Image acquisition method, device, computer equipment, storage medium and program product

Abstract

The application relates to an image acquisition method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: a computer equipment determines an initial flight path trajectory of a UAV according to a first containment model of a containment; receives a first image of the containment sent by the UAV; establishes a second containment model of the containment according to the first image; determines a shooting parameter of the UAV according to the resolution of a camera and a preset crack width; determines a target flight path trajectory of the UAV according to the second containment model and the shooting parameter; and finally receives a second image of the containment sent by the UAV. The image of the containment can be acquired according to the target flight path trajectory, the efficiency of acquiring the image of the containment can be improved, the time consumption is short, and then the image of the containment can be applied to the defect detection of the containment, and the efficiency of the defect detection is improved.

Description

Technical Field

[0001] This application relates to the field of photogrammetry technology, and in particular to an image acquisition method, apparatus, computer equipment, storage medium, and program product. Background Technology

[0002] The containment vessel of a nuclear power plant is a large-volume concrete structure with an extremely high safety rating. It is a cylinder approximately 40 meters in diameter and 51 meters high, serving as the last line of defense against the release of radioactive materials produced by nuclear fission within the plant. Although the containment vessel possesses excellent sealing and stability, the exposed walls inevitably undergo structural deformation and functional damage under the combined effects of natural forces and internal pressure, creating potential safety hazards. Every ten years after construction, commissioning, and commercial operation, the containment vessel undergoes a comprehensive pressure test to check its safety performance and ensure production safety. Among the most important tasks is detecting cracks in the containment vessel walls, requiring close-range, high-resolution images of the containment vessel.

[0003] Typically, acquiring high-resolution images of the containment vessel of a nuclear power plant requires manually setting up imaging equipment to capture video or images of the containment vessel from a distance. However, this method of acquiring images of the containment vessel is time-consuming, labor-intensive, and inefficient. Summary of the Invention

[0004] Therefore, it is necessary to provide an image acquisition method, apparatus, computer equipment, storage medium, and program product that can improve the efficiency of acquiring images of the containment structure and reduce the time required, in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides an image acquisition method. The method includes:

[0006] The initial flight path of the UAV is determined based on the first safety shell model of the safety shell; the first safety shell model is a model determined by the images taken by the UAV along the preset flight path when the distance between the UAV and the safety shell is within a first preset distance range.

[0007] The system receives a first image of the containment structure sent by the drone and builds a second containment structure model based on the first image. The first image is an image taken by the drone based on the initial flight path when the distance between the drone and the containment structure is within a second preset distance range. The upper limit of the second preset distance range is less than the lower limit of the first preset distance range.

[0008] The shooting parameters of the drone are determined based on the camera resolution and the preset crack width.

[0009] The target flight path of the UAV is determined based on the second containment model and the shooting parameters.

[0010] Receive a second image of the containment structure sent by the drone; the second image is an image of the containment structure taken by the drone according to the target flight path.

[0011] In one embodiment, the drone's shooting parameters are determined based on the camera's resolution and a preset slit width, including:

[0012] The first size of the image captured by the drone in the length direction is determined based on the product of the pixels in the length direction corresponding to the resolution and the preset crack width.

[0013] The second size of the image captured by the drone in the width direction is determined based on the product of the pixels in the width direction corresponding to the resolution and the preset crack width.

[0014] Based on the first dimension and the second dimension, the shooting parameters of the drone are determined.

[0015] In one embodiment, determining the drone's shooting parameters based on the first size and the second size includes:

[0016] Based on the first dimension and the second dimension, determine the shooting distance between the drone and the containment shell;

[0017] The lateral overlap of the drone is determined based on the first dimension and the preset first cutting dimension in the length direction;

[0018] The heading overlap of the UAV is determined based on the second dimension and the preset second cutting dimension in the width direction;

[0019] The movement distance of the UAV is determined based on the lateral overlap, the forward overlap, the first dimension, and the second dimension.

[0020] The shooting parameters include the shooting distance, the lateral overlap, and the movement distance of the drone.

[0021] In one embodiment, determining the lateral overlap of the drone based on the first dimension and a preset first cutting dimension in the length direction includes:

[0022] Determine the first ratio between the first cutting size and the first dimension;

[0023] The difference between the first preset value and the first ratio is taken as the lateral overlap.

[0024] In one embodiment, determining the heading overlap of the drone based on the second dimension and a preset second cutting dimension in the width direction includes:

[0025] Determine a second ratio between the second cutting dimension and the second dimension;

[0026] The difference between the second preset value and the second ratio is taken as the heading overlap.

[0027] In one embodiment, determining the movement distance of the UAV based on the lateral overlap, the forward overlap, the first dimension, and the second dimension includes:

[0028] Determine the first difference between the third preset value and the lateral overlap, and determine the first product result of the first difference and the first dimension;

[0029] The horizontal movement distance of the drone is determined based on the result of the first product.

[0030] Determine the second difference between the third preset value and the heading overlap, and determine the second product result of the second difference and the second dimension;

[0031] The vertical movement distance of the drone is determined based on the result of the second product;

[0032] The moving distance includes the horizontal moving distance and / or the vertical moving distance.

[0033] Secondly, this application also provides an image acquisition device. The device includes:

[0034] The first determining module is used to determine the initial flight path of the UAV based on the first safety shell model of the safety shell; the first safety shell model is a model determined based on the images taken by the UAV along the preset flight path when the distance between the UAV and the safety shell is within a first preset distance range.

[0035] The first receiving module is used to receive a first image of the safety shell sent by the drone, and to build a second safety shell model of the safety shell based on the first image; the first image is an image taken by the drone based on the initial flight path when the distance between the drone and the safety shell is within a second preset distance range, and the upper limit of the second preset distance range is less than the lower limit of the first preset distance range.

[0036] The second determining module is used to determine the shooting parameters of the drone based on the camera resolution and the preset crack width;

[0037] The third determining module is used to determine the target flight path of the UAV based on the second containment model and the shooting parameters.

[0038] The second receiving module is used to receive a second image of the containment structure sent by the drone; the second image is an image of the containment structure taken by the drone according to the target flight path.

[0039] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the above-described method.

[0040] Fourthly, this application also provides a computer-readable storage medium. This computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the above-described method.

[0041] Fifthly, this application also provides a computer program product. This computer program product includes a computer program that, when executed by a processor, implements the steps of the above-described method.

[0042] The aforementioned image acquisition method, apparatus, computer equipment, storage medium, and program product involve the computer equipment determining the initial flight path of the UAV based on a first safety shell model, receiving a first image of the safety shell transmitted by the UAV, establishing a second safety shell model based on the first image, determining the UAV's shooting parameters based on the camera resolution and a preset slit width, determining the UAV's target flight path based on the second safety shell model and the shooting parameters, and finally receiving a second image of the safety shell transmitted by the UAV. Specifically, the first safety shell model is a model determined by images captured by the UAV along a preset flight path when the distance between the UAV and the safety shell is within a first preset distance range; the first image is an image captured by the UAV based on the initial flight path when the distance between the UAV and the safety shell is within a second preset distance range, where the upper limit of the second preset distance range is less than the lower limit of the first preset distance range; and the second image is an image of the safety shell captured by the UAV based on the target flight path. Traditional methods require manual equipment setup for image acquisition of containment structures. In this application, however, a first image is acquired by a UAV following an initial flight path. A second containment structure model is then built based on the first image. Simultaneously, the UAV's shooting parameters are determined based on the resolution and preset crack width. Finally, a target flight path for the UAV that meets the requirements is determined based on the second containment structure model and the shooting parameters. The image of the containment structure is then acquired based on the target flight path, which improves the efficiency of image acquisition and reduces the time required. Consequently, the images of the containment structure can be applied to containment defect detection, thereby improving the efficiency of containment defect detection. Attached Figure Description

[0043] Figure 1 This is an application environment diagram of an image acquisition method in one embodiment;

[0044] Figure 2 A schematic flowchart illustrating an image acquisition method provided in an embodiment of this application;

[0045] Figure 3 A schematic diagram of a dual-ducted unmanned aerial vehicle (UAV) provided in an embodiment of this application;

[0046] Figure 4 This is one of the flowcharts illustrating a method for determining shooting parameters provided in an embodiment of this application;

[0047] Figure 5 A second schematic flowchart illustrating a method for determining shooting parameters provided in an embodiment of this application;

[0048] Figure 6 A flowchart illustrating a method for determining lateral overlap provided in an embodiment of this application;

[0049] Figure 7 A flowchart illustrating a method for determining heading overlap provided in an embodiment of this application;

[0050] Figure 8 A flowchart illustrating a method for determining the movement distance of a drone provided in an embodiment of this application;

[0051] Figure 9 This is a schematic diagram illustrating the horizontal movement distance of the UAV provided in an embodiment of this application.

[0052] Figure 10 This is a schematic diagram of the vertical movement distance of the UAV provided in the embodiments of this application;

[0053] Figure 11 This is a schematic diagram of the drone flight path provided in this application;

[0054] Figure 12 A structural block diagram of an image acquisition device provided in this application;

[0055] Figure 13 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0057] The image acquisition method provided in this application embodiment can be applied to, for example... Figure 1In the application environment shown, when the distance between the drone 101 and the safety shell 103 is within a first preset distance range, the drone 101 captures an image of the safety shell 103 along a preset flight path and sends the captured image to the computer device 102. The computer device 102 models the captured image to determine a first safety model of the safety shell 103, and plans an initial flight path for the drone 101 based on the first safety model. When the distance between the drone 101 and the safety shell 103 is within a second preset distance range, the drone 101 captures a first image of the safety shell 103 along the initial flight path and sends the first image to the computer device 102. The computer device 102 models the first image to determine a second safety model of the safety shell 103, determines the shooting parameters of the drone 101 based on the camera resolution and a preset crack width, and plans a target flight path for the drone 101 based on the second safety model and the shooting parameters. The drone 101 then captures a second image of the safety shell based on the target flight path.

[0058] In one embodiment, Figure 2 This is a flowchart illustrating an image acquisition method provided in an embodiment of this application, applied to... Figure 1 Taking a computer device as an example, the explanation includes the following steps:

[0059] S201. Determine the initial flight path of the UAV based on the first safety shell model of the safety shell; the first safety shell model is a model determined by the images taken by the UAV along the preset flight path when the distance between the UAV and the safety shell is within a first preset distance range.

[0060] The containment structure may include a nuclear reactor protective enclosure. The first preset distance range may be 70 meters to 100 meters.

[0061] In this embodiment, the UAV uses oblique imaging technology to capture images of the containment vessel and its surrounding environment along a preset flight path within a first preset distance range, obtaining images with positioning information. A computer receives these images and inputs them into modeling software to create a first containment vessel model. The computer then imports this first containment vessel model into trajectory planning software to obtain the UAV's initial flight path.

[0062] It should be noted that the effective pixel count of the drone can be 45 million, and the distance from the ground when the drone is taking pictures can be between 120 meters and 150 meters.

[0063] S202. Receive a first image of the safety shell sent by the UAV, and establish a second safety shell model based on the first image; the first image is an image taken by the UAV based on the initial flight path when the distance between the UAV and the safety shell is within a second preset distance range, and the upper limit of the second preset distance range is less than the lower limit of the first preset distance range.

[0064] The upper limit of the second preset distance range is less than the lower limit of the first preset distance range. For example, the first preset distance range is between 70 meters and 100 meters, and the second preset distance range is between 15 meters and 30 meters.

[0065] In this embodiment, the drone photographs the containment structure within a second preset distance range based on the initial flight path of the drone output by the computer device, obtaining a first image of the containment structure with positioning information. After receiving the first image of the containment structure sent by the drone, the computer device inputs the first image into modeling software for modeling, obtaining a second containment structure model. The distance of the drone from the ground during the photographing process can be between 0 meters and 80 meters.

[0066] S203. Determine the drone's shooting parameters based on the camera's resolution and the preset crack width.

[0067] In this embodiment of the application, the computer device can obtain the size of the image captured by the drone based on the product of the pixels in the length direction corresponding to the camera resolution and the preset crack width, and the product of the pixels in the width direction corresponding to the resolution and the preset crack width. The size of the image captured by the drone can be used to determine the shooting parameters of the drone, which may include the shooting distance between the drone and the containment shell, the lateral overlap of the drone, the directional overlap of the drone, and the movement distance of the drone.

[0068] S204. Determine the target flight path trajectory of the UAV based on the second containment model and shooting parameters.

[0069] In this embodiment of the application, the computer device can determine the target flight path of the UAV based on the second containment model, the shooting distance between the UAV and the containment, the lateral overlap of the UAV, the directional overlap of the UAV, and the movement distance of the UAV.

[0070] S205, Receive the second image of the containment structure sent by the UAV; the second image is an image of the containment structure taken by the UAV according to the target flight path.

[0071] In this embodiment of the application, the UAV takes a picture of the containment structure according to the target flight path to obtain a second image of the containment structure. The computer device receives the second image of the containment structure sent by the UAV and can stitch the acquired second images together to obtain a complete image of the containment structure.

[0072] It should be noted that the drone that takes the second image of the containment vessel can be a dual-ducted drone, as shown in the reference. Figure 3 , Figure 3 This is a schematic diagram of a dual-ducted unmanned aerial vehicle (UAV) provided in an embodiment of this application. The dual-ducted UAV has the characteristics of vertical take-off and landing, good aerodynamic performance, small diameter, large lift, high load, and better safety due to the propeller being protected by the duct. It can improve the wind resistance and safety performance of the aircraft in containment scenarios.

[0073] The first containment model is built based on images obtained from long-distance photography of the containment structure using a preset flight path. The UAV then photographs the containment structure again using an initial flight path planned based on the first containment model, obtaining the first image; this time, the UAV's distance from the containment structure is less than the previous photographing distance. A more accurate second containment model is then constructed based on the first image. A target flight path is then constructed using the second containment model and photographing parameters to obtain the second image; this time, the UAV's distance from the containment structure is less than the previous two photographing distances. It should be noted that when the UAV is close to the containment structure, the real-time kinematic (RTK) signal is insufficient. In the preset and initial flight paths, the UAV is relatively far from the containment structure, so positioning and photography can be achieved based on RTK signals. However, the images taken when the UAV is far from the containment structure do not meet the requirements for containment crack detection. The target flight path required for crack detection allows the UAV to photograph close to the containment structure. Since the UAV is close to the containment structure, RTK signals cannot be used for positioning and photography. Therefore, when the UAV photographs the containment structure based on the target flight path, precise positioning and photography can be achieved using high-precision map navigation and laser vision.

[0074] In the above image acquisition method, the computer device determines the initial flight path of the UAV based on a first safety shell model of the safety shell, then receives a first image of the safety shell sent by the UAV, and establishes a second safety shell model of the safety shell based on the first image. Based on the camera resolution and a preset slit width, the device determines the UAV's shooting parameters, then determines the UAV's target flight path based on the second safety shell model and the shooting parameters, and finally receives a second image of the safety shell sent by the UAV. The first safety shell model is a model determined by images taken by the UAV along a preset flight path when the distance between the UAV and the safety shell is within a first preset distance range. The first image is an image taken by the UAV based on the initial flight path when the distance between the UAV and the safety shell is within a second preset distance range, where the upper limit of the second preset distance range is less than the lower limit of the first preset distance range. The second image is an image of the safety shell taken by the UAV based on the target flight path. Traditional methods require manual equipment setup for image acquisition of containment structures. In this application, however, a first image is acquired by a UAV following an initial flight path. A second containment structure model is then built based on the first image. Simultaneously, the UAV's shooting parameters are determined based on the resolution and preset crack width. Finally, a target flight path for the UAV that meets the requirements is determined based on the second containment structure model and the shooting parameters. The image of the containment structure is then acquired based on the target flight path, which improves the efficiency of image acquisition and reduces the time required. Consequently, the images of the containment structure can be applied to containment defect detection, thereby improving the efficiency of containment defect detection.

[0075] In one embodiment, Figure 4 This is one of the flowcharts illustrating a method for determining shooting parameters provided in this application. This embodiment relates to a possible implementation of how to determine the shooting parameters of a drone based on the camera's resolution and a preset crack width. Based on the above embodiment, step S203 includes:

[0076] S401. Determine the first dimension of the image captured by the drone in the length direction based on the product of the pixels in the length direction corresponding to the resolution and the preset crack width.

[0077] The preset crack width can be 0.2 mm.

[0078] In this embodiment, the computer device multiplies the number of pixels in the length direction corresponding to the camera's resolution by a preset crack width to obtain a product. Based on this product, the first size of the image captured by the drone in the length direction can be determined. For example, if the number of pixels in the length direction corresponding to the resolution is 7360 pixels and the preset crack width is 0.2 mm, multiplying the number of pixels by the preset crack width yields a product of 1.472 meters. The first size of the image captured by the drone in the length direction can be a value less than 1.472 meters, such as 1.2 meters. Therefore, 1.2 meters can be used as the first size of the image captured by the drone in the length direction.

[0079] S402. Determine the second dimension of the image captured by the drone in the width direction based on the product of the pixels in the width direction corresponding to the resolution and the preset crack width.

[0080] In this embodiment, the computer device multiplies the pixels in the width direction corresponding to the camera's resolution by a preset crack width to obtain a product. Based on this product, the first size of the image captured by the drone in the width direction can be determined. For example, if the pixels in the width direction corresponding to the resolution are 4912 pixels and the preset crack width is 0.2 mm, multiplying the pixels by the preset crack width yields a product of 0.9824 meters. The second size of the image captured by the drone in the length direction can be a value less than 0.9824 meters, such as 0.8 meters. Therefore, 0.8 meters can be used as the second size of the image captured by the drone in the length direction.

[0081] S403. Determine the drone's shooting parameters based on the first and second dimensions.

[0082] In this embodiment of the application, the computer device can determine the shooting distance between the drone and the containment shell, the lateral overlap of the drone, the directional overlap of the drone, and the movement distance of the drone based on the first size and the second size of the image captured by the drone.

[0083] In this embodiment, the first dimension of the image captured by the UAV in the length direction is determined by multiplying the pixels in the length direction corresponding to the resolution with the preset crack width. The second dimension of the image captured by the UAV in the width direction is determined by multiplying the pixels in the width direction corresponding to the resolution with the preset crack width. Based on the first and second dimensions, the shooting parameters of the UAV are determined. The UAV shooting parameters obtained by this method can be used to plan a flight path that meets the shooting requirements, thereby obtaining a high-resolution image of the containment structure. This image can be applied to containment defect detection to improve detection efficiency.

[0084] In one embodiment, Figure 5This is a second flowchart illustrating a method for determining shooting parameters according to an embodiment of this application. This embodiment relates to a possible implementation of how to determine the shooting parameters of a drone based on a first size and a second size. Based on the above embodiment, step S403 includes:

[0085] S501. Determine the shooting distance between the drone and the containment shell based on the first and second dimensions.

[0086] In this embodiment, the computer device can determine the shooting distance between the drone and the safety shell based on a first dimension in the length direction and a second dimension in the width direction of the image captured by the drone. Specifically, according to the imaging principle, since the length and width of the image captured by the drone are known, the location at the time of capturing the image can be determined, i.e., the shooting distance between the drone and the safety shell can be determined. For example, if the first dimension in the length direction of the image captured by the drone is 1.2 meters and the first dimension in the width direction is 0.8 meters, the shooting distance between the drone and the safety shell can be determined to be 0.8 meters based on the location at the time of capturing the image.

[0087] S502. Determine the lateral overlap of the UAV based on the first dimension and the preset first cutting dimension in the length direction.

[0088] The first cropping size can be a preset cropping size in the length direction, which is the length dimension of the effective image after cropping. For example, the first cropping size can be 0.75 meters.

[0089] In this embodiment of the application, the computer device calculates the ratio of the first size to the first cropping size based on the first size of the image captured by the drone in the length direction and the preset first cropping size in the length direction, and then subtracts the ratio from the preset value to obtain the result as the lateral overlap of the drone.

[0090] S503. Determine the heading overlap of the UAV based on the second dimension and the preset second cutting dimension in the width direction.

[0091] The second cropping size can be a preset cropping size in the width direction, which is the width dimension of the effective image after cropping. For example, the second cropping size can be 0.6 meters.

[0092] In this embodiment of the application, the computer device calculates the ratio of the second dimension to the second cropping dimension based on the second dimension of the image captured by the drone in the width direction and the preset second cropping dimension in the width direction, and then subtracts the ratio from the preset value to obtain the result as the drone's heading overlap.

[0093] S504. Determine the movement distance of the UAV based on the lateral overlap, the forward overlap, the first dimension, and the second dimension.

[0094] The shooting parameters include shooting distance, lateral overlap, and drone movement distance.

[0095] In this embodiment of the application, the computer device calculates the difference between a preset value and the lateral overlap based on the lateral overlap of the UAV, the forward overlap of the UAV, the first dimension, and the second dimension. Then, the difference is multiplied by the first dimension to obtain the vertical movement distance of the UAV. The difference between the preset value and the forward overlap is calculated and then multiplied by the second dimension to obtain the horizontal movement distance of the UAV.

[0096] In this embodiment, the shooting distance between the UAV and the containment vessel is first determined based on the first and second dimensions. Then, the lateral overlap of the UAV is determined based on the first dimension and a preset first trimming dimension in the length direction. The directional overlap of the UAV is determined based on the second dimension and a preset second trimming dimension in the width direction. Finally, the movement distance of the UAV is determined based on the lateral overlap, directional overlap, first and second dimensions. The UAV shooting parameters obtained by this method can be used to plan a flight path that meets the shooting requirements, thereby obtaining a high-resolution image of the containment vessel. This image can be applied to containment vessel defect detection to improve detection efficiency.

[0097] In one embodiment, Figure 6 This is a flowchart illustrating a method for determining lateral overlap according to an embodiment of this application. This embodiment relates to a possible implementation of how to determine the lateral overlap of a UAV based on a first dimension and a preset first cutting dimension in the length direction. Based on the above embodiment, step S502 includes:

[0098] S601. Determine the first ratio between the first cutting size and the first size.

[0099] In this embodiment of the application, the computer device determines a first ratio between a first cutting size in the preset length direction and a first size in the length direction of the image captured by the drone. For example, if the first cutting size is 0.75 meters and the first size is 1.2 meters, the first ratio between the first cutting size and the first size can be 0.625.

[0100] S602, The difference between the first preset value and the first ratio is used as the lateral overlap.

[0101] The first preset value can be 1.

[0102] In this embodiment, the computer device uses the difference between a first preset value and a first ratio as the lateral overlap of the drone. According to the example in the above embodiment, the first ratio of the first cut size to the first size is 0.625, and the first preset value is 1. Therefore, the difference between the preset value and the first ratio is 0.375, and 37.5% can be used as the lateral overlap of the drone.

[0103] In this embodiment, by determining the first ratio between the first cutting size and the first size, and then using the difference between the first preset value and the first ratio as the lateral overlap, the images captured by the drone during flight can meet the stitching requirements, thereby obtaining a complete containment image.

[0104] In one embodiment, Figure 7 This is a flowchart illustrating a method for determining heading overlap according to an embodiment of this application. This embodiment relates to a possible implementation of how to determine the heading overlap of a UAV based on a second dimension and a preset second cutting dimension in the width direction. Based on the above embodiment, S503 includes:

[0105] S701. Determine the second ratio between the second cutting dimension and the second dimension.

[0106] In this embodiment of the application, the computer device determines a first ratio between a preset second cropping size in the width direction and a second size of the image captured by the drone in the width direction. For example, if the second cropping size is 0.6 meters and the second size is 0.8 meters, the second ratio between the second cropping size and the second size can be 0.75.

[0107] S702, The difference between the second preset value and the second ratio is taken as the heading overlap.

[0108] The second preset value can be equal to the first preset value.

[0109] In this embodiment, the computer device uses the difference between the second preset value and the second ratio as the heading overlap of the UAV. According to the example in the above embodiment, the second ratio of the second cutting size to the first size is 0.75, and the second preset value is 1. Therefore, the difference between the two preset values ​​and the second ratio is 0.25, and 25% can be used as the heading overlap of the UAV.

[0110] In this embodiment, a second ratio between the second cutting size and the second size is determined, and the difference between the second preset value and the second ratio is used as the heading overlap, which enables the images captured by the UAV during flight to meet the stitching requirements, thereby obtaining a complete containment image.

[0111] In one embodiment, Figure 8This is a flowchart illustrating a method for determining the movement distance of a UAV according to an embodiment of this application. This embodiment relates to a possible implementation of how to determine the movement distance of a UAV based on lateral overlap, forward overlap, a first dimension, and a second dimension. Based on the above embodiment, step S504 includes:

[0112] S801. Determine the first difference between the third preset value and the lateral overlap, and determine the first product result of the first difference and the first dimension.

[0113] The third preset value can be 1.

[0114] In this embodiment, the computer device subtracts the third preset value from the lateral overlap to obtain a first difference value, and multiplies the first difference value by the first dimension to obtain a first product result. According to the example in the above embodiment, the first dimension is 1.2 meters, and the lateral overlap is 37.5%. Therefore, the first difference between the third preset value and the lateral overlap is 62.5%. Multiplying the first difference value of 62.5% by the first dimension of 1.2, the first product result is determined to be 0.75 meters.

[0115] S802. Determine the horizontal movement distance of the UAV based on the result of the first product.

[0116] In this embodiment, the computer device uses the first product result obtained in the above embodiments as the horizontal movement distance of the drone. Referring to the above example... Figure 9 , Figure 9 The schematic diagram of the horizontal movement distance of the drone provided in the embodiment of this application shows that the first dimension is 1.2 meters, the lateral overlap of the drone is 37.5%, and the horizontal movement distance of the drone is 0.75 meters.

[0117] S803. Determine the second difference between the third preset value and the heading overlap, and determine the second product result of the second difference and the second dimension.

[0118] In this embodiment, the computer device subtracts the third preset value from the heading overlap to obtain a second difference value, and multiplies the second difference value by the second dimension to obtain a second product result. According to the example in the above embodiment, the second dimension is 0.8 meters, and the heading overlap is 25%. Therefore, the second difference between the third preset value and the heading overlap is 75%. Multiplying the second difference value of 75% by the second dimension of 0.8 meters, the second product result is determined to be 0.6 meters.

[0119] S804. Determine the vertical movement distance of the UAV based on the result of the second product.

[0120] In this embodiment, the computer device uses the second product result obtained in the above embodiments as the vertical movement distance of the UAV. Referring to the above example... Figure 10 , Figure 10 This is a schematic diagram of the vertical movement distance of the UAV provided in the embodiments of this application. The second dimension is 0.8 meters, the directional overlap of the UAV is 25%, and the vertical movement distance of the UAV is 0.6 meters.

[0121] The distance traveled includes horizontal and / or vertical movement.

[0122] In this embodiment, by determining the first difference between the third preset value and the lateral overlap, and determining the first product result of the first difference and the first size, the horizontal movement distance of the UAV is determined according to the first product result. Then, the second difference between the third preset value and the heading overlap is determined, and the second product result of the second difference and the second size is determined. Finally, the vertical movement distance of the UAV is determined according to the second product result, an accurate UAV flight trajectory can be obtained, thereby acquiring a high-resolution image of the containment. Figure 11 This is a schematic diagram of the flight path of the UAV provided in this application. The diagram shows that the UAV 1102 is flying in a vertical direction relative to the containment shell 1101.

[0123] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0124] Based on the same inventive concept, this application also provides an image acquisition apparatus for implementing the image acquisition method described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more image acquisition apparatus embodiments provided below can be found in the limitations of the image acquisition method described above, and will not be repeated here.

[0125] In one embodiment, such as Figure 12 As shown, Figure 12 This application provides a structural block diagram of an image acquisition device 1200, which includes: a first determining module 1201, a first receiving module 1202, a second determining module 1203, a third determining module 1204, and a second receiving module 1205, wherein:

[0126] The first determining module 1201 is used to determine the initial flight path of the UAV based on the first safety shell model of the safety shell; the first safety shell model is a model determined based on the image taken by the UAV along the preset flight path when the distance between the UAV and the safety shell is within a first preset distance range.

[0127] The first receiving module 1202 is used to receive a first image of the safety shell sent by the UAV, and to build a second safety shell model of the safety shell based on the first image; the first image is an image taken by the UAV based on the initial flight path when the distance between the UAV and the safety shell is within a second preset distance range, and the upper limit of the second preset distance range is less than the lower limit of the first preset distance range.

[0128] The second determining module 1203 is used to determine the shooting parameters of the drone based on the camera resolution and the preset crack width.

[0129] The third determining module 1204 is used to determine the target flight path trajectory of the UAV based on the second containment model and the shooting parameters.

[0130] The second receiving module 1205 is used to receive a second image of the containment shell sent by the UAV; the second image is an image of the containment shell taken by the UAV according to the target flight path.

[0131] In one embodiment, the second determining module 1203 includes:

[0132] The first determining unit is used to determine the first size of the image captured by the UAV in the length direction based on the product of the pixels in the length direction corresponding to the resolution and the preset crack width.

[0133] The second determining unit is used to determine the second size of the image captured by the drone in the width direction based on the product of the pixels in the width direction corresponding to the resolution and the preset crack width.

[0134] The third determining unit is used to determine the shooting parameters of the drone based on the first size and the second size.

[0135] In one embodiment, the third determining unit includes:

[0136] The first determining subunit is used to determine the shooting distance between the drone and the containment shell based on the first and second dimensions.

[0137] The second determining subunit is used to determine the lateral overlap of the UAV based on the first dimension and the first cutting dimension in the preset length direction.

[0138] The third determining subunit is used to determine the heading overlap of the UAV based on the second dimension and the preset second cutting dimension in the width direction.

[0139] The fourth determining subunit is used to determine the movement distance of the UAV based on the lateral overlap, the forward overlap, the first dimension, and the second dimension.

[0140] The shooting parameters include shooting distance, lateral overlap, and drone movement distance.

[0141] In one embodiment, the second determining subunit is specifically used to determine a first ratio between the first cutting size and the first size, and to use the difference between the first preset value and the first ratio as the lateral overlap.

[0142] In one embodiment, the third determining subunit is specifically used to determine a second ratio between the second cutting size and the second size, and to use the difference between the second preset value and the second ratio as the heading overlap.

[0143] In one embodiment, the fourth determining subunit is specifically used to determine a first difference between a third preset value and a lateral overlap, and to determine a first product result of the first difference and a first dimension; to determine the horizontal movement distance of the UAV based on the first product result; to determine a second difference between the third preset value and a heading overlap, and to determine a second product result of the second difference and a second dimension; and to determine the vertical movement distance of the UAV based on the second product result; wherein the movement distance includes the horizontal movement distance and / or the vertical movement distance.

[0144] Each module in the aforementioned image acquisition device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0145] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 13 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores data. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements an image acquisition method.

[0146] Those skilled in the art will understand that Figure 13The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0147] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0148] The initial flight path of the UAV is determined based on the first safety shell model of the safety shell; the first safety shell model is a model determined by the images taken by the UAV along the preset flight path when the distance between the UAV and the safety shell is within a first preset distance range.

[0149] Receive a first image of the safety shell sent by the drone, and build a second safety shell model based on the first image; the first image is an image taken by the drone based on the initial flight path when the distance between the drone and the safety shell is within a second preset distance range, and the upper limit of the second preset distance range is less than the lower limit of the first preset distance range;

[0150] Determine the drone's shooting parameters based on the camera's resolution and the preset crack width;

[0151] The target flight path of the UAV is determined based on the second containment model and shooting parameters;

[0152] Receive a second image of the containment structure sent by the drone; the second image is an image of the containment structure taken by the drone according to the target flight path.

[0153] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0154] The first dimension of the image captured by the drone in the length direction is determined by multiplying the pixels in the length direction corresponding to the resolution with the preset crack width.

[0155] The second size of the image captured by the drone in the width direction is determined by multiplying the pixels in the width direction corresponding to the resolution with the preset crack width.

[0156] The drone's shooting parameters are determined based on the first and second dimensions.

[0157] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0158] Determine the shooting distance between the drone and the containment shell based on the first and second dimensions;

[0159] The lateral overlap of the drone is determined based on the first dimension and the preset first cutting dimension in the length direction;

[0160] The heading overlap of the UAV is determined based on the second dimension and the preset second cutting dimension in the width direction;

[0161] The movement distance of the UAV is determined based on the lateral overlap, the forward overlap, the first dimension, and the second dimension.

[0162] The shooting parameters include shooting distance, lateral overlap, and drone movement distance.

[0163] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0164] Determine a first ratio between the first cutting dimension and the first dimension;

[0165] The difference between the first preset value and the first ratio is used as the lateral overlap.

[0166] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0167] Determine a second ratio between the second cutting dimension and the second dimension;

[0168] The difference between the second preset value and the second ratio is taken as the heading overlap.

[0169] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0170] Determine the first difference between the third preset value and the lateral overlap, and determine the first product result of the first difference and the first dimension;

[0171] The horizontal movement distance of the UAV is determined based on the result of the first product.

[0172] Determine the second difference between the third preset value and the heading overlap, and determine the second product result of the second difference and the second dimension;

[0173] The vertical movement distance of the UAV is determined based on the result of the second product;

[0174] The distance traveled includes horizontal and / or vertical movement.

[0175] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0176] The initial flight path of the UAV is determined based on the first safety shell model of the safety shell; the first safety shell model is a model determined by the images taken by the UAV along the preset flight path when the distance between the UAV and the safety shell is within a first preset distance range.

[0177] Receive a first image of the safety shell sent by the drone, and build a second safety shell model based on the first image; the first image is an image taken by the drone based on the initial flight path when the distance between the drone and the safety shell is within a second preset distance range, and the upper limit of the second preset distance range is less than the lower limit of the first preset distance range;

[0178] Determine the drone's shooting parameters based on the camera's resolution and the preset crack width;

[0179] The target flight path of the UAV is determined based on the second containment model and shooting parameters;

[0180] Receive a second image of the containment structure sent by the drone; the second image is an image of the containment structure taken by the drone according to the target flight path.

[0181] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0182] The first dimension of the image captured by the drone in the length direction is determined by multiplying the pixels in the length direction corresponding to the resolution with the preset crack width.

[0183] The second size of the image captured by the drone in the width direction is determined by multiplying the pixels in the width direction corresponding to the resolution with the preset crack width.

[0184] The drone's shooting parameters are determined based on the first and second dimensions.

[0185] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0186] Determine the shooting distance between the drone and the containment shell based on the first and second dimensions;

[0187] The lateral overlap of the drone is determined based on the first dimension and the preset first cutting dimension in the length direction;

[0188] The heading overlap of the UAV is determined based on the second dimension and the preset second cutting dimension in the width direction;

[0189] The movement distance of the UAV is determined based on the lateral overlap, the forward overlap, the first dimension, and the second dimension.

[0190] The shooting parameters include shooting distance, lateral overlap, and drone movement distance.

[0191] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0192] Determine a first ratio between the first cutting dimension and the first dimension;

[0193] The difference between the first preset value and the first ratio is used as the lateral overlap.

[0194] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0195] Determine a second ratio between the second cutting dimension and the second dimension;

[0196] The difference between the second preset value and the second ratio is taken as the heading overlap.

[0197] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0198] Determine the first difference between the third preset value and the lateral overlap, and determine the first product result of the first difference and the first dimension;

[0199] The horizontal movement distance of the UAV is determined based on the result of the first product.

[0200] Determine the second difference between the third preset value and the heading overlap, and determine the second product result of the second difference and the second dimension;

[0201] The vertical movement distance of the UAV is determined based on the result of the second product;

[0202] The distance traveled includes horizontal and / or vertical movement.

[0203] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0204] The initial flight path of the UAV is determined based on the first safety shell model of the safety shell; the first safety shell model is a model determined by the images taken by the UAV along the preset flight path when the distance between the UAV and the safety shell is within a first preset distance range.

[0205] Receive a first image of the safety shell sent by the drone, and build a second safety shell model based on the first image; the first image is an image taken by the drone based on the initial flight path when the distance between the drone and the safety shell is within a second preset distance range, and the upper limit of the second preset distance range is less than the lower limit of the first preset distance range;

[0206] Determine the drone's shooting parameters based on the camera's resolution and the preset crack width;

[0207] The target flight path of the UAV is determined based on the second containment model and shooting parameters;

[0208] Receive a second image of the containment structure sent by the drone; the second image is an image of the containment structure taken by the drone according to the target flight path.

[0209] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0210] The first dimension of the image captured by the drone in the length direction is determined by multiplying the pixels in the length direction corresponding to the resolution with the preset crack width.

[0211] The second size of the image captured by the drone in the width direction is determined by multiplying the pixels in the width direction corresponding to the resolution with the preset crack width.

[0212] The drone's shooting parameters are determined based on the first and second dimensions.

[0213] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0214] Determine the shooting distance between the drone and the containment shell based on the first and second dimensions;

[0215] The lateral overlap of the drone is determined based on the first dimension and the preset first cutting dimension in the length direction;

[0216] The heading overlap of the UAV is determined based on the second dimension and the preset second cutting dimension in the width direction;

[0217] The movement distance of the UAV is determined based on the lateral overlap, the forward overlap, the first dimension, and the second dimension.

[0218] The shooting parameters include shooting distance, lateral overlap, and drone movement distance.

[0219] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0220] Determine a first ratio between the first cutting dimension and the first dimension;

[0221] The difference between the first preset value and the first ratio is used as the lateral overlap.

[0222] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0223] Determine a second ratio between the second cutting dimension and the second dimension;

[0224] The difference between the second preset value and the second ratio is taken as the heading overlap.

[0225] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0226] Determine the first difference between the third preset value and the lateral overlap, and determine the first product result of the first difference and the first dimension;

[0227] The horizontal movement distance of the UAV is determined based on the result of the first product.

[0228] Determine the second difference between the third preset value and the heading overlap, and determine the second product result of the second difference and the second dimension;

[0229] The vertical movement distance of the UAV is determined based on the result of the second product;

[0230] The distance traveled includes horizontal and / or vertical movement.

[0231] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0232] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0233] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0234] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. An image acquisition method, characterized in that, The method includes: The initial flight path of the UAV is determined based on the first safety shell model of the safety shell; the first safety shell model is a model determined by the images taken by the UAV along the preset flight path when the distance between the UAV and the safety shell is within a first preset distance range. The system receives a first image of the containment structure sent by the drone and establishes a second containment structure model based on the first image. The first image is an image taken by the drone based on the initial flight path when the distance between the drone and the containment structure is within a second preset distance range. The upper limit of the second preset distance range is less than the lower limit of the first preset distance range. The shooting parameters of the drone are determined based on the camera resolution and the preset crack width; The target flight path of the UAV is determined based on the second containment model and the shooting parameters; Receive a second image of the containment structure sent by the drone; the second image is an image of the containment structure taken by the drone according to the target flight path. The step of determining the drone's shooting parameters based on the camera's resolution and a preset crack width includes: The first size of the image captured by the drone in the length direction is determined based on the product of the pixels in the length direction corresponding to the resolution and the preset crack width. The second size of the image captured by the drone in the width direction is determined based on the product of the pixels in the width direction corresponding to the resolution and the preset crack width. The shooting parameters of the drone are determined based on the first size and the second size.

2. The method according to claim 1, characterized in that, Determining the shooting parameters of the drone based on the first size and the second size includes: Based on the first dimension and the second dimension, determine the shooting distance between the drone and the containment shell; The lateral overlap of the UAV is determined based on the first dimension and the preset first cutting dimension in the length direction; The heading overlap of the UAV is determined based on the second dimension and the preset second cutting dimension in the width direction; The movement distance of the UAV is determined based on the lateral overlap, the forward overlap, the first dimension, and the second dimension; The shooting parameters include the shooting distance, the lateral overlap, and the movement distance of the drone.

3. The method according to claim 2, characterized in that, Determining the lateral overlap of the drone based on the first dimension and a preset first cutting dimension in the length direction includes: Determine a first ratio between the first cutting size and the first size; The difference between the first preset value and the first ratio is taken as the lateral overlap.

4. The method according to claim 2, characterized in that, Determining the heading overlap of the UAV based on the second dimension and a preset second cutting dimension in the width direction includes: Determine a second ratio between the second cutting dimension and the second dimension; The difference between the second preset value and the second ratio is taken as the heading overlap.

5. The method according to claim 2, characterized in that, Determining the movement distance of the UAV based on the lateral overlap, the forward overlap, the first dimension, and the second dimension includes: Determine a first difference between a third preset value and the lateral overlap, and determine a first product of the first difference and the first size; The horizontal movement distance of the UAV is determined based on the first product result; Determine a second difference between the third preset value and the heading overlap, and determine a second product result of the second difference and the second dimension; The vertical movement distance of the UAV is determined based on the result of the second product; The moving distance includes the horizontal moving distance and / or the vertical moving distance.

6. An image acquisition device, characterized in that, The device includes: The first determining module is used to determine the initial flight path of the UAV based on the first safety shell model of the safety shell; the first safety shell model is a model determined based on the images taken by the UAV along the preset flight path when the distance between the UAV and the safety shell is within a first preset distance range. A first receiving module is configured to receive a first image of the safety shell sent by the UAV, and to establish a second safety shell model of the safety shell based on the first image; the first image is an image taken by the UAV based on the initial flight path when the distance between the UAV and the safety shell is within a second preset distance range, and the upper limit of the second preset distance range is less than the lower limit of the first preset distance range; The second determining module is used to determine the shooting parameters of the drone based on the camera resolution and the preset crack width; The third determining module is used to determine the target flight path of the UAV based on the second containment model and the shooting parameters; The second receiving module is used to receive a second image of the containment structure sent by the UAV; the second image is an image of the containment structure taken by the UAV according to the target flight path. The step of determining the drone's shooting parameters based on the camera's resolution and a preset crack width includes: The first size of the image captured by the drone in the length direction is determined based on the product of the pixels in the length direction corresponding to the resolution and the preset crack width. The second size of the image captured by the drone in the width direction is determined based on the product of the pixels in the width direction corresponding to the resolution and the preset crack width. The shooting parameters of the drone are determined based on the first size and the second size.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

Images