Streaming media cloud video rendering method, system, device and medium

Abstract

The invention discloses a streaming media cloud video rendering method, system and device and a storage medium. The method comprises the following steps: segmenting an obtained target video according to a preset granularity to obtain n target sub-video files, and extracting a video recording starting moment and a video recording ending moment of each target sub-video file; according to the video recording starting moment and the video recording ending moment, renaming the n target sub-video files to obtain a historical video file and send the historical video file to an object storage, and the object storage responding to the operation of querying the historical video file of any day sent by the client, converting the historical video file list of the day into a video file playing address list and sending the video file playing address list to the client, and generating a video playing progress bar of the day by the client according to the video file playing address list; wherein the historical video file list of the day comprises a plurality of target sub-videos of which the video starting time is the day. The method can be widely applied to the technical field of data processing.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a streaming media cloud video rendering method, system, device and storage medium. Background Art

[0002] With the rapid development of Internet of Things technology, more and more devices need to record in real time and store them in the cloud. The traditional method of video storage is to upload the video files from the acquisition device to the cloud, and the cloud stores them in a predetermined location. This leads to the storage files being too large, inconvenient and inefficient to download and backup, and the inability to intuitively display the recording time period, resulting in poor user experience. Therefore, there are still technical problems that need to be solved in the relevant technology. Summary of the invention

[0003] The purpose of this application is to solve one of the technical problems existing in the prior art to at least a certain extent.

[0004] To this end, an object of an embodiment of the present application is to provide a streaming media cloud video rendering method, system, device and storage medium, which can improve file storage efficiency and improve the user experience during the video playback process.

[0005] In order to achieve the above-mentioned technical objectives, the technical solution adopted by the embodiment of the present application includes: a streaming media cloud video rendering method, comprising: obtaining a target video captured by a video capture device; dividing the target video according to a preset granularity to obtain n target sub-video files and extracting the recording start time and the recording end time of each target sub-video file; renaming the n target sub-video files according to the recording start time and the recording end time to obtain a historical video file and sending it to the object storage, so that the object storage responds to the operation of querying the historical video files of any day sent by the client, converts the historical video file list of the day into a video file playback address list and sends it to the client, and enables the client to generate a video playback progress bar for the day according to the video file playback address list; wherein the historical video file list of the day includes several target sub-videos whose recording start time is the day, where n is greater than or equal to 2.

[0006] In addition, the method for rendering streaming media cloud video according to the above embodiment of the present invention may also have the following additional technical features:

[0007] Furthermore, in an embodiment of the present application, segmenting the target video according to a preset granularity to obtain n target sub-video files specifically includes: determining each segmentation node of the target video according to the preset granularity; and segmenting the target video based on each segmentation node to obtain n target sub-video files.

[0008] Furthermore, in an embodiment of the present application, determining each segmentation node of the target recorded video on a preset timeline according to the preset granularity includes: determining the time difference between any two of the segmentation nodes according to the preset granularity; taking a preset reference moment as the starting point, determining a segmentation node at each interval of the time difference.

[0009] Furthermore, in an embodiment of the present application, the extracting of the recording start time and the recording end time of each target sub-video file specifically includes: determining the recording start time of the 2nd to nth target sub-video files and determining the recording end time of the 1st to n-1th target sub-video files according to the segmentation node; using the end time of the target recorded video as the recording end time of the nth target sub-video file; using the start time of the target recorded video as the recording start time of the 1st target sub-video file.

[0010] Further, in an embodiment of the present application, the name of the target sub-video file includes a name prefix, a name infix, and a name suffix, and the renaming of the n target sub-video files according to the video recording start time and the video recording end time includes:

[0011] Determine the name infix and the name prefix according to the video recording start time;

[0012] The name suffix is ​​determined according to the end time of the video recording.

[0013] Furthermore, in an embodiment of the present application, the step of determining the name prefix based on the start time of the recording includes: extracting the numerical values ​​corresponding to the year, month, day, hour and minute in the start time of the recording; concatenating the numerical values ​​into a character string, and using the character string as the name prefix.

[0014] Furthermore, in an embodiment of the present application, determining the name infix based on the start time of the recording includes: calculating the time difference between the start time of the recording and a preset reference time; converting the time difference into a difference in seconds, and using the difference in seconds as the name infix.

[0015] On the other hand, the embodiment of the present application further provides a streaming media cloud video rendering system, including:

[0016] An acquisition unit, used to acquire a target video captured by a video acquisition device;

[0017] The first processing unit is used to segment the target video according to a preset granularity to obtain n target sub-video files and extract the video recording start time and the video recording end time of each target sub-video file;

[0018] The second processing unit is used to rename n target sub-video files according to the recording start time and the recording end time, obtain historical video files and send them to the object storage, so that the object storage responds to the operation of querying the historical video files of any day sent by the client, converts the historical video file list of the day into a video file playback address list and sends it to the client, and enables the client to generate a video playback progress bar for the day according to the video file playback address list; wherein the historical video file list of the day includes several target sub-videos whose recording start time is the day, and n is greater than or equal to 2.

[0019] On the other hand, the present application also provides a streaming media cloud video rendering device, comprising:

[0020] at least one processor;

[0021] at least one memory for storing at least one program;

[0022] When the at least one program is executed by the at least one processor, the at least one processor implements a streaming media cloud video rendering method as described in any one of the invention contents.

[0023] In addition, the present application also provides a computer-readable storage medium, which stores processor-executable instructions. When the processor executes the instructions, the processor-executable instructions are used to execute a streaming media cloud video rendering method as described in any of the above items.

[0024] The advantages and benefits of the present application will be partially given in the following description, and partially become apparent from the following description, or be understood through the practice of the present application:

[0025] The present application can obtain the target video captured by the video capture device; divide the target video according to the preset granularity to obtain n target sub-video files and extract the recording start time and the recording end time of each target sub-video file; rename the n target sub-video files according to the recording start time and the recording end time to obtain the historical video file and send it to the object storage, so that the object storage responds to the operation of querying the historical video files of any day sent by the client, converts the historical video file list of the day into a video file playback address list and sends it to the client, and enables the client to generate the video playback progress bar of the day according to the video file playback address list; wherein the historical video file list of the day includes several target sub-videos with the recording start time of the day, wherein n is greater than or equal to 2. The present application facilitates downloading and backup by dividing the video file and then storing it. By rendering the video file according to the video file playback address list and generating the video playback progress bar of the day, the user experience is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic diagram of the steps of a streaming media cloud video rendering method in a specific embodiment of the present invention;

[0027] Figure 2 It is a structural schematic diagram of a device for implementing a streaming media cloud video rendering method in a specific embodiment of the present invention;

[0028] Figure 3 A schematic diagram of the steps of a streaming media cloud video rendering method in another specific embodiment of the present invention;

[0029] Figure 4 This is a rendering effect diagram of a streaming media cloud recording progress bar in a specific embodiment of the present invention;

[0030] Figure 5 It is a structural schematic diagram of a streaming media cloud video rendering system in a specific embodiment of the present invention;

[0031] Figure 6 The present invention is a schematic structural diagram of a streaming media cloud video rendering device in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0032] The embodiments of the present invention are described in detail below with reference to the accompanying drawings to explain the principles and processes of the streaming media cloud video rendering method, system, device and storage medium in the embodiments of the present invention.

[0033] Reference Figure 1 ,exist Figure 1In the present invention, a streaming media cloud video rendering method may include steps S101 to S103.

[0034] S101, obtaining a target video captured by a video capture device.

[0035] S102: Segment the target video according to a preset granularity to obtain n target sub-video files and extract the recording start time and the recording end time of each target sub-video file.

[0036] S103. According to the recording start time and the recording end time, n target sub-video files are renamed to obtain historical video files and sent to the object storage, so that the object storage responds to the operation of querying the historical video files of any day sent by the client, converts the historical video file list of the day into a video file playback address list and sends it to the client, and enables the client to generate a video playback progress bar for the day according to the video file playback address list; wherein the historical video file list of the day includes a number of target sub-videos whose recording start time is the day, wherein n is greater than or equal to 2.

[0037] It is understandable that the preset granularity may be 3 minutes, 5 minutes, 10 minutes or other time granularity.

[0038] Furthermore, the step of segmenting the target recorded video according to a preset granularity to obtain n target sub-video files may include steps S201 and S202.

[0039] S201: Determine each segmentation node of the target video according to a preset granularity.

[0040] S202: Segment the target recorded video based on each segmentation node to obtain n target sub-video files.

[0041] In some feasible embodiments of the present application, the processor can determine each segmentation node of the target video according to a preset granularity. After obtaining the segmentation node, the processor can segment the target video based on each segmentation node to obtain n target sub-video files.

[0042] Furthermore, the step of determining each segmentation node of the target video on the preset time axis according to the preset granularity includes steps S301 and S302.

[0043] S301: Determine the time difference between any two adjacent segmentation nodes according to a preset granularity.

[0044] S302: Taking the preset reference time as the starting point, a split node is determined for each time difference.

[0045] In some feasible embodiments of the present application, the processor can determine the time difference between any two adjacent segmentation nodes according to a preset granularity. Taking the preset reference time as the starting point, the processor can determine a segmentation node at each interval of the time difference. Specifically, if the preset granularity is 5 minutes, the time difference between any two adjacent segmentation nodes is 5 minutes, and it is assumed that the preset reference time is 00:00:00 on ...

[0046] Furthermore, the step of extracting the recording start time and the recording end time of each target sub-video file may include steps S401 and S402.

[0047] S401 . Determine the start time of recording the second to nth target sub-video files and the end time of recording the first to n-1th target sub-video files according to the segmentation node.

[0048] S402: Taking the end time of the target recorded video as the end time of recording of the nth target sub-video file.

[0049] S403: Taking the start time of the target recorded video as the recording start time of the first target sub-video file.

[0050] In some feasible embodiments of the present application, the processor can determine the recording start time of the second to nth target sub-video files according to the segmentation node. The processor can also determine the recording end time of the first to n-1th target sub-video files according to the segmentation node.

[0051] Furthermore, the name of the target sub-video file may include a name prefix, a name infix and a name suffix. According to the start time and the end time of the recording, the step of renaming the n target sub-video files may specifically include steps S501 and S502.

[0052] S501. Determine the name infix and the name prefix according to the video recording start time.

[0053] S502: Determine the name suffix according to the end time of the video recording.

[0054] In some feasible embodiments of the present application, the processor may determine the name infix according to the start time of the video recording. The processor may also determine the name prefix and the name suffix according to the end time of the video recording.

[0055] Furthermore, according to the video recording start time, the step of determining the name prefix may specifically include steps S601 and S602.

[0056] S601, extracting the values ​​corresponding to the year, month, day, hour and minute at the start time of the video recording.

[0057] S602: Concatenate the values ​​into a string and use the string as a name prefix.

[0058] In some feasible embodiments of the present application, the processor may extract the numerical values ​​corresponding to the year, month, day, hour, and minute at the start time of the video recording, and then concatenate the numerical values ​​into a string, and use the string as a name prefix.

[0059] For example, the recording start time is 15:30:29 on October 30, 2024, and the character string at this time is 202410301530.

[0060] Furthermore, according to the start time of recording, determining the name suffix may include steps S701 and S702.

[0061] S701: Calculate the time difference between the video recording start time and the preset reference time.

[0062] S702: Convert the time difference into seconds, and use the seconds as a name infix.

[0063] For example, the preset reference time is 00:00 on January 1, 1970, and the recording start time is 02:00:00 on January 1, 1970. Then the suffix in the name is the time 7200 seconds obtained by subtracting the two dates.

[0064] The specific implementation principle of this application is described below with reference to the accompanying drawings:

[0065] Reference Figure 2-Figure 4 , the streaming media cloud video rendering of an embodiment of the present application may include the following steps:

[0066] (1) Video data acquisition and preprocessing

[0067] IoT devices (such as cameras, NVRs, etc.) collect streaming data in real time and transmit the data to the streaming server through the network. After receiving the data, the streaming server can perform pre-processing such as format conversion and compression to optimize storage and transmission efficiency.

[0068] (2) File segmentation by 5-minute granularity

[0069] The streaming media server divides the pre-processed streaming media data into 5-minute granularity files according to a custom algorithm and saves them in FLV format. This step can make the size of each video file moderate, which is convenient for subsequent storage, downloading and management.

[0070] The custom file segmentation algorithm is designed as follows:

[0071]

[0072]

[0073] This file segmentation algorithm is used to segment files according to the set time slices (fragments) during video recording. Its working principle is as follows:

[0074] a) Get the current time:

[0075] Use time.Now() to get the current system time and store it in the nowTime variable.

[0076] b) Calculation start time:

[0077] By subtracting duration milliseconds (i.e., the current video file duration) from the current time nowTime, the start time startTime corresponding to the video file is calculated.

[0078] c) Extract minutes:

[0079] Extracts the minutes from the current time nowTime and stores it in the nowMinute variable.

[0080] Extract the minutes from the start time startTime and store it in the startMinute variable.

[0081] d) Get the fragment duration:

[0082] Get the number of minutes from r.Fragment (a time.Duration type variable representing the fragment duration) and store it in the fragment variable.

[0083] e) Determine whether the fragmentation is completed:

[0084] Checks whether the current minute nowMinute is not equal to the starting minute startMinute to ensure that at least one full minute has passed.

[0085] Check whether the current minute nowMinute is divisible by the fragment duration fragment, that is, whether the current time is exactly the end point of a fragment duration.

[0086] If both of the above conditions are met, it means that the current time has reached the end point of a segment duration and the file can be split.

[0087] Example of custom file segmentation algorithm:

[0088] Assume that r.Fragment is set to 5 minutes (300 seconds), and the duration of the current video file is 200 seconds (3 minutes and 20 seconds).

[0089] nowTime is assumed to be 14:05:00.

[0090] The startTime is 14:01:40 (because 200 seconds are subtracted from the current time).

[0091] nowMinute is 5.

[0092] startMinute is 1 (because 14:01:40 is the first minute).

[0093] fragment is 5.

[0094] According to the algorithm:

[0095] nowMinute! =startMinute is true (5!=1).

[0096] nowMinute%fragment==0 is true (5%5==0).

[0097] Therefore, the condition is met, indicating that the current time (14:05:00) is exactly the end point of a 5-minute segment, and the function returns true, indicating that file segmentation is required.

[0098] (3) File naming and uploading

[0099] Generate a file name containing the start time and end time of the video for each split video file. The file name format is designed as "YYYYMMDDHHMM_StartTime_EndTime.flv". "YYYYMMDDHHMM" represents the year, month, day, hour, and minute of the start time of the video, which is also the time corresponding to some split nodes. "StartTime_EndTime" represents the start and end time of the video (the total number of seconds from 00:00:00 UTC on January 1, 1970 to the present). Example:

[0100] 202407051505_1720163229_1720163401.flv

[0101] 202407051510_1720163401_1720163623.flv

[0102] 202407051515_1720163785_1720163999.flv

[0103] Afterwards, these files are uploaded to object storage OSS for storage.

[0104] (4) Client requests IoT platform

[0105] The client initiates a video playback request for a certain day to the IoT platform. The IoT platform obtains the video file list for a certain day through the API interface provided by the object storage OSS, converts the video file list into a video file playback address list, where the address is authenticated and encrypted, and then the IoT platform can return the list to the client.

[0106] (5) Client playback progress bar rendering information generation

[0107] After the client obtains the playback address list of the video files for a certain day, it can generate a playback progress bar for the day based on the file name information stored in the object storage OSS. Each time period on the progress bar corresponds to a video file, and the client can also use color, icons or other visual elements to mark which time periods have videos.

[0108] (6) Client requests object storage OSS

[0109] After the client generates a one-day playback progress bar, each time period on the progress bar corresponds to a playback address for a video file. Based on the playback address, the client can access the video file stored in the cloud through the API provided by the object storage OSS. The client can click on the specified time period to initiate a playback request according to its needs. OSS supports HTTP streaming, and the data will be downloaded and played at the same time. The high concurrent access capability of the object storage OSS ensures that the client can smoothly access and play the required video files.

[0110] (7) Document management and maintenance

[0111] The IoT platform can regularly manage and maintain the video files stored in the object storage OSS, such as deleting expired files, etc. In addition, the IoT platform can also provide file search, classification and other functions to facilitate users to quickly find the required video files.

[0112] (8) Security and Privacy Protection

[0113] This embodiment can improve the security of streaming media data and enhance privacy protection. This embodiment can be implemented through encrypted transmission of the playback address and access control means to prevent data leakage or malicious access.

[0114] In summary, the streaming media cloud video rendering method of the present application has the following advantages:

[0115] 1. This application generates a one-day playback progress bar based on the file name information (YYYYMMDDHHMM_StartTime_EndTime), so that users can intuitively understand which time periods have recordings. This application can improve the user experience and reduce the difficulty of video monitoring and operation and maintenance for operation and maintenance personnel.

[0116] 2. This application uses object storage OSS to store streaming media data, which has the advantages of high efficiency, scalability and low cost. At the same time, through specific file segmentation and naming strategies, the readability and manageability of video files are improved.

[0117] In addition, refer to Figure 5 ,and Figure 1 Corresponding to the method, an embodiment of the present application also provides a streaming media cloud video rendering system. The system may include: an acquisition unit 1001, a first processing unit 1002, and a second processing unit 1003. The acquisition unit 1001 can acquire the target video captured by the video acquisition device; the first processing unit 1002 can be used to divide the target video according to the preset granularity to obtain n target sub-video files and extract the video start time and the video end time of each target sub-video file; the second processing unit 1003 can be used to rename the n target sub-video files according to the video start time and the video end time, obtain the historical video file and send it to the object storage, so that the object storage responds to the operation of querying the historical video file of any day sent by the client, converts the historical video file list of the day into a video file playback address list and sends it to the client, and enables the client to generate the video playback progress bar of the day according to the video file playback address list; wherein the historical video file list of the day includes a number of target sub-videos with the video start time of the day, where n is greater than or equal to 2.

[0118] It should be noted that the acquisition unit can be any integrated circuit unit or microprocessor unit obtained by integrating a chip having a processing function and its peripheral circuits through existing integration technology. The first processing unit and the second processing unit can also be any integrated circuit module or microprocessor module obtained by integrating a chip having a processing function and its peripheral circuits through existing integration technology. The first processing unit and the second processing unit can also include one or more memories. One or more memories can be used to store the specific algorithm used for compression adjustment processing in this application.

[0119] In some embodiments of the present application, the acquisition unit 1001 can be set in the same gateway or device with a processor as the processing unit 1002. The specific device connection mode and device setting of the acquisition unit 1001 and the first processing unit 1002 and the first processing unit 1002 and the second processing unit 1003 are not limited.

[0120] It should be noted that the contents of the above-mentioned streaming media cloud video rendering method embodiment are all applicable to the present streaming media cloud video rendering system embodiment, and the functions specifically implemented by the present streaming media cloud video rendering system embodiment are the same as those of the above-mentioned streaming media cloud video rendering method embodiment, and the beneficial effects achieved are also the same as those achieved by the above-mentioned streaming media cloud video rendering method embodiment.

[0121] and Figure 1 Corresponding to the method, the embodiment of the present application also provides a streaming media cloud video rendering device, the specific structure of which can be referred to Figure 6 ,include:

[0122] at least one processor 1011;

[0123] At least one memory 1012, used to store at least one program;

[0124] When the at least one program is executed by the at least one processor, the at least one processor implements the streaming media cloud video rendering method.

[0125] The contents of the above method embodiments are all applicable to the present device embodiments. The functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0126] and Figure 1 Corresponding to the method, an embodiment of the present application further provides a computer-readable storage medium, which stores instructions executable by a processor, and the processor-executable instructions are used to execute the streaming media cloud video rendering method when executed by the processor.

[0127] The contents of the above streaming media cloud video rendering method embodiment are all applicable to the present storage medium embodiment. The functions specifically implemented by the present storage medium embodiment are the same as those of the above streaming media cloud video rendering method embodiment, and the beneficial effects achieved are also the same as those achieved by the above streaming media cloud video rendering method embodiment.

[0128] In some optional embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the application is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Optional embodiments are expected, wherein the order of various operations is changed and the sub-operation described as a part of a larger operation is performed independently.

[0129] In addition, although the present application is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present application. More specifically, in view of the properties, functions, and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional techniques of the engineer. Therefore, those skilled in the art can implement the present application set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present application, which is determined by the full scope of the attached claims and their equivalents.

[0130] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several programs to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0131] The logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable programs for implementing the logical functions, and may be embodied in any computer-readable medium for use by a program execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch and execute a program from a program execution system, device or apparatus), or in conjunction with such program execution systems, devices or apparatuses. For purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by a program execution system, device or apparatus, or in conjunction with such program execution systems, devices or apparatuses.

[0132] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0133] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable program execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0134] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0135] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

[0136] The above is a specific description of the preferred implementation of the present application, but the present application is not limited to the described embodiments. Technical personnel familiar with the field may make various equivalent modifications or substitutions without violating the spirit of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present application.

Claims

1. A streaming media cloud video rendering method, characterized in that: The following steps are involved: Obtain the target video captured by the video capture device; The target video is segmented according to a preset granularity to obtain n target sub-video files and the video recording start time and the video recording end time of each target sub-video file are extracted; According to the video start time and the video end time, the n target sub-video files are renamed to obtain a historical video file and sent to the object storage, so that the object storage responds to the operation of querying the historical video files of any day sent by the client, converts the historical video file list of the day into a video file playback address list and sends it to the client, and enables the client to generate a video playback progress bar for the day according to the video file playback address list; The historical video file list of the day includes a number of target sub-videos whose recording start time is the day, where n is greater than or equal to 2.

2. According to the streaming media cloud video rendering method of claim 1, it is characterized in that: The target video is segmented according to a preset granularity to obtain n target sub-video files, including: Determine each segmentation node of the target video according to the preset granularity; Based on each of the segmentation nodes, the target recorded video is segmented to obtain n target sub-video files.

3. According to claim 2, a streaming media cloud video rendering method is characterized in that: The step of determining each segmentation node of the target video on a preset time axis according to the preset granularity includes: Determine the time difference between any two of the segmentation nodes according to the preset granularity; Taking the preset reference time as the starting point, a segmentation node is determined at each interval of the time difference.

4. According to claim 1, a streaming media cloud video rendering method is characterized in that: The step of extracting the video recording start time and the video recording end time of each target sub-video file includes: According to the segmentation node, determining the recording start time of the second to nth target sub-video files and determining the recording end time of the first to n-1th target sub-video files; The end time of the target video is used as the end time of the video recording of the nth target sub-video file; The start time of the target recorded video is used as the recording start time of the first target sub-video file.

5. According to claim 1, a streaming media cloud video rendering method is characterized in that: The name of the target sub-video file includes a name prefix, a name infix and a name suffix, and the renaming of the n target sub-video files according to the video recording start time and the video recording end time includes: Determine the name infix and the name prefix according to the video recording start time; The name suffix is ​​determined according to the end time of the video recording.

6. A streaming media cloud video rendering method according to claim 5, characterized in that: The step of determining the name prefix according to the video recording start time includes: Extract the values ​​corresponding to the year, month, day, hour and minute at the start time of the video recording; The numerical values ​​are concatenated into a character string, and the character string is used as the prefix of the name.

7. A streaming media cloud video rendering method according to claim 5, characterized in that: The determining the name suffix according to the video recording start time includes: Calculate the time difference between the video recording start time and the preset reference time; The time difference is converted into a difference in seconds, and the difference in seconds is used as the name infix.

8. A streaming media cloud video rendering system, characterized in that: include: An acquisition unit, used to acquire a target video captured by a video acquisition device; The first processing unit is used to segment the target video according to a preset granularity to obtain n target sub-video files and extract the video recording start time and the video recording end time of each target sub-video file; The second processing unit is used to rename the n target sub-video files according to the video start time and the video end time, obtain the historical video files and send them to the object storage, so that the object storage responds to the operation of querying the historical video files of any day sent by the client, converts the historical video file list of the day into a video file playback address list and sends it to the client, and enables the client to generate a video playback progress bar for the day according to the video file playback address list; The historical video file list of the day includes a number of target sub-videos whose recording start time is the day, where n is greater than or equal to 2.

9. A streaming media cloud video rendering device, characterized in that include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements a streaming media cloud video rendering method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing instructions executable by a processor, characterized in that: The processor-executable instructions are used to execute a streaming media cloud video rendering method as described in any one of claims 1-7 when executed by the processor.

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