Image material collection method and device, equipment and storage medium

Abstract

The invention relates to the technical field of image processing, and discloses an image material collection method, device and equipment and a storage medium, and the method comprises the steps: responding to a material import operation for a favorite, analyzing an imported image material, obtaining original data of the imported image material, preprocessing the original data, obtaining target data, and storing the target data in a database; storing target data into the favorite, and constructing a data index corresponding to the target data in the favorite; when the image material is stored in the favorite, the image material is preprocessed, the target data obtained through preprocessing is stored in the favorite, and when the image material in the favorite is used subsequently, the image material does not need to be loaded, but the target data in the favorite is directly used, so that the material reading speed is increased, and the reading efficiency is improved. And therefore, the favorite performance is optimized, and the user experience is improved.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to an image material collection method, device, equipment and storage medium. Background Art

[0002] At present, the method for collecting related image materials is to directly store the image materials in the file system and store the URL of the image materials in the favorites. However, when using the image materials in the above method, it is necessary to access the corresponding URL file in the favorites to load the image materials stored in the file system, which has the disadvantages of slow material reading speed and poor favorites performance. Summary of the invention

[0003] The main purpose of the present application is to provide an image material collection method, device, equipment and storage medium, aiming to solve the technical problem that the related image material collection method directly stores the image material into the file system and stores the URL of the image material into the favorites, resulting in slow material reading speed and poor favorites performance.

[0004] To achieve the above-mentioned purpose, the present application provides an image material collection method, the image material collection method comprising:

[0005] In response to a material import operation for a favorites folder, the imported image material is parsed to obtain original data of the imported image material;

[0006] Preprocessing the original data to obtain target data, wherein the preprocessing is to extract key data of the imported image material from the original data;

[0007] The target data is stored in the favorites folder, and a data index corresponding to the target data is constructed in the favorites folder.

[0008] Optionally, the preprocessing the original data to obtain target data includes:

[0009] Extracting key data of the imported image material from the original data;

[0010] Performing data conversion on the key data to obtain converted data;

[0011] The key data and the converted data are classified to obtain target data.

[0012] Optionally, the key data includes at least one or a combination of thermal radiation data, temperature matrix data, shooting time, text note content, temperature measurement configuration parameters and thermal imaging configuration parameters.

[0013] Optionally, the converted data includes compressed data and / or thumbnails;

[0014] The step of converting the key data to obtain converted data includes:

[0015] Compressing the key data to obtain compressed data, wherein the compressed data is compressed thermal radiation data;

[0016] And / or, the image material is compressed according to the key data to obtain a thumbnail, and the thumbnail is a thermal imaging thumbnail.

[0017] Optionally, after storing the target data into the favorites and constructing a data index corresponding to the target data in the favorites, the method further includes:

[0018] responding to an image retrieval operation for the favorites and determining an image retrieval category and an image retrieval condition according to the image retrieval operation;

[0019] Searching the favorites for a target data category that matches the image retrieval category;

[0020] The target data of the target data category matching the image search category is searched for search data that satisfies the image search condition, and the search data that satisfies the search condition is displayed.

[0021] Optionally, after storing the target data into the favorites and constructing a data index corresponding to the target data in the favorites, the method further includes:

[0022] In response to a secondary analysis operation on the favorites, obtaining a data index corresponding to the secondary analysis operation;

[0023] Adjusting the target data corresponding to the data index corresponding to the secondary analysis operation to obtain adjusted data;

[0024] Acquiring data required for secondary analysis, wherein the data required for secondary analysis includes the adjusted data;

[0025] Perform secondary analysis on the image material according to the data required for the secondary analysis, obtain secondary analysis results, and display the secondary analysis results.

[0026] Optionally, after storing the target data into the favorites and constructing a data index corresponding to the target data in the favorites, the method further includes:

[0027] In response to a batch processing operation on the favorites, obtaining a data index corresponding to the batch processing operation;

[0028] Acquire batch processing data from the favorites according to the data index corresponding to the batch processing operation;

[0029] The batch processing data is batch processed according to the batch processing operation to obtain a batch processing result, and the batch processing result is displayed.

[0030] Optionally, after storing the target data into the favorites and constructing a data index corresponding to the target data in the favorites, the method further includes:

[0031] In response to an image viewing operation on the favorites, obtaining a data index corresponding to the image viewing operation;

[0032] Selecting part of the target data from the favorites according to the data index corresponding to the image viewing operation;

[0033] A thumbnail image and / or attribute information of the thumbnail image corresponding to the image viewing operation is generated based on part of the target data, and the thumbnail image and / or attribute information of the thumbnail image is displayed.

[0034] Optionally, after storing the target data into the favorites and constructing a data index corresponding to the target data in the favorites, the method further includes:

[0035] Displaying the material to be processed in the work board, wherein the material to be processed is an image material generated according to the target data stored in the favorites;

[0036] In response to the function selection operation, displaying the function module interface and the selected material corresponding to the selected function module, wherein the selected function module is a function module selected from a plurality of function modules according to the function selection operation, and the selected material is a material selected from the to-be-processed material according to the material selection operation;

[0037] After the selected function module completes processing of the selected material, the processed material is cached in the work board.

[0038] Optionally, after the selected function module completes processing of the selected material and caches the processed material in the work board, the method further includes:

[0039] Displaying cached materials in the work board, wherein the cached materials are processed materials cached in the work board, and the processed materials are materials processed by at least one functional module among the multiple functional modules;

[0040] In response to the function switching operation, displaying a function module interface and a target material corresponding to the switched function module, wherein the switched function module is a function module selected from the plurality of function modules according to the function switching operation, and the target material is a material selected from the cached materials according to the function switching operation;

[0041] After the post-switching functional module completes processing of the target material, the processing result of the post-switching functional module is displayed.

[0042] In addition, to achieve the above-mentioned purpose, the present application also proposes an image material collection device, the image material collection device comprising:

[0043] A material parsing module, configured to, in response to a material import operation for a favorites folder, parse the imported image material to obtain original data of the imported image material;

[0044] A material processing module, used for preprocessing the original data to obtain target data, wherein the preprocessing is to extract key data of the imported image material from the original data;

[0045] The material collection module is used to store the target data into the favorites folder and construct a data index corresponding to the target data in the favorites folder.

[0046] In addition, to achieve the above-mentioned purpose, the present application also proposes an image material collection device, which includes a memory, a processor, and an image material collection program stored in the memory and executable on the processor, and the image material collection program is configured to implement the image material collection method described above.

[0047] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, on which an image material collection program is stored, and when the image material collection program is executed by a processor, the image material collection method as described above is implemented.

[0048] One or more technical solutions proposed in this application have at least the following technical effects:

[0049] In the present application, it is disclosed that in response to a material import operation for a favorites folder, the imported image material is parsed, the original data of the imported image material is obtained, the original data is preprocessed, the target data is obtained, the target data is stored in the favorites folder, and a data index corresponding to the target data is constructed in the favorites folder; since the present application preprocesses the image material when storing the image material in the favorites folder, and stores the target data obtained by the preprocessing in the favorites folder, when the image material in the favorites folder is used subsequently, there is no need to load the image material, but the target data in the favorites folder is directly used, thereby improving the material reading speed, and further optimizing the favorites performance and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0052] Figure 1 A schematic diagram of the collection method of related image materials;

[0053] Figure 2 This is a schematic diagram of the process of the first embodiment of the image material collection method of the present application;

[0054] Figure 3 A schematic diagram of a software interaction interface of an embodiment of the image material collection method of the present application;

[0055] Figure 4 This is a flow chart of a second embodiment of the image material collection method of the present application;

[0056] Figure 5 This is a flowchart of a third embodiment of the image material collection method of the present application;

[0057] Figure 6 This is another schematic diagram of the software interaction interface of an embodiment of the image material collection method of the present application;

[0058] Figure 7 This is another schematic diagram of the software interaction interface of an embodiment of the image material collection method of the present application;

[0059] Figure 8 This is another schematic diagram of the software interaction interface of an embodiment of the image material collection method of the present application;

[0060] Fig. 9 This is another schematic diagram of the software interaction interface of an embodiment of the image material collection method of the present application;

[0061] Fig.10 This is a schematic diagram of the module structure of the image material collection device according to an embodiment of the present application;

[0062] Fig.11 Schematic diagram of the device structure of the hardware operating environment involved in the image material collection method in the embodiment of the present application.

[0063] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0064] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0065] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0066] Currently, in the power inspection industry, users have the need to manage and retrieve massive amounts of images (a user can take hundreds of images a day, and a substation needs regular inspections). Users use thermal imagers or audio-visual cameras to photograph and archive inspection targets (equipment). These images have great storage value: 1. As a record or proof of inspection work; 2. Post-secondary analysis, because thermal radiation images support viewing temperature data, as well as secondary temperature measurement and thermal imaging for further diagnosis; 3. Big data analysis, by collating the temperature distribution of the same target taken at different times, predicting and preventing equipment failures. In order to facilitate the management of inspection images, images are usually collected through favorites.

[0067] However, in the related art, the favorites manage URLs. When reading and editing are needed, the image is loaded by accessing the corresponding URL file. Figure 1 To explain, Figure 1 Schematic diagram of the collection method of related image materials. In the figure, the collection method of related image materials (such as the imported image in the figure) is to directly import the image material (such as the hot Figure 1 , sonograms, and thermal Figure 2), save the URL of the image material into the favorites (form a URL list as shown in the figure). However, when using the image material (such as viewing images and analyzing pictures in the figure), the above method needs to access the corresponding URL file in the favorites (such as accessing the URL in the URL list in the figure) to load the image material stored in the file system (such as accessing the file system through the system proxy in the figure to load the heat map or audio-visual image, where the file system can be a local disk or server), which has the defects of slow material reading speed and poor favorites performance.

[0068] Therefore, in order to overcome the above-mentioned defects, the present application provides a solution, which includes: in response to a material import operation for a favorites folder, parsing the imported image material, obtaining the original data of the imported image material, preprocessing the original data, obtaining target data, storing the target data in the favorites, and constructing a data index corresponding to the target data in the favorites; since the present application preprocesses the image material when storing the image material in the favorites, and stores the target data obtained by the preprocessing in the favorites, when the image material in the favorites is used subsequently, there is no need to load the image material, but directly use the target data in the favorites, thereby improving the material reading speed, and then optimizing the favorites performance and improving the user experience.

[0069] It should be noted that the execution subject of the embodiment of the present application can be an image material collection device with data processing, network communication and program running functions, such as a computer, or other electronic devices that can achieve the same or similar functions, and this embodiment does not impose any restrictions on this.

[0070] Based on this, the present application embodiment provides a method for collecting image materials, referring to Figure 2 , Figure 2 This is a flowchart of the first embodiment of the image material collection method of the present application.

[0071] In a first embodiment, the image material collection method includes:

[0072] Step S10: In response to the material import operation for the favorites, the imported image material is parsed to obtain the original data of the imported image material.

[0073] It should be understood that the application scenario of the embodiment of the present application may be to collect image materials through favorites, wherein the image materials may be objects for editing, processing and reading data by software, and the image materials may include JPEG files, thermal radiation pictures, audio-visual pictures, and thermal radiation videos, etc. Therefore, the specific application scenario of the embodiment of the present application may also be in the power inspection scenario, collecting JPEG files, thermal radiation pictures, audio-visual pictures, and thermal radiation videos, etc. through favorites, and the present embodiment does not limit this.

[0074] A thermal radiation image can be a picture file with thermal radiation data and all data required for secondary analysis attached to a JPEG file. An audio-visual image can be a picture file with sound data and all data required for secondary analysis attached to it. A thermal radiation video can be a file format of continuous thermal radiation data. Secondary analysis can include audio-visual secondary analysis and thermal image secondary analysis. Taking thermal image secondary analysis as an example, thermal image secondary analysis includes secondary temperature measurement and secondary thermal imaging. Secondary temperature measurement depends on thermal radiation data, temperature measurement parameters, etc.; secondary thermal imaging depends on thermal radiation data, image parameters, etc.

[0075] For ease of understanding, refer to Figure 3 This invention is provided for illustration, but is not intended to limit the present application. Figure 3 This is a schematic diagram of the software interaction interface of an embodiment of the image material collection method of the present application. In the figure, as an example, it is assumed that the execution subject is a computer, and a software interaction interface is displayed on the computer. The software interaction interface includes a material management interface, and the material management interface includes a favorites interface. As an example, the user's material import operation can be to click the import material component in the favorites interface to import the image material into the favorites.

[0076] Step S20: preprocessing the original data to obtain target data;

[0077] The preprocessing is to extract key data of the imported image material from the original data.

[0078] It should be understood that in order to reduce the amount of stored data, in this embodiment, the preprocessing can be to extract the key data of the imported image material from the original data. In a specific implementation, it can be to discard the irrelevant format description data in the original data and only retain the content data and metadata. Among them, the content data is the actual data content. In a specific implementation, the content data can be text data (such as articles), image data (such as illustrations), audio data (such as recordings), video data (such as continuous frames) and sensor data (such as temperature, radiation, pressure), etc. In a thermal radiation image, the core content data may include thermal radiation data and thermal imaging screenshots (JPEG). In an audio-visual image, the core content data may include audio data and cloud image screenshots. Metadata is data that provides background information required to understand other data, that is, data that describes data. Metadata may include structured metadata and descriptive metadata, which are used to describe the structure, data elements, relationships and other characteristics of the data. Without metadata, such as the unit of grams, the number 8 is meaningless. In a specific implementation, metadata may include date information of the file system, processing parameters, sequence files, audit trails or data required for reconstruction and analysis activities, etc.

[0079] Step S30: storing the target data into the favorites folder, and constructing a data index corresponding to the target data in the favorites folder.

[0080] It should be understood that the data index corresponding to the target data can be customized. For example, the data index can be defined as a combination of a file name and a favorites location, which is not limited in this embodiment.

[0081] It can be understood that storing the target data and the data index corresponding to the target data in the favorites can be directly storing the target data and the data index corresponding to the target data in the storage space corresponding to the favorites, wherein the storage space can be a memory, a disk, a server, etc., and this embodiment does not limit this. Of course, in order to facilitate the tracing of the original data of the imported material, in this embodiment, when storing the target data and the data index corresponding to the target data in the favorites, the original data of the imported material can also be backed up, specifically, the original data of the imported material can be stored in a preset backup storage space, wherein the preset backup storage space can be pre-set, and this embodiment does not limit this.

[0082] When storing image materials into favorites, this embodiment preprocesses the image materials and stores the target data obtained by the preprocessing into the favorites. When the image materials in the favorites are used subsequently, there is no need to load the image materials, but the target data in the favorites is directly used, thereby improving the material reading speed, optimizing the favorites performance, and improving the user experience.

[0083] Furthermore, after step S30, it also includes: responding to an image retrieval operation for the favorites, and determining an image retrieval category and an image retrieval condition according to the image retrieval operation; searching for a target data category matching the image retrieval category in the favorites; retrieving retrieval data that meets the image retrieval condition in the target data of the target data category matching the image retrieval category, and displaying the retrieval data that meets the retrieval condition.

[0084] It should be understood that when preprocessing the raw data of the imported material, this embodiment can also classify the data, thereby greatly improving the data retrieval capability, providing data retrieval capabilities such as time, fuzzy search of text, highest temperature pictures, and pictures with the most noise.

[0085] In a specific implementation, for example, through an image search operation, all materials containing a fixed field in a text note can be quickly found and viewed after obtaining the index.

[0086] Furthermore, in order to improve the loading speed of image viewing, after step S30, it also includes: in response to the image viewing operation for the favorites, obtaining the data index corresponding to the image viewing operation; selecting part of the target data from the favorites according to the data index corresponding to the image viewing operation; generating a thumbnail corresponding to the image viewing operation and / or the attribute information of the thumbnail based on the part of the target data, and displaying the thumbnail and / or the attribute information of the thumbnail.

[0087] It should be understood that when a user views an image, since only partial data is displayed in this embodiment, the loading speed of the image viewing is improved. In a specific implementation, for example, when viewing images in batches, thumbnails are displayed, so the favorites only need to provide the corresponding information without returning a complete copy of the original image file (i.e., only part of the target data needs to be selected from the target data to generate a thumbnail corresponding to the image viewing operation for display); similarly, when a user views the properties of an image, the metadata of the image (such as the shooting time of the file, etc.) is displayed (i.e., only part of the target data needs to be selected from the target data to generate the attribute information of the thumbnail for display).

[0088] It can be understood that selecting part of the target data from the favorites according to the data index corresponding to the image viewing operation can be by matching the data index corresponding to the image viewing operation with the data index stored in the favorites, and selecting the target data corresponding to the data index that successfully matches the data index corresponding to the image viewing operation as the part of the target data.

[0089] Furthermore, in order to improve the speed of secondary analysis, after step S30, it also includes: in response to the secondary analysis operation on the favorites, obtaining the data index corresponding to the secondary analysis operation; adjusting the target data corresponding to the data index corresponding to the secondary analysis operation to obtain adjusted data; obtaining the data required for secondary analysis, wherein the data required for secondary analysis includes the adjusted data; performing secondary analysis on the image material according to the data required for secondary analysis, obtaining the secondary analysis result, and displaying the secondary analysis result.

[0090] It is understandable that secondary analysis only requires data and not files. Therefore, since this embodiment preprocesses the image material when storing the image material in the favorites, and stores the target data obtained by the preprocessing in the favorites, the target data in the favorites can be directly called during the secondary analysis. Among them, the secondary analysis can include audio-visual secondary analysis and thermal image secondary analysis. Taking thermal image secondary analysis as an example, thermal image secondary analysis includes secondary temperature measurement and secondary thermal imaging. Secondary temperature measurement depends on thermal radiation data, temperature measurement parameters, etc.; secondary thermal imaging depends on thermal radiation data, image parameters, etc.

[0091] It should be understood that, considering that there may be errors in the data of the imported material and the defects of inaccurate secondary analysis in actual applications, it is necessary to modify the data of the imported material before performing secondary analysis. Since this embodiment can operate from the data granularity, the user can re-enter or modify the data for secondary temperature measurement or secondary thermal imaging (for example, the distance parameter of the measurement previously entered is wrong, in this case, the data can be modified before performing secondary temperature measurement). In a specific implementation, the data index corresponding to the secondary analysis operation can be matched with the data index stored in the favorites, and the target data corresponding to the data index that successfully matches the data index corresponding to the secondary analysis operation is selected as the data to be adjusted, and the data to be adjusted is adjusted according to the secondary analysis operation to obtain the adjusted data. Among them, the data required for the secondary analysis may include the adjusted data, and may also include the adjusted data and the key analysis data. The key analysis data can be determined according to the secondary analysis operation, for example, specified from the target data stored in the favorites according to the secondary analysis operation, or input according to the secondary analysis operation, etc. This embodiment does not limit this.

[0092] Furthermore, in order to improve the batch processing capability of favorites, after step S30, it also includes: in response to a batch processing operation for the favorites, obtaining a data index corresponding to the batch processing operation; obtaining batch processing data from the favorites according to the data index corresponding to the batch processing operation; batch processing the batch processing data according to the batch processing operation, obtaining batch processing results, and displaying the batch processing results.

[0093] It is understandable that, since this embodiment pre-processes the image material and completes the key data extraction operation when storing the image material in the favorites, the amount of data during batch processing is reduced, thereby improving the batch processing capability of the favorites. In a specific implementation, the data index corresponding to the batch processing operation can be matched with the data index stored in the favorites, and the target data corresponding to the data index that successfully matches the data index corresponding to the batch processing operation is selected as the batch processing data.

[0094] Reference Figure 4 , Figure 4 This is a flow chart of the second embodiment of the image material collection method of the present application, based on the above Figure 1 The first embodiment shown provides a second embodiment of the image material collection method of the present application.

[0095] In the second embodiment, the step S20 includes:

[0096] Step S201: extracting key data of the imported image material from the original data.

[0097] It should be understood that in order to further optimize the favorites performance, in this embodiment, when preprocessing the original data of the imported material, data conversion is also performed on the key data to obtain converted data, and the key data and the converted data are classified to obtain target data.

[0098] It is understandable that in order to reduce the amount of stored data, in this embodiment, the preprocessing can be to extract the key data of the imported image material from the original data. In a specific implementation, it can be to discard the irrelevant format description data in the original data and only retain the content data and metadata. Among them, the content data is the actual data content. In a specific implementation, the content data can be text data (such as articles), image data (such as illustrations), audio data (such as recordings), video data (such as continuous frames) and sensor data (such as temperature, radiation, pressure), etc. In a thermal radiation image, the core content data may include thermal radiation data and thermal imaging screenshots (JPEG). In an audio-visual image, the core content data may include audio data and cloud image screenshots. Metadata is data that provides background information required to understand other data, that is, data that describes data. Metadata may include structured metadata and descriptive metadata, which are used to describe the structure, data elements, relationships and other characteristics of the data. Without metadata, such as the unit of grams, the number 8 is meaningless. In a specific implementation, metadata may include date information of the file system, processing parameters, sequence files, audit trails or data required for reconstruction and analysis activities, etc.

[0099] For ease of understanding, the following examples are given, but are not intended to limit the present application. As an example, assuming that the imported material is a thermal radiation image, and the original data is the original data of the thermal radiation image, then the original data of the thermal radiation image is preprocessed to obtain at least one or more combinations of key data such as thermal radiation data, temperature matrix data, shooting time, text note content, temperature measurement configuration parameters, and thermal imaging configuration parameters, and this embodiment does not limit this.

[0100] Step S202: performing data conversion on the key data to obtain converted data.

[0101] It should be understood that, in order to facilitate the subsequent processing of the material, in this embodiment, the preprocessing can also be to convert the key data to obtain the converted data, and the converted data can be the intermediate result of the function that the user has a high probability of using. In a specific implementation, the key data can be converted into a data object that is easier to process. For example, the data conversion can be to compress the key data to obtain compressed data, and the data conversion can also be to compress the image material according to the key data to obtain a thumbnail, which is not limited in this embodiment. Among them, the data compression of the key data can be to compress the key data according to a preset compression algorithm to obtain compressed data, and the preset compression algorithm can be preset, for example, the preset compression algorithm can be at least one of a lossless compression algorithm, a lossy compression algorithm, and a hybrid compression algorithm, which is not limited in this embodiment. The image material is compressed according to the key data to obtain a thumbnail, which can be compressed according to the key data through a preset thumbnail model to obtain a thumbnail, and the preset thumbnail model can be preset, for example, the preset thumbnail model can be a deep learning model, a generative adversarial network, etc., which is not limited in this embodiment.

[0102] For ease of understanding, the following examples are given, but are not intended to limit the present application. As an example, assuming that the imported material is a thermal radiation image, the data conversion may be to convert 14-bit thermal radiation data (i.e., key data) into 8-bit thermal radiation data (i.e., converted data), and the data conversion may also be to generate a thermal imaging thumbnail based on the key data, which is not limited in this embodiment.

[0103] After the key data is converted, the batch processing capability of the favorites can be further improved. For ease of understanding, the following examples are given, but this application is not limited. As an example, assume that the batch processing operation is to switch the pseudo-color of thermal imaging, and switching the pseudo-color of thermal imaging is a time-consuming operation. Switching the pseudo-color of thermal imaging can be simply understood as two steps: Step 1: Convert 14-bit thermal radiation data to 8-bit thermal radiation data; Step 2: Map the 8-bit data to a pseudo-color image. Step 1 is very time-consuming, and Step 2 is very fast. Since the present embodiment has already converted the 8-bit data block in advance and stored it in the favorites during data conversion, the present embodiment can greatly improve the batch processing capability of certain image changes (such as switching the pseudo-color of thermal imaging).

[0104] Furthermore, in order to improve the accuracy of data conversion, the step S202 includes: obtaining user behavior data corresponding to the favorites; analyzing the user behavior data to obtain the user's frequently used functions of the favorites; and converting the key data according to the user's frequently used functions to obtain converted data.

[0105] It is understandable that, considering that the converted data can be the intermediate result of the function that the user is likely to use, in this embodiment, the user behavior data corresponding to the favorites can also be analyzed to obtain the user's commonly used functions of the favorites, and the key data can be converted according to the user's commonly used functions.

[0106] Step S203: Classify the key data and the converted data to obtain target data.

[0107] It should be understood that, in order to improve the data retrieval capability of the favorites, in this embodiment, when pre-processing the original data of the imported material, the data may also be classified to facilitate subsequent data retrieval.

[0108] It is understandable that the classification of key data and converted data can be based on the data content (such as classifying thermal radiation data into one category, classifying temperature matrix data into another category, etc.). In the specific storage process, similar data can also be stored in the same space, reorganized, classified and compressed to reduce the overall volume, and the access speed of files can be improved by aligning data storage, distinguishing data read and write frequencies, and designing caches.

[0109] In this embodiment, when preprocessing the original data of the imported material, data conversion is also performed on the key data to obtain converted data, and the key data and the converted data are classified to obtain target data, so as to further optimize the favorites performance.

[0110] The present application also provides a method for collecting image materials. Figure 5 , Figure 5 This is a flowchart diagram of the third embodiment of the image material collection method of the present application.

[0111] In the third embodiment, after step S30, the method further includes:

[0112] Step S40: displaying the material to be processed in the work board, wherein the material to be processed is an image material generated according to the target data stored in the favorites.

[0113] It should be noted that the work board can be a display window that visualizes the data (which can exist in memory or disk) during the material processing process, or it can be an operation window that temporarily manages multiple data objects, including sorting and grouping of materials. This implementation does not limit this. In a specific implementation, the navigation area of ​​the software interaction interface includes multiple functional modules (such as material management, material analysis, and report export functional modules). The cached material is the processed material cached in the work board, and the processed material is the material processed by at least one of the multiple functional modules. Among them, material analysis can refer to secondary analysis materials, and secondary analysis materials can include audio-visual secondary analysis and thermal imaging secondary analysis. Taking thermal imaging secondary analysis as an example, thermal imaging secondary analysis includes secondary temperature measurement and secondary thermal imaging. Secondary temperature measurement depends on thermal radiation data, temperature measurement parameters, etc.; secondary thermal imaging depends on thermal radiation data, image parameters, etc.

[0114] It is understandable that displaying the to-be-processed material in the work board may be generating thumbnails of the image material in the favorites and / or attribute information of the thumbnails according to the target data stored in the favorites, and this embodiment does not impose any limitation on this.

[0115] In a specific implementation, the material to be processed may be, in addition to image material generated according to target data stored in the favorites, material to be edited added through the material management function module and added to the work board, which is not limited in this embodiment.

[0116] For ease of understanding, refer to Figure 6 This invention is provided for illustration, but is not intended to limit the present application. Figure 6 Another schematic diagram of the software interaction interface of an embodiment of the image material collection method of the present application is shown in the figure. As an example, it is assumed that the execution subject is a computer, and a software interaction interface is displayed on the computer. The software interaction interface includes a navigation area, a function module interface and a work board. The function modules in the navigation area include material management, material analysis and report export. Then the user can click the material management function module to initiate a material addition request (the underline in the figure indicates that it is selected). After the computer receives the material addition request, the material management interface can be displayed in the function module interface. The material management interface includes a favorite and an add to edit material component. The favorite is used to display the materials that the user has collected in advance. The user can select materials from the favorites and add them to the work board; the user can also click the to edit material component to add the material to the work board. For example, if the materials added to the work board are material A and material B, then material A and material B are displayed in the work board. Of course, the user can also import image materials into the favorites. As an example, the user's material import operation can be to click the import material component in the favorites interface to import the image material into the favorites.

[0117] Furthermore, in order to reduce the initial loading time, in this embodiment, when adding materials to the work board, only the uniform resource locator can be loaded first, and there is no need to immediately cache data. The display of the material to be processed in the work board also includes: responding to the material adding operation, and determining the material to be processed according to the material adding operation; obtaining the uniform resource locator of the material to be processed; and adding the uniform resource locator of the material to be processed to the work board.

[0118] It should be noted that the material adding operation can be to select the material to be edited from the favorites through the material management function module and add the material to be edited to the work board; or to add the material to be edited through the material management function module and add the material to be edited to the work board, which is not limited in this embodiment. Among them, the material to be processed can be the material to be edited selected from the favorites or the material to be edited added through the material management function module, which is not limited in this embodiment.

[0119] It should be understood that URL (Uniform Resource Locator) can be a string used to identify and locate resources. In order to improve the software response speed, in this embodiment, when adding materials to the work board, only the URL can be loaded (that is, only the URL of the material is cached in the work board), and there is no need to cache data immediately. Only when the content is actually accessed or modified, the data is loaded and cached through the URL, thereby reducing unnecessary consumption of storage space.

[0120] Of course, in order to achieve a quick response, in this embodiment, the material can also be directly loaded when adding the material to the work board, that is, the material can be directly cached in the work board. Since the material has been downloaded locally during the initial loading, the user can get an immediate response when accessing the content, thereby reducing waiting time.

[0121] Step S50: In response to a function selection operation, a function module interface and selected material corresponding to the selected function module are displayed, wherein the selected function module is a function module selected from multiple function modules according to the function selection operation, and the selected material is a material selected from the material to be processed according to the material selection operation.

[0122] It should be noted that the function selection operation may be an operation of selecting any function module from multiple function modules to process the material to be processed (such as selecting a material analysis function module from multiple function modules to perform secondary analysis on the material to be processed). The function module interface corresponding to the selected function module may be an operation interface corresponding to the selected function module.

[0123] For ease of understanding, refer to Figure 7 This invention is provided for illustration, but is not intended to limit the present application. Figure 7 This is another schematic diagram of the software interaction interface of an embodiment of the image material collection method of the present application. In the figure, as an example, it is assumed that the execution subject is a computer, and a software interaction interface is displayed on the computer. The software interaction interface includes a navigation area, a function module interface and a work board. The function modules in the navigation area include material management, material analysis and report export. The function selection operation is to select the material analysis function module to perform a secondary analysis on material A (the underline in the figure indicates that it is selected), then the function module interface is switched to the material analysis interface, and material A is displayed in the material analysis interface. The material analysis interface also includes multiple material analysis components (such as area selection, secondary temperature measurement and secondary thermal imaging, etc., not shown in the figure), and the user can click on the material analysis component to perform a secondary analysis on material A.

[0124] Furthermore, since only the uniform resource locator is loaded during the initial loading, and no data caching is performed, when the content is actually accessed or modified, data needs to be loaded and cached through the URL, and the function module interface and the selected material corresponding to the selected function module are displayed in response to the function selection operation, including: obtaining the uniform resource locator of the selected material; loading the selected material according to the uniform resource locator of the selected material; and processing the loaded selected material through the selected function module.

[0125] Step S60: After the selected functional module completes processing of the selected material, the processed material is cached in the work board.

[0126] In a specific implementation, after the selected functional module completes processing of the selected material, caching the processed material into the work board may be storing data of the processed material in a memory.

[0127] For ease of understanding, refer to Figure 8 This invention is provided for illustration, but is not intended to limit the present application. Figure 8 This is another schematic diagram of the software interaction interface of an embodiment of the image material collection method of the present application. In the figure, as an example, it is assumed that the execution subject is a computer, and a software interaction interface is displayed on the computer. The software interaction interface includes a navigation area, a function module interface and a work board. The function modules in the navigation area include material management, material analysis and report export. The function selection operation is to select the material analysis function module to perform a secondary analysis on material A (the underline in the figure indicates that it is selected). After the material analysis function module completes the secondary analysis of material A, the material A' obtained by the secondary analysis is displayed in the material analysis interface. At the same time, material A' is also displayed on the work board.

[0128] Furthermore, in order to avoid memory explosion caused by the increase in the amount of materials, after the selected functional module completes processing of the selected materials, the processed materials are cached in the working board, including: after the selected functional module completes processing of the selected materials, the material size of the processed materials is obtained; according to the material size, a target storage space is selected, wherein the target storage space includes memory or disk; and based on the target storage space, the processed materials are cached in the working board.

[0129] It should be understood that in order to avoid memory explosion caused by the increase in the amount of material, in this embodiment, when the memory space is insufficient, part of the data can also be stored in the disk. In the specific implementation, the material size of the processed material is obtained, and it is determined whether the material size of the processed material is smaller than the free space size of the memory space. If so, the memory is selected as the target storage space, and the processed material is cached in the work board, which is essentially storing the data of the processed material in the memory; if not, the disk is selected as the target storage space, and the processed material is cached in the work board, which is essentially storing the data of the processed material in the disk; of course, in order to further increase the storage space, in this embodiment, the data of the processed material can also be stored in the server, and this embodiment does not limit this.

[0130] Furthermore, in order to overcome the defect that the related technology needs to rely on files to achieve data synchronization between modules and realize flexible switching between various functional modules, in this embodiment, after the selected functional module completes processing of the selected material and caches the processed material in the work board, it also includes: displaying the cached material in the work board, wherein the cached material is the processed material cached in the work board, and the processed material is the material processed by at least one functional module among multiple functional modules; in response to the function switching operation, displaying the function module interface and target material corresponding to the switched function module, wherein the switched function module is the function module selected from multiple function modules according to the function switching operation, and the target material is the material selected from the cached material according to the function switching operation; after the switched function module completes processing of the target material, displaying the processing result of the switched function module.

[0131] It should be understood that the application scenario of the embodiment of the present application can be to analyze and process image materials through software, wherein the material can be an object for software to edit, process and read data, and the material can include JPEG files, thermal radiation pictures, audio-visual pictures, and thermal radiation videos, etc., which are not limited in this embodiment. A thermal radiation picture can be a picture file in which thermal radiation data and all data required for secondary analysis (such as content data and metadata) are attached to a JPEG file. The content data is the actual data content. In a specific implementation, the content data can be text data (such as articles), image data (such as illustrations), audio data (such as recordings), video data (such as continuous frames), and sensor data (such as temperature, radiation, pressure), etc. In a thermal radiation picture, the core content data can include thermal radiation data and thermal imaging screenshots (JPEG). In an audio-visual picture, the core content data can include audio data and cloud picture screenshots. Metadata is data that provides background information required to understand other data, that is, data that describes data. Metadata can include structured metadata and descriptive metadata, which are used to describe the structure, data elements, relationships and other characteristics of the data. Without metadata, such as the unit gram, the number 8 is meaningless. In a specific implementation, metadata may include file system date information, processing parameters, sequence files, audit trails, or data required to reconstruct analysis activities.

[0132] It can be understood that, in this embodiment, the cached material is visualized so that the user can directly understand the current status of the material used for secondary analysis or exporting reports.

[0133] It should be understood that this embodiment achieves flexible switching between various functional modules by caching the results of various functional modules to the work board and realizing fast data synchronization between modules through caching. Therefore, in this embodiment, the cached material can be processed in response to the function switching operation and according to the function switching operation, wherein the function switching operation can be an operation of switching from one functional module to another functional module (such as switching from the material analysis functional module to the report export functional module).

[0134] For ease of understanding, refer to Fig. 9 This invention is provided for illustration, but is not intended to limit the present application. Fig. 9This is another schematic diagram of the software interaction interface of an embodiment of the image material collection method of the present application. In the figure, as an example, it is assumed that the execution subject is a computer, and a software interaction interface is displayed on the computer. The software interaction interface includes a navigation area, a functional module interface and a work board. The functional modules in the navigation area include material management, material analysis and report export. The function switching operation is to switch from secondary analysis of material A' to report export of material A' (the underline in the figure indicates that it is selected), then the functional module interface is switched from the material analysis interface to the report output interface, and material A' is displayed in the report output interface. The report output interface also includes multiple report output components, and the user can click the report output component to process the material A'.

[0135] Furthermore, in order to facilitate users to manage materials, in this embodiment, the ability to edit materials in the work board is provided to users through material visualization. Before the function switching operation is responded to, the function module interface corresponding to the switched function module and the target material are displayed, it also includes: responding to the material management operation, wherein the material management operation includes at least one of a deletion operation, a sequence adjustment operation and a grouping operation; editing the cached material according to the material management operation to obtain the edited material; accordingly, in response to the function switching operation, the function module interface corresponding to the switched function module and the target material are displayed, including: in response to the function switching operation, the function module interface corresponding to the switched function module and the edited material are displayed.

[0136] In order to realize the cleaning of cache, in this embodiment, the work board supports the delete operation, that is, the user can delete the cached materials in the work board through the delete operation; in order to facilitate the subsequent material analysis, in this embodiment, the work board also supports the order adjustment operation, that is, the user can adjust the order of the cached materials in the work board through the order adjustment operation; in order to realize material group analysis and material switching by group and improve the analysis efficiency, in this embodiment, the work board also supports the grouping function, that is, the user can group the cached materials in the work board through the grouping operation. Of course, in addition to the above three material management operations, the work board can also support other material management operations, which are not limited in this embodiment.

[0137] It should be understood that after the switched functional module completes processing of the target material, the processing result of the switched functional module may be displayed on the report export interface, or may be output, and this embodiment does not impose any limitation on this.

[0138] Compared with the related art that requires two software to realize the analysis function and the output report function respectively, in this embodiment, the results of each functional module are cached to the work board, and the data between modules are quickly synchronized through the cache, so that only one software is needed to realize the combination of multiple functional modules.

[0139] It should be understood that, considering that the processing method of related image materials relies on files to achieve data synchronization between modules, the erroneous operation of saving files is irreversible, and users need to back up. Therefore, in order to overcome the above defects, in this embodiment, cache is used to quickly synchronize data between modules (rather than relying on files), and only when a file save operation is received, the original file will be saved according to the file save operation, so there is no need to worry about dirtying the original file (such as inspection or scientific research materials, which have high storage value and can be used as evidence, can be used as historical data to predict the future, etc.).

[0140] After displaying the cached material in the work board, the method further includes: in response to a file saving operation, selecting a material to be saved from the cached material according to the file saving operation; writing the material to be saved into an original file corresponding to the material to be saved, obtaining a target file, and outputting the target file.

[0141] It should be understood that, considering that the processing method of related image materials relies on files to achieve data synchronization between modules, the erroneous operation of saving files is irreversible, and users need to back up. Therefore, in order to overcome the above defects, in this embodiment, cache is used to quickly synchronize data between modules (rather than relying on files), and only when a file save operation is received, the original file will be saved according to the file save operation, so there is no need to worry about dirtying the original file (such as inspection or scientific research materials, which have high storage value and can be used as evidence, can be used as historical data to predict the future, etc.).

[0142] It can be understood that writing the material to be saved into the original file corresponding to the material to be saved may be writing the material to be saved into the storage space corresponding to the original file.

[0143] This embodiment uses the cache to quickly synchronize data between modules. Only when a file saving operation is received, the original file is saved according to the file saving operation, so there is no need to worry about dirtying the original file.

[0144] It is understandable that the thermal radiation image needs to be provided to the application software for secondary analysis, so the consistency and parsability of the format will be ensured when designing the content data and metadata format, and JPEG has a standard metadata protocol, such as Exif or GPS. Similarly, similar designs are also used in audio and video images. Since all data in thermal radiation images or audio and video images have corresponding fixed file formats, parsing is supported. Therefore, in this embodiment, the imported image material can be parsed according to the fixed file format to obtain the original data of the imported image material, wherein the fixed file format can be pre-set.

[0145] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the image material collection method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0146] This application also provides an image material collection device, please refer to Fig.10 , the image material collection device comprises:

[0147] The material parsing module 10 is used to parse the imported image material in response to the material import operation for the favorites, and obtain the original data of the imported image material;

[0148] The material processing module 20 is used to pre-process the original data to obtain target data, wherein the pre-processing is to extract key data of the imported image material from the original data;

[0149] The material collection module 30 is used to store the target data into the favorites folder and construct a data index corresponding to the target data in the favorites folder.

[0150] The image material collection device provided by the present application adopts the image material collection method in the above embodiment, which can solve the technical problem that the related image material collection method directly stores the image material in the file system and stores the URL of the image material in the favorites, thereby having the defects of slow material reading speed and poor favorites performance. Compared with the related technology, the beneficial effects of the image material collection device provided by the present application are the same as the beneficial effects of the image material collection method provided by the above embodiment, and the other technical features in the image material collection device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0151] The present application provides an image material collection device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the image material collection method in the above-mentioned embodiment one.

[0152] Reference below Fig.11, which shows a schematic diagram of the structure of an image material collection device suitable for implementing the embodiment of the present application. The image material collection device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Fig.11 The image material collection device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0153] like Fig.11 As shown, the image material collection device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a ROM (Read Only Memory) 1002 or a program loaded from a storage device 1003 to a RAM (Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the image material collection device are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, an LCD (Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the image material collection device to communicate with other devices wirelessly or by wire to exchange data. Although the image material collection device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0154] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0155] The image material collection device provided by the present application adopts the image material collection method in the above embodiment, which can solve the technical problem that the related image material collection method directly stores the image material in the file system and stores the URL of the image material in the favorites, thereby having the defects of slow material reading speed and poor favorites performance. Compared with the related technology, the beneficial effects of the image material collection device provided by the present application are the same as the beneficial effects of the image material collection method provided by the above embodiment, and the other technical features in the image material collection device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0156] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0157] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0158] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, wherein the computer-readable program instructions are used to execute the image material collection method in the above-mentioned embodiment.

[0159] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable Read Only Memory), optical fiber, CD-ROM (CD-Read Only Memory, portable compact disk read-only memory), optical storage device, magnetic storage device, or any suitable combination of the above. In the present embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0160] The computer-readable storage medium may be included in the image material collection device; or may exist independently without being assembled into the image material collection device.

[0161] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the image material collection device, the image material collection device executes the image material collection method described above.

[0162] The computer program code for performing the operation of the present application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a LAN (Local Area Network) or a WAN (Wide Area Network), or it can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0163] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a 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. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0164] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0165] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned image material collection method, and can solve the technical problem that the related image material collection method directly stores the image material into the file system and stores the URL of the image material into the favorites, thereby having the defects of slow material reading speed and poor favorites performance. Compared with the related art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the image material collection method provided by the above-mentioned embodiment, and will not be repeated here.

[0166] The above descriptions are only some embodiments of the present application, and are not intended to limit the protection scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the protection scope of the present application.

Claims

1. A method for collecting image materials, characterized in that: The image material collection method comprises: In response to a material import operation for a favorites folder, the imported image material is parsed to obtain original data of the imported image material; Preprocessing the original data to obtain target data, wherein the preprocessing is to extract key data of the imported image material from the original data; The target data is stored in the favorites folder, and a data index corresponding to the target data is constructed in the favorites folder.

2. The image material collection method according to claim 1, characterized in that: The preprocessing of the original data to obtain target data includes: Extracting key data of the imported image material from the original data; Performing data conversion on the key data to obtain converted data; The key data and the converted data are classified to obtain target data.

3. The image material collection method according to claim 2, characterized in that: The key data includes at least one or a combination of multiple items of thermal radiation data, temperature matrix data, shooting time, text note content, temperature measurement configuration parameters, and thermal imaging configuration parameters.

4. The image material collection method according to claim 2, characterized in that: The converted data includes compressed data and / or thumbnails; The step of converting the key data to obtain converted data includes: Compressing the key data to obtain compressed data, wherein the compressed data is compressed thermal radiation data; And / or, the image material is compressed according to the key data to obtain a thumbnail, and the thumbnail is a thermal imaging thumbnail.

5. The image material collection method according to any one of claims 1 to 4, characterized in that: After storing the target data into the favorites and constructing a data index corresponding to the target data in the favorites, the method further includes: responding to an image retrieval operation for the favorites and determining an image retrieval category and an image retrieval condition according to the image retrieval operation; Searching the favorites for a target data category that matches the image retrieval category; The target data of the target data category matching the image search category is searched for search data that satisfies the image search condition, and the search data that satisfies the search condition is displayed.

6. The image material collection method according to any one of claims 1 to 4, characterized in that: After storing the target data into the favorites and constructing a data index corresponding to the target data in the favorites, the method further includes: In response to a secondary analysis operation on the favorites, obtaining a data index corresponding to the secondary analysis operation; Adjusting the target data corresponding to the data index corresponding to the secondary analysis operation to obtain adjusted data; Acquiring data required for secondary analysis, wherein the data required for secondary analysis includes the adjusted data; Perform secondary analysis on the image material according to the data required for the secondary analysis, obtain secondary analysis results, and display the secondary analysis results.

7. The image material collection method according to any one of claims 1 to 4, characterized in that: After storing the target data into the favorites and constructing a data index corresponding to the target data in the favorites, the method further includes: In response to a batch processing operation on the favorites, obtaining a data index corresponding to the batch processing operation; Acquire batch processing data from the favorites according to the data index corresponding to the batch processing operation; The batch processing data is batch processed according to the batch processing operation to obtain a batch processing result, and the batch processing result is displayed.

8. The image material collection method according to any one of claims 1 to 4, characterized in that: After storing the target data into the favorites and constructing a data index corresponding to the target data in the favorites, the method further includes: In response to an image viewing operation on the favorites, obtaining a data index corresponding to the image viewing operation; Selecting part of the target data from the favorites according to the data index corresponding to the image viewing operation; A thumbnail image and / or attribute information of the thumbnail image corresponding to the image viewing operation is generated based on part of the target data, and the thumbnail image and / or attribute information of the thumbnail image is displayed.

9. The image material collection method according to any one of claims 1 to 4, characterized in that: After storing the target data into the favorites and constructing a data index corresponding to the target data in the favorites, the method further includes: Displaying the material to be processed in the work board, wherein the material to be processed is an image material generated according to the target data stored in the favorites; In response to the function selection operation, displaying the function module interface and the selected material corresponding to the selected function module, wherein the selected function module is a function module selected from a plurality of function modules according to the function selection operation, and the selected material is a material selected from the to-be-processed material according to the material selection operation; After the selected function module completes processing of the selected material, the processed material is cached in the work board.

10. The image material collection method according to claim 9, characterized in that: After the selected function module completes processing of the selected material and caches the processed material into the work board, the method further includes: Displaying cached materials in the work board, wherein the cached materials are processed materials cached in the work board, and the processed materials are materials processed by at least one functional module among the multiple functional modules; In response to the function switching operation, displaying a function module interface and a target material corresponding to the switched function module, wherein the switched function module is a function module selected from the plurality of function modules according to the function switching operation, and the target material is a material selected from the cached materials according to the function switching operation; After the post-switching functional module completes processing of the target material, the processing result of the post-switching functional module is displayed.

11. An image material collection device, characterized in that: The image material collection device comprises: A material parsing module, configured to, in response to a material import operation for a favorites folder, parse the imported image material to obtain original data of the imported image material; A material processing module, used for preprocessing the original data to obtain target data, wherein the preprocessing is to extract key data of the imported image material from the original data; The material collection module is used to store the target data into the favorites folder and construct a data index corresponding to the target data in the favorites folder.

12. An image material collection device, characterized in that: The image material collection device comprises: a memory, a processor, and an image material collection program stored in the memory and executable on the processor. When the image material collection program is executed by the processor, the image material collection method according to any one of claims 1 to 10 is implemented.

13. A storage medium, characterized in that: The storage medium stores an image material collection program, and when the image material collection program is executed by the processor, the image material collection method according to any one of claims 1 to 10 is implemented.

Images