, the system, device and each module thereof provided by the present invention can be completely programmed by logically programming the method steps. The same program is implemented in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, and embedded microcontrollers, among others. Therefore, the system, device and each module provided by the present invention can be regarded as a hardware component, and the modules included in it for realizing various programs can also be regarded as the structure in the hardware component; A module for realizing various functions can be regarded as either a software program realizing a method or a structure within a hardware component.

Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art may make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. In the case of no conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims (10)

1. A high-precision map automatic quality inspection system based on QGIS is characterized in that, comprising: a data acquisition module, a data rendering module and a data processing module; The data acquisition module transmits the original data to the data rendering module, the original data includes road-related vector data, the QGIS in the data rendering module performs data rendering and display and the QT performs visualization operations, and then the rendered image data is sent to the data processing module for further processing. The data processing module includes a data display module, a data editing module, a data quality inspection module, a data repair module, a data conversion module and a data segmentation module; The data display module renders and displays the high-precision map data based on QGIS; the data editing module performs geometric modification and attribute editing on the vector data; the data quality inspection module performs geometric topology inspection and attribute information inspection on the vector data; The data repair module is used for automatic batch repair of errors detected by the data quality inspection module; the data conversion module is used for conversion between data formats; the data segmentation module is used for large-scale data cutting, and then realizes task allocation. 2. the automatic quality inspection system based on QGIS of high-precision map according to claim 1, is characterized in that, described original data also comprises high-precision map data, protobuf data and road picture data; The high-precision map data includes road-related point cloud data; The protobuf data includes data for transmission; The road picture data includes a road picture including time stamp information, and the road picture and point cloud data can be associated through the time stamp. 3. the automatic quality inspection system based on QGIS of high-precision map according to claim 1, it is characterized in that, data display module carries out visual color matching according to different layers and attribute information on high-precision map display, road real scene picture and Track point data binding display, including vector data loading, raster data loading, protobuf file reading conversion loading, road boundary line data pnt_types analysis and track viewing module. 4. the high-precision map automatic quality inspection system based on QGIS according to claim 1, is characterized in that, the data quality inspection module is used for carrying out quality inspection to the high-precision map data of production, based on the topology checker of QGIS It can perform quality checks between multiple layers, including geometric direction checks, duplicate ID checks, hanging point checks, geometric duplicate checks, jagged line checks, upstream-downstream relationship checks, and road boundary line ID checks. 5. The automatic quality inspection system for high-precision maps based on QGIS according to claim 4, wherein the geometric direction inspection is used to check the line direction of the road center line hd_center and the road line hd_boundary layers, when two lines When the first end point is connected or the end point is connected and the angle between the two lines is greater than 120°, it means that the direction of the two lines is wrong; The duplicate ID check is used to check whether there is a duplicate value in the id attribute value of the vector layer by traversing the elements, if so, then check whether the corresponding vector layer is duplicated, and delete one of the duplicated layers; if not, then pass the inspection ; The hanging point check is used to check the vector line layer, including a single layer hanging point check and a multi-layer hanging point check, and the multi-layer hanging point check indexes all the end points of the input multiple layers Check, where the hanging point is when the head end point or tail end point of a line is not connected with other line end points, then it is determined that the end point is a hanging point; The geometric duplication check is used to check the geometric elements of the vector layer, including single-layer inspection and multi-layer inspection, and the multi-layer geometric duplication check traverses all layer elements to establish a geometric index to judge geometric duplication; The checking of the upstream and downstream relationship determines the correctness of the corresponding two attribute values through the geometric topology relationship; The road boundary line ID check finds the left and right boundaries of each line in the road centerline hd_center through the spatial topology relationship, and judges whether the boundary id is the attribute value of left_bid and right_bid. 6. The QGIS-based automatic quality inspection system for high-precision maps according to claim 1, wherein the data repair module adopts specific repair methods for different errors to perform batch repair, including short-distance hanging point repair and invalid geometry repair , Duplicate ID repair, jagged line repair; The short-distance suspension point repair adsorbs the two suspension points so that the two lines are connected, and then completes the repair of the suspension points whose distance is smaller than the threshold. 7. the automatic quality inspection system of high-precision map based on QGIS according to claim 2, is characterized in that, data conversion module carries out format conversion and block processing for the point cloud data of large amount of data; The format conversion includes converting road point cloud data into block tif data, converting point cloud range original data into multiple shp files for loading, and converting shp point data with elevation into las point cloud data format. 8. The QGIS-based automatic quality inspection system for high-precision maps according to claim 1, wherein the data segmentation module is used to divide the vector layer into multiple layers according to the specified range or specified surface elements. 9. A high-precision map automatic quality inspection method based on QGIS, characterized in that, comprising: Data acquisition step: loading raw data, which includes road-related vector data; Data rendering step: using QGIS to perform data rendering display and analysis on the data, and using QT to develop the interface view so as to perform visual operation; Data detection step: perform geometric modification and attribute editing on the rendered vector data, and perform geometric topology inspection and attribute information inspection on the vector data to obtain corresponding detection results; Data repairing step: automatic batch repairing of errors in the detection results. 10. The QGIS-based automatic quality inspection method for high-precision maps according to claim 8, further comprising a data conversion step: performing format conversion and block processing on the point cloud data of a large amount of data, for use in data loading and processing; The format conversion includes converting the road point cloud data into block tif data, converting the point cloud range original data into multiple shp files for loading, and converting the shp point cloud data with elevation into a common point cloud data format ; It also includes a data segmentation step: dividing the vector layer into multiple layers according to the specified range or the specified area features.

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