CN116723419A - Acquisition speed optimization method and device for billion-level high-precision camera - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/95—Computational photography systems, e.g. light-field imaging systems
- H04N23/951—Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/70—Circuitry for compensating brightness variation in the scene
- H04N23/73—Circuitry for compensating brightness variation in the scene by influencing the exposure time
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
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Abstract
The application discloses an acquisition speed optimization method and device for a billion-level high-precision camera. Wherein the method comprises the following steps: obtaining working parameters and target optimization parameters of a camera, wherein the target optimization parameters comprise: resolution optimization parameters, exposure time optimization parameters; optimizing the working parameters of the camera according to the resolution optimization parameters to obtain a first optimization result; extracting an exposure time parameter in the working parameters of the camera, and comparing the exposure time parameter with the exposure time optimization parameter to obtain a first comparison result; and comparing the first comparison result with a preset threshold value to obtain a second comparison result, and optimizing the exposure time according to the first optimization result and the second comparison result to obtain a second optimization result. The application solves the technical problems that the billion-grade camera acquisition parameter optimization method in the prior art only constructs the expected target of image acquisition according to the image generation efficiency of the camera, thereby improving the acquisition speed in terms of parameters, and thus, when processing more complex or diversified image data, an optimization strategy cannot be quickly made, and a large amount of calculation resources are wasted.
Description
Technical Field
The application relates to the field of camera parameter optimization, in particular to an acquisition speed optimization method and device for a billion-level high-precision camera.
Background
Along with the continuous development of intelligent science and technology, intelligent equipment is increasingly used in life, work and study of people, and the quality of life of people is improved and the learning and working efficiency of people is increased by using intelligent science and technology means.
At present, aiming at the acquisition speed and the image acquisition speed of camera parameters, the acquisition bandwidth or the speed of an acquisition algorithm is generally confirmed and improved in the optimization process, and the running stability and the running performance quality of the camera with hundred million-level pixels are ensured. However, the billion-level camera acquisition parameter optimization method in the prior art only constructs an expected target of image acquisition according to the image generation efficiency of the camera, so that the acquisition speed is increased in terms of parameters, and thus, when more complex or diversified image data are processed, an optimization strategy cannot be quickly made, and a great deal of calculation resources are wasted.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the application provides a method and a device for optimizing the acquisition speed of a billion-level high-precision camera, which at least solve the technical problems that the billion-level camera acquisition parameter optimization method in the prior art only constructs an expected target of image acquisition according to the image generation efficiency of the camera, so that the acquisition speed is improved in terms of parameters, and an optimization strategy cannot be quickly made when more complex or diversified image data are processed, and a large amount of calculation resources are wasted.
According to an aspect of an embodiment of the present application, there is provided an acquisition speed optimization method for a billion-level high-precision camera, including: obtaining working parameters and target optimization parameters of a camera, wherein the target optimization parameters comprise: resolution optimization parameters, exposure time optimization parameters; optimizing the working parameters of the camera according to the resolution optimization parameters to obtain a first optimization result; extracting an exposure time parameter in the working parameters of the camera, and comparing the exposure time parameter with the exposure time optimization parameter to obtain a first comparison result; and comparing the first comparison result with a preset threshold value to obtain a second comparison result, and optimizing the exposure time according to the first optimization result and the second comparison result to obtain a second optimization result.
Optionally, before the optimizing the working parameters of the camera according to the resolution optimization parameters to obtain a first optimization result, the method further includes: acquiring the preset resolution rule; matching the resolution optimization parameter with the preset resolution rule to obtain a matching result, wherein the matching result comprises: the method meets the application requirements and does not meet the application requirements, wherein the preset resolution rule is used for representing the resolution guarantee requirements under the preset application scene.
Optionally, the extracting an exposure time parameter from the working parameters of the camera, and comparing the exposure time parameter with the exposure time optimization parameter, to obtain a first comparison result includes: extracting exposure time parameters in the working parameters of the camera; and comparing and calculating the exposure time parameter and the exposure time optimization parameter by using a threshold comparison algorithm to obtain the first comparison result representing the difference value of the two parameters.
Optionally, the comparing the first comparison result with a preset threshold value to obtain a second comparison result, and optimizing the exposure time according to the first optimization result and the second comparison result, where obtaining the second optimization result includes: comparing the parameters in the first comparison result with the preset threshold parameters to obtain a second comparison result, wherein the second comparison result comprises: the threshold range is not exceeded, and the threshold range is exceeded; and when the second comparison result does not exceed the threshold range, optimizing according to the exposure time optimization parameter on the basis of the first optimization result to obtain the second optimization result.
According to another aspect of an embodiment of the present application, there is also provided an acquisition speed optimizing apparatus for a billion-level high-precision camera, including: the system comprises an acquisition module, a target optimization module and a control module, wherein the acquisition module is used for acquiring working parameters and target optimization parameters of a camera, and the target optimization parameters comprise: resolution optimization parameters, exposure time optimization parameters; the optimizing module is used for optimizing the working parameters of the camera according to the resolution optimizing parameters to obtain a first optimizing result; the extraction module is used for extracting exposure time parameters in the working parameters of the camera, and comparing the exposure time parameters with the exposure time optimization parameters to obtain a first comparison result; and the comparison module is used for comparing the first comparison result with a preset threshold value to obtain a second comparison result, and optimizing the exposure time according to the first optimization result and the second comparison result to obtain a second optimization result.
Optionally, the apparatus further includes: the acquisition module is also used for acquiring the preset resolution rule; the matching module is used for matching the resolution optimization parameter with the preset resolution rule to obtain a matching result, wherein the matching result comprises the following steps: the method meets the application requirements and does not meet the application requirements, wherein the preset resolution rule is used for representing the resolution guarantee requirements under the preset application scene.
Optionally, the extracting module includes: the extraction unit is used for extracting exposure time parameters in the working parameters of the camera; and the comparison unit is used for comparing and calculating the exposure time parameter and the exposure time optimization parameter by using a threshold comparison algorithm to obtain the first comparison result representing the difference value of the two parameters.
Optionally, the comparison module includes: the comparison unit is configured to perform a comparison operation on the parameter in the first comparison result and the preset threshold parameter to obtain the second comparison result, where the second comparison result includes: the threshold range is not exceeded, and the threshold range is exceeded; and the optimizing unit is used for optimizing according to the exposure time optimizing parameter on the basis of the first optimizing result to obtain the second optimizing result when the second comparing result does not exceed the threshold range.
According to another aspect of the embodiments of the present application, there is also provided a nonvolatile storage medium including a stored program, wherein the program when run controls a device in which the nonvolatile storage medium is located to execute an acquisition speed optimization method for a billion-level high-precision camera.
According to another aspect of the embodiment of the present application, there is also provided an electronic device including a processor and a memory; the memory has stored therein computer readable instructions for execution by the processor, wherein the computer readable instructions when executed perform a method of acquisition speed optimization for a billion-level high precision camera.
In the embodiment of the application, the working parameters of the camera and the target optimization parameters are acquired, wherein the target optimization parameters comprise: resolution optimization parameters, exposure time optimization parameters; optimizing the working parameters of the camera according to the resolution optimization parameters to obtain a first optimization result; extracting an exposure time parameter in the working parameters of the camera, and comparing the exposure time parameter with the exposure time optimization parameter to obtain a first comparison result; the first comparison result is compared with a preset threshold value to obtain a second comparison result, and the exposure time is optimized according to the first optimization result and the second comparison result to obtain a second optimization result, so that the technical problems that in the prior art, the hundred million-level camera acquisition parameter optimization method only constructs an expected target of image acquisition according to the camera image generation efficiency, the acquisition speed is improved from parameters, and therefore, when complex or diversified image data are processed, an optimization strategy cannot be made very rapidly, and a large amount of calculation resources are wasted are solved.
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a flow chart of a method of acquisition speed optimization for a billion-level high-precision camera in accordance with an embodiment of the present application;
FIG. 2 is a block diagram of an acquisition speed optimization apparatus for a billion-level high-precision camera in accordance with an embodiment of the present application;
fig. 3 is a block diagram of a terminal device for performing the method according to the application according to an embodiment of the application;
fig. 4 is a memory unit for holding or carrying program code for implementing a method according to the application, according to an embodiment of the application.
Detailed Description
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In accordance with an embodiment of the present application, there is provided a method embodiment of an acquisition speed optimization method for a billion-level high-precision camera, it being noted that the steps shown in the flowchart of the figures may be performed in a computer system, such as a set of computer-executable instructions, and, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in an order other than that shown herein.
Example 1
FIG. 1 is a flow chart of a method for acquisition speed optimization for a billion-level high-precision camera, as shown in FIG. 1, according to an embodiment of the present application, the method comprising the steps of:
step S102, acquiring working parameters and target optimization parameters of a camera, wherein the target optimization parameters comprise: resolution optimization parameters, exposure time optimization parameters.
Specifically, in order to solve the technical problem that in the prior art, the method for optimizing the acquisition parameters of the hundred-level camera only constructs the expected target of image acquisition according to the image generation efficiency of the camera, so as to increase the acquisition speed in terms of parameters, so that when processing more complex or diversified image data, an optimization strategy cannot be quickly made, and a great deal of computing resources are wasted, firstly, the working parameters of the camera or the array device need to be acquired, wherein the working parameters comprise all parameters of the camera operation, such as exposure time, transmission bandwidth and the like, and the target optimization parameters need to be acquired, and the target optimization parameters comprise: resolution optimization parameters, exposure time optimization parameters.
Step S104, optimizing the working parameters of the camera according to the resolution optimization parameters to obtain a first optimization result.
Specifically, after the working parameters of the camera are obtained, the working parameters of the camera are required to be optimized according to the condition of the optimization target, so that the running state of the camera is optimized through the optimized parameters, and the efficiency of image acquisition, transmission and analysis is improved.
Optionally, before the optimizing the working parameters of the camera according to the resolution optimization parameters to obtain a first optimization result, the method further includes: acquiring the preset resolution rule; matching the resolution optimization parameter with the preset resolution rule to obtain a matching result, wherein the matching result comprises: the method meets the application requirements and does not meet the application requirements, wherein the preset resolution rule is used for representing the resolution guarantee requirements under the preset application scene.
Specifically, before resolution optimization is performed, the embodiment of the application needs to acquire the expected optimization parameters of the resolution, namely the preset resolution rule, wherein the preset resolution rule is a resolution expected value configured or selected by a user according to an application scene, and the value is converted into a rule form by using a conversion algorithm, so that the resolution optimization parameters and the preset resolution optimization rule are compared and matched, and the resolution optimization scheme can be compared and verified with the actual preset resolution rule before the resolution parameters are optimized, so that a matching result is obtained. For example, before the optimizing the camera operating parameters according to the resolution optimizing parameters to obtain the first optimizing result, the method further includes: acquiring the preset resolution rule; matching the resolution optimization parameter with the preset resolution rule to obtain a matching result, wherein the matching result comprises: the method meets the application requirements and does not meet the application requirements, wherein the preset resolution rule is used for representing the resolution guarantee requirements under the preset application scene.
Step S106, extracting an exposure time parameter in the working parameters of the camera, and comparing the exposure time parameter with the exposure time optimization parameter to obtain a first comparison result.
Optionally, the extracting an exposure time parameter from the working parameters of the camera, and comparing the exposure time parameter with the exposure time optimization parameter, to obtain a first comparison result includes: extracting exposure time parameters in the working parameters of the camera; and comparing and calculating the exposure time parameter and the exposure time optimization parameter by using a threshold comparison algorithm to obtain the first comparison result representing the difference value of the two parameters.
Specifically, after the resolution parameter is optimized according to the embodiment of the present application, the optimization of the exposure time parameter may be extracting the exposure time parameter in the working parameters of the camera, and comparing the exposure time parameter with the exposure time optimization parameter to obtain a first comparison result, where the obtaining of the first comparison result includes: extracting exposure time parameters in the working parameters of the camera; and comparing and calculating the exposure time parameter and the exposure time optimization parameter by using a threshold comparison algorithm to obtain the first comparison result representing the difference value of the two parameters.
And S108, comparing the first comparison result with a preset threshold value to obtain a second comparison result, and optimizing the exposure time according to the first optimization result and the second comparison result to obtain a second optimization result.
Optionally, the comparing the first comparison result with a preset threshold value to obtain a second comparison result, and optimizing the exposure time according to the first optimization result and the second comparison result, where obtaining the second optimization result includes: comparing the parameters in the first comparison result with the preset threshold parameters to obtain a second comparison result, wherein the second comparison result comprises: the threshold range is not exceeded, and the threshold range is exceeded; and when the second comparison result does not exceed the threshold range, optimizing according to the exposure time optimization parameter on the basis of the first optimization result to obtain the second optimization result.
Specifically, after resolution optimization is performed in the embodiment of the present application, it is required to determine whether further exposure time optimization is required, so that a comparison result of a difference value of exposure parameters and a preset threshold value needs to be compared to obtain a comparison conclusion whether the comparison result exceeds the threshold value, thereby determining whether to perform exposure time optimization based on the first optimization.
By the embodiment, the technical problems that the billion-grade camera acquisition parameter optimization method in the prior art only constructs an expected target of image acquisition according to the image generation efficiency of the camera, so that the acquisition speed is improved in terms of parameters, and an optimization strategy cannot be quickly made when more complex or diversified image data are processed, and a large amount of computing resources are wasted are solved.
Example two
Fig. 2 is a block diagram of an acquisition speed optimization apparatus for a billion-level high-precision camera according to an embodiment of the present application, as shown in fig. 2, the apparatus including:
an obtaining module 20, configured to obtain a camera working parameter and a target optimization parameter, where the target optimization parameter includes: resolution optimization parameters, exposure time optimization parameters.
Specifically, in order to solve the technical problem that in the prior art, the method for optimizing the acquisition parameters of the hundred-level camera only constructs the expected target of image acquisition according to the image generation efficiency of the camera, so as to increase the acquisition speed in terms of parameters, so that when processing more complex or diversified image data, an optimization strategy cannot be quickly made, and a great deal of computing resources are wasted, firstly, the working parameters of the camera or the array device need to be acquired, wherein the working parameters comprise all parameters of the camera operation, such as exposure time, transmission bandwidth and the like, and the target optimization parameters need to be acquired, and the target optimization parameters comprise: resolution optimization parameters, exposure time optimization parameters.
And the optimizing module 22 is configured to optimize the camera working parameter according to the resolution optimizing parameter to obtain a first optimizing result.
Specifically, after the working parameters of the camera are obtained, the working parameters of the camera are required to be optimized according to the condition of the optimization target, so that the running state of the camera is optimized through the optimized parameters, and the efficiency of image acquisition, transmission and analysis is improved.
Optionally, the apparatus further includes: the acquisition module is also used for acquiring the preset resolution rule; the matching module is used for matching the resolution optimization parameter with the preset resolution rule to obtain a matching result, wherein the matching result comprises the following steps: the method meets the application requirements and does not meet the application requirements, wherein the preset resolution rule is used for representing the resolution guarantee requirements under the preset application scene.
Specifically, before resolution optimization is performed, the embodiment of the application needs to acquire the expected optimization parameters of the resolution, namely the preset resolution rule, wherein the preset resolution rule is a resolution expected value configured or selected by a user according to an application scene, and the value is converted into a rule form by using a conversion algorithm, so that the resolution optimization parameters and the preset resolution optimization rule are compared and matched, and the resolution optimization scheme can be compared and verified with the actual preset resolution rule before the resolution parameters are optimized, so that a matching result is obtained. For example, before the optimizing the camera operating parameters according to the resolution optimizing parameters to obtain the first optimizing result, the method further includes: acquiring the preset resolution rule; matching the resolution optimization parameter with the preset resolution rule to obtain a matching result, wherein the matching result comprises: the method meets the application requirements and does not meet the application requirements, wherein the preset resolution rule is used for representing the resolution guarantee requirements under the preset application scene.
The extracting module 24 is configured to extract an exposure time parameter from the camera working parameters, and compare the exposure time parameter with the exposure time optimization parameter to obtain a first comparison result.
Optionally, the extracting module includes: the extraction unit is used for extracting exposure time parameters in the working parameters of the camera; and the comparison unit is used for comparing and calculating the exposure time parameter and the exposure time optimization parameter by using a threshold comparison algorithm to obtain the first comparison result representing the difference value of the two parameters.
Specifically, after the resolution parameter is optimized according to the embodiment of the present application, the optimization of the exposure time parameter may be extracting the exposure time parameter in the working parameters of the camera, and comparing the exposure time parameter with the exposure time optimization parameter to obtain a first comparison result, where the obtaining of the first comparison result includes: extracting exposure time parameters in the working parameters of the camera; and comparing and calculating the exposure time parameter and the exposure time optimization parameter by using a threshold comparison algorithm to obtain the first comparison result representing the difference value of the two parameters.
The comparison module 26 is configured to compare the first comparison result with a preset threshold value to obtain a second comparison result, and optimize the exposure time according to the first optimization result and the second comparison result to obtain a second optimization result.
Optionally, the comparison module includes: the comparison unit is configured to perform a comparison operation on the parameter in the first comparison result and the preset threshold parameter to obtain the second comparison result, where the second comparison result includes: the threshold range is not exceeded, and the threshold range is exceeded; and the optimizing unit is used for optimizing according to the exposure time optimizing parameter on the basis of the first optimizing result to obtain the second optimizing result when the second comparing result does not exceed the threshold range.
Specifically, after resolution optimization is performed in the embodiment of the present application, it is required to determine whether further exposure time optimization is required, so that a comparison result of a difference value of exposure parameters and a preset threshold value needs to be compared to obtain a comparison conclusion whether the comparison result exceeds the threshold value, thereby determining whether to perform exposure time optimization based on the first optimization.
By the embodiment, the technical problems that the billion-grade camera acquisition parameter optimization method in the prior art only constructs an expected target of image acquisition according to the image generation efficiency of the camera, so that the acquisition speed is improved in terms of parameters, and an optimization strategy cannot be quickly made when more complex or diversified image data are processed, and a large amount of computing resources are wasted are solved.
According to another aspect of the embodiments of the present application, there is also provided a nonvolatile storage medium including a stored program, wherein the program when run controls a device in which the nonvolatile storage medium is located to execute an acquisition speed optimization method for a billion-level high-precision camera.
Specifically, the method comprises the following steps: obtaining working parameters and target optimization parameters of a camera, wherein the target optimization parameters comprise: resolution optimization parameters, exposure time optimization parameters; optimizing the working parameters of the camera according to the resolution optimization parameters to obtain a first optimization result; extracting an exposure time parameter in the working parameters of the camera, and comparing the exposure time parameter with the exposure time optimization parameter to obtain a first comparison result; and comparing the first comparison result with a preset threshold value to obtain a second comparison result, and optimizing the exposure time according to the first optimization result and the second comparison result to obtain a second optimization result. Optionally, before the optimizing the working parameters of the camera according to the resolution optimization parameters to obtain a first optimization result, the method further includes: acquiring the preset resolution rule; matching the resolution optimization parameter with the preset resolution rule to obtain a matching result, wherein the matching result comprises: the method meets the application requirements and does not meet the application requirements, wherein the preset resolution rule is used for representing the resolution guarantee requirements under the preset application scene. Optionally, the extracting an exposure time parameter from the working parameters of the camera, and comparing the exposure time parameter with the exposure time optimization parameter, to obtain a first comparison result includes: extracting exposure time parameters in the working parameters of the camera; and comparing and calculating the exposure time parameter and the exposure time optimization parameter by using a threshold comparison algorithm to obtain the first comparison result representing the difference value of the two parameters. Optionally, the comparing the first comparison result with a preset threshold value to obtain a second comparison result, and optimizing the exposure time according to the first optimization result and the second comparison result, where obtaining the second optimization result includes: comparing the parameters in the first comparison result with the preset threshold parameters to obtain a second comparison result, wherein the second comparison result comprises: the threshold range is not exceeded, and the threshold range is exceeded; and when the second comparison result does not exceed the threshold range, optimizing according to the exposure time optimization parameter on the basis of the first optimization result to obtain the second optimization result.
According to another aspect of the embodiment of the present application, there is also provided an electronic device including a processor and a memory; the memory has stored therein computer readable instructions for execution by the processor, wherein the computer readable instructions when executed perform a method of acquisition speed optimization for a billion-level high precision camera.
Specifically, the method comprises the following steps: obtaining working parameters and target optimization parameters of a camera, wherein the target optimization parameters comprise: resolution optimization parameters, exposure time optimization parameters; optimizing the working parameters of the camera according to the resolution optimization parameters to obtain a first optimization result; extracting an exposure time parameter in the working parameters of the camera, and comparing the exposure time parameter with the exposure time optimization parameter to obtain a first comparison result; and comparing the first comparison result with a preset threshold value to obtain a second comparison result, and optimizing the exposure time according to the first optimization result and the second comparison result to obtain a second optimization result. Optionally, before the optimizing the working parameters of the camera according to the resolution optimization parameters to obtain a first optimization result, the method further includes: acquiring the preset resolution rule; matching the resolution optimization parameter with the preset resolution rule to obtain a matching result, wherein the matching result comprises: the method meets the application requirements and does not meet the application requirements, wherein the preset resolution rule is used for representing the resolution guarantee requirements under the preset application scene. Optionally, the extracting an exposure time parameter from the working parameters of the camera, and comparing the exposure time parameter with the exposure time optimization parameter, to obtain a first comparison result includes: extracting exposure time parameters in the working parameters of the camera; and comparing and calculating the exposure time parameter and the exposure time optimization parameter by using a threshold comparison algorithm to obtain the first comparison result representing the difference value of the two parameters. Optionally, the comparing the first comparison result with a preset threshold value to obtain a second comparison result, and optimizing the exposure time according to the first optimization result and the second comparison result, where obtaining the second optimization result includes: comparing the parameters in the first comparison result with the preset threshold parameters to obtain a second comparison result, wherein the second comparison result comprises: the threshold range is not exceeded, and the threshold range is exceeded; and when the second comparison result does not exceed the threshold range, optimizing according to the exposure time optimization parameter on the basis of the first optimization result to obtain the second optimization result.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present application, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, fig. 3 is a schematic hardware structure of a terminal device according to an embodiment of the present application. As shown in fig. 3, the terminal device may include an input device 30, a processor 31, an output device 32, a memory 33, and at least one communication bus 34. The communication bus 34 is used to enable communication connections between the elements. The memory 33 may comprise a high-speed RAM memory or may further comprise a non-volatile memory NVM, such as at least one magnetic disk memory, in which various programs may be stored for performing various processing functions and implementing the method steps of the present embodiment.
Alternatively, the processor 31 may be implemented as, for example, a central processing unit (Central Processing Unit, abbreviated as CPU), an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components, and the processor 31 is coupled to the input device 30 and the output device 32 through wired or wireless connections.
Alternatively, the input device 30 may include a variety of input devices, for example, may include at least one of a user-oriented user interface, a device-oriented device interface, a programmable interface of software, a camera, and a sensor. Optionally, the device interface facing the device may be a wired interface for data transmission between devices, or may be a hardware insertion interface (such as a USB interface, a serial port, etc.) for data transmission between devices; alternatively, the user-oriented user interface may be, for example, a user-oriented control key, a voice input device for receiving voice input, and a touch-sensitive device (e.g., a touch screen, a touch pad, etc. having touch-sensitive functionality) for receiving user touch input by a user; optionally, the programmable interface of the software may be, for example, an entry for a user to edit or modify a program, for example, an input pin interface or an input interface of a chip, etc.; optionally, the transceiver may be a radio frequency transceiver chip, a baseband processing chip, a transceiver antenna, etc. with a communication function. An audio input device such as a microphone may receive voice data. The output device 32 may include a display, audio, or the like.
In this embodiment, the processor of the terminal device may include functions for executing each module of the data processing apparatus in each device, and specific functions and technical effects may be referred to the above embodiments and are not described herein again.
Fig. 4 is a schematic hardware structure of a terminal device according to another embodiment of the present application. Fig. 4 is a specific embodiment of the implementation of fig. 3. As shown in fig. 4, the terminal device of the present embodiment includes a processor 41 and a memory 42.
The processor 41 executes the computer program code stored in the memory 42 to implement the methods of the above-described embodiments.
The memory 42 is configured to store various types of data to support operation at the terminal device. Examples of such data include instructions for any application or method operating on the terminal device, such as messages, pictures, video, etc. The memory 42 may include a random access memory (random access memory, simply referred to as RAM) and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.
Optionally, a processor 41 is provided in the processing assembly 40. The terminal device may further include: a communication component 43, a power supply component 44, a multimedia component 45, an audio component 46, an input/output interface 47 and/or a sensor component 48. The components and the like specifically included in the terminal device are set according to actual requirements, which are not limited in this embodiment.
The processing component 40 generally controls the overall operation of the terminal device. The processing component 40 may include one or more processors 41 to execute instructions to perform all or part of the steps of the methods described above. Further, the processing component 40 may include one or more modules that facilitate interactions between the processing component 40 and other components. For example, processing component 40 may include a multimedia module to facilitate interaction between multimedia component 45 and processing component 40.
The power supply assembly 44 provides power to the various components of the terminal device. Power supply components 44 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for terminal devices.
The multimedia component 45 comprises a display screen between the terminal device and the user providing an output interface. In some embodiments, the display screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the display screen includes a touch panel, the display screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or slide action, but also the duration and pressure associated with the touch or slide operation.
The audio component 46 is configured to output and/or input audio signals. For example, the audio component 46 includes a Microphone (MIC) configured to receive external audio signals when the terminal device is in an operational mode, such as a speech recognition mode. The received audio signals may be further stored in the memory 42 or transmitted via the communication component 43. In some embodiments, audio assembly 46 further includes a speaker for outputting audio signals.
The input/output interface 47 provides an interface between the processing assembly 40 and peripheral interface modules, which may be click wheels, buttons, etc. These buttons may include, but are not limited to: volume button, start button and lock button.
The sensor assembly 48 includes one or more sensors for providing status assessment of various aspects for the terminal device. For example, the sensor assembly 48 may detect the open/closed state of the terminal device, the relative positioning of the assembly, the presence or absence of user contact with the terminal device. The sensor assembly 48 may include a proximity sensor configured to detect the presence of nearby objects in the absence of any physical contact, including detecting the distance between the user and the terminal device. In some embodiments, the sensor assembly 48 may also include a camera or the like.
The communication component 43 is configured to facilitate communication between the terminal device and other devices in a wired or wireless manner. The terminal device may access a wireless network based on a communication standard, such as WiFi,2G or 3G, or a combination thereof. In one embodiment, the terminal device may include a SIM card slot, where the SIM card slot is used to insert a SIM card, so that the terminal device may log into a GPRS network, and establish communication with a server through the internet.
From the above, it will be appreciated that the communication component 43, the audio component 46, and the input/output interface 47, the sensor component 48 referred to in the embodiment of fig. 4 may be implemented as an input device in the embodiment of fig. 3.
In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present application and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present application, which are intended to be comprehended within the scope of the present application.
Claims (10)
1. An acquisition speed optimization method for a billion-level high-precision camera, comprising:
obtaining working parameters and target optimization parameters of a camera, wherein the target optimization parameters comprise: resolution optimization parameters, exposure time optimization parameters;
optimizing the working parameters of the camera according to the resolution optimization parameters to obtain a first optimization result;
extracting an exposure time parameter in the working parameters of the camera, and comparing the exposure time parameter with the exposure time optimization parameter to obtain a first comparison result;
and comparing the first comparison result with a preset threshold value to obtain a second comparison result, and optimizing the exposure time according to the first optimization result and the second comparison result to obtain a second optimization result.
2. The method of claim 1, wherein prior to said optimizing said camera operating parameters according to said resolution optimization parameters to obtain a first optimization result, said method further comprises:
acquiring the preset resolution rule;
matching the resolution optimization parameter with the preset resolution rule to obtain a matching result, wherein the matching result comprises: the method meets the application requirements and does not meet the application requirements, wherein the preset resolution rule is used for representing the resolution guarantee requirements under the preset application scene.
3. The method of claim 1, wherein the extracting the exposure time parameter from the camera operating parameters and comparing the exposure time parameter with the exposure time optimization parameter to obtain a first comparison result comprises:
extracting exposure time parameters in the working parameters of the camera;
and comparing and calculating the exposure time parameter and the exposure time optimization parameter by using a threshold comparison algorithm to obtain the first comparison result representing the difference value of the two parameters.
4. The method of claim 1, wherein comparing the first comparison result with a preset threshold value to obtain a second comparison result, and optimizing the exposure time according to the first optimization result and the second comparison result, and obtaining a second optimization result comprises:
comparing the parameters in the first comparison result with the preset threshold parameters to obtain a second comparison result, wherein the second comparison result comprises: the threshold range is not exceeded, and the threshold range is exceeded;
and when the second comparison result does not exceed the threshold range, optimizing according to the exposure time optimization parameter on the basis of the first optimization result to obtain the second optimization result.
5. An acquisition speed optimization apparatus for a billion-level high-precision camera, comprising:
the system comprises an acquisition module, a target optimization module and a control module, wherein the acquisition module is used for acquiring working parameters and target optimization parameters of a camera, and the target optimization parameters comprise: resolution optimization parameters, exposure time optimization parameters;
the optimizing module is used for optimizing the working parameters of the camera according to the resolution optimizing parameters to obtain a first optimizing result;
the extraction module is used for extracting exposure time parameters in the working parameters of the camera, and comparing the exposure time parameters with the exposure time optimization parameters to obtain a first comparison result;
and the comparison module is used for comparing the first comparison result with a preset threshold value to obtain a second comparison result, and optimizing the exposure time according to the first optimization result and the second comparison result to obtain a second optimization result.
6. The apparatus of claim 5, wherein the apparatus further comprises:
the acquisition module is also used for acquiring the preset resolution rule;
the matching module is used for matching the resolution optimization parameter with the preset resolution rule to obtain a matching result, wherein the matching result comprises the following steps: the method meets the application requirements and does not meet the application requirements, wherein the preset resolution rule is used for representing the resolution guarantee requirements under the preset application scene.
7. The apparatus of claim 5, wherein the extraction module comprises:
the extraction unit is used for extracting exposure time parameters in the working parameters of the camera;
and the comparison unit is used for comparing and calculating the exposure time parameter and the exposure time optimization parameter by using a threshold comparison algorithm to obtain the first comparison result representing the difference value of the two parameters.
8. The apparatus of claim 5, wherein the comparison module comprises:
the comparison unit is configured to perform a comparison operation on the parameter in the first comparison result and the preset threshold parameter to obtain the second comparison result, where the second comparison result includes: the threshold range is not exceeded, and the threshold range is exceeded;
and the optimizing unit is used for optimizing according to the exposure time optimizing parameter on the basis of the first optimizing result to obtain the second optimizing result when the second comparing result does not exceed the threshold range.
9. A non-volatile storage medium, characterized in that the non-volatile storage medium comprises a stored program, wherein the program, when run, controls a device in which the non-volatile storage medium is located to perform the method of any one of claims 1 to 4.
10. An electronic device comprising a processor and a memory; the memory has stored therein computer readable instructions for executing the processor, wherein the computer readable instructions when executed perform the method of any of claims 1 to 4.
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