Image classification device based on deep learning

Abstract

An image classification device based on deep learning disclosed by the present invention comprises an arch-shaped frame, uniformly distributed support columns are fixedly connected in the right side of the arch-shaped frame, and one end of each support column is fixedly connected with a groove plate. Through cooperative work of a second motor, a lead screw, a nut pair, a guide column, a moving seat, a connecting column, an electric sliding rail and a sliding block, flexible adjustment of the height and the left-right position of a camera is achieved, accurate image collection can be conducted on objects at different heights and positions, the comprehensiveness and accuracy of image collection are improved, and the working efficiency is improved. And image classification requirements in various scenes are met.

Description

Technical Field

[0001] The present invention relates to the technical field of image classification, and in particular to an image classification device based on deep learning. Background Art

[0002] With the advancement of science and technology, people's demand for image understanding is growing. In many fields, such as medical imaging diagnosis, autonomous driving, industrial product quality inspection, etc., a large number of images need to be classified quickly and accurately. Traditional image classification methods based on manual features (such as SIFT, HOG, etc.) and machine learning algorithms (such as support vector machines) gradually show their limitations when faced with complex and changeable image data.

[0003] In the industrial parts quality inspection scenario, parts may have various complex shapes and structures. Fixed-position cameras may cause some defects of parts to be blocked or deformed due to shooting angle problems. This will cause the collected images to fail to truly present the defect features of the parts, resulting in errors in the subsequent quality classification based on these images. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an image classification device based on deep learning.

[0005] In order to achieve the above-mentioned objectives, the present invention adopts the following technical scheme: a deep learning-based image classification device, comprising an arch frame, a uniformly distributed support column fixedly connected to the inside of the right side of the arch frame, a groove plate fixedly connected to one end of the support column, a first motor fixedly connected to the middle end of the left side of the groove plate, a rotating plate fixedly connected to the output end of the first motor, inclined rods rotatably connected to both ends of the rotating plate, a moving disk rotatably connected to one end of the inclined rod, a uniformly distributed guide block fixedly connected to the left outer wall of the groove plate, a display screen is arranged between the moving disks, three hard disks are arranged at the bottom of the display screen, and a controller is fixedly connected to the top of the middle end of the arch frame.

[0006] As a further description of the above technical solution:

[0007] A moving plate is arranged on the right inner wall of the arch frame, and an electric slide rail is fixedly connected to the left inner wall of the moving plate.

[0008] As a further description of the above technical solution:

[0009] The outer wall of the guide block is slidably connected with a moving block, and the moving block is fixedly connected with the moving disk.

[0010] As a further description of the above technical solution:

[0011] A sliding block is slidably connected to the outer wall of the electric slide rail, and a camera is fixedly connected to the left side of the sliding block.

[0012] As a further description of the above technical solution:

[0013] A second motor is fixedly connected to the bottom right side of the arch frame, and a lead screw is fixedly connected to the output end of the second motor.

[0014] As a further description of the above technical solution:

[0015] The outer ring at the top of the screw rod is threadedly connected with a nut pair, and the top of the nut pair is fixedly connected with a moving seat.

[0016] As a further description of the above technical solution:

[0017] Guide columns are penetrated and slidably connected inside the front and rear ends of the moving seat, and the guide columns are fixedly connected to the arch frame.

[0018] As a further description of the above technical solution:

[0019] The tops of both front and rear ends of the moving seat are fixedly connected with connecting columns, and the connecting columns are fixedly connected to the moving plate.

[0020] The present invention has the following beneficial effects:

[0021] In the present invention, firstly, through the coordinated work of the second motor, the screw, the nut pair, the guide column, the moving seat, the connecting column, the electric slide rail and the sliding block, the flexible adjustment of the camera height and the left and right position is realized, and accurate image capture of objects at different heights and positions is possible, thereby improving the comprehensiveness and accuracy of image capture, and being suitable for image classification needs in various scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is an overall structural diagram of an image classification device based on deep learning proposed by the present invention;

[0023] Figure 2 A structural diagram of a first motor of an image classification device based on deep learning proposed by the present invention;

[0024] Figure 3 This is a schematic diagram of the structure of an electric slide rail of an image classification device based on deep learning proposed by the present invention.

[0025] Legend:

[0026] 1. Arch frame; 2. Controller; 3. Support column; 4. Groove plate; 5. Electric slide rail; 6. First motor; 7. Rotating plate; 8. Inclined rod; 9. Moving disk; 10. Guide block; 11. Moving block; 12. Display screen; 13. Hard disk; 14. Moving plate; 15. Sliding block; 16. Camera; 17. Second motor; 18. Guide column; 19. Nut pair; 20. Screw rod; 21. Moving seat; 22. Connecting column. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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.

[0028] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific position, be constructed and operated in a specific position, and therefore cannot be understood as limiting the present invention; the terms "first", "second", and "third" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance. In addition, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0029] Reference Figure 1-3An embodiment of the present invention is as follows: an image classification device based on deep learning comprises an arch frame 1, a uniformly distributed support column 3 is fixedly connected to the right inner side of the arch frame 1, a groove plate 4 is fixedly connected to one end of the support column 3, a first motor 6 is fixedly connected to the middle end of the left side of the groove plate 4, a rotating plate 7 is fixedly connected to the output end of the first motor 6, an inclined rod 8 is rotatably connected to both ends of the rotating plate 7, a moving disk 9 is rotatably connected to one end of the inclined rod 8, and the moving disk 9 can produce corresponding displacement changes by rotating the rotating plate 7 and by means of the transmission of the inclined rod 8, a uniformly distributed guide block 10 is fixedly connected to the outer wall of the left side of the groove plate 4, a display screen 12 is arranged between the moving disks 9, and three hard disks 13 are arranged at the bottom of the display screen 12, a controller 2 is fixedly connected to the top of the middle end of the arch frame 1, the display screen 12 can be used to display relevant information or results of image classification, and three hard disks 13 are arranged at the bottom, and the hard disk 13 can be used to store important information such as image data, deep learning models and classification results. A controller 2 is fixedly connected to the top of the middle end of the arch frame 1. The controller 2 can control and coordinate various components of the entire device, such as controlling the start and stop of the motor, the transmission and processing of data, etc.

[0030] A moving plate 14 is provided on the right inner wall of the arch frame 1, and an electric slide rail 5 is fixedly connected to the left inner wall of the moving plate 14. A moving block 11 is slidably connected to the outer wall of the guide block 10, and the moving block 11 is fixedly connected to the moving disk 9, so that the moving disk 9 can move smoothly on the electric slide rail 5 through the moving block 11 under the guidance of the guide block 10. A sliding block 15 is slidably connected to the outer wall of the electric slide rail 5, and a camera 16 is fixedly connected to the left side of the sliding block 15. The camera 16 can be used to collect image data. By sliding on the electric slide rail 5, the position of the camera 16 can be adjusted to obtain images at different angles or positions. A second motor 17 is fixedly connected to the bottom of the right side of the arch frame 1, and a screw rod 20 is fixedly connected to the output end of the second motor 17. A nut is threadedly connected to the outer ring of the top of the screw rod 20 When the second motor 17 is started, the screw rod 20 is driven to rotate, thereby causing the nut pair 19 to move up and down along the screw rod 20. A moving seat 21 is fixedly connected to the top of the nut pair 19. Guide columns 18 are penetrated and slidably connected inside the front and rear ends of the moving seat 21, and the guide columns 18 are fixedly connected to the arch frame 1. The guide columns 18 provide a stable guiding effect for the up and down movement of the moving seat 21 to prevent it from shifting during the movement. Connecting columns 22 are fixedly connected to the tops of the front and rear ends of the moving seat 21, and the connecting columns 22 are fixedly connected to the moving plate 14. When the moving seat 21 moves up and down, it can drive the moving plate 14 and the components connected thereto to move up and down together, thereby realizing the adjustment of the height position of the camera 16 to better adapt to different image acquisition requirements.

[0031] Working principle: The first motor 6 starts, driving the rotating plate 7 to rotate, and the rotating plate 7 pushes the moving plate 9 to move through the inclined rod 8. Under the action of the guide block 10 and the moving block 11, the moving plate 9 can move smoothly left and right to fix the display screen 12. The second motor 17 starts, driving the screw rod 20 to rotate. Since the screw rod 20 is threadedly connected to the nut pair 19, and the nut pair 19 is fixed to the moving seat 21, and the moving seat 21 is guided by the guide column 18, the moving seat 21 can move up and down smoothly when the screw rod 20 rotates. The up and down movement of the moving seat 21 drives the moving plate 14 to move up and down through the connecting column 22, and then adjusts the height position of the camera 16 to adapt to the image acquisition of objects at different heights. The camera moves left and right through the sliding block 15 on the electric slide rail 5, so that it can capture images of objects at different positions. The collected image information is transmitted to the controller 2. After receiving the image information collected by the camera 16, the controller 2 uses a deep learning algorithm to classify and process the image. The deep learning algorithm can identify features in the image by learning a large amount of image data, and classify the image into different categories based on these features. The classification results are displayed on the display screen 12, allowing the user to intuitively see the classification of the image. At the same time, the classification results will be stored in the hard disk 13 for subsequent viewing and analysis.

[0032] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A deep learning-based image classification device, comprising an arch frame (1), characterized in that: The right side of the arch frame (1) is fixedly connected to a uniformly distributed support column (3), one end of the support column (3) is fixedly connected to a groove plate (4), the left middle end of the groove plate (4) is fixedly connected to a first motor (6), the output end of the first motor (6) is fixedly connected to a rotating plate (7), both ends of the rotating plate (7) are rotatably connected to inclined rods (8), one end of the inclined rod (8) is rotatably connected to a moving disk (9), the left outer wall of the groove plate (4) is fixedly connected to a uniformly distributed guide block (10), a display screen (12) is arranged between the moving disks (9), and three hard disks (13) are arranged at the bottom of the display screen (12), and the top of the middle end of the arch frame (1) is fixedly connected to a controller (2).

2. The image classification device based on deep learning according to claim 1, characterized in that: A movable plate (14) is provided on the right inner wall of the arch frame (1), and an electric slide rail (5) is fixedly connected to the left inner wall of the movable plate (14).

3. The image classification device based on deep learning according to claim 1, characterized in that: The outer wall of the guide block (10) is slidably connected to a moving block (11), and the moving block (11) is fixedly connected to the moving plate (9).

4. The image classification device based on deep learning according to claim 2, characterized in that: The outer wall of the electric slide rail (5) is slidably connected to a slide block (15), and the left side of the slide block (15) is fixedly connected to a camera (16).

5. The image classification device based on deep learning according to claim 1, characterized in that: A second motor (17) is fixedly connected to the bottom of the right side of the arch frame (1), and a lead screw (20) is fixedly connected to the output end of the second motor (17).

6. The image classification device based on deep learning according to claim 5, characterized in that: The outer ring of the top of the screw rod (20) is threadedly connected to a nut pair (19), and the top of the nut pair (19) is fixedly connected to a moving seat (21).

7. The image classification device based on deep learning according to claim 6, characterized in that: Guide columns (18) are inserted through and slidably connected to the interior of both front and rear ends of the movable seat (21), and the guide columns (18) are fixedly connected to the arch frame (1).

8. The image classification device based on deep learning according to claim 6, characterized in that: The tops of both front and rear ends of the movable seat (21) are fixedly connected with connecting columns (22), and the connecting columns (22) are fixedly connected to the movable plate (14).

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