Paper cup production quality inspection system based on image recognition

Abstract

The invention discloses a paper cup production quality inspection system based on image recognition, which belongs to the technical field of paper cup production quality inspection and comprises a production analysis module, an acquisition module and a quality inspection module. The production analysis module is used for analyzing the paper cup production line, obtaining production line information of the paper cup production line and collecting a paper cup production video of the paper cup production line; setting a paper cup production model of paper cup production according to the paper cup production video and the production line information; determining image acquisition areas of the paper cups according to the paper cup production model, and installing and debugging acquisition equipment according to the image acquisition areas; the acquisition module is used for performing real-time image acquisition in a paper cup production process, acquiring acquired images of each image acquisition area, setting corresponding paper cup marks for each acquired image, and sending each acquired image to the quality inspection module; and the quality inspection module is used for carrying out quality inspection on the received acquired images to obtain a quality inspection model, and carrying out quality inspection on the acquired images through the quality inspection model to obtain quality inspection results of the images.

Description

Technical Field

[0001] The present invention belongs to the technical field of paper cup production quality inspection, and in particular is a paper cup production quality inspection system based on image recognition. Background Art

[0002] During the production process of paper cups, paper cups are often in a state of continuous movement, which poses a challenge to intelligent quality inspection based on image recognition. Traditional quality inspection methods usually rely on manual sampling inspection, which is not only inefficient, but also easily affected by human factors, resulting in inaccurate quality inspection results. As the degree of automation of paper cup production lines continues to increase, the production speed of paper cups is also getting faster and faster, and traditional quality inspection methods can no longer meet the needs of production lines. In particular, many current production equipment is not equipped with quality inspection equipment, resulting in the inability of existing quality inspection capabilities to meet production needs.

[0003] Based on this, in order to achieve efficient quality inspection of paper cup production, the present invention provides a paper cup production quality inspection system based on image recognition. Summary of the invention

[0004] In order to solve the problems existing in the above solutions, the present invention provides a paper cup production quality inspection system based on image recognition.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A paper cup production quality inspection system based on image recognition, including a production analysis module, a collection module and a quality inspection module; The production analysis module is used to analyze the paper cup production line, obtain the production line information of the paper cup production line, and collect the paper cup production video of the paper cup production line; and set the paper cup production model of the paper cup production according to the paper cup production video and the production line information; The image acquisition areas of the paper cup are determined according to the paper cup production model, and the acquisition equipment is installed and debugged according to the image acquisition areas.

[0006] Further, the method of setting a paper cup production model for paper cup production according to the paper cup production video and production line information includes: Acquire design information of the paper cup, and set a paper cup model according to the design information; determine a production path of the paper cup according to the paper cup production video and the production line information, and set a moving path of the paper cup model according to the production path; Determining rotation data of the paper cup model at each position in the moving path according to the paper cup production video; The paper cup model is moved along the moving path, and rotation adjustment is performed during the movement of the paper cup model according to the rotation data of each position in the moving path to form several groups of model movement processes of the paper cup model, and a paper cup production model is established according to each model movement process.

[0007] Furthermore, the method for determining each image acquisition area of ​​the paper cup according to the paper cup production model includes: Screening and adjusting the paper cup production model, identifying the rotation atlas of each position of the moving path in the paper cup production model, merging each position in the moving path according to each rotation atlas, and obtaining each unit segment; determining the unit atlas of each unit segment according to the movement process of each model, wherein the unit atlas is composed of each unit image; Setting collection requirements, determining the installation positions and collection ranges of the installation positions according to the paper cup production model, performing collection simulation according to the installation positions, collection requirements and unit atlas, and determining the installation modes to be selected; The candidate installation methods are screened to determine a target installation method, and the image acquisition areas are determined according to the target installation method.

[0008] Furthermore, the method for screening and adjusting the paper cup production model includes: Determine a moving path where image acquisition cannot be performed according to the production line information, mark it as a shielding segment, and make corresponding marks in the paper cup production model according to the shielding segment; The quality inspection requirements of the paper cup image are obtained, and a conformity assessment model is established according to the quality inspection requirements. The expression of the conformity assessment model is: ; Where: s is the input data, the input data is the paper cup image, the output data is the image evaluation value HG(s), and the image evaluation value is 1 or 2; Identify the rotation data of each position of the moving path in the paper cup production model, evaluate each rotation data through the qualified evaluation model, remove each paper cup image with an image evaluation value of 2 from the rotation data, and obtain a rotation atlas; complete the screening and adjustment of the paper cup production model.

[0009] Furthermore, the method for merging the positions in the moving path according to the rotation atlases includes: Step SA1: The platform establishes a quality inspection model, taking the starting point of each production link of the moving path as the initial point; simulates and adjusts the rotation atlas of each position to obtain the quality inspection simulation data corresponding to each position; Step SA2: Mark the positions adjacent to the initial point as evaluation points. When there are no evaluation points, end the analysis. Identify the quality inspection simulation data corresponding to the initial point and the evaluation point respectively; perform quality inspection effect evaluation on the quality inspection simulation data corresponding to the initial point and the evaluation point through the quality inspection model to obtain the corresponding quality inspection effect results, including whether the effect does not meet the requirements and whether the effect meets the requirements; Step SA3: When the quality inspection result shows that the effect meets the requirements, the initial point and the corresponding evaluation point are merged to obtain the initial segment, and then step SA4 is entered; When the quality inspection result is that the effect does not meet the requirements, the initial point is marked as a unit segment, the evaluation point is marked as the initial point, and the process returns to step SA2; Step SA4: Mark the position adjacent to the initial segment as an evaluation point, identify the quality inspection simulation data corresponding to the initial segment and the evaluation point respectively; perform quality inspection effect evaluation on the quality inspection simulation data corresponding to the initial segment and the evaluation point through the quality inspection model to obtain the corresponding quality inspection effect result; Step SA5: When the quality inspection result shows that the effect meets the requirements, the initial segment and the corresponding evaluation point are merged to obtain a new initial segment; When the quality inspection result is that the effect does not meet the requirements, the initial segment is marked as a unit segment, the evaluation point is marked as the initial point, and the process returns to step SA2; Step SA6: Loop step SA5.

[0010] Furthermore, after the acquisition equipment is installed and debugged, real-time production analysis is performed and corresponding production control early warnings are issued.

[0011] Furthermore, the method for performing production analysis and production control early warning includes: Acquire the full-process images of the paper cups corresponding to different control parameters of each production link in real time, and calculate the acquisition completeness rate of the full-process images of the paper cups; According to the formula Calculate the corresponding quality inspection value; Where: PA is the quality inspection value; δ is the collection completeness rate; Taking the control parameters of each production link as the independent variable and the quality inspection value as the dependent variable to form each quality inspection coordinate point, each quality inspection coordinate point is input into the coordinate space in real time, and the coordinate space is dynamically updated according to the production of paper cups; real-time control and early warning are carried out according to the preset quality inspection limit and coordinate space.

[0012] Furthermore, the quality inspection value ranges from [0, 10].

[0013] The acquisition module is used to perform real-time image acquisition during the paper cup production process, obtain the acquired images of each image acquisition area, set a corresponding paper cup mark for each acquired image, and send each acquired image to the quality inspection module.

[0014] The quality inspection module is used to perform quality inspection on each received collected image, obtain a quality inspection model, perform quality inspection on each collected image through the quality inspection model, obtain quality inspection results of each image, integrate the quality inspection results of each image corresponding to the paper cup, and obtain a comprehensive quality inspection result corresponding to the paper cup; and perform corresponding sorting processing according to the comprehensive quality inspection result.

[0015] Compared with the prior art, the present invention has the following beneficial effects: Through the cooperation among the production analysis module, acquisition module and quality inspection module, intelligent quality inspection of paper cup production is realized. At the same time, intelligent analysis is carried out on many existing paper cup production lines without intelligent quality inspection, and the quality inspection method is optimized to achieve efficient quality inspection based on image recognition. At the same time, the control parameters can be intelligently adjusted according to the quality inspection requirements without affecting the production of paper cups, ensuring the quality inspection of paper cups during high-speed production processes. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0018] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] like Figure 1 As shown, a paper cup production quality inspection system based on image recognition includes a production analysis module, a collection module and a quality inspection module; The production analysis module is used to analyze the current paper cup production line, obtain production line information of the paper cup production line, and the production line information includes relevant information such as production process and information of each production equipment; obtain the paper cup production video of the paper cup production line, and it is not necessary to collect the corresponding paper cup production video for the production process blocked by the equipment; set a paper cup production model for paper cup production according to the paper cup production video and production line information, and the paper cup production model is used to display the movement process of the paper cup model during the production process; Determine each image acquisition area of ​​the paper cup according to the paper cup production model; install and debug the acquisition equipment according to each image acquisition area.

[0020] In one embodiment, the method of setting the paper cup production model for paper cup production according to the paper cup production video and the production line information is to set it based on the existing technology, such as manually set by the staff of the platform.

[0021] In one embodiment, a method for setting a paper cup production model for paper cup production based on a paper cup production video and production line information includes: Obtain design information of the paper cup, including size, pattern and other related information, and set a paper cup model according to the design information. The paper cup model is a three-dimensional visualization model established based on existing modeling technology; Determine the production path of the paper cups according to the paper cup production video and production line information, and set the moving path of the paper cup model according to the production path; According to the paper cup production video, various possible rotation situations of the paper cup model during the movement are determined. The statistics are mainly conducted according to each production link to form various possible rotation situations of each production link. Because the paper cups in some production links will have a certain rotation, while the paper cups in some production links will not rotate, it is possible to conduct statistics based on the paper cup production video to determine the rotation situation of each production link, and determine the rotation data based on the rotation situation, that is, determine the possible collected paper cup images based on the rotation situation and the paper cup images, and integrate them into the rotation data; Move the paper cup model along the moving path, and perform rotation adjustment during the moving process of the paper cup model according to the rotation data of each production link, so as to form several groups of model moving processes of the paper cup model, which need to be listed in full, and establish a paper cup production model according to the moving process of each model; that is, randomly display the moving process of each model through the paper cup production model, and randomly display the next one after one ends, but the possible image of the paper cup model at the corresponding position in the moving path can be determined, and the moving process of each model at that position can be determined by integrating.

[0022] In one implementation, the method for determining each image acquisition area of ​​a paper cup according to a paper cup production model includes: Screen and adjust the paper cup production model, that is, screen out the situations that do not need to be analyzed, reduce the amount of data processing, and improve efficiency; Identify the rotation atlas of each position of the moving path in the paper cup production model, merge each position in the moving path according to each rotation atlas, obtain each unit segment, identify the rotation atlas of each position corresponding to the unit segment, merge the paper cup images of each position in the same process according to the corresponding model moving process, form a new merged image, mark it as a unit image, and use the paper cup image corresponding to the midpoint position as the reference image to supplement the paper cup images that are not in the reference image; each unit image forms a unit atlas; Set the acquisition requirements. The acquisition requirements are that the image of the entire paper cup needs to be completely acquired. The overall image formed by merging the acquired images also meets the acquisition requirements. Determine the installation positions and the acquisition range of each installation position according to the paper cup production model, perform acquisition simulation according to each installation position, acquisition requirements and unit atlas, and determine the installation methods to be selected; that is, simulate the image acquisition equipment at each installation position in the paper cup production model, crop each unit atlas according to the acquisition range, and judge whether the cropped unit atlas can guarantee the acquisition of a complete paper cup image according to the acquisition requirements. Judge according to the movement process of each model, that is, each model movement process needs to meet the acquisition requirements, and mark each installation method that meets the acquisition requirements as a candidate installation method; Screen the candidate installation methods, determine the target installation method, determine the image acquisition areas according to the acquisition range of the target installation method, and then install and debug the acquisition equipment according to the image acquisition area to ensure the image acquisition area is acquired.

[0023] In one embodiment, the method for screening and adjusting the paper cup production model includes: According to the production line information, the moving paths that cannot be used for image acquisition are determined and marked as shielded segments. According to the shielded segments, corresponding marks are made in the paper cup production model, indicating that the data of the shielded segments do not need to be analyzed later; The quality inspection requirements of paper cup images are obtained, that is, what requirements the paper cup images need to meet, such as clarity, etc. A qualified evaluation model is established according to the quality inspection requirements. The qualified evaluation model is used to evaluate the quality inspection requirements of the corresponding paper cup images and determine whether the paper cup images meet the quality inspection requirements. Because some images of paper cups cannot be used for quality inspection and evaluation during movement and rotation, they need to be eliminated to avoid the subsequent inability to fully collect paper cup images. The expression of the qualified evaluation model is: ; Where: s is the input data, the input data is the paper cup image, the output data is the image evaluation value HG(s), and the image evaluation value is 1 or 2; Identify the rotation data of each position of the moving path in the paper cup production model, evaluate each rotation data through the qualified evaluation model, remove each paper cup image with an image evaluation value of 2 from the corresponding rotation data, and mark the existing rotation data as a rotation atlas; complete the screening and adjustment of the paper cup production model.

[0024] In one embodiment, the method for merging the positions in the moving path according to the rotation atlases is based on the existing technology.

[0025] In one embodiment, the method for merging positions in the moving path according to the rotation atlases includes: Step SA1: The platform establishes a quality inspection model. The quality inspection model is established based on existing technology and is used to inspect the paper cup image to determine whether there are quality inspection problems. It is established based on existing image recognition technology, etc. Since there are mature image recognition models, it will not be described in detail. The starting point of each production link of the moving path is taken as the initial point; the rotating atlas of each position is simulated and adjusted to obtain the quality inspection simulation data corresponding to each position, that is, assuming that a certain position of the paper cup has a corresponding quality inspection problem, each rotating atlas is adjusted synchronously to form a rotating atlas of multiple quality inspection situations, which are integrated into the quality inspection simulation data of the position; Step SA2: Mark the positions adjacent to the initial point as evaluation points; when there are no evaluation points, end the analysis; Identify the quality inspection simulation data corresponding to the initial point and the evaluation point respectively; The quality inspection model is used to evaluate the quality inspection effect of the quality inspection simulation data corresponding to the initial point and the evaluation point, and the corresponding quality inspection effect results are obtained, including the effect that does not meet the requirements and the effect that meets the requirements. That is, the quality inspection model is used to analyze whether the quality inspection effects of the collected images at the two positions are the same. Because many collected images at two adjacent positions are basically the same, the quality inspection effects are the same, and the evaluation can be carried out according to the corresponding model movement process. The same two results can be regarded as the same quality inspection effect, or there can be a certain proportion deviation. The specific settings are based on the needs. Position merging is mainly used to reduce the amount of data analysis and improve analysis efficiency in the future; Step SA3: When the quality inspection result shows that the effect meets the requirements, the initial point and the corresponding evaluation point are merged to obtain the initial segment, and then step SA4 is entered; When the quality inspection result is that the effect does not meet the requirements, the initial point is independently marked as a unit segment, and the corresponding evaluation point is marked as the initial point, that is, the evaluation point for effect evaluation with the above initial point, and return to step SA2; Step SA4: Mark the positions adjacent to the initial segment as evaluation points, identify the quality inspection simulation data corresponding to the initial segment and the evaluation points respectively, and the quality inspection simulation data of the initial segment is the collection of quality inspection simulation data corresponding to each position; that is, the subsequent merging can only be performed if the effects between each position in the initial segment and the evaluation points meet the requirements; The quality inspection model is used to evaluate the quality inspection effect of the quality inspection simulation data corresponding to the initial segment and the evaluation point, and the corresponding quality inspection effect results are obtained; Step SA5: When the quality inspection result shows that the effect meets the requirements, the initial segment and the corresponding evaluation point are merged to obtain a new initial segment; When the quality inspection result is that the effect does not meet the requirements, the initial segment is marked as a unit segment, the corresponding evaluation point is marked as the initial point, and the process returns to step SA2; Step SA6: Loop step SA5.

[0026] In one embodiment, the various installation methods to be selected are screened using existing methods, such as evaluating based on evaluation parameters such as cost, clarity, and fault tolerance, calculating priority values ​​in combination with corresponding weight coefficients, and screening can also be performed based on other existing technologies.

[0027] In one embodiment, after the acquisition equipment is installed and debugged, production analysis is performed to obtain the full-process images of the paper cups corresponding to different control parameters of each production link in real time, that is, the overall mosaic of the paper cup images acquired by each image acquisition area, and calculate the acquisition completeness rate of the full-process images of the paper cups, that is, the completeness rate compared with the designed overall image; According to the formula Calculate the corresponding quality inspection value; where: PA is the quality inspection value, and the value range of the quality inspection value is [0, 10]; δ is the acquisition completeness rate; Taking the control parameters of each production link as the independent variable and the quality inspection value as the dependent variable to form each quality inspection coordinate point, each quality inspection coordinate point is input into the coordinate space in real time, and the coordinate space is dynamically updated according to the production of paper cups; Get the quality inspection value that needs to be achieved set by the user, mark it as the quality inspection limit, and make real-time control warnings based on the quality inspection limit and coordinate space. That is, when the control parameters are about to fall below the quality inspection limit again, make corresponding control warnings.

[0028] The acquisition module is used to perform real-time image acquisition during the paper cup production process, obtain the acquired images of each image acquisition area, and mark each acquired image with a corresponding paper cup mark to indicate which paper cup the acquired image belongs to; and send each acquired image to the quality inspection module.

[0029] The quality inspection module is used to perform quality inspection on each received collected image, obtain a quality inspection model, perform quality inspection on each collected image through the quality inspection model, obtain corresponding image quality inspection results, integrate the quality inspection results of each image corresponding to the paper cup, and obtain a comprehensive quality inspection result corresponding to the paper cup; and perform corresponding sorting processing according to the obtained comprehensive quality inspection result.

[0030] The above formulas are all calculated by removing dimensions and taking their numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0031] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A paper cup production quality inspection system based on image recognition, characterized in that: Including production analysis module, acquisition module and quality inspection module; The production analysis module is used to analyze the paper cup production line, obtain the production line information of the paper cup production line, and collect the paper cup production video of the paper cup production line; and set the paper cup production model of the paper cup production according to the paper cup production video and the production line information; Determine each image acquisition area of ​​the paper cup according to the paper cup production model, and install and debug the acquisition equipment according to the image acquisition area; The acquisition module is used to perform real-time image acquisition during the paper cup production process, obtain the acquired images of each image acquisition area, set a corresponding paper cup mark for each acquired image, and send each acquired image to the quality inspection module; The quality inspection module is used to perform quality inspection on each received collected image, obtain a quality inspection model, perform quality inspection on each collected image through the quality inspection model, obtain quality inspection results of each image, integrate the quality inspection results of each image corresponding to the paper cup, and obtain a comprehensive quality inspection result corresponding to the paper cup; Carry out corresponding sorting processing according to the comprehensive quality inspection results.

2. A paper cup production quality inspection system based on image recognition according to claim 1, characterized in that: The method for setting a paper cup production model for paper cup production according to paper cup production video and production line information includes: Acquire design information of the paper cup, and set a paper cup model according to the design information; determine a production path of the paper cup according to the paper cup production video and the production line information, and set a moving path of the paper cup model according to the production path; Determining rotation data of the paper cup model at each position in the moving path according to the paper cup production video; The paper cup model is moved along the moving path, and rotation adjustment is performed during the movement of the paper cup model according to the rotation data of each position in the moving path to form several groups of model movement processes of the paper cup model, and a paper cup production model is established according to each model movement process.

3. The paper cup production quality inspection system based on image recognition according to claim 1, characterized in that: The method for determining each image acquisition area of ​​a paper cup according to a paper cup production model includes: Screening and adjusting the paper cup production model, identifying the rotation atlas of each position of the moving path in the paper cup production model, merging each position in the moving path according to each rotation atlas, and obtaining each unit segment; determining the unit atlas of each unit segment according to the movement process of each model, wherein the unit atlas is composed of each unit image; Setting collection requirements, determining the installation positions and collection ranges of the installation positions according to the paper cup production model, performing collection simulation according to the installation positions, collection requirements and unit atlas, and determining the installation modes to be selected; The candidate installation methods are screened to determine a target installation method, and the image acquisition areas are determined according to the target installation method.

4. The paper cup production quality inspection system based on image recognition according to claim 3 is characterized in that: Methods for screening and adjusting the paper cup production model include: Determine a moving path where image acquisition cannot be performed according to the production line information, mark it as a shielding segment, and make corresponding marks in the paper cup production model according to the shielding segment; The quality inspection requirements of the paper cup image are obtained, and a conformity assessment model is established according to the quality inspection requirements. The expression of the conformity assessment model is: ; Where: s is the input data, the input data is the paper cup image, the output data is the image evaluation value HG(s), and the image evaluation value is 1 or 2; Identify the rotation data of each position of the moving path in the paper cup production model, evaluate each rotation data through the qualified evaluation model, remove each paper cup image with an image evaluation value of 2 from the rotation data, and obtain a rotation atlas; complete the screening and adjustment of the paper cup production model.

5. The paper cup production quality inspection system based on image recognition according to claim 3 is characterized in that: Methods for merging positions in the moving path according to the rotation atlases include: Step SA1: The platform establishes a quality inspection model, taking the starting point of each production link of the moving path as the initial point; simulates and adjusts the rotation atlas of each position to obtain the quality inspection simulation data corresponding to each position; Step SA2: Mark the positions adjacent to the initial point as evaluation points. When there are no evaluation points, end the analysis. Identify the quality inspection simulation data corresponding to the initial point and the evaluation point respectively; perform quality inspection effect evaluation on the quality inspection simulation data corresponding to the initial point and the evaluation point through the quality inspection model to obtain the corresponding quality inspection effect results, including whether the effect does not meet the requirements and whether the effect meets the requirements; Step SA3: When the quality inspection result shows that the effect meets the requirements, the initial point and the corresponding evaluation point are merged to obtain the initial segment, and then step SA4 is entered; When the quality inspection result is that the effect does not meet the requirements, the initial point is marked as a unit segment, the evaluation point is marked as the initial point, and the process returns to step SA2; Step SA4: Mark the position adjacent to the initial segment as an evaluation point, identify the quality inspection simulation data corresponding to the initial segment and the evaluation point respectively; perform quality inspection effect evaluation on the quality inspection simulation data corresponding to the initial segment and the evaluation point through the quality inspection model to obtain the corresponding quality inspection effect result; Step SA5: When the quality inspection result shows that the effect meets the requirements, the initial segment and the corresponding evaluation point are merged to obtain a new initial segment; When the quality inspection result is that the effect does not meet the requirements, the initial segment is marked as a unit segment, the evaluation point is marked as the initial point, and the process returns to step SA2; Step SA6: Loop step SA5.

6. The paper cup production quality inspection system based on image recognition according to claim 1, characterized in that: After the acquisition equipment is installed and debugged, real-time production analysis is carried out and corresponding production control early warnings are issued.

7. The paper cup production quality inspection system based on image recognition according to claim 6, characterized in that: Methods for production analysis and production control early warning include: Acquire the full-process images of the paper cups corresponding to different control parameters of each production link in real time, and calculate the acquisition completeness rate of the full-process images of the paper cups; According to the formula Calculate the corresponding quality inspection value; Where: PA is the quality inspection value; δ is the collection completeness rate; Taking the control parameters of each production link as the independent variable and the quality inspection value as the dependent variable to form each quality inspection coordinate point, each quality inspection coordinate point is input into the coordinate space in real time, and the coordinate space is dynamically updated according to the production of paper cups; real-time control and early warning are carried out according to the preset quality inspection limit and coordinate space.

8. The paper cup production quality inspection system based on image recognition according to claim 7, characterized in that: The quality inspection value range is [0, 10].

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