CN113068024A - Real-time snap analysis method and storage medium - Google Patents
Real-time snap analysis method and storage medium Download PDFInfo
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- CN113068024A CN113068024A CN202110297625.9A CN202110297625A CN113068024A CN 113068024 A CN113068024 A CN 113068024A CN 202110297625 A CN202110297625 A CN 202110297625A CN 113068024 A CN113068024 A CN 113068024A
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Abstract
A real-time capture analysis method comprises the following steps of carrying out real-time capture storage according to a subcode stream under the background of online transmission of a main code stream, and uploading data stored in the capture storage to a server to carry out implementation analysis on a data stream. By the technical scheme, real-time image capture can be performed according to the sub-code stream, multi-format data can be analyzed under the condition that the work of the main code stream is not influenced, and the multi-format data can be transmitted to the server. The IDLE of a local PC or equipment is not occupied, and the complex algorithm calculation amount is not operated on the local equipment, so that the CPU resource of the equipment is saved, and the efficiency is higher.
Description
Technical Field
The invention relates to the field of picture processing, in particular to a cloud capture analysis method.
Background
When the prior art carries out grab image analysis comparison, high-quality pictures cannot be grabbed, such as the pictures in the patent US10867221B 2: a computer method and system for automatic determination of high quality digital content. The system or method described in this patent relates to obtaining a RAW image, comparing the obtained RAW image with a target value (i.e. the high quality image described herein), outputting the comparison result, and determining the quality of the captured image. But lacks the function of simultaneously capturing RAW, YUV and JPEG images and ISP parameter information thereof at one time.
Disclosure of Invention
Therefore, a multi-core processor evaluation adjustment method needs to be provided to meet the flexible conversion that a single-core processor carries out super-frequency processing or a multi-core processor occupies a memory to recover a standard frequency processing state;
in order to achieve the above object, the inventor provides a real-time capture analysis method, which includes the following steps of opening a subcode stream under the background of subjective debugging of main code stream online transmission preview, performing real-time capture storage according to the subcode stream, and synchronously uploading the stored data to a server for real-time analysis of the data.
Specifically, the Linux device receives a real-time image capturing instruction, wherein the real-time image capturing instruction comprises a voice instruction, a webpage instruction or a serial port.
In particular, the amount of the solvent to be used,
and performing real-time image capture and storage according to the subcode stream, wherein register information of RAW image data, YUV image data, JPEG image data and VICAP/ISP/ISPP is stored, and the cloud server analyzes the YUV image data stored by image capture to obtain the statistical results of signal-to-noise ratio, brightness and color.
Specifically, the server implements a statistical algorithm of signal-to-noise ratio, brightness and color through OpenCV, and analyzes and compares data stored in the real-time capture.
A real-time capture and analysis storage medium stores a computer program, wherein the computer program comprises the following steps of opening a subcode stream under the background of subjective debugging of main code stream online transmission preview, carrying out real-time capture and storage according to the subcode stream, and synchronously uploading the stored data to a server for real-time analysis of the data.
Specifically, the computer program further executes a step when being executed, and the Linux device receives a real-time image capturing instruction, wherein the real-time image capturing instruction comprises a voice instruction or a webpage instruction or a serial port.
In particular, the amount of the solvent to be used,
and performing real-time image capture and storage according to the subcode stream, wherein register information of RAW image data, YUV image data, JPEG image data and VICAP/ISP/ISPP is stored, and the cloud server analyzes the YUV image data stored by image capture to obtain the statistical results of signal-to-noise ratio, brightness and color.
Specifically, the server implements a statistical algorithm of signal-to-noise ratio, brightness and color through OpenCV, and analyzes and compares data stored in the real-time capture.
By the technical scheme, real-time image capture can be performed according to the sub-code stream, multi-format data can be analyzed under the condition that the work of the main code stream is not influenced, and the multi-format data can be transmitted to the server. The IDLE of a local PC or equipment is not occupied, and the complex algorithm calculation amount is not operated on the local equipment, so that the CPU resource of the equipment is saved, and the efficiency is higher.
Drawings
Fig. 1 is a flowchart of a real-time snapshot analysis method according to an embodiment of the present invention.
Detailed Description
To explain technical contents, structural features, and objects and effects of the technical solutions in detail, the following detailed description is given with reference to the accompanying drawings in conjunction with the embodiments.
Referring to fig. 1, a real-time snapshot analysis method is introduced, which includes the following steps that S100, in the context of online transmission of a main code stream, performs real-time snapshot storage according to a sub-code stream, and a data upload server that performs snapshot storage performs implementation analysis on a data stream. Most ISPs can copy data input by one camera into two paths and output the two paths of data to the two paths of code streams of mainpath and selfpath, and the data become a main code stream and a sub code stream respectively. The technical scheme of the IQ Tune engineer can perform real-time grab according to the subcode stream, analyze multi-format data under the condition of not influencing the work of the main code stream, and transmit the data to the server. The IDLE of a local PC or equipment is not occupied, and the complex algorithm calculation amount is not operated on the local equipment, so that the CPU resource of the equipment is saved, and the efficiency is higher.
Specifically, the method further comprises the step of S101 receiving a real-time image capturing instruction, wherein the real-time image capturing instruction comprises a voice instruction or a webpage instruction.
Specifically, real-time capture storage is carried out according to the subcode stream, the capture format comprises storage of RAW image data, YUV image data and JPEG image data, and the server analyzes the data stored in the capture to obtain the statistical results of signal-to-noise ratio, brightness and color.
Further, the server analyzes and compares the data stored in the real-time snapshot through OpenCV.
Specifically, the embodiment can be implemented in Linux equipment, a real-time capture analysis tool can receive a client voice instruction, a webpage instruction, a serial port instruction and the like under the condition of not influencing the real-time preview of a main code stream, open a subcode stream for capture storage, wherein the subcode stream can be obtained through a code stream copying function of an ISP (internet service provider), the result of capture storage of the subcode stream is uploaded to a server, and the server performs real-time analysis and comparison through opencv and an independently-implemented algorithm (luminance histogram statistics, signal-to-noise ratio and the like) to obtain objective signal-to-noise ratio, luminance and color statistics results, so that an engineer debugging the Camera can conveniently make reference.
If the equipment is nearby, the equipment can capture pictures through voice/serial ports;
if the equipment is not nearby, the equipment can access the Linux equipment through the web to issue the grab image instruction.
The grab can simultaneously store the parameter information of RAW, YUV, JPEG and ISP.
And actively uploading the grab picture result to a server.
And the server actively analyzes and counts the image capturing result and stores the statistical result to the shared directory.
The method can achieve the aim of convenient operation for users. The statistical algorithm is processed at the cloud, the IDLE of a local PC or equipment is not occupied, and the complex algorithm calculated amount does not run on the local equipment, so that the CPU resource of the equipment is saved, and the efficiency is higher. And objective statistical results are obtained in real time, and user debugging is assisted. Meanwhile, the compatibility is good, and the chip can be adapted to any chip based on a Linux platform.
The scheme also introduces a real-time capture and analysis storage medium, which stores a computer program, wherein the computer program comprises the following steps of opening the subcode stream under the background of subjective debugging of online transmission and preview of the main code stream, performing real-time capture and storage according to the subcode stream, and synchronously uploading the stored data to a server for real-time analysis of the data when the computer program is run.
Specifically, the computer program further executes a step when being executed, and the Linux device receives a real-time image capturing instruction, wherein the real-time image capturing instruction comprises a voice instruction or a webpage instruction or a serial port.
In particular, the amount of the solvent to be used,
and performing real-time image capture and storage according to the subcode stream, wherein register information of RAW image data, YUV image data, JPEG image data and VICAP/ISP/ISPP is stored, and the cloud server analyzes the YUV image data stored by image capture to obtain the statistical results of signal-to-noise ratio, brightness and color.
Specifically, the server implements a statistical algorithm of signal-to-noise ratio, brightness and color through OpenCV, and analyzes and compares data stored in the real-time capture.
By the technical scheme, real-time image capture can be performed according to the sub-code stream, multi-format data can be analyzed under the condition that the work of the main code stream is not influenced, and the multi-format data can be transmitted to the server. The IDLE of a local PC or equipment is not occupied, and the complex algorithm calculation amount is not operated on the local equipment, so that the CPU resource of the equipment is saved, and the efficiency is higher.
It should be noted that, although the above embodiments have been described herein, the invention is not limited thereto. Therefore, based on the innovative concepts of the present invention, the technical solutions of the present invention can be directly or indirectly applied to other related technical fields by making changes and modifications to the embodiments described herein, or by using equivalent structures or equivalent processes performed in the content of the present specification and the attached drawings, which are included in the scope of the present invention.
Claims (8)
1. A real-time capture analysis method is characterized by comprising the following steps of opening a subcode stream under the background of subjective debugging of main code stream online transmission preview, carrying out real-time capture storage according to the subcode stream, and synchronously uploading the stored data to a server for carrying out real-time analysis on the data.
2. The real-time snapshot analysis method of claim 1, further comprising the step of receiving a real-time snapshot instruction by the Linux device, wherein the real-time snapshot instruction comprises a voice instruction or a web page instruction or a serial port.
3. The real-time snap-shot analysis method according to claim 1,
and performing real-time image capture and storage according to the subcode stream, wherein register information of RAW image data, YUV image data, JPEG image data and VICAP/ISP/ISPP is stored, and the cloud server analyzes the YUV image data stored by image capture to obtain the statistical results of signal-to-noise ratio, brightness and color.
4. The real-time grab image analysis method according to claim 1, wherein the server implements a statistical algorithm of signal-to-noise ratio, brightness and color through OpenCV, and analyzes and compares data stored in the real-time grab image.
5. A real-time capture and analysis storage medium is characterized in that a computer program is stored, and the computer program is executed when being executed, wherein the computer program comprises the following steps of opening a subcode stream under the background of subjective debugging of online transmission and preview of a main code stream, carrying out real-time capture and storage according to the subcode stream, and synchronously uploading the stored data to a server for carrying out real-time analysis on the data.
6. The real-time snapshot analysis storage medium of claim 5, wherein the computer program when executed further performs the steps comprising the Linux device receiving a real-time snapshot instruction comprising a voice instruction or a web page instruction or a serial port.
7. The real-time snap-shot analysis storage medium of claim 5,
and performing real-time image capture and storage according to the subcode stream, wherein register information of RAW image data, YUV image data, JPEG image data and VICAP/ISP/ISPP is stored, and the cloud server analyzes the YUV image data stored by image capture to obtain the statistical results of signal-to-noise ratio, brightness and color.
8. The storage medium of claim 5, wherein the server implements a statistical algorithm of signal-to-noise ratio, brightness, and color by OpenCV, and analyzes and compares data stored in the real-time snapshot.
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