Image processing method and device, system, equipment and storage medium

Abstract

The invention relates to the technical field of image recognition of video streams, and discloses an image processing method, which comprises the following steps: acquiring an AI video stream generated by camera equipment under the condition that the camera equipment is started; extracting information associated with the image processing demand from the AI video stream; and sending the information associated with the image processing demand to the camera device, and processing the non-AI video stream by the camera device according to the image processing demand and the information associated with the image processing demand. In the method, the process of identifying the image in the AI video stream is completed by host equipment connected with camera equipment. The computing power of the host equipment is much higher than that of the camera equipment when processing the image, so that the computing power of the AI function of the camera equipment can be improved. The invention further discloses an image processing device and system, equipment and a storage medium.

Description

Technical Field

[0001] The present application relates to the technical field of image recognition of video streams, and in particular to an image processing method and apparatus, system, device, and storage medium. Background Art

[0002] At present, cameras with AI (artificial intelligence) functions can use built-in AI chips to perform image recognition on the captured videos to achieve corresponding AI functions. For example, the camera can achieve AI functions such as color enhancement of images in videos and portrait tracking in videos.

[0003] However, when the image recognition process of the video is more complex or cumbersome, the computing power of the artificial intelligence chip built into the camera is difficult to meet the computing power requirements of the image recognition process. The relevant technology adopts the method of configuring an additional NPU (Neural Processing Unit) chip in the camera. Although the additional NPU chip configured in the camera can appropriately improve the AI ​​computing power of the camera, the additional configuration of the NPU chip will increase the cost of the camera. Summary of the invention

[0004] The embodiments of the present disclosure provide an image processing method and apparatus, system, device, and storage medium, which can improve the computing power of the AI ​​function of a camera device without increasing the cost of the camera device. In a first aspect, the embodiments of the present disclosure provide an image processing method, which is applied to a host device; wherein the host device is connected to a camera device, and the camera device transmits multiple video streams to the host device, and the multiple video streams include one AI video stream and at least one non-AI video stream; the method includes:

[0005] When the camera device is turned on, obtaining an AI video stream generated by the camera device;

[0006] extracting information associated with image processing requirements from the AI ​​video stream;

[0007] The information associated with the image processing requirement is sent to the camera device so that the camera device processes the non-AI video stream according to the image processing requirement and the information associated with the image processing requirement.

[0008] In a second aspect, an embodiment of the present disclosure provides an image processing method, which is applied to a camera device; wherein the camera device is connected to a host device, and the camera device transmits multiple video streams to the host device, and the multiple video streams include one AI video stream and at least one non-AI video stream; the method includes:

[0009] receiving information associated with image processing requirements sent by a host device;

[0010] Processing non-AI video streams based on image processing requirements and information associated with the image processing requirements;

[0011] Among them, the information associated with the image processing requirements is extracted by the host device from the AI ​​video stream generated by the camera device.

[0012] In a third aspect, an embodiment of the present disclosure provides an image processing device, which is integrated in a host device; wherein the host device is connected to a camera device, and the camera device transmits multiple video streams to the host device, wherein the multiple video streams include one AI video stream and at least one non-AI video stream; the device includes:

[0013] A video transceiver module, used to obtain the AI ​​video stream generated by the camera device when the camera device is turned on;

[0014] An information extraction module, used to extract information associated with image processing requirements from the AI ​​video stream;

[0015] An information sending module is used to send the information associated with the image processing requirements to the camera device, so that the camera device processes the non-AI video stream according to the image processing requirements and the information associated with the image processing requirements.

[0016] In a fourth aspect, an embodiment of the present disclosure provides an image processing device, which is integrated in a camera device; wherein the camera device is connected to a host device, and the camera device transmits multiple video streams to the host device, and the multiple video streams include one AI video stream and at least one non-AI video stream; the camera device can be connected to the host device, and the camera device can transmit multiple video streams to the host device based on the UVC protocol, and the multiple video streams include one AI video stream and at least one non-AI video stream; the device includes:

[0017] An information receiving module, used to receive information associated with image processing requirements sent by a host device; wherein the information associated with the image processing requirements is extracted by the host device from an AI video stream generated by a camera device;

[0018] A video processing module is used to process non-AI video streams based on image processing requirements and information associated with the image processing requirements.

[0019] In a fifth aspect, an embodiment of the present disclosure provides an image processing system, including: a host device and a camera device; the host device and the camera device, and the camera device transmits multiple video streams to the host device, and the multiple video streams include one AI video stream and at least one non-AI video stream; wherein:

[0020] A host device, used to implement the image processing method described in the first aspect;

[0021] A camera device, used to implement the image processing method described in the second aspect above.

[0022] In a sixth aspect, an embodiment of the present disclosure provides an electronic device, comprising a processor and a memory storing program instructions, wherein the processor is configured to execute the image processing method described in the first aspect when running the program instructions; or the processor is configured to execute the image processing method described in the second aspect when running the program instructions.

[0023] In a seventh aspect, an embodiment of the present disclosure provides a storage medium storing program instructions, wherein when the program instructions are run, the image processing method described in the first aspect is executed; or, the image processing method described in the second aspect is executed.

[0024] The image processing method, apparatus, system, device, and storage medium provided by the embodiments of the present disclosure can achieve the following technical effects:

[0025] During the operation of the camera device, multiple video streams can be transmitted to the connected host device, including one AI video stream for performing AI calculations and at least one non-AI video stream for displaying to the user. In this way, the host device can obtain the AI ​​video stream from the camera device for AI calculation. During the AI ​​calculation process, information associated with the image processing requirements can be extracted from the AI ​​video stream, that is, information associated with the AI ​​function that the camera device needs to implement can be extracted, and the information associated with the image processing requirements can be sent to the camera device, so that the host device implements the image processing process of the AI ​​video stream. Subsequently, the camera device uses the information associated with the image processing requirements sent by the host device to process the non-AI video stream, that is, adjust the non-AI video stream for display to the user, and send the processed or adjusted non-AI video stream to the host device, so that the host device displays the AI-processed video. In the embodiment of the present disclosure, the process of extracting information associated with the AI ​​function based on the AI ​​video stream, that is, the process of identifying the image in the AI ​​video stream, is that the host device obtains the AI ​​video stream from the camera device and performs image recognition, thereby completing the AI ​​recognition operation of the image in the AI ​​video stream. Since the overall computing power of the host device is much higher than the computing power of the built-in artificial intelligence chip of the camera device when processing images, the AI ​​computing power of the camera device can be improved by using the host device to perform AI recognition on the AI ​​video stream images generated by the camera device. In addition, when the camera device is connected to the host device and the host device is used to perform AI recognition on the AI ​​video stream images generated by the camera device, the camera device does not need to be additionally configured with a chip for AI calculation. Therefore, the computing power of the AI ​​function of the camera device can be improved without increasing the cost of the camera device.

[0026] The above general description and the following description are exemplary and explanatory only and are not intended to limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] One or more embodiments are exemplarily described by corresponding drawings, which do not limit the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements, and the drawings do not constitute a scale limitation, and wherein:

[0028] Figure 1 is a schematic diagram of a traditional image processing system;

[0029] Figure 2 is a schematic diagram of another traditional image processing system;

[0030] Figure 3 is a schematic diagram of an image processing system provided by an embodiment of the present disclosure;

[0031] Figure 4is a schematic diagram of another image processing system provided by an embodiment of the present disclosure;

[0032] Figure 5 is a flow chart of an image processing method provided by an embodiment of the present disclosure;

[0033] Figure 6 is a schematic diagram of an image processing device provided by an embodiment of the present disclosure;

[0034] Figure 7 is a schematic diagram of another image processing device provided by an embodiment of the present disclosure;

[0035] Figure 8 It is a schematic diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0036] In order to be able to understand the features and technical contents of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings. The attached drawings are for reference only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the convenience of explanation, a full understanding of the disclosed embodiments is provided through multiple details. However, one or more embodiments can still be implemented without these details. In other cases, to simplify the drawings, well-known structures and devices can be simplified for display.

[0037] The terms "first", "second", etc. in the specification and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged where appropriate, so that the embodiments of the embodiments of the present disclosure described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions.

[0038] Unless otherwise specified, the term "plurality" means two or more and the term "multiple" means two or more.

[0039] In the embodiment of the present disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B indicates: A or B.

[0040] The term "and / or" is a description of the association relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B.

[0041] The term "correspondence" may refer to an association relationship or a binding relationship. The correspondence between A and B means that there is an association relationship or a binding relationship between A and B.

[0042] At present, cameras with AI (artificial intelligence) functions can use built-in AI chips to perform image recognition on captured videos to achieve corresponding AI functions. For example, the camera can achieve AI functions such as enhancing the color of an object in an image and tracking people in a video.

[0043] Combination Figure 1 As shown, the conventional image processing system includes a camera 11 and a display device 12. Among them:

[0044] The camera 11 has a built-in AI chip, which can recognize the video image captured by the camera 11 according to the AI ​​function indicated by the user, that is, perform AI calculation of the corresponding function, and transmit the recognized video image to the display device 12 for display. Thus, according to user needs, the AI ​​processing function of the video image is realized.

[0045] However, when the image recognition process of the video is relatively complex or cumbersome, the computing power of the AI ​​chip built into the camera 11 is difficult to meet the computing power requirements of the image recognition process. Figure 2 As shown, another conventional image processing system includes a camera 21 and a display device 22. Among them:

[0046] In addition to the built-in AI chip, the camera 21 is also equipped with multiple NPU chips. The NPU chip can recognize the video image captured by the camera 21 according to the AI ​​function indicated by the user, that is, perform AI calculations of the corresponding functions, and transmit the recognized video image to the display device 22 for display. Although the additional NPU chip configured in the camera 21 can appropriately improve the AI ​​computing power of the camera, the additional configuration of the NPU chip will increase the cost of the camera.

[0047] In view of this, the embodiments of the present disclosure provide an image processing method and apparatus, system, device, and storage medium, which can improve the computing power of the AI ​​function of a camera device without increasing the cost of the camera device.

[0048] In the disclosed embodiment, the camera device may be a USB (Universal Serial Bus) device with a camera function, or a USB-HID (Human Interface Device) device.

[0049] In the disclosed embodiment, the host device may be a computer with a video image processing function. Specifically, the host device may be a network computer (e.g., a server that can provide services to the outside), or a PC (Personal Computer), such as a desktop computer, a laptop computer, a small laptop computer, a tablet computer, and an ultrabook.

[0050] In the disclosed embodiment, the UVC protocol, namely the USB video class, is a protocol standard defined for USB video capture devices.

[0051] Combination Figure 3 As shown, an embodiment of the present disclosure provides an image processing system, including a camera device 31 and a host device 32. The host device 32 can be connected to the camera device 31. The camera device 31 can transmit multiple video streams to the host device 32 based on the UVC protocol (UVC protocol version is 1.5 and above).

[0052] Optionally, the multiple video streams include one AI video stream and at least one non-AI video stream. For example, the multiple video streams include one AI video stream and two non-AI video streams, and the two non-AI video streams are video stream 1 and video stream 2. In addition, the AI ​​video stream can be provided to the host device 32 for AI recognition, and the AI ​​video stream can be obtained by encoding the full amount of video data acquired by the camera device 31 according to the AI ​​function that the user needs to implement. For example, the AI ​​function that the user needs to implement is to perform color enhancement on the image of a specific area in the video stream image, and the AI ​​video stream encoded by the camera device 31 may only include the image of the specific area in the video stream image. For another example, the AI ​​function that the user needs to implement is to track the portrait in the video stream image, and the AI ​​video stream encoded by the camera device 31 may only include the image of the portrait in the video stream image.

[0053] In this way, since the AI ​​video stream is related to the AI ​​function that the user needs to implement, that is, it is related to the user's image processing requirements, the data in the AI ​​video stream only needs to meet the image processing requirements. When the AI ​​function that the user needs to implement does not require the use of the full amount of video data for AI calculation, the camera device 31 can transmit part of the video data to the camera device. Thereby, the speed at which the camera device 31 transmits the AI ​​video stream to the host device 32 can be improved, thereby improving the efficiency of the image processing system in performing image recognition on the video stream image.

[0054] Optionally, the host device 32 includes a controller 321 and a display device 322. The controller 321 can perform image recognition on the AI ​​video stream and control the host device 32 to feed back the image recognition result to the camera device 31. The display device 322 is integrated in the host device 32 and is used to display the video stream processed by AI.

[0055] Optionally, combined Figure 4 As shown, the display device 322 is not limited to being integrated inside the host device 32, but can also be installed and connected to the host device 32, including but not limited to physical connection, electrical connection or signal transmission connection, etc. The host device 32 can transmit the AI-processed video stream to the display device 322 for display.

[0056] based on Figure 3 or Figure 4 The image processing system shown in the figure, the embodiment of the present disclosure provides an image processing method, and the embodiment of the present disclosure is described from the perspective of the interaction between the camera device and the host device. Figure 5 As shown, the method provided by the embodiment of the present disclosure includes:

[0057] S51: When the camera device is connected to the host device, the host device enumerates device information of the camera device.

[0058] S52, the host device obtains device information from the camera device.

[0059] S53: The host device identifies the camera device according to the device information of the camera device.

[0060] S54, the host device starts the detection service and periodically detects whether the camera device is turned on by the preset application.

[0061] S55, when the camera device is turned on, the host device sends a request to the camera device to obtain the AI ​​video stream.

[0062] S56, the camera device transmits the AI ​​video stream to the host device in response to the request for obtaining the AI ​​video stream.

[0063] S57, the host device extracts information associated with the image processing requirements from the AI ​​video stream.

[0064] S58, the host device sends information associated with the image processing requirement to the camera device.

[0065] S59, the camera device processes the non-AI video stream according to the image processing requirements and information associated with the image processing requirements.

[0066] S60: The camera device transmits the processed non-AI video stream to the host device.

[0067] S61, the host device displays the processed non-AI video stream.

[0068] By adopting the image processing method provided by the embodiment of the present disclosure, during the operation of the camera device, multiple video streams can be transmitted to the connected host device based on the UVC protocol, and the multiple video streams include an AI video stream for performing AI calculations and at least one non-AI video stream for display to the user. In this way, the host device can obtain the AI ​​video stream from the camera device for AI calculations. During the AI ​​calculation process, information associated with the image processing requirements can be extracted from the AI ​​video stream, that is, information associated with the AI ​​function that the camera device needs to implement can be extracted, and the information associated with the image processing requirements can be sent to the camera device, so that the host device implements the image processing process of the AI ​​video stream. Subsequently, the camera device uses the information associated with the image processing requirements sent by the host device to process the non-AI video stream, that is, adjust the non-AI video stream for display to the user, and send the processed or adjusted non-AI video stream to the host device, so that the host device displays the AI-processed video. In the disclosed embodiment, the process of extracting information associated with the AI ​​function based on the AI ​​video stream, that is, the process of recognizing the image in the AI ​​video stream, is that the host device obtains the AI ​​video stream from the camera device and performs image recognition, thereby completing the AI ​​recognition operation of the image in the AI ​​video stream. Since the overall computing power of the host device is much higher than the computing power of the artificial intelligence chip built into the camera device when processing images, the AI ​​computing power of the camera device can be improved by using the host device to perform AI recognition on the AI ​​video stream images generated by the camera device. In addition, when the camera device is connected to the host device and the host device is used to perform AI recognition on the AI ​​video stream images generated by the camera device, the camera device does not need to be additionally configured with a chip for performing AI calculations. Thereby, the computing power of the AI ​​function of the camera device can be improved without increasing the cost of the camera device.

[0069] Optionally, in the above steps S51 to S53, the host device enumerates the device information of the camera device in order to read the device information from the camera device. The device information of the camera device may be a device descriptor of the camera device. The host device may obtain the configuration of the camera device through the device descriptor of the camera device. In the above step S51, the specific process of the host device enumerating the camera device may be as follows:

[0070] When the camera device is connected to the USB interface of the host device, the USB interface of the host device will change its level. The host device can identify the hot plug of the camera device based on the level change of the USB interface. When the host device detects that the camera device has been connected by identifying the hot plug of the camera device, the host device will send a request to the camera device to obtain device information to read the device information of the camera device, and then identify the camera device based on the device information. In addition, the user can enable the camera device to support multi-channel video stream transmission by configuring the device descriptor of the camera device. Moreover, after the device descriptor of the camera device is configured by the user, when the host device identifies the camera device based on the device information of the camera device, it can be identified that the camera device corresponds to multiple virtual devices, and the multiple virtual devices correspond to multiple video streams respectively. For example, the camera device may be configured as device 1, device 2 and device 3, device 1 corresponds to video stream 1, device 2 corresponds to video stream 2, and device 3 corresponds to AI video stream. Subsequently, when the host device obtains the AI ​​video stream from the camera device, it can be obtained from the camera device through device 3.

[0071] Optionally, in the above step S54, a detection service is pre-configured in the host device, and the detection service is used to detect whether the camera device is called by a preset application. When the user uses the preset application on the host device to capture video, the camera device will be called and turned on to enable the camera device to collect video stream data. After the video stream data is uploaded to the host device, it is displayed to the user through the preset application. In the disclosed embodiment, the preset application can be a video conferencing software or a photo taking software on the host device, for example, it can be software such as Tencent Conference and Mailing Conference. In this embodiment, since the camera device will not always be in a state of being turned on by the application, the detection service periodically detects the camera device, which can reduce the situation where the detection service always occupies the host device, thereby saving the memory resources of the host device. On the other hand, the detection service periodically detects the device, and can also timely monitor whether the camera device is turned on, so that when the camera device is turned on, the video stream data of the camera device can be processed by AI in a timely manner, so as to improve the timeliness or reliability of the host device's AI processing of the video image.

[0072] Optionally, in the above step S57, during the process of the host device performing image recognition on the AI ​​video stream, the information extracted by the host device from the AI ​​video stream is related to the image processing requirements. For example, when the image processing requirement is portrait tracking, it is necessary to extract the pixel coordinate information corresponding to the portrait from the AI ​​video stream image. For another example, when the image processing requirement is to enlarge and display a specific area in a video image, it is necessary to extract the pixel coordinate information of the specific area from the AI ​​video stream image. It should be noted that the pixel coordinates represent the position of the pixels related to the image processing requirements in the AI ​​video stream image.

[0073] Optionally, in the above step S59, the camera device processes the non-AI video stream according to the image processing requirements and the information associated with the image processing requirements, including: determining the processing strategy of the image in the non-AI video stream according to the image processing requirements. Based on the information associated with the image processing requirements and the processing strategy of the image in the non-AI video stream, the image in the non-AI video stream is processed.

[0074] Exemplarily, assuming that the user's image processing requirement is to perform color enhancement on the image in the target area, the information associated with the image processing requirement extracted by the host device from the AI ​​video stream is the pixel coordinate information in the target area. After the pixel coordinate information in the target area is sent by the host device to the camera device, the camera device determines that the image processing strategy in the non-AI video stream is color enhancement based on the image processing requirement. In addition, the camera device can determine the pixel coordinates that need to be color enhanced from the image of the non-AI video stream based on the pixel coordinate information in the target area. Based on the pixel coordinates that need to be color enhanced in the non-AI video stream image, the image of the corresponding pixel point is color enhanced.

[0075] Optionally, in the disclosed embodiment, in order to facilitate the host device to perform AI calculations corresponding to image processing requirements based on the AI ​​video stream, the camera device can convert the AI ​​video stream into a YUV format, where Y represents brightness, that is, grayscale value, and U and V represent chroma, which is used to describe the color and saturation of the video stream image and to specify the color of the video stream image pixel. In this way, since the brightness parameter and chroma parameter are separately represented in the AI ​​video stream in YUV format, the efficiency of the host device performing AI calculations on the AI ​​video stream can be improved.

[0076] Combination Figure 6 As shown, the embodiment of the present disclosure provides an image processing device, which is integrated on the host device of the above embodiment. The image processing device includes a video transceiver module 601, an information extraction module 602 and an information sending module 603. Among them:

[0077] The video transceiver module 601 is used to obtain the AI ​​video stream generated by the camera device when the camera device is turned on.

[0078] The information extraction module 602 is used to extract information associated with image processing requirements from the AI ​​video stream.

[0079] The information sending module 603 is used to send information associated with the image processing requirements to the camera device, so that the camera device processes the non-AI video stream according to the image processing requirements and the information associated with the image processing requirements.

[0080] Optionally, the video transceiver model 601 is also used to: send a request to obtain an AI video stream to the camera device, so that the camera device responds to the request to obtain the AI ​​video stream and transmits the AI ​​video stream to the host device; and receive the AI ​​video stream transmitted by the camera device.

[0081] Optionally, the video transceiver model 601 is further used to: send a request to obtain a non-AI video stream to the camera device, so that the camera device responds to the request to obtain a non-AI video stream and transmits a processed non-AI video stream to the host device. Receive the processed non-AI video stream transmitted by the camera device, and display the processed non-AI video stream.

[0082] Optionally, the image processing apparatus provided by the embodiment of the present disclosure further includes a device detection module, which is used to start a detection service; and periodically detect whether the camera device is turned on by a preset application program through the detection service.

[0083] The image processing device provided in the embodiment of the present disclosure can execute the actions of the host device in the aforementioned embodiment. Its implementation principle and technical effects are similar and will not be described in detail here.

[0084] Combination Figure 7 As shown, the embodiment of the present disclosure further provides an image processing device, which is integrated on the above-mentioned camera device. The image processing device includes an information receiving module 701 and a video processing module 702.

[0085] The information receiving module 701 is used to receive information associated with the image processing requirement sent by the host device; wherein the information associated with the image processing requirement is extracted by the host device from the AI ​​video stream generated by the camera device;

[0086] The video processing module 702 is used to process the non-AI video stream according to the image processing requirements and information associated with the image processing requirements.

[0087] Among them, the information associated with the image processing requirements is extracted by the host device from the AI ​​video stream generated by the camera device.

[0088] Optionally, the video processing module 702 is further used to: determine a processing strategy for images in the non-AI video stream according to image processing requirements. Based on the information associated with the image processing requirements and the processing strategy for images in the non-AI video stream, process the images in the non-AI video stream.

[0089] Optionally, the image processing apparatus provided in the embodiment of the present disclosure further includes an image transmission module 703, which is used to receive a request for obtaining an AI video stream sent by a host device, and transmit the AI ​​video stream to the host device in response to the request for obtaining the AI ​​video stream.

[0090] Optionally, the image transmission module 703 is further configured to: receive a request for obtaining a non-AI video stream sent by a host device, and in response to the request for obtaining a non-AI video stream, transmit the processed non-AI video stream to the host device.

[0091] The image processing device provided in the embodiment of the present disclosure can execute the actions of the camera device in the aforementioned embodiment. Its implementation principle and technical effects are similar and will not be repeated here.

[0092] Combination Figure 8 As shown, an embodiment of the present disclosure provides an electronic device 800, including a processor 100 and a memory 101. Optionally, the device may also include a communication interface 102 and a bus 103. The processor 100, the communication interface 102, and the memory 101 may communicate with each other through the bus 103. The communication interface 102 may be used for information transmission. The processor 100 may call the logic instructions in the memory 101 to execute the image processing method of the above embodiment.

[0093] In addition, the logic instructions in the memory 101 described above may be implemented in the form of software functional units and when sold or used as independent products, may be stored in a computer-readable storage medium.

[0094] The memory 101 is a computer-readable storage medium that can be used to store software programs and computer executable programs, such as program instructions / modules corresponding to the method in the embodiment of the present disclosure. The processor 100 executes the function application and data processing by running the program instructions / modules stored in the memory 101, that is, implements the image processing method in the above embodiment.

[0095] The memory 101 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the memory 101 may include a high-speed random access memory and may also include a non-volatile memory.

[0096] An embodiment of the present disclosure provides a storage medium storing computer executable instructions, wherein the computer executable instructions are configured to execute the above-mentioned image processing method.

[0097] The above-mentioned storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0098] The technical solution of the embodiment of the present disclosure can be embodied in the form of a software product, which is stored in a storage medium and includes one or more instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiment of the present disclosure. The aforementioned storage medium may be a non-transient storage medium, including: 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, and other media that can store program codes, or a transient storage medium.

[0099] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent only possible changes. Unless explicitly required, separate components and functions are optional, and the order of operation may vary. The parts and features of some embodiments may be included in or replace the parts and features of other embodiments. Moreover, the words used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and the claims, unless the context clearly indicates, the singular forms of "a", "an" and "the" are intended to include plural forms as well. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of listings containing one or more associated ones. In addition, when used in the present application, the term "comprise" and its variants "comprises" and / or comprising refer to the presence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof. In the absence of further restrictions, the elements defined by the sentence "comprising a ..." do not exclude the presence of other identical elements in the process, method or device comprising the elements. In this article, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the various embodiments may refer to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can refer to the description of the method part.

[0100] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The technicians may use different methods for each specific application to implement the described functions, but such implementations should not be considered to exceed the scope of the embodiments of the present disclosure. The technicians may clearly understand that, for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above may refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0101] In the embodiments disclosed herein, the disclosed methods and products (including but not limited to devices, equipment, etc.) can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units can be only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to implement this embodiment. In addition, each functional unit in the embodiment of the present disclosure may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit.

[0102] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. An image processing method, characterized in that: Applied to a host device; wherein the host device is connected to a camera device, and the camera device transmits multiple video streams to the host device, wherein the multiple video streams include one AI video stream and at least one non-AI video stream; the method includes: When the camera device is turned on, obtaining an AI video stream generated by the camera device; extracting information associated with image processing requirements from the AI ​​video stream; The information associated with the image processing requirement is sent to the camera device so that the camera device processes the non-AI video stream according to the image processing requirement and the information associated with the image processing requirement.

2. The method according to claim 1, characterized in that Obtaining the AI ​​video stream generated by the camera device, including: Sending a request for obtaining an AI video stream to the camera device, so that the camera device responds to the request for obtaining the AI ​​video stream and transmits the AI ​​video stream to the host device; Receive the AI ​​video stream transmitted by the camera device.

3. The method according to claim 1 or 2, characterized in that: The method further comprises: After determining that the camera device successfully processes the non-AI video stream, sending a request to the camera device to obtain the non-AI video stream, so that the camera device responds to the request to obtain the non-AI video stream and transmits the processed non-AI video stream to the host device; Receive the processed non-AI video stream transmitted by the camera device, and display the processed non-AI video stream.

4. The method according to claim 1 or 2, characterized in that: Before the camera device is turned on, the method further includes: Start testing services; The detection service periodically detects whether the camera device is turned on by a preset application.

5. An image processing method, characterized in that: Applied to a camera device; wherein the camera device is connected to a host device, and the camera device transmits multiple video streams to the host device, wherein the multiple video streams include one AI video stream and at least one non-AI video stream; the method includes: receiving information associated with image processing requirements sent by the host device; Processing the non-AI video stream according to the image processing requirement and the information associated with the image processing requirement; The information associated with the image processing requirements is extracted by the host device from the AI ​​video stream generated by the camera device.

6. The method according to claim 5, characterized in that Processing a non-AI video stream according to the image processing requirement and the information associated with the image processing requirement, including: Determine a processing strategy for images in a non-AI video stream according to the image processing requirements; Based on the information associated with the image processing requirements and the processing strategy of the images in the non-AI video stream, the images in the non-AI video stream are processed.

7. The method according to claim 5 or 6, characterized in that: Before receiving the information associated with the image processing requirement sent by the host device, the method further includes: Receiving a request for obtaining an AI video stream sent by the host device; In response to the request to obtain the AI ​​video stream, the AI ​​video stream is transmitted to the host device.

8. The method according to claim 5 or 6, characterized in that: After processing the non-AI video stream according to the image processing requirement and the information associated with the image processing requirement, the method further includes: Receiving a request for obtaining a non-AI video stream sent by the host device; In response to the request to obtain the non-AI video stream, the processed non-AI video stream is transmitted to the host device.

9. An image processing device, characterized in that: Integrated in a host device; wherein the host device is connected to a camera device, and the camera device transmits multiple video streams to the host device, wherein the multiple video streams include one AI video stream and at least one non-AI video stream; the device includes: A video transceiver module, used to obtain the AI ​​video stream generated by the camera device when the camera device is turned on; An information extraction module, used to extract information associated with image processing requirements from the AI ​​video stream; An information sending module is used to send the information associated with the image processing requirements to the camera device, so that the camera device processes the non-AI video stream according to the image processing requirements and the information associated with the image processing requirements.

10. An image processing device, characterized in that: Integrated in a camera device; wherein the camera device is connected to a host device, and the camera device transmits multiple video streams to the host device, wherein the multiple video streams include one AI video stream and at least one non-AI video stream; the device includes: An information receiving module, configured to receive information associated with image processing requirements sent by the host device; wherein the information associated with image processing requirements is extracted by the host device from the AI ​​video stream generated by the camera device; The video processing module is used to process the non-AI video stream according to the image processing requirements and the information associated with the image processing requirements.

11. An image processing system, characterized in that: include: A host device and a camera device; the host device is connected to the camera device, and the camera device transmits multiple video streams to the host device, wherein the multiple video streams include one AI video stream and at least one non-AI video stream; wherein: The host device is used to implement the image processing method according to any one of claims 1 to 4; The camera device is used to implement the image processing method according to any one of claims 5 to 8.

12. An electronic device comprising a processor and a memory storing program instructions, characterized in that: The processor is configured to execute the image processing method according to any one of claims 1 to 8 when running the program instructions.

13. A storage medium storing program instructions, characterized in that: When the program instructions are executed, the image processing method according to any one of claims 1 to 8 is executed.

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