Image data processing device and processing method thereof, and computer readable storage medium

Abstract

The present application relates to the field of data processing technology, and discloses an image data processing device and a processing method thereof, and a computer-readable storage medium. The method comprises: obtaining image data sent by an image acquisition device; determining the image type of the image data; if the image type of the image data is a preset first image type, compressing the image data; and storing the compressed image data. In the above manner, the processing efficiency of image data can be improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to an image data processing device and a processing method thereof, and a computer-readable storage medium. Background Art

[0002] Data is usually stored in storage devices. Due to the limited capacity of storage devices, it is often necessary to clean up the data in a certain period of time. In order to keep the data in the storage device for a longer time, the data stored in the storage device is usually compressed to reduce the space occupied by the data.

[0003] The related art mainly requires secondary processing of historical data in the storage device and then saves it as new data, which reduces the data processing efficiency. Moreover, the event detection results of historical data are only used as the basis for the order in which the historical data is overwritten, which does not extend the storage time of historical data and does not improve the utilization rate of the storage device. Summary of the invention

[0004] The main technical problem solved by the present application is to provide an image data processing device and a processing method thereof, and a computer-readable storage medium, which can improve the processing efficiency of image data.

[0005] In order to solve the above problems, a technical solution adopted by the present application is to provide an image data processing method, which includes: acquiring image data sent by an image acquisition device; determining the image type of the image data; if the image type of the image data is a preset first image type, compressing the image data; and storing the compressed image data.

[0006] Wherein, determining the image type of the image data includes: dividing the image data into at least one image frame group; determining the image type corresponding to each image frame group; if the image type of the image data is a preset first image type, compressing the image data, including: if the image type of the image frame group is a preset first image type, compressing the image frame group.

[0007] The method further comprises: if the image type of the image frame group is a preset second image type, storing the image frame group.

[0008] Among them, if the image type of the image picture group is a preset second image type, the image picture group is stored, including: extracting features from the image picture group to obtain corresponding feature information in the image picture group; if the feature information matches the preset feature information, determining that the image type of the image picture group is the second image type; and storing the image picture group.

[0009] Wherein, if the image type of the image picture group is a preset second image type, the image picture group is stored, including: if the image type of the image picture group is the preset second image type, determining that the image picture group is a first target image picture group; acquiring at least one second target image picture group before the first target image picture group, and acquiring at least one third target image picture group after the first target image picture group; forming an image picture group segment with at least one second target image picture group, the first target image picture group and at least one third target image picture group; and storing the image picture group segment.

[0010] The image type of at least one second target image picture group and at least one third target image picture group is the first image type.

[0011] Among them, if the image type of the image data is a preset first image type, the image data is compressed, including: if the image type of the image data is a preset first image type, the storage space usage rate is obtained; if the storage space usage rate is greater than or equal to a set threshold, the image data is cleared; if the storage space usage rate is less than the set threshold, the image data is compressed.

[0012] The image data is compressed, including: determining key frames and non-key frames in the image data; retaining key frames and clearing non-key frames; and storing the compressed image data, including: storing key frames.

[0013] In order to solve the above-mentioned problem, another technical solution adopted in the present application is to provide an image data processing device, which includes a processor and a memory coupled to the processor; wherein the memory is used to store a computer program, and the processor is used to execute the computer program to implement the method provided by the above-mentioned technical solution.

[0014] In order to solve the above problem, another technical solution adopted by the present application is to provide a computer-readable storage medium, which is used to store a computer program. When the computer program is executed by a processor, it is used to implement the method provided by the above technical solution.

[0015] The beneficial effects of the present application are as follows: Different from the prior art, the image data processing device and processing method provided by the present application, and a computer-readable storage medium. The method obtains image data sent by an image acquisition device; determines the image type of the image data; if the image type of the image data is a preset first image type, compresses the image data; and stores the compressed image data in a manner that can compress the image data sent by the image acquisition device in real time and then store it, rather than performing secondary processing on the stored image data, thereby improving the processing efficiency of the image data. Furthermore, since the compression is performed before storage, the operation of the storage device is reduced, and the performance of the storage device is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0017] Figure 1 It is a flowchart of an embodiment of an image data processing method provided by the present application;

[0018] Figure 2 is a flowchart of another embodiment of the image data processing method provided by the present application;

[0019] Figure 3 It is a flowchart of an embodiment of step 22 provided by the present application;

[0020] Figure 4 It is a flowchart of an embodiment of step 222 provided by the present application;

[0021] Figure 5 is a flowchart of another embodiment of the image data processing method provided by the present application;

[0022] Figure 6 is a flowchart of an embodiment of step 53 provided by the present application;

[0023] Figure 7 is a flowchart of another embodiment of step 53 provided by the present application;

[0024] Figure 8 is a flowchart of another embodiment of the image data processing method provided by the present application;

[0025] Fig. 9 is a flowchart of an embodiment of step 85 provided by the present application;

[0026] Fig.10 is a flowchart of another embodiment of the image data processing method provided by the present application;

[0027] Fig.11 is a structural schematic diagram of an embodiment of an image data processing device provided by the present application;

[0028] Fig.12 It is a structural schematic diagram of an embodiment of a computer-readable storage medium provided by the present application. DETAILED DESCRIPTION

[0029] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It will be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for ease of description, only some but not all structures related to the present application are shown in the drawings. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0030] The terms "first", "second", etc. in this application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0031] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0032] See also Figure 1 , Figure 1 1 is a flow chart of an embodiment of an image data processing method provided by the present application. The method comprises:

[0033] Step 11: Acquire the image data sent by the image acquisition device.

[0034] In some embodiments, the image acquisition device may be a surveillance image acquisition device, such as a surveillance camera. The image acquisition device may also be a conventional camera, such as a camera on a smart phone or a tablet computer.

[0035] Therefore, the image acquisition device can be set separately from the image data processing device, and the image data processing device is provided with a memory for storing image data. Alternatively, the image acquisition device, the image data processing device and the memory are set separately, and the image acquisition device transmits the image data to the image data processing device, and then the image data processing device processes the image data and stores the processed image data in the memory.

[0036] Similarly, the image acquisition device can be integrated with the image data processing device, and the image data processing device is provided with a memory for storing image data.

[0037] In some embodiments, the acquired image data may be a video of a preset time length, such as a 1-minute video, a 2-minute video, or a 3-minute video. The video of the preset time length may be cached by the image acquisition device and then sent out.

[0038] In some embodiments, the acquired image data may be real-time, and the image data processing device may cache the image data, and perform subsequent processing on the cached image data when the time length of the cached image data exceeds a preset time length.

[0039] Step 12: Determine the image type of the image data.

[0040] In some embodiments, the image data may be segmented at a preset time interval to obtain a plurality of image data segments, and then image recognition is performed on each image data segment to determine the image type of each image data segment. For example, if the image data is 3 minutes long, the preset time interval is set to 30 seconds, and the image data may be segmented into 6 image data segments. Image recognition is performed on the 6 image data segments to determine the image type of each image data segment.

[0041] In some embodiments, the information in the image data may be identified by image recognition technology to determine the image type of the image data. For example, the image type of the partial image data with human information in the image data may be determined as human, the image type of the partial image data with animal information in the image data may be determined as animal, and the image type of the partial image data without obvious information in the image data may be determined as no information.

[0042] Step 13: If the image type of the image data is a preset first image type, compress the image data.

[0043] In this embodiment, the image data corresponding to the first image type is identified as image data that can be compressed. For example, if the above-mentioned image type without information is determined as the first image type, this part of the image data can be compressed.

[0044] In some embodiments, the first image type can be set according to actual needs. For example, for monitoring image acquisition equipment, which is mainly used to acquire person information, the image type of image data other than person information can be determined as the first image type.

[0045] The image data corresponding to the first image type may be compressed by using methods such as Holman coding, predictive coding, LZW (Lempel-Ziv-Welch Encoding) algorithm, and JPEG (Joint Photographic Experts Group) coding.

[0046] Step 14: Store the compressed image data.

[0047] The remaining image data that is not of the first image type is directly stored.

[0048] In this embodiment, by acquiring image data sent by an image acquisition device; determining the image type of the image data; and compressing the image data if the image type of the image data is a preset first image type; and storing the compressed image data, the image data sent by the image acquisition device can be compressed in real time and then stored, rather than performing secondary processing on the stored image data, thereby improving the processing efficiency of the image data. Furthermore, because compression is performed before storage, operations on the storage device are reduced, thereby improving the performance of the storage device.

[0049] See also Figure 2 , Figure 2 1 is a flow chart of another embodiment of the image data processing method provided by the present application. The method comprises:

[0050] Step 21: Acquire image data sent by the image acquisition device.

[0051] Step 22: Divide the image data into at least one image frame group.

[0052] An image picture group is a group of continuous pictures, referred to as GOP (Group of Pictures). Therefore, the image data can be divided into at least one image picture group according to the division rule of the image picture group.

[0053] In some embodiments, see Figure 3 , step 22 may be the following process:

[0054] Step 221: Determine key frames in the image data.

[0055] Image data is determined by continuous image frames, and key frames in image data can be directly determined from data corresponding to the image frames. For example, the frame types corresponding to image frames include I frames (key frames), P frames, and B frames. Usually, an image picture group starts with an I frame, followed by several P frames and B frames. Therefore, key frames can be determined based on frame types.

[0056] Step 222: Based on the key frames, the image data is divided into image picture groups corresponding to each key frame.

[0057] In some embodiments, see Figure 4 , step 222 may be the following process:

[0058] Step 2221: Taking the key frame as the starting point, obtain all non-key frames between the key frame and the next key frame.

[0059] Among them, non-key frames include P frames and B frames.

[0060] Step 2222: The key frame and all non-key frames are regarded as an image picture group.

[0061] The above-mentioned method of dividing the image picture groups is to use each key frame as a dividing point, and regard the key frame and the non-key frame after the key frame as an image picture group, so that the image data is divided into a plurality of image picture groups mainly based on the key frames.

[0062] Step 23: Determine the image type corresponding to each image frame group.

[0063] According to the above embodiment, each image frame group is identified to determine the image type corresponding to each image frame group.

[0064] Step 24: If the image type of the image frame group is a preset first image type, compression processing is performed on the image frame group.

[0065] Step 25: Store the compressed image frame group.

[0066] In this embodiment, the image frame group belonging to the first image type is compressed and then stored in the above manner, rather than performing secondary processing on the image data that has been stored, thereby improving the processing efficiency of the image data. Furthermore, because compression is performed before storage, the operation of the storage device is reduced, the performance of the storage device is improved, and different processing can be performed for different image types, making the stored image data more targeted. After the image data is compressed, it occupies a better storage space and can extend the storage time of the stored image data.

[0067] See also Figure 5 , Figure 51 is a flow chart of another embodiment of the image data processing method provided by the present application. The method comprises:

[0068] Step 51: Acquire image data sent by the image acquisition device.

[0069] Step 52: Divide the image data into at least one image frame group.

[0070] Step 51 and step 52 have the same or similar technical solutions as any of the above embodiments, and will not be described in detail here.

[0071] Step 53: If the image type of the image frame group is a preset second image type, the image frame group is stored.

[0072] In this embodiment, the image data corresponding to the second image type is identified as image data that does not need to be compressed and can be directly stored. For example, the image types of people and animals in the above embodiment can be determined as the second image type, and this part of the image data can be directly stored.

[0073] In some embodiments, the second image type can be set according to actual needs. For example, for a monitoring image acquisition device, which is mainly used to collect information about people, the image type of the image data of the person information can be determined as the second image type, and the remaining image types are determined as the first image type. The image frame group of the first image type is compressed according to the technical solution of the above embodiment.

[0074] In some embodiments, when performing image type recognition, the specific recognized image type can be set according to actual needs. For example, for surveillance images, only the recognition of character information can be set, and the image types of the remaining image picture groups that cannot recognize character information are uniformly classified as the first image type, and the image types of the image picture groups that can recognize character information are uniformly classified as the second image type.

[0075] In some embodiments, see Figure 6 , step 53 may be the following process:

[0076] Step 531: If the image type of the image frame group is a preset second image type, the image frame group is determined to be a first target image frame group.

[0077] Step 532: Acquire at least one second target image picture group before the first target image picture group, and acquire at least one third target image picture group after the first target image picture group.

[0078] For example, when performing image frame group segmentation, each image frame group is numbered in the order of the time axis. Then, image type recognition is performed on each numbered image frame group. When the image type of the image frame group is a preset second image type, it is determined as a first target image frame group. According to the set requirements, a number of second target image frame groups before the first target image frame group and a number of third target image frame groups after the first target image frame group are obtained. For example, if the preset requirement is to obtain 3, and the first target image frame group is numbered 5, the second target image frame groups numbered 2, 3 and 4 and the third target image frame groups numbered 6, 7 and 8 are obtained.

[0079] The image type of the second target image group and the third target image group may not be the second image type, but because the second target image group and the third target image group are continuous with the first target image group, there are more correlations and corresponding details, so they need to be retained for subsequent viewing.

[0080] In some embodiments, the image type of at least one second target image group of pictures and at least one third target image group of pictures is the first image type.

[0081] Step 533: Form an image group segment by combining at least one second target image picture group, the first target image picture group and at least one third target image picture group.

[0082] The above-mentioned groups of picture numbers 2, 3, 4, 5, 6, 7 and 8 may be used as group of picture segments.

[0083] Step 534: Store the image frame group fragments.

[0084] By storing the image picture group associated with the image picture group of the second image type, the stored image picture group can retain the details of the image picture group of the second image type, making the stored image data more meaningful and convenient for subsequent viewing.

[0085] Therefore, in this embodiment, if the image type of the image frame group in any of the above embodiments is the preset first image type, the image frame group may be compressed by compressing the image frame group of the first image type that participates in forming the image frame group fragment.

[0086] In an application scenario, if continuous GOPs are all of the second image type, these GOPs can be formed into an image group segment in the above manner. For example, there are 100 GOPs divided according to the sequence number, among which the GOPs of sequence numbers 8, 9 and 10 are of the second image type, and the predetermined requirement is to obtain 4. Then, according to the formation rule of the image group segment, the image group segment corresponding to sequence number 8 includes the GOPs of sequence numbers 4-12, the image group segment corresponding to sequence number 9 includes the GOPs of sequence numbers 5-13, and the image group segment corresponding to sequence number 10 includes the GOPs of sequence numbers 6-14. Therefore, if there are repeated image groups in these image group segments, deduplication is required, and the image group segments corresponding to the GOPs of sequence numbers 8, 9 and 10 finally include the GOPs of sequence numbers 4-14.

[0087] In another embodiment, see Figure 7 , step 53 may be the following process:

[0088] Step 71: extract features from the image frame group to obtain corresponding feature information in the image frame group.

[0089] For example, an image recognition algorithm may be used to extract features from an image frame group to obtain feature information.

[0090] Step 72: If the characteristic information matches the preset characteristic information, determine that the image type of the image frame group is the second image type.

[0091] The preset feature information can be set according to actual needs. For example, for monitoring image acquisition equipment, which is mainly used to collect person information, face feature information can be used as the preset feature information.

[0092] In other embodiments, a network model can be used to enable the network model to perform multiple feature recognitions and extract features from the image frame group. If the extracted feature information matches any preset feature information, the image type of the image frame group is determined to be the second image type. The remaining unmatched image frame groups are the first image type.

[0093] Step 73: Store the image frame group.

[0094] The image picture groups of the second image type are stored.

[0095] The specific storage method can refer to any of the above embodiments and will not be described in detail here.

[0096] In this embodiment, the image frame group belonging to the first image type is compressed and then stored in the above manner, rather than performing secondary processing on the image data that has been stored, thereby improving the processing efficiency of the image data. Furthermore, because compression is performed before storage, the operation of the storage device is reduced, the performance of the storage device is improved, and different processing can be performed for different image types, making the stored image data more targeted. After the image data is compressed, it occupies a better storage space and can extend the storage time of the stored image data.

[0097] See also Figure 8 , Figure 8 1 is a flow chart of another embodiment of the image data processing method provided by the present application. The method comprises:

[0098] Step 81: Acquire image data sent by the image acquisition device.

[0099] Step 82: Determine the image type of the image data.

[0100] Step 83: If the image type of the image data is a preset first image type, obtain the storage space usage rate.

[0101] Since the image data of the first image type needs to be compressed before being stored, it indicates that the image data of the first image type is not very important to a certain extent. Therefore, the storage space usage rate needs to be considered during storage.

[0102] Step 84: If the storage space usage is greater than or equal to the set threshold, the image data is cleared.

[0103] If the storage space usage is greater than or equal to the set threshold, the image data is cleared.

[0104] Step 85: If the storage space usage rate is less than the set threshold, compress the image data.

[0105] In some embodiments, see Fig. 9 , step 85 may be the following process:

[0106] Step 851: Determine key frames and non-key frames in the image data.

[0107] The key frame and the non-key frame are determined according to the method in any of the above embodiments.

[0108] Step 852: Keep key frames and clear non-key frames.

[0109] Step 86: Store the compressed image data.

[0110] The keyframes are then stored.

[0111] In this embodiment, the image frame group belonging to the first image type is compressed and then stored in the above manner, rather than performing secondary processing on the image data that has been stored, thereby improving the processing efficiency of the image data. Furthermore, because compression is performed before storage, the operation of the storage device is reduced, the performance of the storage device is improved, and different processing can be performed for different image types, making the stored image data more targeted. After the image data is compressed, it occupies a better storage space and can extend the storage time of the stored image data.

[0112] See also Fig.10 , Fig.10 1 is a flow chart of another embodiment of the image data processing method provided by the present application. The method comprises:

[0113] Step 101: Acquire image data sent by an image acquisition device.

[0114] Step 102: Divide the image data into at least one image frame group.

[0115] Step 103: Determine the image type corresponding to each image frame group.

[0116] The image type includes a first image type and a second image type.

[0117] Here, image recognition is performed on each image frame group to determine the corresponding image type.

[0118] The image picture group whose image type is the second image type is determined as the first target image picture group, at least one second target image picture group before the first target image picture group is obtained, and at least one third target image picture group after the first target image picture group is obtained, at least one second target image picture group, the first target image picture group and at least one third target image picture group are formed into image picture group segments, and then the types of image picture groups corresponding to these image picture group segments are determined as the second image type. The image types of the remaining image picture groups are the first image type.

[0119] Step 104: compress the image frame group of the first image type.

[0120] Here, the storage space usage rate needs to be obtained, and if the storage space usage rate is greater than or equal to the set threshold, the image frame group of the first image type is cleared. If the storage space usage rate is less than the set threshold, the image frame group of the first image type is compressed.

[0121] Step 105: storing the image frame group of the second image type and the compressed image frame group.

[0122] In an application scenario, the image acquisition device is a video recording device, and the data processing method of the image data processing device can be the following process:

[0123] 1. Receive the video sent by the video recording device, divide the video into multiple GOPs with key frames as the separation points, each GOP is a continuous video image that can be decoded independently, assign a sequence number to each GOP, add a sequence header before the GOP, and add the above sequence number information to the sequence header. The sequence numbers assigned to each GOP remain continuous, for example, the sequence numbers are continuous integers starting from 1.

[0124] 2. Analyze each GOP one by one. Specifically, after decoding the GOP, use the corresponding recognition algorithm to analyze the video content to obtain the analysis result. Each analysis result includes the GOP number and the corresponding image type.

[0125] For example, a face is detected in the GOP with the sequence number 5, and no object or event is detected in the GOP with the sequence number 100. A face can be classified as the second image type, and a face without any object or event can be classified as the first image type.

[0126] 3. Further divide the GOP according to the analysis results. For example, if the analysis results contain information about people or events, the corresponding event video should be determined for the GOP of the analysis results. The method for determining the event video is as follows: take the serial number of the GOP containing people or events as the midpoint, and extend the preset duration forward and backward along the time axis, wherein the duration is in units of GOP, that is, one GOP is one duration, and the GOPs corresponding to the serial numbers of these preset durations are defined as event videos. For example, a face is detected in the GOP with serial number 5, and the preset duration is 3 GOPs. Then, take serial number 5 as the midpoint, extend 3 GOPs forward along the time axis, determine the starting serial number of the event video as 2, extend 3 GOPs backward along the time axis, determine the ending serial number of the event video as 8, then the time period corresponding to this event video is the GOP with serial number [2, 3, 4, 5, 6, 7, 8]. If the duration of each GOP is 2s, then the above event video corresponds to 7*2s=14s of video before and after the event. The time period of the newly added event recording can be put into the array for management.

[0127] 4. Then, based on these serial numbers, determine the GOPs that need to be stored or compressed. For example, the GOPs with serial numbers 2-8 can be stored directly. The remaining GOPs without confirmed events are compressed. Specifically, if the GOP belongs to the above event recording, it is stored, otherwise it is compressed. Before compressing the GOP that needs to be compressed, it is necessary to query the storage space usage rate. If the storage space usage rate is greater than or equal to the set threshold, the GOP is discarded.

[0128] 5. Store the compressed GOP.

[0129] In this embodiment, through the above method, the image data can be compressed by event-driven, the storage time of the image data can be extended, and the details of the event recording can be retained. At the same time, the attributes of the event can be saved, which is convenient for querying the image data corresponding to the event. The processing efficiency of the image data can be improved. Further, because the compression is performed before storage, the operation of the storage device is reduced, the performance of the storage device is improved, and different processing can be performed for different image types, making the stored image data more targeted. After the image data is compressed, it occupies a better storage space, which can extend the storage time of the stored image data.

[0130] See also Fig.11 , Fig.11 1 is a schematic diagram of the structure of an embodiment of an image data processing device provided by the present application. The image data processing device 110 includes a processor 111 and a memory 112 coupled to the processor 111; wherein the memory 112 is used to store a computer program, and the processor 111 is used to execute the computer program to implement the following method:

[0131] Acquire image data sent by an image acquisition device; determine the image type of the image data; if the image type of the image data is a preset first image type, compress the image data; and store the compressed image data.

[0132] It can be understood that the processor 111 is also used to execute a computer program to implement the method provided in any of the above embodiments.

[0133] See also Fig.12 , Fig.12 1 is a schematic diagram of a computer readable storage medium according to an embodiment of the present application. The computer readable storage medium 120 is used to store a computer program 121. When the computer program 121 is executed by a processor, it is used to implement the following method:

[0134] Acquire image data sent by an image acquisition device; determine the image type of the image data; if the image type of the image data is a preset first image type, compress the image data; and store the compressed image data.

[0135] It can be understood that when the computer program 121 is executed by a processor, it is used to implement the method provided by any of the above embodiments.

[0136] In the several embodiments provided in this application, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device implementation described above is only illustrative, for example, the division of the modules or units is only a logical function division, and 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.

[0137] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0138] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0139] If the integrated units in the above other embodiments are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) or a processor (processor) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), disk or optical disk and other media that can store program codes.

[0140] The above description is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for processing image data, characterized in that: The method comprises: Acquire image data sent by an image acquisition device; Determining an image type of each image frame group in the image data; If the image type of the image frame group is a preset first image type, compressing the image data; Storing the compressed image data; If the image type of the image picture group is a preset second image type, the image picture group is stored, including: if the image type of the image picture group is the preset second image type, determining that the image picture group is a first target image picture group; acquiring at least one second target image picture group before the first target image picture group, and acquiring at least one third target image picture group after the first target image picture group; forming an image picture group segment with the at least one second target image picture group, the first target image picture group and the at least one third target image picture group; wherein the image types of the at least one second target image picture group and the at least one third target image picture group are the first image type; The image picture group fragments are stored.

2. The method according to claim 1, characterized in that The determining the image type of each image frame group in the image data comprises: dividing the image data into at least one image frame group; The image type corresponding to each of the image frame groups is determined.

3. The method according to claim 1, characterized in that If the image type of the image picture group is a preset second image type, storing the image picture group further includes: Extracting features from the image group to obtain corresponding feature information in the image group; If the characteristic information matches the preset characteristic information, determining that the image type of the image frame group is the second image type; The image picture group is stored.

4. The method according to claim 1, characterized in that: If the image type of the image data is a preset first image type, compressing the image data comprises: If the image type of the image data is a preset first image type, obtaining a storage space usage rate; If the storage space usage rate is greater than or equal to a set threshold, clearing the image data; If the storage space usage rate is less than a set threshold, the image data is compressed.

5. The method according to claim 4, characterized in that The compressing the image data comprises: Determine key frames and non-key frames in the image data; Keep the key frame and clear the non-key frame; The step of storing the compressed image data comprises: The key frame is stored.

6. An image data processing device, characterized in that: The image data processing device includes a processor and a memory coupled to the processor; The memory is used to store a computer program, and the processor is used to execute the computer program to implement the method according to any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the computer program is used to implement the method according to any one of claims 1 to 5.

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