CN110855947B - Image snapshot processing method and device - Google Patents
Image snapshot processing method and device Download PDFInfo
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- CN110855947B CN110855947B CN201911175755.4A CN201911175755A CN110855947B CN 110855947 B CN110855947 B CN 110855947B CN 201911175755 A CN201911175755 A CN 201911175755A CN 110855947 B CN110855947 B CN 110855947B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/075—Ramp control
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
Abstract
The invention provides a method and a device for processing snapshot of an image, wherein the method comprises the following steps: a first camera acquires a video code stream which is pushed and collected when a second camera detects that a target moves in a video, wherein the first camera is a camera supporting an image capturing function, and the second camera is a camera not supporting the image capturing function; analyzing the video code stream to determine whether the video code stream meets a predetermined condition; under the condition that the video code stream meets the preset condition, carrying out image snapshot on the video code stream; the generated snapshot image is sent to the second camera, the problem that in the related technology, due to the fact that the low-end camera cannot complete snapshot, all the low-end cameras need to be replaced by high-end cameras to achieve image snapshot, cost is high, the low-end cameras transmit video code streams to the high-end cameras, the high-end cameras assist in completing image snapshot, and image snapshot can be completed without replacing the low-end cameras.
Description
Technical Field
The invention relates to the field of image processing, in particular to an image snapshot processing method and device.
Background
At present, the requirement of a user on video monitoring is higher and higher, a camera is required to be visible and clearly seen before, and then the camera is understood at present, so that manual intervention is greatly reduced no matter a motor vehicle is illegal to stop or is identified by an airplane or a non-man. And as deep learning technology is widely used, the target identification accuracy rate is higher and higher. However, the smart algorithm is resource consuming, and the low-end camera may not be able to run the smart snap function.
The related art provides an illegal parking snapshot method, which comprises the following steps: detecting whether the multiple monitoring scenes obtained by the shooting device have the illegal parking targets, obtaining the monitoring scenes with the illegal parking targets as target monitoring scenes, and carrying out multiple times of snapshot on the illegal parking targets in the target monitoring scenes according to the types of the evidence images of the illegal parking targets needing to be snapshot and the snapshot sequence and time interval among the evidence images of various types to obtain the multiple evidence images of the illegal parking targets. The illegal stop snapshot of the method also has requirements on the performance of the camera, and the low-end camera cannot support the illegal stop snapshot.
Generally, in some use scenes, the installation camera may be a high-end camera in part and a low-end camera in part. The low-end camera does not support the smart snap function, and if the camera is replaced with a high-end camera, the cost is high.
Aiming at the problem that in the related technology, due to the fact that the low-end cameras cannot complete snapshot, all the low-end cameras need to be replaced by high-end cameras to realize image snapshot, and the cost is too high, a solution is not provided.
Disclosure of Invention
The embodiment of the invention provides an image snapshot processing method and device, and aims to at least solve the problem that in the related technology, due to the fact that a low-end camera cannot complete snapshot, image snapshot can be realized only by replacing all low-end cameras with high-end cameras, and cost is too high.
According to an embodiment of the present invention, there is provided an image capture processing method including:
the method comprises the steps that a first camera acquires a video code stream which is pushed to be collected when a second camera detects that a target moves in a video, wherein the first camera is a camera supporting an image capturing function, and the second camera is a camera not supporting the image capturing function;
the first camera analyzes the video code stream to determine whether the video code stream meets a preset condition;
under the condition that the video code stream meets the preset condition, the first camera carries out image snapshot on the video code stream;
and the first camera sends the generated snapshot image to the second camera.
Optionally, the analyzing, by the first camera, the video code stream to determine whether the video code stream meets a predetermined condition includes:
the first camera decodes the video code stream to obtain a plurality of images, and the images are input into a pre-trained target neural network model to obtain the probability that the video code stream output by the target neural network model contains a preset behavior or a target object;
under the condition that the probability is greater than or equal to a preset threshold value, the first camera determines that the video code stream contains a preset behavior or a target object, and determines that the video code stream meets the preset condition;
and under the condition that the probability is smaller than the preset threshold value, the first camera determines that the video code stream does not contain a preset behavior or a target object, and determines that the video code stream does not meet the preset condition.
Optionally, when the analysis result satisfies a predetermined condition, the capturing, by the first camera, the video code stream by the first camera includes:
under the condition that the video code stream contains the preset behavior or the target object, the first camera acquires a target monitoring scene with the preset behavior or the target object from the video code stream;
and the first camera carries out one or more times of image capturing on the preset behavior or the target object in the target monitoring scene to obtain one or more target capturing images of the preset behavior or the target object.
Optionally, when the first camera acquires a video code stream pushed when the second camera detects that the target moves in the video, the method further includes: the first camera sends an acquisition instruction for acquiring the service type and the target area of the second camera to the second camera; the first camera receives the service type and the target area of the second camera returned by the second camera according to the acquisition instruction;
the first camera analyzing the video code stream to determine whether the video code stream meets a predetermined condition includes: and the first camera analyzes the video code stream in the target area according to the service type of the second camera to determine whether the video code stream meets a preset condition.
Optionally, the acquiring, by the first camera, a video code stream of a second camera with a mapping relationship established in advance includes:
the first camera acquires a video code stream pushed when the second camera which establishes a mapping relation in advance detects that a target moves in a video through a real-time streaming protocol (RTSP) or a private protocol, wherein the video code stream carries an IP address of the second camera.
Optionally, after the first camera performs image capturing on the video code stream, the method further includes:
the first camera generates the snapshot image according to the identification of the second camera, wherein the snapshot image carries the IP address of the second camera;
the first camera sending the generated snapshot image to the second camera includes:
and the first camera sends the snapshot image to the second camera by using a real-time streaming protocol (RTSP) or a private protocol according to the IP address of the second camera.
Optionally, the predetermined behavior comprises at least one of: abnormal behavior, violation behavior, and parking violation behavior.
According to another embodiment of the present invention, there is also provided an image-capturing processing apparatus applied to a first camera indicating an image capturing function, including:
the acquisition module is used for acquiring a video code stream pushed when a second camera detects that a target moves in a video, wherein the second camera is a camera which does not support an image capturing function;
the analysis module is used for analyzing the video code stream to determine whether the video code stream meets a preset condition;
the image snapshot module is used for carrying out image snapshot on the video code stream under the condition that the video code stream meets the preset condition;
and the sending module is used for sending the generated snapshot image to the second camera.
Optionally, the analysis module comprises:
the input submodule is used for decoding the video code stream to obtain a plurality of images, inputting the images into a pre-trained target neural network model, and obtaining the probability that the video code stream output by the target neural network model contains a preset behavior or a target object;
the first determining submodule is used for determining that the video code stream contains a preset behavior or a target object and determining that the video code stream meets the preset condition under the condition that the probability is greater than or equal to a preset threshold value;
and the second determining submodule is used for determining that the video code stream does not contain a preset behavior or a target object and determining that the video code stream does not meet the preset condition under the condition that the probability is smaller than the preset threshold value.
Optionally, the image capturing module comprises:
the obtaining sub-module is used for obtaining a target monitoring scene with the preset behavior or the target object from the video code stream under the condition that the video code stream contains the preset behavior or the target object;
and the image capturing sub-module is used for capturing one or more images of the preset behavior or the target object in the target monitoring scene to obtain one or more target capturing images of the preset behavior or the target object.
Optionally, the apparatus further comprises: the receiving module is used for sending an acquisition instruction for acquiring the service type and the target area of the second camera to the second camera; receiving the service type and the target area of the second camera returned by the second camera according to the acquisition instruction;
the analysis module is further configured to analyze the video code stream in the target area according to the service type of the second camera to determine whether the video code stream meets a predetermined condition.
Optionally, the obtaining module is further configured to
And acquiring a video code stream pushed by the second camera with a mapping relation established in advance when the second camera detects that the target moves in the video through a real-time streaming protocol (RTSP) or a private protocol, wherein the video code stream carries the IP address of the second camera.
Optionally, the apparatus further comprises:
the generating module is used for generating the snapshot image according to the identifier of the second camera, wherein the snapshot image carries the IP address of the second camera;
the sending module is further configured to send the captured image to the second camera according to the IP address of the second camera by using a real-time streaming protocol RTSP protocol or a private protocol.
Optionally, the predetermined behavior comprises at least one of: abnormal behavior, violation behavior, and parking violation behavior.
According to a further embodiment of the present invention, a computer-readable storage medium is also provided, in which a computer program is stored, wherein the computer program is configured to perform the steps of any of the above-described method embodiments when executed.
According to yet another embodiment of the present invention, there is also provided an electronic device, including a memory in which a computer program is stored and a processor configured to execute the computer program to perform the steps in any of the above method embodiments.
According to the invention, a first camera acquires a video code stream pushed when a second camera detects that a target moves in a video, wherein the first camera is a camera supporting an image capturing function, and the second camera is a camera not supporting the image capturing function; analyzing the video code stream to determine whether the video code stream meets a preset condition; under the condition that the video code stream meets the preset condition, carrying out image snapshot on the video code stream; the generated snapshot image is sent to the second camera, the problem that in the related technology, due to the fact that the low-end camera cannot complete snapshot, all the low-end cameras need to be replaced by high-end cameras to achieve image snapshot, and therefore cost is high can be solved, the low-end camera transmits video code streams to the high-end camera, the high-end camera assists in completing image snapshot, and image snapshot can be completed without replacing the low-end camera.
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 embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a block diagram of a hardware structure of a mobile terminal of an image snapshot processing method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method of image capture processing according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a video snapshot according to an embodiment of the present invention;
FIG. 4 is a flow chart of a high-end camera performing an intelligent snap shot in accordance with an embodiment of the invention;
fig. 5 is a block diagram of an image capture processing apparatus according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
Example 1
The method provided by the first embodiment of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Taking a mobile terminal as an example, fig. 1 is a hardware structure block diagram of a mobile terminal of an image capture processing method according to an embodiment of the present invention, as shown in fig. 1, a mobile terminal 10 may include one or more processors 102 (only one is shown in fig. 1) (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA), and a memory 104 for storing data, and optionally, the mobile terminal may further include a transmission device 106 for a communication function and an input/output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration, and does not limit the structure of the mobile terminal. For example, the mobile terminal 10 may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
The memory 104 may be used to store a computer program, for example, a software program of application software and a module, such as a computer program corresponding to the message receiving method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, so as to implement the method described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the mobile terminal 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal 10. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
At large-scale square or garden, before intelligence snapshot technique and chip are not mature yet, installed more low-end camera, if want to change for taking the camera of intelligence snapshot, then can introduce a small amount of high-end camera, the low-end camera can be carried out the intelligence with the help of high-end camera and clap, has reduced and has replaced high-end camera cost.
The intelligent snapshot camera is arranged in a certain planned scene, but due to cost control factors, all high-end cameras cannot be installed, a small number of high-end cameras can be installed, most low-end cameras are installed, and the intelligent snapshot function is completed through the high-end cameras and the auxiliary low-end cameras.
In this embodiment, an image capturing method operating in the mobile terminal or the network architecture is provided, and fig. 2 is a flowchart of an image capturing method according to an embodiment of the present invention, as shown in fig. 2, the flowchart includes the following steps:
step S202, a first camera acquires a video code stream pushed when a second camera detects that a target moves in a video, wherein the first camera is a camera supporting an image capturing function, and the second camera is a camera not supporting the image capturing function;
specifically, when the second camera detects that the target of the video moves, the second camera pushes the collected video code stream to the first camera.
The first camera in the embodiment of the invention can be applied to general scenes (such as squares, parks, entrances and exits, urban roads, shopping malls, crossroads and the like) to take a snapshot of targets such as motor vehicles, non-locomotives, people, human faces and the like. The snapshot is to identify a target (such as an airplane, a non-man, a human face, a license plate and the like) through an intelligent algorithm, and then to snapshot the target and store a picture or an image. The second camera is a low-end camera, and the low-end camera is a camera with low performance, such as a CPU (central processing unit), a memory and the like, and is insufficient for running an intelligent snapshot function. The first camera is a high-end camera, the high-end camera has high performance such as a CPU (central processing unit), a memory and the like, the intelligent capturing function of the first camera can be operated, and meanwhile, the first camera can be accessed to a plurality of paths of videos of the low-end camera for intelligent capturing.
In an embodiment of the present invention, the step S202 may specifically include:
the first camera acquires a video code stream of the second camera with a mapping relation established in advance, wherein the video code stream carries an IP address of the second camera.
Further, the first camera obtains a video code stream of the second camera with a mapping relationship established in advance through a Real Time Streaming Protocol (RTSP) Protocol or a private Protocol. The RTSP protocol is an application layer protocol in the TCP/IP protocol system, and defines how a one-to-many application can effectively transmit multimedia data, including video stream, picture stream, etc., through an IP network. Private protocol: the proprietary protocol refers to some protocols established inside manufacturers, which are used for video stream, picture stream and the like transmitted by cameras, and are not commonly used among camera manufacturers.
Step S204, the first camera analyzes the video code stream to determine whether the video code stream meets a preset condition;
in an embodiment of the present invention, the step S204 may specifically include: the first camera decodes the video code stream to obtain a plurality of images, and the images are input into a pre-trained target neural network model to obtain the probability that the video code stream output by the target neural network model contains a preset behavior or a target object; under the condition that the probability is greater than or equal to a preset threshold value, the first camera determines that the video code stream contains a preset behavior or a target object, and determines that the video code stream meets the preset condition; and under the condition that the probability is smaller than the preset threshold value, the first camera determines that the video code stream does not contain a preset behavior or a target object, and determines that the video code stream does not meet the preset condition.
The target neural network model can be obtained in advance according to deep learning training, wherein the deep learning is a method based on data time-line characteristic learning in machine learning, and machine learning of a human cranial neural structure can be simulated.
Step S206, the first camera carries out image capturing on the video code stream under the condition that the video code stream meets the preset condition;
optionally, the step S206 may specifically include: under the condition that the video code stream contains the preset behavior or the target object, the first camera acquires a target monitoring scene with the preset behavior or the target object from the video code stream; and the first camera carries out one or more times of image capturing on the preset behavior or the target object in the target monitoring scene to obtain one or more target capturing images of the preset behavior or the target object.
And step S208, the first camera sends the generated snapshot image to the second camera.
In the embodiment of the invention, after the first camera captures the image of the video code stream, the first camera generates the captured image according to the identifier of the second camera, wherein the captured image carries the IP address of the second camera; correspondingly, the step S208 may specifically include: and the first camera sends the snapshot image to the second camera by using a real-time streaming protocol (RTSP) or a private protocol according to the IP address of the second camera.
Through the steps S202 to S208, the first camera acquires a video code stream acquired by the second camera at a predetermined time period, wherein the first camera is a camera supporting an image capturing function, and the second camera is a camera not supporting the image capturing function; analyzing the video code stream to determine whether the video code stream meets a preset condition; under the condition that the video code stream meets the preset condition, carrying out image snapshot on the video code stream; the generated snapshot image is sent to the second camera, the problem that in the related technology, due to the fact that the low-end camera cannot complete snapshot, all the low-end cameras need to be replaced by high-end cameras to achieve image snapshot, and therefore cost is high can be solved, the low-end camera transmits video code streams to the high-end camera, the high-end camera assists in completing image snapshot, and image snapshot can be completed without replacing the low-end camera.
In the embodiment of the invention, when the first camera acquires a video code stream pushed when the second camera detects that a target moves in a video, the first camera sends an acquisition instruction for acquiring the service type and the target area of the second camera to the second camera; the first camera receives the service type and the target area of the second camera returned by the second camera according to the acquisition instruction; correspondingly, the step S204 may specifically include: and the first camera analyzes the video code stream in the target area according to the service type of the second camera to determine whether the video code stream meets a preset condition. The method comprises the steps that a service type is configured in advance in a low-end camera (namely, a second camera), a rule box (namely, a target area, an analysis target object or an area with a preset behavior) is drawn in a picture, the high-end camera can send a command to acquire the service type and the rule box of the low-end camera through a network while acquiring a video code stream, and then corresponding snapshot service is carried out. The capture can be implemented only when the illegal parking class meets the illegal parking condition, and the low-end equipment can store the pictures sent back by the high-end camera into the SD card or upload the pictures to the storage server. The type of service may specifically include an violation, person, motor vehicle or non-motor vehicle, etc. For people, the face and the human body are captured during capturing, and the gender, age group, label, clothes and the like can be specifically identified; for the non-motor vehicles, the body of the non-motor vehicle is captured, and the type of the vehicle, the number of people on the vehicle and the like can be specifically identified; for the motor vehicle, the motor vehicle itself can be captured, and the license plate, the color, the brand and the like can be identified. When the high-end camera acquires the video code stream of the low-end camera, a command is sent to acquire the service type of the low-end camera, and then structured analysis of the video is carried out. And after the low-end camera receives the snapshot image, pushing the image to the client or the storage server.
The predetermined behavior in the embodiment of the present invention includes at least one of: abnormal behavior, violation behavior, and parking violation behavior. The abnormal behavior may be an abnormal behavior such as fighting, or an abnormal behavior such as a person crashing and crying, or an abnormal behavior such as a person falling down, and the above is merely an example and does not limit the embodiment of the present invention. The target object may be a person, an object, or the like.
Taking the violation behaviors as an example, the number of times of capturing the violation targets in the video code stream for multiple times may be, but is not limited to, one time, two times, three times, or four times. For example, the number of times the illicit target is captured is three.
In a plurality of snapshot images obtained by taking multiple snapshots of an illegal target in a video code stream, the types of the snapshot images can be the same or different. In this embodiment, the types of the snap-shot images include, but are not limited to: panorama, close-up map, and feature map. The panorama is a monitoring range diagram of a monitoring scene where the illegal parking target is located, the close map is an overall diagram of the illegal parking target, and the feature diagram is a license plate of the illegal parking target or a diagram capable of representing identity information of the illegal parking target.
The capturing sequence among the various types of captured images may be according to the sequence of the panorama, the close-up view and the feature map, may also be according to the sequence of the close-up view, the feature map and the panorama, and may also be other capturing sequences, which are not specifically limited herein. In this embodiment, the snapshot sequence among the various types of evidence images is taken as an example of a panoramic image, a close-up image, and a feature image.
The time interval between the various types of snap shots may be several seconds, several minutes, or ten minutes, and is not particularly limited and may be set according to actual conditions. The time intervals between the various types of evidence graphs may be the same or different, and are not specifically limited herein.
In some scenes with both high-end cameras and low-end cameras, the low-end camera performs intelligent snapshot by using the peripheral high-end camera, so that the problem that the low-end camera cannot perform intelligent snapshot in the scene is solved.
When the periphery of the low-end camera is provided with the high-end camera, the high-end camera pulls the video code stream from the low-end camera, the high-end camera carries out intelligent snapshot, and the captured picture is sent back to the low-end camera.
Fig. 3 is a schematic diagram of video capture according to an embodiment of the present invention, and as shown in fig. 3, a low-end camera sends a code stream to a high-end camera, and the high-end camera sends back a captured picture to the low-end camera, which specifically includes:
the high-end camera pulls the code stream from the low-end camera, which low-end cameras are configured and accessed in the high-end camera in advance, and as long as the mapping relation between the IP addresses of the high-end camera and the low-end cameras is established, the high-end camera can pull the code stream from the corresponding low-end cameras by using the RTSP protocol or the private protocol, for example, the mapping relation shown in table 1 is established.
TABLE 1
Fig. 4 is a flowchart of the intelligent snapshot performed by the high-end camera according to the embodiment of the present invention, and as shown in fig. 4, the flowchart includes:
step S401, a code stream is pulled from a low-end camera;
step S402, decoding the code stream to obtain a picture;
step S403, performing video analysis on the picture, wherein a deep learning method can be adopted to identify a target in the video;
step S404, judging whether a target is identified in the video, if so, executing step S405, otherwise, returning to step S401;
and S405, if the target is identified, capturing the target, and temporarily storing the captured picture and recording the IP address of the low-end camera corresponding to the picture.
And the high-end camera sends the captured picture back to the low-end camera, specifically, the high-end camera detects whether the picture is generated in the intelligent capturing process, and if the picture is generated, the picture is sent to the low-end camera by using an RTSP (real time streaming protocol) or a private protocol according to the IP address corresponding to the picture.
Example 2
According to another embodiment of the present invention, there is also provided an image-capturing processing apparatus applied to a first camera indicating an image capturing function, and fig. 5 is a block diagram of the image-capturing processing apparatus according to the embodiment of the present invention, as shown in fig. 5, including:
the acquiring module 52 is configured to acquire a video code stream pushed when a second camera detects that a target moves in a video, where the second camera is a camera that does not support an image capturing function;
an analysis module 54, configured to analyze the video code stream to determine whether the video code stream meets a predetermined condition;
the image capturing module 56 is configured to capture an image of the video code stream when the video code stream meets the predetermined condition;
a sending module 58, configured to send the generated snapshot image to the second camera.
Optionally, the analysis module 54 comprises:
the input submodule is used for decoding the video code stream to obtain a plurality of images, inputting the images into a pre-trained target neural network model, and obtaining the probability that the video code stream output by the target neural network model contains a preset behavior or a target object;
the first determining submodule is used for determining that the video code stream contains a preset behavior or a target object and determining that the video code stream meets the preset condition under the condition that the probability is greater than or equal to a preset threshold value;
and the second determining submodule is used for determining that the video code stream does not contain a preset behavior or a target object and determining that the video code stream does not meet the preset condition under the condition that the probability is smaller than the preset threshold value.
Optionally, the image capturing module 56 includes:
the obtaining sub-module is used for obtaining a target monitoring scene with the preset behavior or the target object from the video code stream under the condition that the video code stream contains the preset behavior or the target object;
and the image capturing sub-module is used for capturing one or more images of the preset behavior or the target object in the target monitoring scene to obtain one or more target capturing images of the preset behavior or the target object.
Optionally, the apparatus further comprises: the receiving module is used for sending an acquisition instruction for acquiring the service type and the target area of the second camera to the second camera; receiving the service type and the target area of the second camera returned by the second camera according to the acquisition instruction;
the analysis module is further configured to analyze the video code stream in the target area according to the service type of the second camera to determine whether the video code stream meets a predetermined condition.
Optionally, the obtaining module 52 is further configured to
And acquiring a video code stream pushed by the second camera with a mapping relation established in advance when the second camera detects that the target moves in the video through a real-time streaming protocol (RTSP) or a private protocol, wherein the video code stream carries the IP address of the second camera.
Optionally, the apparatus further comprises:
the generating module is used for generating the snapshot image according to the identifier of the second camera, wherein the snapshot image carries the IP address of the second camera;
the sending module is further configured to send the captured image to the second camera according to the IP address of the second camera by using a real-time streaming protocol RTSP protocol or a private protocol.
Optionally, the predetermined behavior comprises at least one of: abnormal behavior, violation behavior, and parking violation behavior.
It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
Example 3
Embodiments of the present invention also provide a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to perform the steps of any of the above method embodiments when executed.
Alternatively, in the present embodiment, the storage medium may be configured to store a computer program for executing the steps of:
s1, acquiring a video code stream pushed when a second camera detects that a target moves in a video, wherein the second camera is a camera which does not support an image capturing function;
s2, analyzing the video code stream to determine whether the video code stream meets the predetermined condition;
s3, when the video code stream meets the preset condition, capturing the video code stream;
and S4, sending the generated snapshot image to the second camera.
Optionally, in this embodiment, the storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Example 4
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
s1, acquiring a video code stream pushed when a second camera detects that a target moves in a video, wherein the second camera is a camera which does not support an image capturing function;
s2, analyzing the video code stream to determine whether the video code stream meets the predetermined condition;
s3, when the video code stream meets the preset condition, capturing the video code stream;
and S4, sending the generated snapshot image to the second camera.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and this embodiment is not described herein again.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An image snapshot processing method, comprising:
a first camera acquires a video code stream pushed when a second camera detects that a target moves in a video, wherein the first camera is a camera supporting an image capturing function, and the second camera is a camera not supporting the image capturing function;
the first camera analyzes the video code stream to determine whether the video code stream meets a preset condition;
under the condition that the video code stream meets the preset condition, the first camera carries out image snapshot on the video code stream;
and the first camera sends the generated snapshot image to the second camera.
2. The method of claim 1, wherein analyzing the video codestream by the first camera to determine whether the video codestream satisfies a predetermined condition comprises:
the first camera decodes the video code stream to obtain a plurality of images, and the images are input into a pre-trained target neural network model to obtain the probability that the video code stream output by the target neural network model contains a preset behavior or a target object;
under the condition that the probability is greater than or equal to a preset threshold value, the first camera determines that the video code stream contains a preset behavior or a target object, and determines that the video code stream meets the preset condition;
and under the condition that the probability is smaller than the preset threshold value, the first camera determines that the video code stream does not contain a preset behavior or a target object, and determines that the video code stream does not meet the preset condition.
3. The method of claim 2, wherein, in a case that an analysis result satisfies a predetermined condition, the capturing, by the first camera, the image of the video code stream includes:
under the condition that the video code stream contains the preset behavior or the target object, the first camera acquires a target monitoring scene with the preset behavior or the target object from the video code stream;
and the first camera carries out one or more times of image capturing on the preset behavior or the target object in the target monitoring scene to obtain one or more target capturing images of the preset behavior or the target object.
4. The method of claim 1,
when the first camera acquires a video code stream pushed by the second camera when the second camera detects that the target moves in the video, the method further comprises the following steps: the first camera sends an acquisition instruction for acquiring the service type and the target area of the second camera to the second camera;
the first camera receives the service type and the target area of the second camera returned by the second camera according to the acquisition instruction;
the first camera analyzing the video code stream to determine whether the video code stream meets a predetermined condition includes:
and the first camera analyzes the video code stream in the target area according to the service type of the second camera to determine whether the video code stream meets a preset condition.
5. The method of claim 1, wherein the acquiring, by the first camera, the video code stream pushed by the second camera when the second camera detects that the target moves in the video comprises:
the first camera acquires a video code stream pushed when the second camera which establishes a mapping relation in advance detects that a target moves in a video through a real-time streaming protocol (RTSP) or a private protocol, wherein the video code stream carries an IP address of the second camera.
6. The method of claim 5,
after the first camera captures the images of the video code stream, the method further comprises:
the first camera generates the snapshot image according to the identification of the second camera, wherein the snapshot image carries the IP address of the second camera;
the first camera sending the generated snapshot image to the second camera includes:
and the first camera sends the snapshot image to the second camera by using a real-time streaming protocol (RTSP) or a private protocol according to the IP address of the second camera.
7. A method according to claim 2 or 3, characterized in that the predetermined behavior comprises at least one of: abnormal behavior, violation behavior, and parking violation behavior.
8. An image capture processing apparatus applied to a first camera indicating an image capture function, comprising:
the acquisition module is used for acquiring a video code stream pushed when a second camera detects that a target moves in a video, wherein the second camera is a camera which does not support an image capturing function;
the analysis module is used for analyzing the video code stream to determine whether the video code stream meets a preset condition;
the image snapshot module is used for carrying out image snapshot on the video code stream under the condition that the video code stream meets the preset condition;
and the sending module is used for sending the generated snapshot image to the second camera.
9. A computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to carry out the method of any one of claims 1 to 7 when executed.
10. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and wherein the processor is arranged to execute the computer program to perform the method of any of claims 1 to 7.
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| CN113596395A (en) * | 2021-07-26 | 2021-11-02 | 浙江大华技术股份有限公司 | Image acquisition method and monitoring equipment |
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