CN113052845A - Method and device for detecting vehicle carpet lamp - Google Patents
Method and device for detecting vehicle carpet lamp Download PDFInfo
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Abstract
The invention provides a method and a device for detecting a vehicle carpet lamp, wherein the method comprises the following steps: acquiring a target detection image presented by a vehicle carpet lamp, and acquiring brightness data of the target detection image; acquiring characteristic data of the target detection image according to the target detection image and the brightness data of the target detection image; and carrying out qualified detection on the vehicle carpet lamp according to the characteristic data of the target detection image. According to the detection method of the vehicle carpet lamp, the vehicle carpet lamp can be accurately detected, and the user experience is greatly improved.
Description
Technical Field
The invention relates to the technical field of vehicle detection, in particular to a detection method and a detection device for a vehicle carpet lamp.
Background
With the continuous development of automobile electronics, luxurious and comfortable travel experience is created, the automobile factory target is achieved, the welcome optical blanket like a angel wing is possessed, and a distinctive ceremony feeling and technological feeling are created. The vehicle carpet lamp indicates that when opening the door, a lamp area is put out to the lamp below the door, under the environment that light is not good, conveniently gets on or off the bus.
However, in the related art, the vehicle carpet lamp cannot be accurately detected, and thus, the user experience is greatly reduced.
Disclosure of Invention
The invention provides a detection method of a vehicle carpet lamp for solving the technical problems, which can accurately detect the vehicle carpet lamp and greatly improve the user experience.
The technical scheme adopted by the invention is as follows:
a method of detecting a vehicle carpet light, comprising the steps of: acquiring a target detection image presented by the vehicle carpet lamp, and acquiring brightness data of the target detection image; acquiring characteristic data of the target detection image according to the target detection image and the brightness data of the target detection image; and performing qualified detection on the vehicle carpet lamp according to the characteristic data of the target detection image.
The feature data of the target detection image comprises a length value of the target detection image, wherein the qualified detection of the vehicle carpet lamp according to the feature data of the target detection image comprises the following steps: comparing the length value of the target detection image with a standard length, and judging whether the difference value between the length value of the target detection image and the standard length is greater than a preset length; and if the difference value between the length value of the target detection image and the standard length is greater than the preset length, judging that the vehicle carpet lamp is unqualified.
The feature data of the target detection image further includes uniformity of the target detection image, wherein performing qualification detection on the vehicle carpet lamp according to the feature data of the target detection image further includes: comparing the uniformity of the target detection image with a standard uniformity, and judging whether the difference value between the uniformity of the target detection image and the standard uniformity is greater than a preset uniformity; and if the difference value between the uniformity of the target detection image and the standard uniformity is greater than the preset uniformity, judging that the vehicle carpet lamp is unqualified.
The feature data of the target detection image further includes a gradient of the target detection image, wherein performing the qualified detection on the vehicle carpet lamp according to the feature data of the target detection image further includes: comparing the gradient of the target detection image with a standard gradient, and judging whether the difference value of the gradient of the target detection image and the standard gradient is greater than a preset gradient; and if the difference value between the gradient of the target detection image and the standard gradient is greater than the preset gradient, judging that the vehicle carpet lamp is unqualified.
The feature data of the target detection image further includes blackness of the target detection image, wherein the qualified detection of the vehicle carpet lamp according to the feature data of the target detection image further includes: comparing the blackness of the target detection image with a standard blackness, and judging whether the difference value between the blackness of the target detection image and the standard blackness is greater than a preset blackness; and if the difference value between the blackness of the target detection image and the standard blackness is greater than the preset blackness, judging that the vehicle carpet lamp is unqualified.
A detection apparatus of a vehicle carpet light, comprising: the first acquisition module is used for acquiring a target detection image presented by the vehicle carpet lamp and acquiring brightness data of the target detection image; the second acquisition module is used for acquiring the characteristic data of the target detection image according to the target detection image and the brightness data of the target detection image; and the detection module is used for carrying out qualified detection on the vehicle carpet lamp according to the characteristic data of the target detection image.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method for detecting a vehicle carpet light as described above when executing the computer program.
A non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of detecting a vehicle carpet light described above.
The invention has the beneficial effects that:
the invention can accurately detect the vehicle carpet lamp, and greatly improves the user experience.
Drawings
FIG. 1 is a flow chart of a method of detecting a vehicle carpet light according to an embodiment of the present invention;
fig. 2 is a block diagram schematically illustrating an apparatus for detecting a carpet light for a vehicle according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a flowchart of a method of detecting a vehicle carpet light according to an embodiment of the present invention.
As shown in fig. 1, the method for detecting a vehicle carpet light according to an embodiment of the present invention may include the steps of:
and S1, acquiring a target detection image presented by the vehicle carpet lamp, and acquiring brightness data of the target detection image.
Specifically, the vehicle carpet lamp can be imaged by a high-precision million-level pixel CCD imaging brightness system and a diffuse reflection white screen, wherein the pixels of the CCD are not less than 3000X 2700, the diffuse reflection white screen adopts a special spraying process, the good near-lambert diffuse reflector characteristic is achieved, the installation is always fixed, and the stability and the uniformity are good.
In one embodiment of the present invention, a high-precision imaging brightness test system may be used to capture target detection images presented by a vehicle carpet light and obtain brightness data of the target detection images. The high-precision imaging brightness test system adopts advanced semiconductor refrigeration and temperature control technology, has good V (lambda) matching and high measurement stability, wherein V (lambda) is a visual function, and lambda is the wavelength of light.
S2, feature data of the object detection image is acquired based on the object detection image and the luminance data of the object detection image.
In one embodiment of the present invention, the feature data of the target detection image may include: one or more of length value, uniformity, gradient and blackness of the target detection image.
After a target detection image presented by a vehicle carpet lamp is acquired through a high-precision imaging brightness test system, image data can be analyzed through LPTS (Low Temperature Poly-silicon) projection lamp online detection system analysis software to obtain a length value of the target detection image. After the brightness data of the target detection image is obtained through the high-precision imaging brightness test system, the uniformity, gradient and blackness of the target detection image can be calculated through the LPTS projection lamp on-line detection system analysis software according to the brightness data. The LPTS projection lamp on-line detection system analysis software is high in measurement speed, full-screen brightness information can be obtained through one-time sampling, and parameters such as uniformity, gradient and blackness can be quickly calculated.
And S3, performing qualified detection on the vehicle carpet lamp according to the characteristic data of the target detection image.
Specifically, in the embodiment of the invention, a precise imaging system and an intelligent software algorithm can be integrated, and the online test can be carried out on the performances of the carpet lamp such as luminosity and the like, namely, the vehicle carpet lamp is subjected to qualified detection according to the characteristic data of the target detection image presented by the vehicle carpet lamp, so that the vehicle carpet lamp can be accurately detected, and the user experience is greatly improved.
How to acquire the feature data of the target detection image and how to perform the qualification testing on the vehicle carpet lamp according to the feature data of the target detection image will be described in detail with reference to specific embodiments.
According to one embodiment of the present invention, the feature data of the target detection image includes a length value of the target detection image, wherein the qualification testing of the vehicle carpet light according to the feature data of the target detection image includes: comparing the length value of the target detection image with the standard length, and judging whether the difference value between the length value of the target detection image and the standard length is greater than the preset length; and if the difference value between the length value of the target detection image and the standard length is greater than the preset length, judging that the vehicle carpet lamp is unqualified.
Specifically, after a target detection image presented by the vehicle carpet lamp is acquired through the high-precision imaging brightness test system, the image data can be analyzed through the LPTS projection lamp online detection system analysis software to obtain a length value of the target detection image, and the length value of the target detection image is compared with a standard length to judge whether the vehicle carpet lamp is qualified. As a possible implementation manner, the difference between the length value of the target detection image and the standard length may be calculated, and whether the calculated difference is greater than a preset length is determined, if so, it is determined that the deviation between the length value of the target detection image and the standard length is large, that is, it is determined that the vehicle carpet lamp is not qualified.
According to another embodiment of the present invention, the feature data of the target detection image further includes uniformity of the target detection image, wherein the qualification testing of the carpet lights of the vehicle according to the feature data of the target detection image further includes: comparing the uniformity of the target detection image with the standard uniformity, and judging whether the difference value between the uniformity of the target detection image and the standard uniformity is greater than the preset uniformity; and if the difference value between the uniformity of the target detection image and the standard uniformity is greater than the preset uniformity, judging that the vehicle carpet lamp is unqualified.
Specifically, after the brightness data of the target detection image is acquired by the high-precision imaging brightness test system, the uniformity of the target detection image can be calculated according to the brightness data by the LPTS projection lamp online detection system analysis software. Here, one point may be taken at a certain distance (e.g., 300 mm) in the direction of the horizontal axis of the object detection image up to the end of the object detection image, for example, A, B, C and D four points are taken in the direction of the horizontal axis of the object detection image, and the luminance values of A, B, C and D four points are acquired, and the luminance difference value between the points a and B, the luminance difference value between the points B and C, and the luminance difference value between the points C and D are sequentially calculated. And then comparing the brightness difference value between the points A and B, the brightness difference value between the points B and C and the brightness difference value between the points C and D with the corresponding standard uniformity respectively to judge whether the vehicle carpet lamp is qualified or not. As a possible implementation manner, the difference between the brightness difference between the points a and B and the first standard uniformity may be calculated, and whether the calculated difference is greater than the first preset uniformity is determined, if so, the deviation between the brightness difference between the points a and B and the first standard uniformity is determined to be greater, that is, the vehicle carpet lamp is determined to be unqualified; calculating the difference value between the brightness difference value between the points B and C and a second standard uniformity, and judging whether the calculated difference value is greater than a second preset uniformity, if so, judging that the deviation between the brightness difference value between the points B and C and the second standard uniformity is greater, namely judging that the vehicle carpet lamp is unqualified; and calculating the difference value between the brightness difference value between the points C and D and the third standard uniformity, and judging whether the calculated difference value is greater than a third preset uniformity, if so, judging that the deviation between the brightness difference value between the points C and D and the third standard uniformity is greater, namely judging that the vehicle carpet lamp is unqualified.
According to still another embodiment of the present invention, the feature data of the target detection image further includes a gradient of the target detection image, wherein the qualification of the vehicle carpet light according to the feature data of the target detection image further includes: comparing the gradient of the target detection image with the standard gradient, and judging whether the difference value of the gradient of the target detection image and the standard gradient is greater than a preset gradient; and if the difference value between the gradient of the target detection image and the standard gradient is greater than the preset gradient, judging that the vehicle carpet lamp is unqualified.
Specifically, after the brightness data of the target detection image is acquired by the high-precision imaging brightness test system, the gradient of the target detection image can be calculated according to the brightness data by the LPTS projection lamp online detection system analysis software. Here, a plurality of points may be taken in the direction of the horizontal axis of the object detection image, and a point may be taken at a distance (e.g., 200 mm) after each point, for example, E, F and G three points may be taken in the direction of the horizontal axis of the object detection image, then, in the direction of the horizontal axis, E1 point (200 mm from E point) 200mm after E point, F1 point (200 mm from F point) 200mm after F point, G1 point (200 mm from G point by G1 point) may be taken 200mm after G point, and luminance values of E, F, G, E1, F1, and G1 may be obtained, and thereby, a quotient of the luminance value of E point and the luminance value of E1 point, a quotient of the luminance value of F point and the luminance value of F1 point, and a quotient of the luminance value of G point and a quotient of the luminance value of G1 point may be calculated. And then comparing the quotient of the brightness value of the point E and the brightness value of the point E1, the quotient of the brightness value of the point F and the brightness value of the point F1, and the quotient of the brightness value of the point G and the brightness value of the point G1 with the corresponding standard gradients respectively to judge whether the vehicle carpet lamp is qualified or not. As a possible implementation manner, the difference between the quotient of the brightness value at the point E and the brightness value at the point E1 and the first standard gradient is calculated, and whether the calculated difference is greater than the first preset gradient is determined, if so, the deviation between the gradient at the point E and the point E1 and the first standard gradient is determined to be greater, that is, the vehicle carpet lamp is determined to be unqualified; calculating the difference between the quotient of the brightness value of the point F and the brightness value of the point F1 and a second standard gradient, and judging whether the calculated difference is greater than a second preset gradient, if so, judging that the deviation between the gradient of the point F and the point F1 and the second standard gradient is greater, namely judging that the vehicle carpet lamp is unqualified; and calculating the difference between the quotient of the brightness value of the point G and the brightness value of the point G1 and the third standard gradient, and judging whether the calculated difference is greater than the third preset gradient, if so, judging that the deviation between the gradient of the point G and the point G1 and the third standard gradient is greater, namely judging that the vehicle carpet lamp is unqualified.
According to still another embodiment of the present invention, the feature data of the target detection image further includes a blackness of the target detection image, wherein the qualification testing of the vehicle carpet light according to the feature data of the target detection image further includes: comparing the blackness of the target detection image with the standard blackness, and judging whether the difference value between the blackness of the target detection image and the standard blackness is greater than the preset blackness or not; and if the difference value between the blackness of the target detection image and the standard blackness is greater than the preset blackness, judging that the vehicle carpet lamp is unqualified.
Specifically, after the brightness data of the target detection image is acquired by the high-precision imaging brightness test system, the blackness of the target detection image can be calculated according to the brightness data by the LPTS projection lamp online detection system analysis software. Wherein, a plurality of light and dark boundary regions can be intercepted on the target detection image, and a dot can be taken from each light and dark boundary region (the boundary of the bright region and the dark region), for example, H, I and J dots can be taken, then the average illumination value of the H dots is calculated, and the quotient of the average illumination value of the H dots and the illumination value of the corresponding light and dark boundary region is calculated; calculating the average illumination value of the I round point, and calculating the quotient of the average illumination value of the I round point and the illumination value of the corresponding light and shade boundary area; and calculating the average illumination value of the J dots, and calculating the quotient of the average illumination value of the J dots and the illumination value of the corresponding light and shade boundary area.
And comparing the quotient of the average illumination value of the H dot and the illumination value of the corresponding light and shade boundary area, the quotient of the average illumination value of the I dot and the illumination value of the corresponding light and shade boundary area, and the quotient of the average illumination value of the J dot and the illumination value of the corresponding light and shade boundary area with the corresponding standard blackness to judge whether the vehicle carpet lamp is qualified or not. As a possible implementation manner, the difference between the quotient of the average illuminance value of the H dot and the illuminance value of the corresponding light and dark boundary region and the first standard blackness is calculated, and whether the calculated difference is greater than the first preset blackness is judged, if so, the difference between the blackness of the H dot and the first standard blackness is judged to be greater, that is, the vehicle carpet lamp is judged to be unqualified; calculating the difference value between the quotient of the average illumination value of the I round point and the illumination value of the corresponding light and dark boundary area and a second standard blackness, and judging whether the calculated difference value is greater than a second preset blackness or not, if so, judging that the deviation between the blackness of the I round point and the second standard blackness is greater, namely judging that the vehicle carpet lamp is unqualified; and calculating the difference value between the quotient of the average illumination value of the J dot and the illumination value of the corresponding light and dark boundary area and the third standard blackness, and judging whether the calculated difference value is greater than the third preset blackness or not, if so, judging that the deviation between the blackness of the J dot and the third standard blackness is greater, namely judging that the vehicle carpet lamp is unqualified.
Further, when the length value, the uniformity, the gradient and the blackness of the target detection image meet the requirements, the vehicle carpet lamp is judged to be qualified.
In summary, according to the detection method of the vehicle carpet lamp in the embodiment of the invention, the target detection image presented by the vehicle carpet lamp is collected, the brightness data of the target detection image is obtained, the feature data of the target detection image is obtained according to the target detection image and the brightness data of the target detection image, and the vehicle carpet lamp is qualified for detection according to the feature data of the target detection image. From this, can accurately detect vehicle carpet lamp, improve user's experience degree greatly.
The invention further provides a detection device of the vehicle carpet lamp, corresponding to the embodiment.
As shown in fig. 2, the detection apparatus of the vehicle carpet light according to the embodiment of the present invention may include: a first acquisition module 100, a second acquisition module 200, and a detection module 300.
The first obtaining module 100 is configured to collect a target detection image presented by a vehicle carpet light, and obtain brightness data of the target detection image; the second obtaining module 200 is configured to obtain feature data of the target detection image according to the target detection image and luminance data of the target detection image; the detection module 300 is used for performing qualification detection on the vehicle carpet lamp according to the feature data of the target detection image.
According to an embodiment of the present invention, the feature data of the target detection image includes a length value of the target detection image, wherein the detection module 300 is specifically configured to: comparing the length value of the target detection image with the standard length, and judging whether the difference value between the length value of the target detection image and the standard length is greater than the preset length; and if the difference value between the length value of the target detection image and the standard length is greater than the preset length, judging that the vehicle carpet lamp is unqualified.
According to an embodiment of the present invention, the feature data of the target detection image further includes uniformity of the target detection image, wherein the detection module 300 is specifically configured to: comparing the uniformity of the target detection image with the standard uniformity, and judging whether the difference value between the uniformity of the target detection image and the standard uniformity is greater than the preset uniformity; and if the difference value between the uniformity of the target detection image and the standard uniformity is greater than the preset uniformity, judging that the vehicle carpet lamp is unqualified.
According to an embodiment of the present invention, the feature data of the target detection image further includes a gradient of the target detection image, wherein the detection module 300 is specifically configured to: comparing the gradient of the target detection image with the standard gradient, and judging whether the difference value of the gradient of the target detection image and the standard gradient is greater than a preset gradient; and if the difference value between the gradient of the target detection image and the standard gradient is greater than the preset gradient, judging that the vehicle carpet lamp is unqualified.
According to an embodiment of the present invention, the feature data of the target detection image further includes a blackness of the target detection image, wherein the detection module 300 is specifically configured to: comparing the blackness of the target detection image with the standard blackness, and judging whether the difference value between the blackness of the target detection image and the standard blackness is greater than the preset blackness or not; and if the difference value between the blackness of the target detection image and the standard blackness is greater than the preset blackness, judging that the vehicle carpet lamp is unqualified.
It should be noted that, for a more specific implementation of the detection apparatus for a vehicle carpet lamp according to the embodiment of the present invention, reference may be made to the above-mentioned embodiment of the detection method for a vehicle carpet lamp, and details are not repeated herein.
According to the detection device of the vehicle carpet lamp, the first acquisition module is used for acquiring the target detection image presented by the vehicle carpet lamp and acquiring the brightness data of the target detection image, the second acquisition module is used for acquiring the characteristic data of the target detection image according to the target detection image and the brightness data of the target detection image, and the detection module is used for carrying out qualified detection on the vehicle carpet lamp according to the characteristic data of the target detection image. From this, can accurately detect vehicle carpet lamp, improve user's experience degree greatly.
The invention further provides a computer device corresponding to the embodiment.
The computer device of the embodiment of the invention comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, and when the processor executes the program, the detection method of the vehicle carpet lamp of the embodiment is realized.
According to the computer equipment provided by the embodiment of the invention, the vehicle carpet lamp can be accurately detected, and the user experience is greatly improved.
The invention also provides a non-transitory computer readable storage medium corresponding to the above embodiment.
A non-transitory computer-readable storage medium of an embodiment of the present invention has stored thereon a computer program that, when executed by a processor, implements the method of detecting a vehicle carpet light described above.
According to the non-transitory computer-readable storage medium provided by the embodiment of the invention, the vehicle carpet lamp can be accurately detected, and the user experience is greatly improved.
In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. The meaning of "plurality" is two or more unless specifically limited otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the present invention, unless otherwise expressly stated or limited, the first feature "on" or "under" the second feature may be directly contacting the first and second features or indirectly contacting the first and second features through an intermediate. Also, a first feature "on," "over," and "above" a second feature may be directly or diagonally above the second feature, or may simply indicate that the first feature is at a higher level than the second feature. A first feature being "under," "below," and "beneath" a second feature may be directly under or obliquely under the first feature, or may simply mean that the first feature is at a lesser elevation than the second feature.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (8)
1. A method of detecting a vehicle carpet light, comprising the steps of:
acquiring a target detection image presented by the vehicle carpet lamp, and acquiring brightness data of the target detection image;
acquiring characteristic data of the target detection image according to the target detection image and the brightness data of the target detection image;
and performing qualified detection on the vehicle carpet lamp according to the characteristic data of the target detection image.
2. The method of claim 1, wherein the feature data of the object detection image comprises a length value of the object detection image, and wherein the qualified detection of the vehicle carpet light according to the feature data of the object detection image comprises:
comparing the length value of the target detection image with a standard length, and judging whether the difference value between the length value of the target detection image and the standard length is greater than a preset length;
and if the difference value between the length value of the target detection image and the standard length is greater than the preset length, judging that the vehicle carpet lamp is unqualified.
3. The method of claim 2, wherein the feature data of the target detection image further comprises uniformity of the target detection image, and wherein the qualifying the vehicle carpet light according to the feature data of the target detection image further comprises:
comparing the uniformity of the target detection image with a standard uniformity, and judging whether the difference value between the uniformity of the target detection image and the standard uniformity is greater than a preset uniformity;
and if the difference value between the uniformity of the target detection image and the standard uniformity is greater than the preset uniformity, judging that the vehicle carpet lamp is unqualified.
4. The method of claim 3, wherein the feature data of the object detection image further comprises a gradient of the object detection image, wherein the qualified detection of the vehicle carpet light according to the feature data of the object detection image further comprises:
comparing the gradient of the target detection image with a standard gradient, and judging whether the difference value of the gradient of the target detection image and the standard gradient is greater than a preset gradient;
and if the difference value between the gradient of the target detection image and the standard gradient is greater than the preset gradient, judging that the vehicle carpet lamp is unqualified.
5. The method of claim 4, wherein the feature data of the target detection image further includes a blackness of the target detection image, wherein the qualified detection of the vehicle carpet light according to the feature data of the target detection image further includes:
comparing the blackness of the target detection image with a standard blackness, and judging whether the difference value between the blackness of the target detection image and the standard blackness is greater than a preset blackness;
and if the difference value between the blackness of the target detection image and the standard blackness is greater than the preset blackness, judging that the vehicle carpet lamp is unqualified.
6. A detection apparatus for a vehicle carpet light, comprising:
the first acquisition module is used for acquiring a target detection image presented by the vehicle carpet lamp and acquiring brightness data of the target detection image;
the second acquisition module is used for acquiring the characteristic data of the target detection image according to the target detection image and the brightness data of the target detection image;
and the detection module is used for carrying out qualified detection on the vehicle carpet lamp according to the characteristic data of the target detection image.
7. A computer arrangement comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the computer program, carries out the method of detecting a vehicle carpet light according to any of claims 1-5.
8. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that the program, when executed by a processor, implements the method of detecting the vehicle carpet light according to any one of claims 1 to 5.
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