CN114040188A - Camera module automatic testing method and system based on voice recognition - Google Patents
Camera module automatic testing method and system based on voice recognition Download PDFInfo
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- CN114040188A CN114040188A CN202111127606.8A CN202111127606A CN114040188A CN 114040188 A CN114040188 A CN 114040188A CN 202111127606 A CN202111127606 A CN 202111127606A CN 114040188 A CN114040188 A CN 114040188A
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- 238000012360 testing method Methods 0.000 title claims abstract description 61
- 238000004458 analytical method Methods 0.000 claims abstract description 7
- 238000007405 data analysis Methods 0.000 claims description 8
- 238000010998 test method Methods 0.000 claims 6
- 238000000034 method Methods 0.000 abstract description 15
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- 230000009286 beneficial effect Effects 0.000 description 1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
- G10L2015/223—Execution procedure of a spoken command
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Abstract
A method and a system for automatically testing a camera module based on voice recognition are provided, wherein the method comprises the following steps: step 1, compiling an automatic test file of a camera module; step 2, recognizing a voice command of an operator, calling the automatic test file of the camera module based on the voice command, and automatically testing the camera module; and 3, acquiring test data of the camera module, analyzing whether the test data meets the preset requirement, and determining the production condition of the camera module based on the analysis result. The invention breaks through the problem of man-machine interaction in a mouse mode when the traditional module factory produces modules, improves the production efficiency, avoids the restriction of operation environment factors in the actual production link, can be well popularized to other fields, and solves the problem of low man-machine interaction efficiency in any module production.
Description
Technical Field
The invention relates to the field of camera module testing, in particular to a camera module automatic testing method and system based on voice recognition.
Background
The existing camera module test is that a tester performs man-machine interaction with test equipment in a mouse click mode, the tester needs to manually select items to be tested, and after the test is completed, a test result is judged.
Disclosure of Invention
In view of the technical defects and technical drawbacks in the prior art, an embodiment of the present invention provides an automatic testing method for a camera module based on voice recognition, which overcomes or at least partially solves the above problems, and the specific scheme is as follows:
as a first aspect of the present invention, a method for automatically testing a camera module based on speech recognition is provided, where the method includes:
step 1, compiling an automatic test file of a camera module;
step 2, recognizing a voice command of an operator, calling the automatic test file of the camera module based on the voice command, and automatically testing the camera module;
and 3, acquiring test data of the camera module, analyzing whether the test data meets the preset requirement, and determining the production condition of the camera module based on the analysis result.
Further, in step 1, the automatic test file of the camera module is an x.dll file, and the flow items to be tested are written in the x.dll file.
Further, step 3 specifically includes:
step 3.1, acquiring the production data specification of the camera module through a GUI interface;
step 3.2, acquiring the AWB data of the camera module according to the current light source environment;
step 3.3, acquiring preset proportion data of the region of interest in the current RAW image data of the camera module;
step 3.4, judging whether the corresponding brightness value in the acquired preset proportion data meets a preset requirement, if not, judging that the production of the camera module is failed, if so, storing the RAW image data into data logs with different formats and purposes, and burning the data logs into a chip of the camera module;
and 3.5, reading the burning data from the chip, judging whether the burning data meets the preset requirement one by one, if not, judging that the production of the camera module is failed, if so, judging that the voice command is successfully executed, and waiting for the next voice command.
Further, in step 3.3, 1/10 partial data of the region of interest in the current RAW map data of the camera module are acquired, and in step 3.4, it is determined whether the corresponding brightness value in 1/10 partial data of the acquired region of interest meets the preset requirement.
Further, the method further comprises: and (3) pre-establishing an appendix I, wherein the appendix I comprises a specification file for judging whether the brightness value meets the preset requirement, and in the step 3.4, judging whether the corresponding brightness value in the partial data of the region of interest meets the preset requirement through the appendix I.
Further, the scheme further comprises: and (3) pre-establishing an appendix II, wherein the appendix II comprises a standard file for judging whether the burning data meets the preset requirement, and in the step 3.5, judging whether the burning data meets the preset requirement through the appendix II byte by byte.
As a second aspect of the present invention, there is provided an automatic test system for a camera module based on voice recognition, the system comprising an editing unit, a voice recognition unit and a data analysis unit;
the editing unit is used for compiling an automatic test file of the camera module;
the voice recognition unit is used for recognizing a voice command of an operator, calling the automatic test file of the camera module based on the voice command, and automatically testing the camera module;
the data analysis unit is used for acquiring test data of the camera module, analyzing whether the test data meets preset requirements or not, and determining the production condition of the camera module based on an analysis result.
Further, the data analysis unit is specifically configured to:
acquiring the production data specification of the camera module through a GUI interface;
acquiring AWB data of the camera module according to the current light source environment;
acquiring preset proportion data of an interest area in current RAW image data of a camera module;
judging whether the corresponding brightness value in the acquired preset proportion data meets a preset requirement, if not, judging that the production of the camera module is failed, if so, storing the RAW image data into data logs with different formats and purposes, and burning the data logs into a chip of the camera module;
reading the burning data from the chip, judging whether the burning data meets the preset requirement byte by byte, if not, judging that the production of the camera module is failed, if so, judging that the voice command is successfully executed, and waiting for the next voice command.
Further, the system further comprises an appendix establishing unit, wherein the appendix establishing unit is used for establishing a required appendix in advance, the appendix comprises an appendix I and an appendix II, the appendix I comprises a specification file for judging whether the brightness value meets the preset requirement, and the appendix II comprises a specification file for judging whether the burning data meets the preset requirement.
The invention has the following beneficial effects:
according to the invention, the voice command of an operator is recognized, the automatic test file of the camera module is automatically called, the camera module is automatically tested, and the test result is automatically analyzed, so that the problem of man-machine interaction in a mouse mode during the production of the module in the traditional module factory is solved, the production efficiency is improved, the restriction of the operation environment factors in the actual production link is avoided, the method can be well popularized to other fields, and the problem of low man-machine interaction efficiency in any module production is solved.
Drawings
Fig. 1 is a schematic flow chart of a method for automatically testing a camera module based on voice recognition 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 present invention, and not all 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.
As shown in fig. 1, as a first embodiment of the present invention, there is provided a method for automatically testing a camera module based on voice recognition, the method including:
step 1, compiling an automatic test file of a camera module, wherein the automatic test file of the camera module is a dll file, and process items needing to be tested, such as SP5508_ SIDA550800373_ VA.dll, are compiled in the dll file;
step 2, recognizing a voice command of an operator, calling the automatic test file of the camera module based on the voice command, and automatically testing the camera module, wherein if the automatic test file of the camera module is called for multiple times and fails after the voice command of the operator is recognized each time, the generation of the module is judged to fail;
and 3, acquiring test data of the camera module, analyzing whether the test data meets the preset requirement, and determining the production condition of the camera module based on the analysis result.
According to the invention, the voice command of an operator is recognized, the automatic test file of the camera module is automatically called, the camera module is automatically tested, and the test result is automatically analyzed, so that the problem of man-machine interaction in a mouse mode during the production of the module in the traditional module factory is solved, the production efficiency is improved, the restriction of the operation environment factors in the actual production link is avoided, the method can be well popularized to other fields, and the problem of low man-machine interaction efficiency in any module production is solved.
Wherein, step 3 specifically includes:
step 3.1, acquiring the production data specification of the camera module through a GUI (Graphical User Interface) Interface;
step 3.2, acquiring AWB (automatic White Balance) data of the camera module according to the current light source environment;
wherein, according to the hardware environment parameters in table 1, a hardware environment is established and obtained by a software mode realized by a computer c + + language. And obtaining the AWB data of the camera module acquired by the current light source environment. The mathematical models of the four channels are as follows: r ═ int (R _ avg-BLC); gr — int (Gr _ avg-BLC); gb ═ int (Gb _ avg-BLC); b ═ int (B _ avg-BLC); g ═ int (Gr + Gb)/2; R/G ═ int (R/G × 128+ 0.5); B/G ═ int (B/G × 128+ 0.5);
TABLE 1
Step 3.3, 1/10 partial data of an interested area in current RAW image data of the camera module are obtained, wherein the RAW image is RAW data obtained by converting a captured light source signal into a digital signal by a CMOS or CCD image sensor, and a RAW file is a file which records RAW information of a digital camera sensor and records some metadata generated by camera shooting;
the method comprises the steps of obtaining an interested area in current RAW image data of a camera module. The method specifically comprises the following steps: determining an image contour, calculating the length and width of the image based on the image contour, determining the central point of the image based on the length and width of the image, and taking the central point of the image as the center to outwards take the area of the length/n and the width/n of the image as an interested area; for example, the image shown in table 1 has a size of 2608 × 1960, i.e., a length 2608 and a width 1960, which are divided by 2 to obtain a length 1304 and a width 980, respectively, so as to find the center point of the image, and 2608/20 and 1960/20, which take the size of the image with the center point of the image as the center, are regions of interest, i.e., rectangular regions with a length 2608/20 and a width 1960/20, which are centered on the center point of the image.
The obtaining of the brightness value from the data of the region of interest specifically includes: acquiring AWB data of the region of interest, and acquiring values of four channels from the AWB data: thus obtaining the brightness value.
Step 3.4, judging whether the corresponding brightness value in the obtained 1/10 partial data meets the preset requirement, if not, judging that the production of the camera module is failed, if so, storing the RAW image data into data logs with different formats and purposes, and burning the data logs into a chip of the camera module;
and 3.5, reading the burning data from the chip, judging whether the burning data meets the preset requirement one by one, if not, judging that the production of the camera module is failed, if so, judging that the voice command is successfully executed, and waiting for the next voice command.
Wherein the method further comprises: the method comprises the steps that an appendix I and an appendix II are established in advance, the appendix I comprises a standard file for judging whether the brightness value meets the preset requirement, the appendix II comprises a standard file for judging whether the burning data meets the preset requirement, in step 3.4, whether the corresponding brightness value in partial data of the region of interest meets the preset requirement is judged through the appendix I, and in step 3.5, whether the burning data meets the preset requirement is judged through the appendix II byte by byte.
As a second embodiment of the present invention, there is also provided an automatic test system for a camera module based on voice recognition, the system including an editing unit, a voice recognition unit, and a data analysis unit;
the editing unit is used for compiling an automatic test file of the camera module;
the voice recognition unit is used for recognizing a voice command of an operator, calling the automatic test file of the camera module based on the voice command, and automatically testing the camera module;
the data analysis unit is used for acquiring test data of the camera module, analyzing whether the test data meets preset requirements or not, and determining the production condition of the camera module based on an analysis result.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (9)
1. A camera module automatic test method based on voice recognition is characterized by comprising the following steps:
step 1, compiling an automatic test file of a camera module;
step 2, recognizing a voice command of an operator, calling the automatic test file of the camera module based on the voice command, and automatically testing the camera module;
and 3, acquiring test data of the camera module, analyzing whether the test data meets the preset requirement, and determining the production condition of the camera module based on the analysis result.
2. The automatic test method for the camera module based on the voice recognition as claimed in claim 1, wherein in the step 1, the automatic test file for the camera module is a _.
3. The automatic test method for the camera module based on the voice recognition according to claim 1, wherein the step 3 specifically comprises:
step 3.1, acquiring the production data specification of the camera module through a GUI interface;
step 3.2, acquiring the AWB data of the camera module according to the current light source environment;
step 3.3, acquiring preset proportion data of the region of interest in the current RAW image data of the camera module;
step 3.4, judging whether the corresponding brightness value in the acquired preset proportion data meets a preset requirement, if not, judging that the production of the camera module is failed, if so, storing the RAW image data into data logs with different formats and purposes, and burning the data logs into a chip of the camera module;
and 3.5, reading the burning data from the chip, judging whether the burning data meets the preset requirement one by one, if not, judging that the production of the camera module is failed, if so, judging that the voice command is successfully executed, and waiting for the next voice command.
4. The automatic test method for camera module based on voice recognition of claim 3, wherein in step 3.3, 1/10 partial data of the region of interest in the current RAW map data of the camera module are obtained, and in step 3.4, it is determined whether the corresponding brightness value in 1/10 partial data of the region of interest meets the preset requirement.
5. The automatic test method for the camera module based on the voice recognition according to claim 3, further comprising: and (3) pre-establishing an appendix I, wherein the appendix I comprises a specification file for judging whether the brightness value meets the preset requirement, and in the step 3.4, judging whether the corresponding brightness value in the partial data of the region of interest meets the preset requirement through the appendix I.
6. The automatic test method for the camera module based on the voice recognition according to claim 3, wherein the scheme further comprises: and (3) pre-establishing an appendix II, wherein the appendix II comprises a standard file for judging whether the burning data meets the preset requirement, and in the step 3.5, judging whether the burning data meets the preset requirement through the appendix II byte by byte.
7. A camera module automatic test system based on voice recognition is characterized by comprising an editing unit, a voice recognition unit and a data analysis unit;
the editing unit is used for compiling an automatic test file of the camera module;
the voice recognition unit is used for recognizing a voice command of an operator, calling the automatic test file of the camera module based on the voice command, and automatically testing the camera module;
the data analysis unit is used for acquiring test data of the camera module, analyzing whether the test data meets preset requirements or not, and determining the production condition of the camera module based on an analysis result.
8. The system for automatically testing a camera module based on speech recognition according to claim 7, wherein the data analysis unit is specifically configured to:
acquiring the production data specification of the camera module through a GUI interface;
acquiring AWB data of the camera module according to the current light source environment;
acquiring preset proportion data of an interest area in current RAW image data of a camera module;
judging whether the corresponding brightness value in the acquired preset proportion data meets a preset requirement, if not, judging that the production of the camera module is failed, if so, storing the RAW image data into data logs with different formats and purposes, and burning the data logs into a chip of the camera module;
reading the burning data from the chip, judging whether the burning data meets the preset requirement byte by byte, if not, judging that the production of the camera module is failed, if so, judging that the voice command is successfully executed, and waiting for the next voice command.
9. The automatic test system for camera modules based on voice recognition according to claim 7, further comprising an appendix establishing unit, wherein the appendix establishing unit is used for establishing a required appendix in advance, the appendix comprises an appendix one and an appendix two, the appendix one contains a specification file for judging whether the brightness value meets a preset requirement, and the appendix two contains a specification file for judging whether the burning data meets the preset requirement.
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Application publication date: 20220211 |