CN112150557B - Mode acquisition method, device and medium for road side perception camera data stream - Google Patents
Mode acquisition method, device and medium for road side perception camera data stream Download PDFInfo
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Abstract
The application discloses a mode acquisition method, a device and a medium for a road side perception camera data stream, which relate to the fields of intelligent transportation, vehicle-road coordination and automatic driving, wherein the method can comprise the following steps: acquiring a data stream from a road side perception camera; constructing an unordered dictionary for the data stream, wherein the unordered dictionary is used for recording the occurrence times of elements included in the data stream and each element in the data stream; if the elements in the data stream change, updating the unordered dictionary according to the change; and taking the element with the largest occurrence number determined according to the unordered dictionary as the mode, and sending the mode to the receiving equipment. By applying the scheme of the application, the processing speed and the like can be improved.
Description
Technical Field
The application relates to a computer application technology, in particular to a mode acquisition method, a mode acquisition device and a mode acquisition medium for a road side perception camera data stream in the fields of intelligent transportation, vehicle-road coordination and automatic driving.
Background
Roadside sensing cameras are typically mounted on red-green light poles or monitor poles, obstacle pixel coordinates are detected by image algorithms, and then camera outliers are used to calculate the position of the obstacle in the 3D world. When the camera is permanently displaced due to the change of the hardware environment or other physical factors, the external parameters fail, and the 3D position detection accuracy of the obstacle is reduced. Therefore, the occurrence of the camera displacement event and the offset are required to be known in time, and when the offset is too large, the calibration personnel can be enabled to recalibrate the external parameters and the like.
In practical applications, the offset of the camera of each frame can be obtained, and after a period of offset is counted, the offsets form a data stream, and the mode, i.e. the element (offset) with the largest occurrence number, can be determined from the data stream as the required offset. In determining the mode, a method is generally adopted to traverse the current data stream, count the occurrence times of each element in the data stream by using the time complexity of O (n), and select the element with the largest occurrence times as the mode. But this approach is slow and time consuming to process.
Disclosure of Invention
The application provides a mode acquisition method, a mode acquisition device and a mode acquisition medium for a road side perception camera data stream.
A mode acquisition method for a roadside aware camera data stream, comprising:
acquiring a data stream from a road side perception camera;
constructing an unordered dictionary for the data stream, wherein the unordered dictionary is used for recording elements included in the data stream and the occurrence times of the elements in the data stream, and updating the unordered dictionary according to element changes in the data stream;
taking the element with the largest occurrence number determined according to the unordered dictionary as the mode;
The mode is sent to the receiving device.
A mode acquisition apparatus for a roadside aware camera data stream, comprising: a first processing module and a second processing module;
The first processing module is used for acquiring a data stream from a road side perception camera, constructing an unordered dictionary for the data stream, and updating the unordered dictionary according to element changes in the data stream, wherein the unordered dictionary is used for recording elements included in the data stream and the occurrence times of the elements in the data stream;
and the second processing module is used for taking the element with the largest occurrence number determined according to the unordered dictionary as the mode and sending the mode to receiving equipment.
An electronic device, comprising:
At least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method as described above.
A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method as described above.
A computer program product comprising a computer program which, when executed by a processor, implements a method as described above.
One embodiment of the above application has the following advantages or benefits: based on the unordered dictionary, the unordered dictionary is utilized to record the latest elements included in the data stream and the occurrence times of the elements in the data stream, and the mode can be determined based on the information recorded in the unordered dictionary, and the unordered dictionary is a data structure capable of operating with the time complexity of O (1), so that the processing speed is improved, the time consumption is reduced and the like compared with the prior method.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
Drawings
The drawings are included to provide a better understanding of the present application and are not to be construed as limiting the application. Wherein:
FIG. 1 is a flowchart of a mode acquisition method for a roadside aware camera data stream according to an embodiment of the present application;
FIG. 2 is a flowchart of a first embodiment of an unordered dictionary updating method according to the present application;
FIG. 3 is a flowchart of a second embodiment of an unordered dictionary updating method according to the present application;
Fig. 4 is a schematic diagram of a mode obtaining apparatus 40 for a data stream of a roadside perception camera according to an embodiment of the present application;
Fig. 5 is a block diagram of an electronic device according to a method according to an embodiment of the application.
Detailed Description
Exemplary embodiments of the present application will now be described with reference to the accompanying drawings, in which various details of the embodiments of the present application are included to facilitate understanding, and are to be considered merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In addition, it should be understood that the term "and/or" herein is merely one association relationship describing the associated object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
Fig. 1 is a flowchart of a mode acquisition method for a roadside aware camera data stream according to an embodiment of the present application. As shown in fig. 1, the following detailed implementation is included.
In 101, a data stream is acquired from a roadside aware camera.
In 102, an unordered dictionary is constructed for the data stream, the unordered dictionary is used for recording elements included in the data stream and the occurrence times of the elements in the data stream, and the unordered dictionary is updated according to element changes in the data stream.
An unordered dictionary is a data structure in the form of a key-value and is a data structure that can operate with the temporal complexity of O (1), which can include lookup, insert, delete, and the like.
With the change of elements in the data stream, the information such as the elements included in the latest data stream, the occurrence times of each element in the data stream and the like can be always recorded by using the unordered dictionary.
At 103, the element with the largest number of occurrences determined from the unordered dictionary is taken as the mode.
At 104, the mode is sent to the receiving device.
It can be seen that, in the above embodiment, the unordered dictionary is used as a basis, the unordered dictionary is used to record the latest elements included in the data stream and the occurrence times of the elements in the data stream, the mode can be determined based on the information recorded in the unordered dictionary, the mode in the data stream is obtained with the space conversion time and the time complexity of O (1), so that the processing speed is improved, the time consumption is reduced, and the like compared with the existing method.
The execution device of the method embodiment of the present application may be various roadside devices, such as a roadside computing device (RSCU, road Side Computing Unit). The receiving device may be a driver-assisted vehicle, an autonomous vehicle, a cloud-controlled platform or a server for subsequent processing according to mode. For example, prompt, data correction, notification of a calibration person to recalibrate the camera parameters, etc. when the camera offset is too large.
Preferably, the structured unordered dictionary described in 102 may include three, referred to as a first unordered dictionary, a second unordered dictionary, and a third unordered dictionary, respectively, for ease of presentation.
The keywords in the first unordered dictionary are elements included in the data stream, and the values in the first unordered dictionary are the number of occurrences of the corresponding keywords in the data stream. The keywords in the second unordered dictionary are the number of occurrences, and the values in the second unordered dictionary are the third unordered dictionary. The keywords in the third unordered dictionary are elements whose number of occurrences in the data stream is the keywords in the corresponding second unordered dictionary.
Assuming that 10 elements, namely, element 1-element 10, are included in the current data stream, then 10 keywords, namely, element 1-element 10, are included in the first unordered dictionary, taking element 1 as an example, the corresponding value is the number of occurrences of element 1 in the data stream, and similarly, for element 2, the corresponding value is the number of occurrences of element 2 in the data stream. The number of occurrences may be the same or different for any two elements.
Assuming that the number of occurrences of element 1-element 10 is 5, 6, 7, 8, 7, 6, 5, 9, 10, respectively, then 6 keywords, 5, 6, 7, 8, 9, 10, respectively, may be included in the second unordered dictionary, with the corresponding values of element 1 and element 8 being taken as key 5 as an example. In addition, the value corresponding to the keyword 5 is one keyword in the third unordered dictionary, that is, the keyword in the third unordered dictionary is an element whose occurrence number in the data stream is the keyword 5 in the second unordered dictionary.
The value corresponding to each keyword in the third unordered dictionary is not limited and may be any content.
The unordered dictionary may be updated based on element changes in the data stream as described in 102. Element changes in the data stream may include: an increase in elements in the data stream, a decrease (deletion) of elements in the data stream, etc. The method is applicable to various conditions and has universal applicability.
Taking the element in the data stream as the offset of the roadside sensing camera as an example, the element stored in the data stream is usually the element acquired in the last preset time, that is, the element in the data stream is dynamically changed, the newly acquired element can be added into the data stream, and the expired element can be deleted from the data stream. The specific value of the predetermined time period may be determined according to actual needs, such as the last day.
The following describes in detail how to update the unordered dictionary for both cases of addition and deletion, respectively.
1) Increase in
When any element is added in the data stream, the added element can be used as the element to be processed, whether the keyword in the first unordered dictionary comprises the element to be processed or not is determined, if not, one piece of data with the keyword being the element to be processed and the corresponding value being 1 can be added in the first unordered dictionary, if the keyword being 1 exists in the second unordered dictionary, the element to be processed is added in the value corresponding to the keyword being 1, if the keyword being 1 does not exist in the second unordered dictionary, one piece of data with the keyword being 1 and the corresponding value being the element to be processed is added, if yes, the value corresponding to the element to be processed in the first unordered dictionary can be added with 1, the element to be processed can be deleted from the value corresponding to the keyword being N-1 in the second unordered dictionary, N represents the result after the value corresponding to the element to be processed in the first unordered dictionary is added with 1, and the element to be processed is added in the value corresponding to the keyword being N in the second unordered dictionary.
Based on the above description, fig. 2 is a flowchart of a first embodiment of the unordered dictionary updating method according to the present application. As shown in fig. 2, the following detailed implementation is included.
In 201, when any element is added in the data stream, the added element is taken as an element to be processed.
In 202, it is determined whether the keywords in the first unordered dictionary include elements to be processed, if not, 203 is executed, and if so, 207 is executed.
I.e. determining whether the element to be processed is recorded as a key in the first unordered dictionary.
In 203, a piece of data with a key word as an element to be processed and a corresponding value of 1 is added to the first unordered dictionary.
Namely, adding a piece of data in the first unordered dictionary, wherein the key words in the data are elements to be processed, and the value is 1.
In 204, it is determined whether a key of 1 is present in the second unordered dictionary, if so, 205 is performed, otherwise 206 is performed.
In 205, the element to be processed is added to the value corresponding to the key word with 1 in the second unordered dictionary, and the flow is ended.
Assuming that one element is originally included in the value corresponding to the key of 1 in the second unordered dictionary, the element to be processed can be added to become two elements.
In 206, a piece of data with a key word of 1 and a corresponding value of the element to be processed is added in the second unordered dictionary, and the flow is ended.
Namely, adding a piece of data in the second unordered dictionary, wherein the keyword in the data is 1, the value is an element to be processed, and the value is also a newly added keyword in the third unordered dictionary.
In 207, the value corresponding to the element to be processed in the first unordered dictionary is added with 1, the element to be processed is deleted from the value corresponding to the keyword N-1 in the second unordered dictionary, N represents the result of adding 1 to the value corresponding to the element to be processed in the first unordered dictionary, the element to be processed is added to the value corresponding to the keyword N in the second unordered dictionary, and the flow is ended.
Since the value (i.e., the number of occurrences) corresponding to the element to be processed changes from N-1 to N, it is necessary to delete the element to be processed from the value corresponding to the key of N-1 in the second unordered dictionary and add the element to be processed to the value corresponding to the key of N in the second unordered dictionary.
Preferably, a parameter is also set for recording the element as mode. Accordingly, after updating the unordered dictionary in the manner described above, the following processing may be further performed: and determining the occurrence times P of the elements serving as the mode in the data stream according to the first unordered dictionary, if N is determined to be larger than P, taking the elements to be processed as the mode, updating the parameters, and otherwise, maintaining the original mode unchanged. If n=p, the element to be processed in the description is the mode recorded in the parameter.
2) Deletion of
When any element is deleted in the data stream, the deleted element is used as an element to be processed, the element to be processed is deleted from the value corresponding to the keyword of L in the second unordered dictionary, L represents the value corresponding to the element to be processed in the first unordered dictionary, if L is larger than one, the element to be processed is added in the value corresponding to the keyword of L-1 in the second unordered dictionary, the value corresponding to the element to be processed in the first unordered dictionary is subtracted by 1, if L is equal to one, the data where the element to be processed is located is deleted from the first unordered dictionary, and each data is respectively composed of the keyword and the corresponding value. In addition, if the value corresponding to the keyword L in the second unordered dictionary is null after deleting the element to be processed from the value corresponding to the keyword L in the second unordered dictionary, the data where the keyword L is located may be deleted from the second unordered dictionary.
Based on the above description, fig. 3 is a flowchart of a second embodiment of the unordered dictionary updating method according to the present application. As shown in fig. 3, the following detailed implementation is included.
In 301, when any element is deleted in the data stream, the deleted element is taken as the element to be processed.
In 302, the element to be processed is deleted from the values corresponding to the keywords L in the second unordered dictionary, L representing the values corresponding to the element to be processed in the first unordered dictionary.
Assuming that the value corresponding to the key of L in the second unordered dictionary includes the element to be processed and another element, the element to be processed may be deleted, and only the other element is retained.
And if the value corresponding to the keyword with L in the second unordered dictionary is empty after deleting the element to be processed from the value corresponding to the keyword with L in the second unordered dictionary, deleting the data where the keyword with L is located from the second unordered dictionary. That is, assuming that only the element to be processed is included in the value corresponding to the keyword of L in the second unordered dictionary, the data where the keyword of L is located may also be deleted from the second unordered dictionary.
In 303, it is determined whether L is greater than one or equal to one, if greater than one, then 304 is performed, and if equal to one, then 305 is performed.
In 304, the element to be processed is added to the value corresponding to the keyword of L-1 in the second unordered dictionary, and the value corresponding to the element to be processed in the first unordered dictionary is subtracted by 1, so that the flow is ended.
In 305, the data of the element to be processed is deleted from the first unordered dictionary, and the flow is ended.
Preferably, a parameter is also set for recording the element as mode. Accordingly, after updating the unordered dictionary in the manner described above, the following processing may be further performed: and determining the occurrence times P of the elements serving as the mode in the data stream according to the first unordered dictionary, if the keywords which are P+1 exist in the second unordered dictionary, taking any element in the values corresponding to the keywords which are P+1 as the mode, updating the parameters, and otherwise, maintaining the original mode unchanged.
The value corresponding to the keyword p+1 in the second unordered dictionary may include one element or may include a plurality of elements, if only one element is included, the element may be directly used as a mode, if a plurality of elements are included, one element may be selected as a mode, for example, the first element may be selected as a mode, or one element may be randomly selected as a mode, etc.
By the method, the unordered dictionary is updated in time, so that information recorded in the unordered dictionary is matched with actual conditions, and the accuracy of the acquired mode is further ensured.
For the user, when the mode needs to be acquired, the mode recorded in the parameter is directly acquired, and the latest mode can be acquired in real time along with the change of the elements in the data stream.
As described above, the elements in the data stream may be the offset of the roadside sensing camera, i.e. the mode offset of the roadside sensing camera may be obtained, and further, the subsequent processing may be performed according to the obtained mode offset in the existing manner, for example, when the obtained mode offset is greater than a predetermined threshold, the calibration personnel may be allowed to recalibrate the camera parameters.
It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present application. In addition, portions of one embodiment that are not described in detail may be referred to in the description of other embodiments.
The above description of the method embodiments further describes the solution of the present application by means of device embodiments.
Fig. 4 is a schematic diagram of a mode obtaining device 40 for a data stream of a roadside perception camera according to an embodiment of the present application. As shown, includes: a first processing module 401 and a second processing module 402.
The first processing module 401 is configured to obtain a data stream from the roadside perception camera, construct an unordered dictionary for the data stream, and update the unordered dictionary according to element changes in the data stream, wherein the unordered dictionary is used for recording elements included in the data stream and occurrence times of each element in the data stream.
And a second processing module 402, configured to take the element with the largest occurrence number determined according to the unordered dictionary as a mode, and send the mode to the receiving device.
Preferably, the unordered dictionary may include: the first unordered dictionary, the second unordered dictionary, and the third unordered dictionary.
The keywords in the first unordered dictionary are elements included in the data stream, and the values in the first unordered dictionary are the number of occurrences of the corresponding keywords in the data stream. The keywords in the second unordered dictionary are the number of occurrences, and the values in the second unordered dictionary are the third unordered dictionary. The keywords in the third unordered dictionary are elements whose number of occurrences in the data stream is the keywords in the corresponding second unordered dictionary. The value corresponding to each keyword in the third unordered dictionary is not limited and may be any content.
The unordered dictionary may be updated based on element changes in the data stream. Element changes in the data stream may include: the elements in the data stream increase and the elements in the data stream decrease.
Specifically, when any element is added to the data stream, the first processing module 401 may determine whether the element to be processed is included in the keywords in the first unordered dictionary, if not, add data with one keyword being the element to be processed and the corresponding value being 1 to the first unordered dictionary, and if the keyword with 1 is present in the second unordered dictionary, add the element to be processed to the value corresponding to the keyword with 1, if the keyword with 1 is not present in the second unordered dictionary, add one keyword being 1 and the corresponding value being the data of the element to be processed, if yes, add 1 to the value corresponding to the element to be processed in the first unordered dictionary, delete the element to be processed from the value corresponding to the keyword with N-1 in the second unordered dictionary, and add the element to be processed to the value corresponding to the keyword with N in the first unordered dictionary.
In addition, the second processing module 402 may further set a parameter for recording the element as the mode, after the updating, determine, according to the first unordered dictionary, the number of occurrences P of the element as the mode in the data stream, and if N is determined to be greater than P, then use the element to be processed as the mode, and update the parameter.
The first processing module 401 may further delete an element to be processed from the values corresponding to the keywords L in the second unordered dictionary when deleting any element in the data stream, wherein L represents the value corresponding to the element to be processed in the first unordered dictionary, and if L is greater than one, the element to be processed is added to the values corresponding to the keywords L-1 in the second unordered dictionary, and the value corresponding to the element to be processed in the first unordered dictionary is subtracted by 1, and if L is equal to one, the data in which the element to be processed is located is deleted from the first unordered dictionary.
In addition, if the value corresponding to the keyword L in the second unordered dictionary is null after deleting the element to be processed from the value corresponding to the keyword L in the second unordered dictionary, the first processing module 401 may further delete the data where the keyword L is located from the second unordered dictionary.
As described above, the second processing module 402 may further set a parameter for recording the element as the mode, after the updating, determine the occurrence number P of the element as the mode in the data stream according to the first unordered dictionary, and if it is determined that the keyword p+1 exists in the second unordered dictionary, update the parameter with any element in the value corresponding to the keyword p+1 as the mode.
The element in the data stream may be an offset of the roadside aware camera.
The specific workflow of the embodiment of the apparatus shown in fig. 4 is referred to the related description in the foregoing method embodiment, and will not be repeated.
In summary, by adopting the scheme of the embodiment of the device of the application, the unordered dictionary is used as a basis, the unordered dictionary is used for recording the latest elements included in the data stream and the occurrence times of the elements in the data stream, and the mode can be determined based on the information recorded in the unordered dictionary, and the unordered dictionary is a data structure capable of operating with the time complexity of O (1), so that compared with the prior method, the processing speed is improved, the time consumption is reduced, and the like.
According to an embodiment of the present application, the present application also provides an electronic device and a readable storage medium.
As shown in fig. 5, is a block diagram of an electronic device according to a method according to an embodiment of the application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the applications described and/or claimed herein.
As shown in fig. 5, the electronic device includes: one or more processors Y01, memory Y02, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing within the electronic device, including instructions stored in or on memory to display graphical information of a graphical user interface on an external input/output device, such as a display device coupled to the interface. In other embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple electronic devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). In fig. 5, a processor Y01 is taken as an example.
The memory Y02 is a non-transitory computer readable storage medium provided by the present application. Wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the methods provided by the present application. The non-transitory computer readable storage medium of the present application stores computer instructions for causing a computer to perform the method provided by the present application.
The memory Y02 serves as a non-transitory computer readable storage medium storing a non-transitory software program, a non-transitory computer executable program, and modules, such as program instructions/modules corresponding to the methods in the embodiments of the present application. The processor Y01 executes various functional applications of the server and data processing, i.e., implements the methods in the above-described method embodiments, by running non-transitory software programs, instructions, and modules stored in the memory Y02.
The memory Y02 may include a memory program area that may store an operating system, at least one application program required for functions, and a memory data area; the storage data area may store data created according to the use of the electronic device, etc. In addition, memory Y02 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory Y02 may optionally include memory located remotely from processor Y01, which may be connected to the electronic device via a network. Examples of such networks include, but are not limited to, the internet, intranets, blockchain networks, local area networks, mobile communication networks, and combinations thereof.
The electronic device may further include: an input device Y03 and an output device Y04. The processor Y01, memory Y02, input device Y03, and output device Y04 may be connected by a bus or otherwise, with bus connections being exemplified in fig. 5.
The input device Y03 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device, such as a touch screen, keypad, mouse, trackpad, touchpad, pointer stick, one or more mouse buttons, trackball, joystick, and like input devices. The output means Y04 may include a display device, an auxiliary lighting means, a tactile feedback means (e.g., a vibration motor), and the like. The display device may include, but is not limited to, a liquid crystal display, a light emitting diode display, and a plasma display. In some implementations, the display device may be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific integrated circuitry, computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
These computing programs (also referred to as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. The terms "machine-readable medium" and "computer-readable medium" as used herein refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, programmable logic devices) for providing machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a cathode ray tube or a liquid crystal display monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local area networks, wide area networks, blockchain networks, and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present application may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution disclosed in the present application can be achieved, and are not limited herein.
The above embodiments do not limit the scope of the present application. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the scope of the present application.
Claims (12)
1. A mode acquisition method for a roadside aware camera data stream, comprising:
acquiring a data stream from a road side perception camera;
Constructing an unordered dictionary for the data stream, wherein the unordered dictionary is used for recording elements included in the data stream and the occurrence times of each element in the data stream, and the elements comprise: an offset of a roadside perception camera, the unordered dictionary comprising: the system comprises a first unordered dictionary, a second unordered dictionary and a third unordered dictionary, wherein keywords in the first unordered dictionary are elements included in the data stream, values in the first unordered dictionary are the occurrence times of corresponding keywords in the data stream, the keywords in the second unordered dictionary are the occurrence times, the values in the second unordered dictionary are the third unordered dictionary, and the keywords in the third unordered dictionary are the elements of the keywords in the second unordered dictionary, the occurrence times of which are corresponding in the data stream; updating the unordered dictionary according to element changes in the data stream, including: when any element is added in the data stream, the added element is used as an element to be processed, whether the element to be processed is included in keywords in the first unordered dictionary is determined, if not, data with one keyword being the element to be processed and the corresponding value being 1 is added in the first unordered dictionary, if keywords with 1 are present in the second unordered dictionary, the element to be processed is added in the value corresponding to the keyword with 1, if keywords with 1 are not present in the second unordered dictionary, one keyword is added to be 1 and the corresponding value is the data of the element to be processed, if yes, the value corresponding to the element to be processed in the first unordered dictionary is added by 1, the element to be processed is deleted from the value corresponding to the keyword with N-1 in the second unordered dictionary, N represents the result after the value corresponding to the element to be processed is added by 1, and the element to be processed is added in the value corresponding to the keyword with N in the second unordered dictionary;
taking the element with the largest occurrence number determined according to the unordered dictionary as the mode;
The mode is sent to the receiving device.
2. The method of claim 1, further comprising:
Setting a parameter for recording an element as the mode;
and after updating, determining the occurrence frequency P of the element serving as the mode in the data stream according to the first unordered dictionary, and if the N is determined to be larger than the P, taking the element to be processed as the mode, and updating the parameter.
3. The method of claim 1, wherein the updating the unordered dictionary based on element changes in the data stream further comprises:
when any element is deleted in the data stream, the deleted element is used as an element to be processed;
deleting the element to be processed from the value corresponding to the keyword with L in the second unordered dictionary, wherein L represents the value corresponding to the element to be processed in the first unordered dictionary;
and if L is greater than one, adding the element to be processed in the value corresponding to the keyword of L-1 in the second unordered dictionary, subtracting 1 from the value corresponding to the element to be processed in the first unordered dictionary, and if L is equal to one, deleting the data in which the element to be processed is located from the first unordered dictionary, wherein the data comprises the keyword and the corresponding value.
4. A method according to claim 3, further comprising: and deleting the data where the keyword with L is located from the second unordered dictionary if the value corresponding to the keyword with L in the second unordered dictionary is empty after deleting the element to be processed from the value corresponding to the keyword with L in the second unordered dictionary.
5. A method according to claim 3, further comprising:
Setting a parameter for recording an element as the mode;
And after updating, determining the occurrence frequency P of the element serving as the mode in the data stream according to the first unordered dictionary, and if the keyword which is P+1 exists in the second unordered dictionary, taking any element in the value corresponding to the keyword which is P+1 as the mode, and updating the parameter.
6. A mode acquisition apparatus for a roadside aware camera data stream, comprising: a first processing module and a second processing module;
the first processing module is configured to obtain a data stream from a roadside perception camera, construct an unordered dictionary for the data stream, and record elements included in the data stream and occurrence times of each element in the data stream, where the elements include: an offset of a roadside perception camera, the unordered dictionary comprising: the system comprises a first unordered dictionary, a second unordered dictionary and a third unordered dictionary, wherein keywords in the first unordered dictionary are elements included in the data stream, values in the first unordered dictionary are the occurrence times of corresponding keywords in the data stream, the keywords in the second unordered dictionary are the occurrence times, the values in the second unordered dictionary are the third unordered dictionary, and the keywords in the third unordered dictionary are the elements of the keywords in the second unordered dictionary, the occurrence times of which are corresponding in the data stream; updating the unordered dictionary according to element changes in the data stream, including: when any element is added in the data stream, the added element is used as an element to be processed, whether the element to be processed is included in keywords in the first unordered dictionary is determined, if not, data with one keyword being the element to be processed and the corresponding value being 1 is added in the first unordered dictionary, if keywords with 1 are present in the second unordered dictionary, the element to be processed is added in the value corresponding to the keyword with 1, if keywords with 1 are not present in the second unordered dictionary, one keyword is added to be 1 and the corresponding value is the data of the element to be processed, if yes, the value corresponding to the element to be processed in the first unordered dictionary is added by 1, the element to be processed is deleted from the value corresponding to the keyword with N-1 in the second unordered dictionary, N represents the result after the value corresponding to the element to be processed is added by 1, and the element to be processed is added in the value corresponding to the keyword with N in the second unordered dictionary;
and the second processing module is used for taking the element with the largest occurrence number determined according to the unordered dictionary as the mode and sending the mode to receiving equipment.
7. The apparatus of claim 6, wherein,
The second processing module is further configured to set a parameter, configured to record an element serving as the mode, determine, according to the first unordered dictionary, a number of occurrences P of the element serving as the mode in the data stream after the updating, and if it is determined that N is greater than P, update the parameter with the element to be processed as the mode.
8. The apparatus of claim 6, wherein,
The first processing module is further configured to, when any element is deleted in the data stream, delete the element to be processed from the value corresponding to the keyword that is L in the second unordered dictionary, where L represents the value corresponding to the element to be processed in the first unordered dictionary, and if L is greater than one, add the element to be processed in the value corresponding to the keyword that is L-1 in the second unordered dictionary, and subtract 1 from the value corresponding to the element to be processed in the first unordered dictionary, and if L is equal to one, delete the data where the element to be processed is located from the first unordered dictionary, where the data includes the keyword and the corresponding value.
9. The apparatus of claim 8, wherein,
The first processing module is further configured to delete, if the value corresponding to the keyword that is L in the second unordered dictionary is empty after deleting the element to be processed from the value corresponding to the keyword that is L in the second unordered dictionary, data where the keyword that is L is located from the second unordered dictionary.
10. The apparatus of claim 8, wherein,
The second processing module is further configured to set a parameter, configured to record an element serving as the mode, determine, according to the first unordered dictionary, a number of occurrences P of the element serving as the mode in the data stream after the updating, and if it is determined that a keyword p+1 exists in the second unordered dictionary, update the parameter with any element in a value corresponding to the keyword p+1 as the mode.
11. An electronic device, comprising:
At least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
12. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-5.
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