CN116614453B - Image transmission bandwidth selection method and device based on cloud interconnection - Google Patents
Image transmission bandwidth selection method and device based on cloud interconnection Download PDFInfo
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/70—Admission control; Resource allocation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
- H04L41/0894—Policy-based network configuration management
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
- H04L41/0896—Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract
The invention discloses an image transmission bandwidth selection method and device based on cloud interconnection. Wherein the method comprises the following steps: acquiring initial transmission parameters and original image data; extracting a complexity mark of the original image data, and uploading the complexity mark to a cloud server; receiving the screening parameters returned by the cloud server, and generating a bandwidth selection strategy according to the screening parameters and the initial transmission parameters; and performing bandwidth allocation operation by utilizing the bandwidth selection strategy to obtain an allocation result. The invention solves the technical problems that in the prior art, the selection of the transmission bandwidth is only to determine how to allocate bandwidth resources according to the performance parameters of the local equipment and the related parameters of the environment acquisition image data, so that the allocation operation of the image transmission resources is limited to the local equipment, the real-time image data analysis can not be performed while the networking is performed, the reasonable bandwidth transmission strategy is selected by utilizing the characteristics of multiple data and high accuracy of the cloud interconnection, and the quality and the efficiency of the image data transmission are reduced.
Description
Technical Field
The invention relates to the field of image equipment parameter optimization, in particular to an image transmission bandwidth selection method and device based on cloud interconnection.
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, when a light field camera or a camera array device monitors an application scene, the transmission bandwidth or the transmission mode of hardware, encryption complexity or an encoding algorithm are regulated according to the condition of image acquisition, but in the prior art, the bandwidth resource is determined to be allocated only according to the performance parameter of local equipment and the related parameter of environment acquisition image data, so that the allocation operation of the image transmission resource is limited to the local equipment, real-time image data analysis can not be performed while networking, a reasonable bandwidth transmission strategy is selected by utilizing the characteristics of multiple cloud interconnection data and high accuracy, and the quality and efficiency of image data transmission are reduced.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the invention provides an image transmission bandwidth selection method and device based on cloud interconnection, which at least solve the technical problems that in the prior art, the selection of transmission bandwidth is only to determine how to allocate bandwidth resources according to the performance parameters of local equipment and the related parameters of environment acquisition image data, so that the allocation operation of the image transmission resources is limited to the local equipment, real-time image data analysis can not be performed while networking, reasonable bandwidth transmission strategies are selected by utilizing the characteristics of multiple data and high accuracy of the cloud interconnection, and the quality and efficiency of image data transmission are reduced.
According to an aspect of the embodiment of the invention, there is provided an image transmission bandwidth selection method based on cloud interconnection, including: acquiring initial transmission parameters and original image data; extracting a complexity mark of the original image data, and uploading the complexity mark to a cloud server; receiving the screening parameters returned by the cloud server, and generating a bandwidth selection strategy according to the screening parameters and the initial transmission parameters; and performing bandwidth allocation operation by utilizing the bandwidth selection strategy to obtain an allocation result.
Optionally, the initial transmission parameters include: total bandwidth parameters, optical field channel parameters, allocation scale parameters.
Optionally, extracting the complexity flag of the original image data and uploading the complexity flag to a cloud server includes: training the complexity marking model according to the historical extraction data; and inputting the original image data into the complexity marking model as an input vector to obtain the complexity marking corresponding to the original image data, wherein the complexity marking represents the image complexity of the original image data.
Optionally, the receiving the filtering parameter returned by the cloud server, and generating the bandwidth selection policy according to the filtering parameter and the initial transmission parameter includes: acquiring the screening parameters transmitted to the local by the cloud server, wherein the screening parameters are generated according to matching of the cloud server and the complexity mark; and comparing the parameter elements in the initial transmission parameters with the screening parameters one by one to obtain the screened bandwidth selection strategy.
According to another aspect of the embodiment of the present invention, there is also provided an image transmission bandwidth selection device based on cloud interconnection, including: the acquisition module is used for acquiring initial transmission parameters and original image data; the extraction module is used for extracting the complexity mark of the original image data and uploading the complexity mark to the cloud server; the receiving module is used for receiving the screening parameters returned by the cloud server and generating a bandwidth selection strategy according to the screening parameters and the initial transmission parameters; and the allocation module is used for performing allocation operation on the bandwidth by utilizing the bandwidth selection strategy to obtain an allocation result.
Optionally, the initial transmission parameters include: total bandwidth parameters, optical field channel parameters, allocation scale parameters.
Optionally, the extracting module includes: the training unit is used for extracting data according to the history and training the complexity marking model; and the input unit is used for inputting the original image data into the complexity marking model as an input vector to obtain the complexity marking corresponding to the original image data, wherein the complexity marking represents the image complexity of the original image data.
Optionally, the receiving module includes: the acquisition unit is used for acquiring the screening parameters transmitted to the local by the cloud server, wherein the screening parameters are generated according to matching of the cloud server and the complexity mark; and the comparison unit is used for comparing the parameter elements in the initial transmission parameters with the screening parameters one by one to obtain the screened bandwidth selection strategy.
According to another aspect of the embodiment of the present invention, there is further provided a nonvolatile storage medium, where the nonvolatile storage medium includes a stored program, and when the program runs, the device where the nonvolatile storage medium is controlled to execute an image transmission bandwidth selection method based on cloud interconnection.
According to another aspect of the embodiment of the present invention, there is also provided an electronic device including a processor and a memory; the memory stores computer readable instructions, and the processor is configured to execute the computer readable instructions, where the computer readable instructions execute a method for selecting an image transmission bandwidth based on cloud interconnection when executed.
In the embodiment of the invention, the initial transmission parameters and the original image data are acquired; extracting a complexity mark of the original image data, and uploading the complexity mark to a cloud server; receiving the screening parameters returned by the cloud server, and generating a bandwidth selection strategy according to the screening parameters and the initial transmission parameters; the bandwidth is allocated by using the bandwidth selection strategy to obtain an allocation result, so that the technical problems that in the prior art, the bandwidth resource is allocated only according to the performance parameters of local equipment and the related parameters of environment acquisition image data, the allocation operation of the image transmission resource is limited to the local equipment, the real-time image data cannot be analyzed while networking, the reasonable bandwidth transmission strategy is selected by using the characteristics of multiple cloud interconnection data and high accuracy, and the quality and the efficiency of image data transmission are reduced are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
fig. 1 is a flowchart of a method for selecting an image transmission bandwidth based on cloud interconnection according to an embodiment of the present invention;
fig. 2 is a block diagram of an image transmission bandwidth selecting device based on cloud interconnection according to an embodiment of the present invention;
fig. 3 is a block diagram of a terminal device for performing the method according to the invention according to an embodiment of the invention;
fig. 4 is a memory unit for holding or carrying program code for implementing a method according to the invention, according to an embodiment of the invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention 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 invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention 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 invention 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.
According to an embodiment of the present invention, there is provided acquiring an initial transmission parameter and original image data; extracting a complexity mark of the original image data, and uploading the complexity mark to a cloud server; receiving the screening parameters returned by the cloud server, and generating a bandwidth selection strategy according to the screening parameters and the initial transmission parameters; the method embodiments of allocating bandwidth using the bandwidth selection policy to obtain allocation results, it should be noted that the steps illustrated in the flowchart of the figures may be performed in a computer system, such as a set of computer-executable instructions, and that although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
Example 1
Fig. 1 is a flowchart of a cloud interconnection-based image transmission bandwidth selection method according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
step S102, acquiring initial transmission parameters and original image data.
Optionally, the initial transmission parameters include: total bandwidth parameters, optical field channel parameters, allocation scale parameters.
Specifically, the embodiment of the invention aims to solve the technical problems that in the prior art, the selection of the transmission bandwidth is only to determine how to allocate bandwidth resources according to the performance parameters of local equipment and the related parameters of environment acquisition image data, so that the allocation operation of the image transmission resources is limited to the local equipment, the analysis of real-time image data can not be performed while networking, the reasonable bandwidth transmission strategy is selected by utilizing the characteristics of multiple cloud interconnection data and high precision, the quality and the efficiency of image data transmission are reduced, the original transmission parameters and the original image data are required to be acquired through the high-precision image pickup equipment, and the original transmission parameters are obtained through the channel hardware parameters established between cameras and are used for subsequent allocation and optimization adjustment of the transmission bandwidth.
Step S104, extracting the complexity mark of the original image data, and uploading the complexity mark to a cloud server.
Specifically, because the original image data acquired by the embodiment of the invention may have the complex condition, in order to reasonably and scientifically allocate the transmission bandwidth subsequently, the complexity mark of the original image data needs to be extracted, and the complexity mark is uploaded to a cloud server for calculation so as to obtain a bandwidth processing strategy corresponding to the complexity mark for subsequent adjustment and optimization of the bandwidth. Optionally, extracting the complexity flag of the original image data and uploading the complexity flag to a cloud server includes: training the complexity marking model according to the historical extraction data; and inputting the original image data into the complexity marking model as an input vector to obtain the complexity marking corresponding to the original image data, wherein the complexity marking represents the image complexity of the original image data.
Step S106, receiving the screening parameters returned by the cloud server, and generating a bandwidth selection strategy according to the screening parameters and the initial transmission parameters.
Optionally, the receiving the filtering parameter returned by the cloud server, and generating the bandwidth selection policy according to the filtering parameter and the initial transmission parameter includes: acquiring the screening parameters transmitted to the local by the cloud server, wherein the screening parameters are generated according to matching of the cloud server and the complexity mark; and comparing the parameter elements in the initial transmission parameters with the screening parameters one by one to obtain the screened bandwidth selection strategy.
Specifically, after the complexity mark of the original image data is uploaded to the cloud interconnected server, the cloud interconnected server is required to be utilized to calculate the screening parameters corresponding to the complexity mark, wherein the screening parameters represent the original image data obtained by the embodiment of the invention in a policy array mode, and how to select a bandwidth allocation policy. For example, the receiving the filtering parameter returned by the cloud server, and generating the bandwidth selection policy according to the filtering parameter and the initial transmission parameter includes: acquiring the screening parameters transmitted to the local by the cloud server, wherein the screening parameters are generated according to matching of the cloud server and the complexity mark; and comparing the parameter elements in the initial transmission parameters with the screening parameters one by one to obtain the screened bandwidth selection strategy.
And S108, performing allocation operation on the bandwidth by utilizing the bandwidth selection strategy to obtain an allocation result.
Specifically, after the bandwidth selection policy is obtained in the embodiment of the present invention, parameters related to image transmission bandwidth allocation in the bandwidth selection policy need to be generated according to the allocation proportion, where the parameters may be used for allocating transmission resources automatically according to the policy allocation parameters by the bandwidth, so as to achieve the best data transmission effect.
By the embodiment, the technical problems that in the prior art, the bandwidth resource is only allocated according to the performance parameters of the local equipment and the related parameters of the environment acquisition image data, so that the allocation operation of the image transmission resources is limited to the local equipment, the real-time image data cannot be analyzed while networking, the reasonable bandwidth transmission strategy is selected by utilizing the characteristics of multiple data and high accuracy of cloud interconnection, and the quality and the efficiency of image data transmission are reduced are solved.
Example two
Fig. 2 is a block diagram of an image transmission bandwidth selection device based on cloud interconnection according to an embodiment of the present invention, and as shown in fig. 2, the device includes:
the acquiring module 20 is configured to acquire the initial transmission parameters and the original image data.
Optionally, the initial transmission parameters include: total bandwidth parameters, optical field channel parameters, allocation scale parameters.
Specifically, the embodiment of the invention aims to solve the technical problems that in the prior art, the selection of the transmission bandwidth is only to determine how to allocate bandwidth resources according to the performance parameters of local equipment and the related parameters of environment acquisition image data, so that the allocation operation of the image transmission resources is limited to the local equipment, the analysis of real-time image data can not be performed while networking, the reasonable bandwidth transmission strategy is selected by utilizing the characteristics of multiple cloud interconnection data and high precision, the quality and the efficiency of image data transmission are reduced, the original transmission parameters and the original image data are required to be acquired through the high-precision image pickup equipment, and the original transmission parameters are obtained through the channel hardware parameters established between cameras and are used for subsequent allocation and optimization adjustment of the transmission bandwidth.
The extracting module 22 is configured to extract a complexity flag of the original image data, and upload the complexity flag to a cloud server.
Specifically, because the original image data acquired by the embodiment of the invention may have the complex condition, in order to reasonably and scientifically allocate the transmission bandwidth subsequently, the complexity mark of the original image data needs to be extracted, and the complexity mark is uploaded to a cloud server for calculation so as to obtain a bandwidth processing strategy corresponding to the complexity mark for subsequent adjustment and optimization of the bandwidth. Optionally, the extracting module includes: the training unit is used for extracting data according to the history and training the complexity marking model; and the input unit is used for inputting the original image data into the complexity marking model as an input vector to obtain the complexity marking corresponding to the original image data, wherein the complexity marking represents the image complexity of the original image data.
And the receiving module 24 is configured to receive the filtering parameter returned by the cloud server, and generate a bandwidth selection policy according to the filtering parameter and the initial transmission parameter.
Optionally, the receiving module includes: the acquisition unit is used for acquiring the screening parameters transmitted to the local by the cloud server, wherein the screening parameters are generated according to matching of the cloud server and the complexity mark; and the comparison unit is used for comparing the parameter elements in the initial transmission parameters with the screening parameters one by one to obtain the screened bandwidth selection strategy.
Specifically, after the complexity mark of the original image data is uploaded to the cloud interconnected server, the cloud interconnected server is required to be utilized to calculate the screening parameters corresponding to the complexity mark, wherein the screening parameters represent the original image data obtained by the embodiment of the invention in a policy array mode, and how to select a bandwidth allocation policy. For example, the receiving the filtering parameter returned by the cloud server, and generating the bandwidth selection policy according to the filtering parameter and the initial transmission parameter includes: acquiring the screening parameters transmitted to the local by the cloud server, wherein the screening parameters are generated according to matching of the cloud server and the complexity mark; and comparing the parameter elements in the initial transmission parameters with the screening parameters one by one to obtain the screened bandwidth selection strategy.
And the allocation module 26 is configured to perform an allocation operation on the bandwidth by using the bandwidth selection policy, so as to obtain an allocation result.
Specifically, after the bandwidth selection policy is obtained in the embodiment of the present invention, parameters related to image transmission bandwidth allocation in the bandwidth selection policy need to be generated according to the allocation proportion, where the parameters may be used for allocating transmission resources automatically according to the policy allocation parameters by the bandwidth, so as to achieve the best data transmission effect.
By the embodiment, the technical problems that in the prior art, the bandwidth resource is only allocated according to the performance parameters of the local equipment and the related parameters of the environment acquisition image data, so that the allocation operation of the image transmission resources is limited to the local equipment, the real-time image data cannot be analyzed while networking, the reasonable bandwidth transmission strategy is selected by utilizing the characteristics of multiple data and high accuracy of cloud interconnection, and the quality and the efficiency of image data transmission are reduced are solved.
According to another aspect of the embodiment of the present invention, there is further provided a nonvolatile storage medium, where the nonvolatile storage medium includes a stored program, and when the program runs, the device where the nonvolatile storage medium is controlled to execute an image transmission bandwidth selection method based on cloud interconnection.
Specifically, the method comprises the following steps: acquiring initial transmission parameters and original image data; extracting a complexity mark of the original image data, and uploading the complexity mark to a cloud server; receiving the screening parameters returned by the cloud server, and generating a bandwidth selection strategy according to the screening parameters and the initial transmission parameters; and performing bandwidth allocation operation by utilizing the bandwidth selection strategy to obtain an allocation result. Optionally, the initial transmission parameters include: total bandwidth parameters, optical field channel parameters, allocation scale parameters. Optionally, extracting the complexity flag of the original image data and uploading the complexity flag to a cloud server includes: training the complexity marking model according to the historical extraction data; and inputting the original image data into the complexity marking model as an input vector to obtain the complexity marking corresponding to the original image data, wherein the complexity marking represents the image complexity of the original image data. Optionally, the receiving the filtering parameter returned by the cloud server, and generating the bandwidth selection policy according to the filtering parameter and the initial transmission parameter includes: acquiring the screening parameters transmitted to the local by the cloud server, wherein the screening parameters are generated according to matching of the cloud server and the complexity mark; and comparing the parameter elements in the initial transmission parameters with the screening parameters one by one to obtain the screened bandwidth selection strategy.
According to another aspect of the embodiment of the present invention, there is also provided an electronic device including a processor and a memory; the memory stores computer readable instructions, and the processor is configured to execute the computer readable instructions, where the computer readable instructions execute a method for selecting an image transmission bandwidth based on cloud interconnection when executed.
Specifically, the method comprises the following steps: acquiring initial transmission parameters and original image data; extracting a complexity mark of the original image data, and uploading the complexity mark to a cloud server; receiving the screening parameters returned by the cloud server, and generating a bandwidth selection strategy according to the screening parameters and the initial transmission parameters; and performing bandwidth allocation operation by utilizing the bandwidth selection strategy to obtain an allocation result. Optionally, the initial transmission parameters include: total bandwidth parameters, optical field channel parameters, allocation scale parameters. Optionally, extracting the complexity flag of the original image data and uploading the complexity flag to a cloud server includes: training the complexity marking model according to the historical extraction data; and inputting the original image data into the complexity marking model as an input vector to obtain the complexity marking corresponding to the original image data, wherein the complexity marking represents the image complexity of the original image data. Optionally, the receiving the filtering parameter returned by the cloud server, and generating the bandwidth selection policy according to the filtering parameter and the initial transmission parameter includes: acquiring the screening parameters transmitted to the local by the cloud server, wherein the screening parameters are generated according to matching of the cloud server and the complexity mark; and comparing the parameter elements in the initial transmission parameters with the screening parameters one by one to obtain the screened bandwidth selection strategy.
The foregoing embodiment numbers of the present invention 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 invention, 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 content 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 content 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 invention 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 invention 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 invention. 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 invention 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 invention, which are intended to be comprehended within the scope of the present invention.
Claims (4)
1. The image transmission bandwidth selection method based on cloud interconnection is characterized by comprising the following steps of:
acquiring initial transmission parameters and original image data;
extracting a complexity mark of the original image data, and uploading the complexity mark to a cloud server;
receiving the screening parameters returned by the cloud server, and generating a bandwidth selection strategy according to the screening parameters and the initial transmission parameters;
performing bandwidth allocation operation by utilizing the bandwidth selection strategy to obtain an allocation result;
the initial transmission parameters include: total bandwidth parameters, optical field channel parameters, allocation ratio parameters;
the extracting the complexity flag of the original image data and uploading the complexity flag to a cloud server includes:
training the complexity marking model according to the historical extraction data;
inputting the original image data into the complexity marking model as an input vector to obtain the complexity marking corresponding to the original image data, wherein the complexity marking represents the image complexity of the original image data;
the step of receiving the screening parameters returned by the cloud server and generating a bandwidth selection strategy according to the screening parameters and the initial transmission parameters comprises the following steps:
acquiring the screening parameters transmitted to the local by the cloud server, wherein the screening parameters are generated according to matching of the cloud server and the complexity mark;
and comparing the parameter elements in the initial transmission parameters with the screening parameters one by one to obtain the screened bandwidth selection strategy.
2. Image transmission bandwidth selection device based on high in clouds interconnection, characterized by comprising:
the acquisition module is used for acquiring initial transmission parameters and original image data;
the extraction module is used for extracting the complexity mark of the original image data and uploading the complexity mark to the cloud server;
the receiving module is used for receiving the screening parameters returned by the cloud server and generating a bandwidth selection strategy according to the screening parameters and the initial transmission parameters;
the allocation module is used for performing allocation operation on the bandwidth by utilizing the bandwidth selection strategy to obtain an allocation result;
the initial transmission parameters include: total bandwidth parameters, optical field channel parameters, allocation ratio parameters;
the extraction module comprises:
the training unit is used for extracting data according to the history and training the complexity marking model;
the input unit is used for inputting the original image data into the complexity marking model as an input vector to obtain the complexity marking corresponding to the original image data, wherein the complexity marking represents the image complexity of the original image data;
the receiving module includes:
the acquisition unit is used for acquiring the screening parameters transmitted to the local by the cloud server, wherein the screening parameters are generated according to matching of the cloud server and the complexity mark;
and the comparison unit is used for comparing the parameter elements in the initial transmission parameters with the screening parameters one by one to obtain the screened bandwidth selection strategy.
3. A non-volatile storage medium comprising a stored program, wherein the program when run controls a device in which the non-volatile storage medium resides to perform the method of claim 1.
4. An electronic device comprising 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 the method of claim 1.
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