TWI795708B - Method and device for determining plant growth height, computer device and medium - Google Patents

Abstract

The present application relates to an image analysis technology, and the present application provides a method and a device for determining a plant growth height, a computer device and a medium. The method controls a camera device to shoot a detecting plant, and obtains a color image of the detecting plant and a depth image of the detecting plant, aligns the color image with the depth image to obtain an alignment image, uses a pre-trained mobilenet-ssd network to detect the color image, and obtains the detection box including the detecting plant, determines a depth of pixel points in the detection box according to the alignment image, de-noises the depth to obtain a target depth, uses a normal distribution algorithm to determine a mean and a standard deviation in the target depth, and determines a height of the detecting plant according to the mean and the standard deviation. This present application can improve an accuracy of the height of the plant.

Description

Method, device, computer device and medium for determining plant growth height

The present application relates to the technical field of image analysis, in particular to a method, device, computer device and medium for determining the height of plant growth.

At present, by analyzing the daily growth of plants, it is helpful to determine the best planting method of plants, so as to improve the yield and quality of plants, thereby reducing planting costs and bringing good news to growers. Because the existing methods for determining the growth height of plants are prone to image damage and noise during image alignment processing, which leads to inaccurate determination of the growth height of plants. Therefore, how to accurately determine the growth height of plants has become an urgent problem. The problem.

In view of the above, it is necessary to provide a method, device, computer device and medium for determining the growth height of plants, which can accurately determine the growth height of plants.

A method for determining the growth height of a plant, which is applied to a computer device, and the computer device is connected to a camera device. The method for determining the growth height of a plant includes: when a height determination request is received, determining the plant to be detected according to the height determination request ; controlling the camera device to photograph the plant to be detected, to obtain a color image and a depth image of the plant to be detected; Align the color image with the depth image to obtain an aligned image; utilize the pre-trained mobilenet-ssd network to detect the color image to obtain a detection frame with the plant to be detected; Determining the depth values of all pixels in the detection frame according to the aligned image; performing denoising processing on the depth values to obtain a target depth value; using a normal distribution algorithm to determine the average value and the target depth value Standard deviation: determine the height of the plant to be detected according to the average value and the standard deviation.

According to an optional embodiment of the present application, the determining the plant to be detected according to the height determination request includes: obtaining all idle threads from a preset thread connection pool; determining the processing rate of each idle thread, and setting the processing rate to Determine the highest idle execution thread as the target idle execution thread; use the target idle execution thread to parse the method body of the height determination request, and obtain all the information carried by the height determination request; obtain the default label, from the all information Obtain the information corresponding to the preset label as the plant identification; determine the plant to be detected according to the plant identification.

According to an optional embodiment of the present application, the controlling the camera device to photograph the plant to be detected, and obtaining the color image and the depth image of the plant to be detected includes: determining the first location where the plant to be detected is located. orientation; control the first lens of the imaging device to move to a second orientation corresponding to the first orientation, and control the first lens to take pictures to obtain the color image; control the second lens of the imaging device The lens is moved to the second orientation, and the second lens is controlled to take pictures to obtain the depth image.

According to an optional embodiment of the present application, the aligning the color image and the depth image to obtain the aligned image includes: Acquire all depth pixels on the depth image; map all depth pixels to a preset depth coordinate system to obtain depth coordinates of all depth pixels; determine the depth coordinates according to all depth coordinates and the preset world coordinate system The world coordinates of all depth pixels; determine the positions of all depth pixels on the color image according to all world coordinates, and determine the color pixels at the positions on the color image; combine each depth pixel with each color pixels are fused to obtain the aligned image.

According to an optional embodiment of the present application, using the pre-trained mobilenet-ssd network to detect the color image, and obtaining the detection frame with the plant to be detected includes: obtaining the mobilenet-ssd network in the A depth convolution kernel and a point convolution kernel; using the depth convolution kernel to extract features of the color image to obtain a feature map; using the point convolution kernel to process the feature map to obtain the detection frame.

According to an optional embodiment of the present application, the performing denoising processing on the depth value to obtain the target depth value includes: obtaining a depth value equal to a preset value from the depth value, and determining the obtained depth value as zero value; delete the zero value from the depth value, and determine the remaining depth value as the target depth value.

According to an optional embodiment of the present application, the determining the height of the plant to be detected according to the average value and the standard deviation includes: adding the average value and the standard deviation to obtain a first value; Subtracting the average value from the standard deviation to obtain a second value; calculating the average value of the first value and the second value to obtain a target value; determining the camera height at the location of the camera device ; Subtracting the camera height from the target value to obtain the plant to be detected height of the object.

A plant growth height determination device, running in a computer device, the computer device is connected to a camera device, and the plant growth height determination device includes: a determination unit, used to determine according to the height when a height determination request is received Request to determine the plant to be detected; the control unit is used to control the camera to take pictures of the plant to be detected to obtain the color image and depth image of the plant to be detected; the processing unit is used to convert the color image Image is aligned with the depth image to obtain an aligned image; a detection unit is used to detect the color image using a pre-trained mobilenet-ssd network to obtain a detection frame with the plant to be detected; The determining unit is further configured to determine depth values of all pixels in the detection frame according to the aligned image; the processing unit is further configured to perform denoising processing on the depth values to obtain a target depth value; The determination unit is also used to determine the average value and standard deviation of the target depth value by using a normal distribution algorithm; the determination unit is also used to determine the target depth value according to the average value and the standard deviation. the height of the plant.

A computer device, the computer device comprising: a memory storing at least one instruction; and a processor executing the instruction stored in the memory to implement the method for determining the plant growth height.

A computer-readable storage medium, wherein at least one instruction is stored in the computer-readable storage medium, and the at least one instruction is executed by a processor in a computer device to implement the method for determining plant growth height.

It can be seen from the above technical solutions that the present application determines the plants to be detected according to the height determination request, can accurately determine the plants to be detected that need height measurement, and then controls the camera to take pictures of the plants to be detected, and obtains the The color image and depth image of the plant to be detected are beneficial to the determination of the plant to be detected. By performing denoising processing on the depth value, a target depth value that does not contain noise can be obtained, reducing image alignment processing. When the interference caused by image damage occurs, the normal distribution algorithm is used to determine the average value and standard deviation of the target depth value, and the height of the plant to be detected is determined according to the average value and the standard deviation, which can The determination accuracy of the growth height of the plant to be detected is improved.

S10~S17: Steps

11: Plant growth height determination device

110: determine unit

111: Control unit

112: Processing unit

113: detection unit

114: Generate unit

115: encryption unit

116: sending unit

1: computer device

12: Storage

13: Processor

2: camera device

20: First shot

21: Second shot

Fig. 1 is an application environment diagram of a preferred embodiment of the method for determining the height of plant growth of the present application.

Fig. 2 is a flow chart of a preferred embodiment of the method for determining the plant growth height of the present application.

Fig. 3 is a functional module diagram of a preferred embodiment of the plant growth height determination device of the present application.

Fig. 4 is a structural schematic diagram of a computer device for implementing a preferred embodiment of the method for determining plant growth height in the present application.

In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

As shown in FIG. 1 , it is an application environment diagram of a preferred embodiment of the method for determining the height of plant growth in the present application. The camera device 2 communicates with the computer device 1 , and the camera device 2 includes a first lens 20 and a second lens 21 . A color image can be captured through the first lens 20 , and a depth image can be captured through the second lens 21 .

As shown in FIG. 2 , it is a flow chart of a preferred embodiment of the method for determining the height of plant growth of the present application. According to different requirements, the order of the steps in the flowchart can be changed, and some steps can be omitted.

The method for determining plant growth height is applied to one or more computer devices 1, and the computer device 1 is a device that can automatically perform numerical calculation and/or information processing according to preset or stored instructions, and its hardware includes But not limited to microprocessors, Application Specific Integrated Circuits (ASICs), Programmable Gate Arrays (Field-Programmable Gate Arrays, FPGAs), Digital Signal Processors (Digital Signal Processors, DSPs), embedded devices wait.

The computer device 1 can be any electronic product capable of man-machine interaction with the user, for example, a personal computer, a tablet computer, a smart phone, a personal digital assistant (Personal Digital Assistant, PDA), a game console, an interactive network TV (Internet Protocol Television, IPTV), smart wearable devices, etc.

The computer device 1 may also include network equipment and/or user equipment. Wherein, the network device includes, but is not limited to, a single network server, a server group composed of multiple network servers, or a cloud composed of a large number of hosts or network servers based on Cloud Computing.

The network where the computer device 1 is located includes but not limited to Internet, wide area network, metropolitan area network, local area network, virtual private network (Virtual Private Network, VPN) and so on.

In at least one embodiment of the present application, the present application is applied to a computer device, and the computer device is connected to a camera device.

Step S10, when a height determination request is received, the plant to be detected is determined according to the height determination request.

In at least one embodiment of the present application, the information carried in the altitude determination request includes: a preset label, a plant identification, and the like.

Further, the plant to be detected can be any plant whose daily growth needs to be analyzed, for example: rose, sunflower, rice, etc.

In at least one embodiment of the present application, the computer device determining the plant to be detected according to the height determination request includes: obtaining all idle threads from a preset thread connection pool; Determine the processing rate of each idle execution thread, and determine the idle execution thread with the highest processing rate as the target idle execution thread; use the target idle execution thread to parse the method body of the height determination request, and obtain the height determination request carried all the information; obtain preset tags, and obtain information corresponding to the preset tags from all the information as plant identifiers; determine the plants to be detected according to the plant identifiers.

Through the preset mapping relationship between tags and plant identifiers, the plant identifiers can be accurately obtained, and thus the plants to be detected can be accurately determined.

Step S11 , controlling the camera device to take pictures of the plants to be detected to obtain a color image and a depth image of the plants to be detected.

In at least one embodiment of the present application, the color image refers to an RGB three-channel color image, and the depth image refers to an image in which the distance from the camera to each point in the scene is used as a pixel value .

In at least one embodiment of the present application, the computer device controls the camera device to photograph the plant to be detected, and obtaining the color image and depth image of the plant to be detected includes: determining the plant to be detected The first orientation where it is located; control the first lens of the camera to move to a second orientation corresponding to the first orientation, and control the first lens to take pictures to obtain the color image; control the camera The second lens of the device is moved to the second orientation, and the second lens is controlled to take pictures to obtain the depth image.

Wherein, the camera device includes two lenses, which are respectively the first lens and the second lens. The camera device can be installed directly above the detected plants to facilitate shooting.

Through the above embodiments, the color image and the depth image including the plant to be detected can be quickly obtained.

Step S12, aligning the color image and the depth image to obtain an aligned image.

In at least one embodiment of the present application, the alignment image refers to an image generated by fusing pixels of the color image and pixels of the depth image.

In at least one embodiment of the present application, the computer device performs alignment processing on the color image and the depth image, and obtaining the alignment image includes: obtaining all depth pixels on the depth image; Map all the depth pixels to the preset depth coordinate system to obtain the depth coordinates of all the depth pixels; determine the world coordinates of all the depth pixels according to all the depth coordinates and the preset world coordinate system; determine the Positions of all depth pixels on the color image, and determining the color pixels at the positions on the color image; fusing each depth pixel with each color pixel to obtain the aligned image.

Wherein, the preset depth coordinate system and the preset world coordinate system can be obtained from an open source system, or can be set arbitrarily by the user according to the application scenario, which is not limited in this application.

Through the above implementation manner, it is possible to generate an aligned image including a depth value, so as to subsequently determine the height of the plant to be detected.

Step S13, using the pre-trained mobilenet-ssd network to detect the color image to obtain a detection frame with the plant to be detected.

In at least one embodiment of the present application, the detection frame is obtained by performing feature extraction on the color image using the convolution kernel in the mobilenet-ssd network.

In at least one embodiment of the present application, the computer device uses a pre-trained mobilenet-ssd network to detect the color image, and obtaining the detection frame with the plant to be detected includes: obtaining the mobilenet-ssd Depth convolution kernel and point convolution kernel in the network; Utilize described depth convolution kernel to extract the feature of described color image, obtain feature map; The feature map is processed by the point convolution kernel to obtain the detection frame.

Wherein, the depth convolution kernel may be a matrix of 16*16*128, further, the point convolution kernel may be a matrix of 1*1*16.

The detection frame can be quickly detected through the pre-trained mobilenet-ssd network, improving the detection efficiency.

Step S14, determining the depth values of all pixels in the detection frame according to the aligned image.

In at least one embodiment of the present application, the depth value refers to the height of the pixel corresponding to the feature point on the plant to be detected from the camera device.

In at least one embodiment of the present application, the computer device determining the depth values of all pixels in the detection frame according to the alignment image includes: the computer device determining that each pixel point is on the alignment image Further, the computer device obtains the depth value at the target position from the alignment image as the depth value of each pixel.

Through the aligned image, the depth values of all the pixels can be accurately and quickly determined.

Step S15, performing denoising processing on the depth value to obtain a target depth value.

In at least one embodiment of the present application, the computer device performs denoising processing on the depth value, and obtaining the target depth value includes: obtaining a depth value equal to a preset value from the depth value, and converting the obtained Determining a depth value as a zero value; deleting the zero value from the depth value, and determining the remaining depth value as the target depth value.

By denoising the depth value to obtain a target depth value, it can be ensured that no interference information is contained in the target depth value, and thus the growth height of the plant to be detected can be accurately determined.

Step S16, using a normal distribution algorithm to determine the mean value and standard deviation of the target depth values.

In at least one embodiment of the present application, the computer device performs normal distribution processing on the target depth value to obtain a normal distribution curve, and further, the computer device determines the average value and The standard deviation.

Step S17, determining the height of the plant to be detected according to the average value and the standard deviation.

In at least one embodiment of the present application, the computer device determining the height of the plant to be detected according to the average value and the standard deviation includes: adding the average value and the standard deviation to obtain The first value; subtracting the average value from the standard deviation to obtain a second value; calculating the average value of the first value and the second value to obtain a target value; determining where the camera is located The camera height of the position; subtracting the camera height from the target value to obtain the height of the plant to be detected.

Through the above implementation manner, the height of the plant to be detected can be accurately determined.

In at least one embodiment of the present application, the method for determining the height of plant growth further includes: when the height is less than a preset height, the computer device generates an alarm message according to the height, further, the computer device adopts A symmetric encryption algorithm encrypts the warning information to obtain ciphertext, further, the computer device determines the warning level of the ciphertext according to the plant to be detected, and the computer device determines the warning mode according to the warning level, Furthermore, the computer device sends the ciphertext in the warning manner.

Wherein, the preset height can be set according to the expected growth rate of the plant to be detected, and the application does not limit the value of the preset height.

Further, the alarm levels include: level one, level two and so on.

Furthermore, the alarming methods include: alarm sound from a speaker, mail, telephone and so on.

Through the above-mentioned embodiment, when the height is lower than the preset height, the warning information can be issued. In addition, by encrypting the warning information, the warning information can be prevented from being tampered with, and the security of the warning information can be improved. At the same time, the warning information can be determined according to the warning level. In this way, the alarm information can be sent in an appropriate alarm mode, making the sending of the alarm information more humanized.

It can be seen from the above technical solutions that the present application determines the plants to be detected according to the height determination request, can accurately determine the plants to be detected that need height measurement, and then controls the camera to take pictures of the plants to be detected, and obtains the The color image and depth image of the plant to be detected are beneficial to the determination of the plant to be detected. By performing denoising processing on the depth value, a target depth value that does not contain noise can be obtained, reducing image alignment processing. When the interference caused by image damage occurs, the normal distribution algorithm is used to determine the average value and standard deviation of the target depth value, and the height of the plant to be detected is determined according to the average value and the standard deviation, which can The determination accuracy of the growth height of the plant to be detected is improved.

As shown in FIG. 3 , it is a functional module diagram of a preferred embodiment of the plant growth height determination device of the present application. The plant growth height determination device 11 includes a determination unit 110 , a control unit 111 , a processing unit 112 , a detection unit 113 , a generation unit 114 , an encryption unit 115 and a sending unit 116 . The module/unit referred to in this application refers to a series of computer program segments that can be executed by the processor 13 and can complete fixed functions, and are stored in the storage 12 . In this embodiment, the functions of each module/unit will be described in detail in subsequent embodiments.

In at least one embodiment of the present application, the present application runs on a computer device, and the computer device is connected to a camera device.

When receiving a height determination request, the determination unit 110 determines the plant to be detected according to the height determination request.

In at least one embodiment of the present application, the information carried in the altitude determination request includes: a preset label, a plant identification, and the like.

Further, the plant to be detected can be any plant whose daily growth needs to be analyzed, for example: rose, sunflower, rice, etc.

In at least one embodiment of the present application, the determining unit 110 determining the plant to be detected according to the height determination request includes: obtaining all idle threads from a preset thread connection pool; determining the processing rate of each idle thread , and determine the idle execution thread with the highest processing rate as the target idle execution thread; use the target idle execution thread to parse the method body of the height determination request to obtain all the information carried in the height determination request; obtain the preset tag, Obtain information corresponding to the preset label from all the information as a plant identifier; determine the plant to be detected according to the plant identifier.

Through the preset mapping relationship between tags and plant identifiers, the plant identifiers can be accurately obtained, and thus the plants to be detected can be accurately determined.

The control unit 111 controls the camera device to take pictures of the plants to be detected to obtain a color image and a depth image of the plants to be detected.

In at least one embodiment of the present application, the color image refers to an RGB three-channel color image, and the depth image refers to an image in which the distance from the camera to each point in the scene is used as a pixel value .

In at least one embodiment of the present application, the control unit 111 controls the camera device to photograph the plant to be detected, and obtaining the color image and the depth image of the plant to be detected includes: determining the plant to be detected The first orientation where the plant is located; controlling the first lens of the camera to move to a second orientation corresponding to the first orientation, and controlling the first lens to take pictures to obtain the color image; controlling the second lens of the camera device to move to the second orientation, and controlling the second lens to take pictures to obtain the depth image.

Wherein, the camera device includes two lenses, which are respectively the first lens and the second lens. The camera device can be installed directly above the detected plants to facilitate shooting.

Through the above embodiments, the color image and the depth image including the plant to be detected can be quickly acquired.

The processing unit 112 performs alignment processing on the color image and the depth image to obtain an aligned image.

In at least one embodiment of the present application, the alignment image refers to an image generated by fusing pixels of the color image and pixels of the depth image.

In at least one embodiment of the present application, the processing unit 112 performs alignment processing on the color image and the depth image, and obtaining the alignment image includes: obtaining all depth pixels on the depth image; All the depth pixels are mapped to the preset depth coordinate system to obtain the depth coordinates of all the depth pixels; the world coordinates of all the depth pixels are determined according to all the depth coordinates and the preset world coordinate system; the world coordinates of all the depth pixels are determined according to all the world coordinates Positions of all the depth pixels on the color image, and determine the color pixels at the positions on the color image; fuse each depth pixel with each color pixel to obtain the aligned image.

Wherein, the preset depth coordinate system and the preset world coordinate system can be obtained from an open source system, or can be set arbitrarily by the user according to the application scenario, which is not limited in this application.

Through the above implementation manner, it is possible to generate an aligned image including a depth value, so as to subsequently determine the height of the plant to be detected.

The detection unit 113 detects the color image using a pre-trained mobilenet-ssd network to obtain a detection frame with the plant to be detected.

In at least one embodiment of the present application, the detection frame is obtained by performing feature extraction on the color image using the convolution kernel in the mobilenet-ssd network.

In at least one embodiment of the present application, the detection unit 113 uses the pre-trained mobilenet-ssd network to detect the color image, and obtaining the detection frame with the plant to be detected includes: obtaining the mobilenet-ssd network Depth convolution kernel and point convolution kernel in ssd network; Utilize described depth convolution kernel to extract the feature of described color image, obtain feature map; Utilize described point convolution kernel to process described feature map, obtain The detection box.

Wherein, the depth convolution kernel may be a matrix of 16*16*128, further, the point convolution kernel may be a matrix of 1*1*16.

The detection frame can be quickly detected through the pre-trained mobilenet-ssd network, improving the detection efficiency.

The determining unit 110 determines depth values of all pixels in the detection frame according to the aligned image.

In at least one embodiment of the present application, the depth value refers to the height of the pixel corresponding to the feature point on the plant to be detected from the camera device.

In at least one embodiment of the present application, the determination unit 110 determining the depth values of all pixels in the detection frame according to the alignment image includes: the determination unit 110 determining that each pixel in the alignment image The target position on the image, further, the determining unit 110 acquires the depth value of the target position from the aligned image as the depth value of each pixel.

Through the aligned image, the depth values of all the pixels can be accurately and quickly determined.

The processing unit 112 performs denoising processing on the depth value to obtain a target depth value.

In at least one embodiment of the present application, the processing unit 112 performs denoising processing on the depth value, and obtaining the target depth value includes: Obtain a depth value equal to a preset value from the depth value, and determine the obtained depth value as a zero value; delete the zero value from the depth value, and determine the remaining depth value as the target depth value.

By denoising the depth value to obtain a target depth value, it can be ensured that no interference information is contained in the target depth value, and thus the growth height of the plant to be detected can be accurately determined.

The determining unit 110 uses a normal distribution algorithm to determine the mean and standard deviation of the target depth values.

In at least one embodiment of the present application, the determining unit 110 performs normal distribution processing on the target depth value to obtain a normal distribution curve, further, the determining unit 110 determines the average value and the standard deviation.

The determining unit 110 determines the height of the plant to be detected according to the average value and the standard deviation.

In at least one embodiment of the present application, the determining unit 110 determining the height of the plant to be detected according to the average value and the standard deviation includes: adding the average value and the standard deviation, Obtain a first value; subtract the average value from the standard deviation to obtain a second value; calculate the average value of the first value and the second value to obtain a target value; determine the camera The camera height at the location; the camera height is subtracted from the target value to obtain the height of the plant to be detected.

Through the above implementation manner, the height of the plant to be detected can be accurately determined.

In at least one embodiment of the present application, when the height is less than the preset height, the generation unit 114 generates warning information according to the height, and further, the encryption unit 115 encrypts the warning information using a symmetric encryption algorithm to obtain the encrypted Further, the determination unit 110 according to the The plant to be detected determines the warning level of the ciphertext, the determining unit 110 determines a warning mode according to the warning level, and further, the sending unit 116 sends the ciphertext in the warning mode.

Wherein, the preset height can be set according to the expected growth rate of the plant to be detected, and the application does not limit the value of the preset height.

Further, the alarm levels include: level one, level two and so on.

Furthermore, the alarming methods include: alarm sound from a speaker, mail, telephone and so on.

Through the above-mentioned embodiment, when the height is lower than the preset height, the warning information can be issued. In addition, by encrypting the warning information, the warning information can be prevented from being tampered with, and the security of the warning information can be improved. At the same time, the warning information can be determined according to the warning level. In this way, the alarm information can be sent in an appropriate alarm mode, making the sending of the alarm information more humanized.

It can be seen from the above technical solutions that the present application determines the plants to be detected according to the height determination request, can accurately determine the plants to be detected that need height measurement, and then controls the camera to take pictures of the plants to be detected, and obtains the The color image and depth image of the plant to be detected are beneficial to the determination of the plant to be detected. By performing denoising processing on the depth value, a target depth value that does not contain noise can be obtained, reducing image alignment processing. When the interference caused by image damage occurs, the normal distribution algorithm is used to determine the average value and standard deviation of the target depth value, and the height of the plant to be detected is determined according to the average value and the standard deviation, which can The determination accuracy of the growth height of the plant to be detected is improved.

As shown in FIG. 4 , it is a schematic structural diagram of a computer device in a preferred embodiment of the method for determining the height of plant growth in the present application.

In one embodiment of the present application, the computer device 1 includes, but is not limited to, a storage 12, a processor 13, and a computer program stored in the storage 12 and operable on the processor 13 , such as a plant growth height determination program.

Those skilled in the art can understand that the schematic diagram is only an example of the computer device 1, and does not constitute a limitation to the computer device 1, and may include more or less components than those shown in the illustration, or a combination Certain components, or different components, for example, the computer device 1 may also include input and output devices, network access devices, bus bars, and the like.

The processor 13 can be a central processing unit (Central Processing Unit, CPU), and can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC) , Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. General-purpose processor can be microprocessor or this processor also can be any conventional processor etc., described processor 13 is the operation core and control center of described computer device 1, utilizes various interfaces and lines to connect whole computer device 1 The various parts of each part, and the operating system that executes the computer device 1 and various types of application programs, program codes, etc. installed.

The processor 13 executes the operating system of the computer device 1 and various installed applications. The processor 13 executes the application program to implement the steps in the above embodiments of the methods for determining the growth height of plants, such as the steps shown in FIG. 2 .

Exemplarily, the computer program can be divided into one or more modules/units, and the one or more modules/units are stored in the storage 12 and executed by the processor 13, to complete this application. The one or more modules/units may be a series of computer program instruction segments capable of accomplishing specific functions, and the instruction segments are used to describe the execution process of the computer program in the computer device 1 . For example, the computer program can be divided into a determination unit 110 , a control unit 111 , a processing unit 112 , a detection unit 113 , a generation unit 114 , an encryption unit 115 and a sending unit 116 .

The storage 12 can be used to store the computer program and/or module, and the processor 13 runs or executes the computer program and/or module stored in the storage 12, and calls the computer program and/or module stored in the storage 12 to realize various functions of the computer device 1. The storage device 12 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application program required by a function (such as a sound playback function, an image playback function, etc.); The area can store materials created according to use of the computer device, and the like. In addition, the storage 12 may include a non-volatile storage, such as a hard disk, storage, plug-in hard disk, smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash memory card (Flash Card), at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices.

The storage 12 may be an external storage and/or an internal storage of the computer device 1 . Further, the storage 12 may be a physical storage, such as a storage stick, a TF card (Trans-flash Card) and the like.

If the integrated modules/units of the computer device 1 are realized in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above-mentioned embodiments in the present application can also be completed by instructing related hardware through computer programs, and the computer programs can be stored in a computer-readable storage medium. When the computer program is executed by the processor, it can realize the steps of the above-mentioned various method embodiments.

Wherein, the computer program includes computer program code, and the computer program code may be in the form of original code, object code, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, flash drive, removable hard disk, magnetic disk, optical disk, computer storage, read-only memory (ROM, Read- Only Memory).

With reference to FIG. 2, the memory 12 in the computer device 1 stores multiple instructions to implement a method for determining the height of plant growth, and the processor 13 can execute the multiple instructions to achieve: when a height determination request is received , determine the plant to be detected according to the height determination request; control the camera to photograph the plant to be detected to obtain a color image and a depth image of the plant to be detected; combine the color image with the The depth image is aligned to obtain an alignment image; the pre-trained mobilenet-ssd network is used to detect the color image to obtain a detection frame with the plant to be detected; determine the alignment image according to the alignment Depth values of all pixels in the detection frame; denoising the depth values to obtain target depth values; A normal distribution algorithm is used to determine the mean value and standard deviation of the target depth value; and the height of the plant to be detected is determined according to the mean value and the standard deviation.

Specifically, for the specific implementation method of the above instruction by the processor 13, reference may be made to the description of the relevant steps in the embodiment corresponding to FIG. 2 , which will not be repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

The modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical units, that is, they may be located in one place, or images may be distributed to multiple on the network unit. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional module in each embodiment of the present application may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented not only in the form of hardware, but also in the form of hardware plus software function modules.

Therefore, no matter from any point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the application is defined by the appended claims rather than the above description, so it is intended to All changes within the meaning and range of equivalents of the elements are embraced in this application. Any attached reference mark in a claim shall not be deemed to limit the claim to which it relates.

In addition, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or devices stated in this application may also be realized by one unit or device through software or hardware. The terms first, second, etc. are used to denote names and do not imply any particular order.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and not to limit them. Although the application has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art It should be understood that the technical solutions of the present application can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present application.

S10~S17: Steps

Claims (9)

A method for determining the growth height of a plant, which is applied to a computer device, and the computer device is connected to a camera device, wherein the method for determining the growth height of a plant includes: when a height determination request is received, determining the height to be determined according to the height determination request Detecting plants; controlling the camera device to photograph the plants to be detected to obtain a color image and a depth image of the plants to be detected; aligning the color images and the depth images to obtain an alignment An image, including: acquiring all depth pixels on the depth image; mapping all depth pixels to a preset depth coordinate system to obtain the depth coordinates of all depth pixels; according to all depth coordinates and the preset world The coordinate system determines the world coordinates of all the depth pixels; determines the positions of all the depth pixels on the color image according to all the world coordinates, and determines the color pixels at the positions on the color image; Each depth pixel is fused with each color pixel to obtain the aligned image; the pre-trained mobilenet-ssd network is used to detect the color image to obtain a detection frame with the plant to be detected; according to the described Aligning the images to determine the depth values of all pixels in the detection frame; performing denoising processing on the depth values to obtain target depth values; using a normal distribution algorithm to determine the average value and standard deviation of the target depth values; The height of the plant to be detected is determined according to the average value and the standard deviation. The method for determining the growth height of a plant according to claim 1, wherein the determining the plant to be detected according to the height determination request includes: obtaining all idle execution threads from a preset execution thread connection pool; determining the number of each idle execution thread processing rate, and determine the idle thread with the highest processing rate as the target idle thread; use the target idle thread to parse the method body of the height determination request, and obtain all the information carried by the height determination request; Obtaining a preset label, obtaining information corresponding to the preset label from all the information as a plant identifier; determining the plant to be detected according to the plant identifier. The method for determining the growth height of plants according to claim 1, wherein the controlling the camera device to take pictures of the plants to be detected, and obtaining the color images and depth images of the plants to be detected includes: determining the The first orientation where the plant to be detected is located; controlling the first lens of the camera device to move to a second orientation corresponding to the first orientation, and controlling the first lens to take pictures to obtain the color image; controlling The second lens of the camera device is moved to the second orientation, and the second lens is controlled to take pictures to obtain the depth image. The method for determining the growth height of a plant according to claim 1, wherein said detecting the color image using a pre-trained mobilenet-ssd network, and obtaining a detection frame with the plant to be detected includes: obtaining the Depth convolution kernel and point convolution kernel in the mobilenet-ssd network; use the depth convolution kernel to extract the features of the color image to obtain a feature map; use the point convolution kernel to process the feature map , to get the detection frame. The method for determining the height of plant growth according to claim 1, wherein said denoising the depth value to obtain the target depth value includes: obtaining a depth value equal to a preset value from the depth value, and The obtained depth value is determined as a zero value; the zero value is deleted from the depth value, and the remaining depth value is determined as the target depth value. The method for determining the growth height of plants according to claim 1, wherein said determining the height of the plant to be detected according to the average value and the standard deviation comprises: adding the average value and the standard deviation Operation to get the first value; Subtracting the average value from the standard deviation to obtain a second value; calculating the average value of the first value and the second value to obtain a target value; determining the camera height at the location of the camera device ; Subtracting the camera height from the target value to obtain the height of the plant to be detected. A plant growth height determination device, running in a computer device, the computer device is connected to a camera device, wherein the plant growth height determination device includes: a determination unit, configured to, when receiving a height determination request, according to the The height determination request determines the plant to be detected; the control unit is used to control the camera to take pictures of the plant to be detected to obtain the color image and depth image of the plant to be detected; the processing unit is used to convert the plant to be detected The color image is aligned with the depth image to obtain an aligned image, including: acquiring all depth pixels on the depth image; mapping all depth pixels to a preset depth coordinate system to obtain the Depth coordinates of all depth pixels; determine the world coordinates of all depth pixels according to all depth coordinates and a preset world coordinate system; determine the positions of all depth pixels on the color image according to all world coordinates, and determine the The color pixel at the position on the color image; each depth pixel is fused with each color pixel to obtain the aligned image; the detection unit is used to detect the mobilenet-ssd network using the pre-trained The color image is used to obtain a detection frame with the plant to be detected; the determination unit is further configured to determine the depth values of all pixels in the detection frame according to the alignment image; the processing unit is also configured to It is used to denoise the depth value to obtain a target depth value; the determination unit is also used to determine the average value and standard deviation of the target depth value by using a normal distribution algorithm; the determination unit is also It is used for determining the height of the plant to be detected according to the average value and the standard deviation. A computer device, wherein the computer device includes: a memory storing at least one instruction; and a processor obtaining the instruction stored in the memory to realize plant growth as described in any one of claims 1 to 6 Highly certain method. A computer-readable storage medium, wherein: at least one instruction is stored in the computer-readable storage medium, and the at least one instruction is acquired by a processor in a computer device to implement any one of claims 1 to 6. A method for determining plant growth height.

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