CN116503494A - Infrared image generation method, device, equipment and storage medium - Google Patents
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Abstract
The invention discloses an infrared image generation method, an infrared image generation device, infrared image generation equipment and a storage medium. The method comprises the following steps: determining temperature areas in the detection areas and quantitative values of temperatures of the temperature areas according to original thermal imaging signals acquired by the infrared thermal imaging sensor; determining the mapping relation between the temperature grade and the color system according to the quantized value of the temperature of each temperature area, the number of the temperature grade and the preset color system; performing color mapping according to quantized values of temperatures of all temperature areas and mapping relations between temperature levels and color systems to generate candidate infrared images, and determining labeling information of the candidate infrared images based on a preset object recognition model; and processing the candidate infrared images according to the target display layers, the target display object types and the labeling information to generate target infrared images. According to the technical scheme, the available information in the signals can be extracted more comprehensively, and accurate and effective infrared images can be generated.
Description
Technical Field
The present invention relates to the field of image technologies, and in particular, to a method, an apparatus, a device, and a storage medium for generating an infrared image.
Background
Along with the wide application of the infrared thermal imaging sensor in the fields of fire scene rescue, post-disaster fire inference and the like, the requirement on the image quality of the imaging of the infrared thermal imaging sensor is higher and higher.
How to process the signals collected by the infrared thermal imaging sensor, more comprehensively extract the available information in the signals, generate accurate and effective infrared images, and assist related personnel to more accurately evaluate and judge the fire scene environment is a problem to be solved at present.
Disclosure of Invention
The invention provides an infrared image generation method, an infrared image generation device, infrared image generation equipment and a storage medium, which can more comprehensively extract available information in signals and generate accurate and effective infrared images.
According to an aspect of the present invention, there is provided an infrared image generation method including:
determining temperature areas in the detection areas and quantitative values of temperatures of the temperature areas according to original thermal imaging signals acquired by the infrared thermal imaging sensor;
determining the mapping relation between the temperature grade and the color system according to the quantized value of the temperature of each temperature area, the number of the temperature grade and the preset color system;
performing color mapping according to quantized values of temperatures of all temperature areas and mapping relations between temperature levels and color systems to generate candidate infrared images, and determining labeling information of the candidate infrared images based on a preset object recognition model;
and processing the candidate infrared images according to the target display layers, the target display object types and the labeling information to generate target infrared images.
According to another aspect of the present invention, there is provided an infrared image generation apparatus including:
the numerical value determining module is used for determining temperature areas in the detection areas and quantized numerical values of temperatures of the temperature areas according to original thermal imaging signals acquired by the infrared thermal imaging sensor;
the relation determining module is used for determining the mapping relation between the temperature grade and the color system according to the quantized value of the temperature of each temperature area, the number of the temperature grade and the preset color system;
the information determining module is used for carrying out color mapping according to the quantized value of the temperature of each temperature region and the mapping relation between the temperature level and the color system, generating a candidate infrared image, and determining the labeling information of the candidate infrared image based on a preset object identification model;
and the image generation module is used for processing the candidate infrared images according to the target display layer, the target display object category and the labeling information to generate target infrared images.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the infrared image generation method of any one of the embodiments of the present invention.
According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to execute the method for generating an infrared image according to any embodiment of the present invention.
According to the technical scheme, according to the original thermal imaging signals acquired by the infrared thermal imaging sensor, temperature areas in the detection area and quantized values of temperatures of the temperature areas are determined; determining the mapping relation between the temperature grade and the color system according to the quantized value of the temperature of each temperature area, the number of the temperature grade and the preset color system; performing color mapping according to quantized values of temperatures of all temperature areas and mapping relations between temperature levels and color systems to generate candidate infrared images, and determining labeling information of the candidate infrared images based on a preset object recognition model; and processing the candidate infrared images according to the target display layers, the target display object types and the labeling information to generate target infrared images. Through processing the signals collected by the infrared thermal imaging sensor, the available information in the signals can be extracted more comprehensively, accurate and effective infrared images are generated, and related personnel are assisted to evaluate and judge the fire scene environment more accurately.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of an infrared image generation method according to an embodiment of the present invention;
FIG. 2 is a flowchart of an infrared image generation method according to a second embodiment of the present invention;
fig. 3 is a block diagram of an infrared image generation device according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," "target," "candidate," "alternative," and the like in the description and claims of the invention and in the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that, as the infrared thermal imaging sensor is widely applied to the fields of fire scene rescue, post-disaster fire inference and the like, the imaging quality of the infrared thermal imaging sensor is related to the quality and density of materials sensitive to infrared spectrum in the sensor and the average infrared thermal radiation of an imaging scene. In special cases such as fire, the following problems are liable to occur: the imaging content of infrared thermal imaging is easily affected by large flames and high-heat smoke particles, so that a phenomenon similar to overexposure (particularly shown as a red or white picture in a scene) occurs, and at the moment, the picture loses part of key information (such as the position and the condition of other things on fire) which are still important and still relatively low in temperature, so that rescue work is affected.
In addition, various materials with different combustion temperatures cannot be effectively distinguished from thermal imaging during combustion, and the traditional method for directly reducing brightness and exposure on a thermal imaging picture is easy to fail to identify information of a low-temperature object.
In order to solve the problem that the traditional thermal imaging cannot accurately image the global picture of the fire scene, the invention provides an infrared thermal imaging sensor signal enhancement scheme aiming at the fire scene, which can process the original thermal imaging signal to generate a more accurate infrared image, improve the available information quantity of imaging data, assist firefighters to evaluate and judge the fire scene environment more accurately, and particularly provide a detailed description for the following embodiments.
Example 1
Fig. 1 is a flowchart of an infrared image generation method according to an embodiment of the present invention. The embodiment is applicable to the case of performing enhancement processing on thermal imaging signals acquired by an infrared thermal imaging sensor to obtain a more accurate and effective infrared image, and the method may be performed by an infrared image generating device, which may be implemented in hardware and/or software, and the infrared image generating device may be configured in an electronic device, such as an infrared thermal imaging sensor. As shown in fig. 1, the infrared image generation method includes:
s101, determining temperature areas in the detection areas and quantitative values of temperatures of the temperature areas according to original thermal imaging signals acquired by the infrared thermal imaging sensor.
The infrared thermal imaging sensor is a preset sensor capable of acquiring thermal signals in the surrounding environment to generate a color heat map (i.e. infrared image). The infrared thermal imaging sensor can be used for example for collecting signals of fire phenomena in a fire scene. The original thermal imaging signal is a digital signal which is converted by an infrared thermal imaging sensor based on the collected infrared radiation. The detection area refers to an area within the detection range of the infrared thermal imaging sensor. The temperature areas refer to the area ranges with the same communicated temperatures in the detection areas, and the detection areas can comprise at least one temperature area, wherein each temperature area corresponds to one temperature, for example, the detection area can comprise two temperature areas, the quantization value of the first temperature area is 50 degrees, and the quantization value of the other temperature area is 100 degrees.
Optionally, an infrared thermal imaging sensor may be used to collect signals in a detection area of a fire scene (fire scene), determine an original thermal imaging signal of the detection area, further analyze the infrared radiation in the original thermal imaging signal based on a preset rule, determine a temperature area in the detection area, and quantify the infrared radiation into corresponding numbers according to the infrared radiation in different temperature areas, so as to determine a quantified value of the temperature in each temperature area.
S102, determining the mapping relation between the temperature grade and the color system according to the quantized value of the temperature of each temperature area, the number of the temperature grade and the preset color system.
The number of temperature levels refers to the number of temperature levels divided by the target, that is, the number of temperature ranges divided by the target in all temperature areas. The preset color system refers to a series of colors of the same color system, for example, red color system and blue color system. Each color system contains at least two different degrees of color of the same color system. The mapping relation between the temperature level and the color system can represent the corresponding relation between the temperature level and different colors in the color system.
Optionally, determining the mapping relationship between the temperature level and the color system according to the quantized value of the temperature in each temperature region, the number of the temperature levels and the preset color system includes: classifying the temperature areas according to the distance relation among the temperature areas in the detection area based on a preset clustering algorithm, and determining a distribution interval according to a clustering result; determining the temperature range of the distribution interval according to the quantized value of the temperature area contained in the distribution interval; determining the temperature range of each temperature grade according to the temperature range of the distribution interval and the number of preset temperature grades; and determining the mapping relation between the temperature grade and the color system according to the preset color system, the temperature range of each temperature grade and the number of the temperature grades.
Alternatively, all the obtained temperature values may be classified by a clustering algorithm, so as to obtain one or more main intervals of the temperature value distribution, i.e. a distribution interval is determined.
Alternatively, after the distribution interval is determined, the maximum value and the minimum value among the quantized values of the temperature region included in the distribution interval may be used as the upper boundary value and the lower boundary value of the temperature range of the distribution interval, thereby determining the temperature range of the distribution interval.
Optionally, after determining the temperature range of the distribution interval, the temperature range of the distribution interval may be divided into sub-temperature ranges according to the number of preset temperature levels, and each temperature level and each sub-temperature range are in one-to-one correspondence, so as to determine the temperature range of each temperature level.
Optionally, determining the mapping relationship between the temperature level and the color system according to the preset color system, the temperature range of each temperature level, and the number of the temperature levels includes: determining a corresponding number of target colors from a preset color system according to the number of the temperature levels, and matching the corresponding target colors for each temperature level; and generating a mapping relation between the temperature grade and the color system according to the corresponding condition of each temperature grade and the target color and the temperature range of each temperature grade.
It should be noted that, after the mapping relationship between the temperature level and the color system is determined according to the corresponding situation of each temperature level and the target color and the temperature range of each temperature level, for each temperature level, there is a unique temperature range corresponding to each temperature level, and at the same time, there is one color corresponding to the unique color system, that is, the target color.
Optionally, after determining the distribution interval, the method further includes: if the number of the determined distribution intervals is at least two, determining a mapping relation between the temperature level and the color system for each distribution interval; if the number of the determined distribution intervals is one, the mapping relation between the temperature level and the color system is directly determined.
If the number of distribution intervals is at least two, the number of corresponding color systems is also at least two.
Alternatively, if the number of the determined distribution intervals is at least two, the above-mentioned operation of determining the mapping relationship between the temperature level and the color system may be performed for each distribution interval, so as to generate the mapping relationship. If the number of the determined distribution intervals is one, the determination of the mapping relationship between the temperature level and the color system may be directly performed for the distribution intervals.
S103, performing color mapping according to quantized values of temperatures of all temperature areas and mapping relations of temperature levels and color systems, generating candidate infrared images, and determining labeling information of the candidate infrared images based on a preset object recognition model.
The candidate infrared image is an infrared image generated after the original infrared image corresponding to the original thermal imaging signal is subjected to color mapping. The object recognition model refers to a pre-trained model which can carry out target detection on the image to recognize different objects in the image.
Optionally, for each temperature region, determining a temperature level to which the quantized value of the temperature region belongs, further determining a target color corresponding to the temperature level according to a mapping relation between the temperature level and a color system, mapping the color of the temperature region to the corresponding target color, and determining an original infrared image after performing color mapping on all the temperature regions as a generated candidate infrared image.
Optionally, determining the labeling information of the candidate infrared image based on the preset object recognition model includes: and carrying out object recognition processing on the candidate infrared images by adopting a pre-trained object recognition model, marking according to a recognition result, and determining marking information of the candidate infrared images. The object recognition model may be, for example, a YOLO (You Only Look Once) object detection model. The annotation information may be annotation information indicating the number, position, type, and the like of the target objects included in the candidate infrared image.
Optionally, after generating the candidate infrared image, the method further includes: determining a region belonging to a preset dark color range under a color system in the candidate infrared image as a high-temperature image layer of the candidate infrared image; and determining the low-temperature image layer of the candidate infrared image according to the region belonging to the preset light color range under the color system in the candidate infrared image.
And S104, processing the candidate infrared images according to the target display layers, the target display object types and the labeling information to generate target infrared images.
The target display layer refers to a layer to be displayed in the candidate infrared images specified by related personnel. The target display object category refers to the category of the target object to be displayed in the candidate infrared image specified by the related personnel.
Optionally, the target display layer is a low-temperature layer and/or a high-temperature layer; the target display object type is flame, corridor or door or window.
Optionally, the labeling information of the candidate infrared image may be screened according to the type of the object to be displayed, the labeling information of the object to be displayed and the target display layer are displayed on the candidate infrared image, the information of the other objects except the object to be displayed and the other display layers except the target display layer are hidden, and the processed candidate infrared image is determined to be the target infrared image.
Optionally, after the target infrared image is determined, the target infrared image can be displayed in a visual manner, that is, the processed infrared image and the labeling information are displayed. And the method is convenient for related personnel to rapidly analyze the field environment.
According to the technical scheme, according to the original thermal imaging signals acquired by the infrared thermal imaging sensor, temperature areas in the detection area and quantized values of temperatures of the temperature areas are determined; determining the mapping relation between the temperature grade and the color system according to the quantized value of the temperature of each temperature area, the number of the temperature grade and the preset color system; performing color mapping according to quantized values of temperatures of all temperature areas and mapping relations between temperature levels and color systems to generate candidate infrared images, and determining labeling information of the candidate infrared images based on a preset object recognition model; and processing the candidate infrared images according to the target display layers, the target display object types and the labeling information to generate target infrared images. Through processing the signals collected by the infrared thermal imaging sensor, the available information in the signals can be extracted more comprehensively, accurate and effective infrared images are generated, and related personnel are assisted to evaluate and judge the fire scene environment more accurately.
Example two
FIG. 2 is a flowchart of an infrared image generation method according to a second embodiment of the present invention; the present embodiment proposes a preferred example of processing the original thermal imaging signal data to generate a color thermal map (i.e., a target infrared image) with a mark and after optimizing imaging based on the above embodiments. As illustrated in fig. 2, the method comprises the following steps:
acquiring original thermal imaging signal data: the original signal is a digital signal converted according to the collected infrared radiation, and the temperature in different ranges of the target area is quantified.
The main distribution interval of the temperature values is obtained: and classifying all obtained temperature values through a clustering algorithm to obtain one or more main intervals of temperature value distribution.
Temperature interval evaluation: the corresponding adjustment algorithm is matched through the quantity judgment of the main temperature interval distribution.
If there is only one main interval of the temperature distribution, the logic of updating the color mapping in the temperature range corresponding to each temperature level is obtained according to the temperature interval range (the difference between the highest temperature and the lowest temperature) and the temperature level to be displayed (the specific formula is as follows). If the temperature range of the main temperature interval is 20-220 degrees, 100 temperature levels need to be displayed, and each temperature level corresponds to 2 degrees. 20 degrees to 22 degrees are the first stage, 22 degrees to 24 degrees are the second stage, and so on.
For example, if t_max=temperature maximum, t_min=temperature minimum, l=the number of temperature levels to be displayed, t_max=the temperature maximum corresponding to each temperature level, t_min=the temperature maximum corresponding to each temperature level, and t_del=the temperature range corresponding to each temperature level, then:
t_max＝T_max/L
t_min＝T_min/L
t_del＝(T_max-T_min)/L
if there are multiple main sections of temperature distribution, the color mapping logic is updated for each section according to the temperature difference range in each main section by the same method. Such as two main temperature intervals, ranging from 20 degrees to 220 degrees, and 500 degrees to 800 degrees, 100 temperature levels and 30 temperature levels, respectively, need to be displayed. For the first temperature interval, each temperature level corresponds to 2 degrees. 20 degrees to 22 degrees are the first stage, 22 degrees to 24 degrees are the second stage, and so on. For the second temperature interval, each temperature level corresponds to 10 degrees. 500 degrees to 510 degrees are the first stage, 510 degrees to 520 degrees are the second stage, and so on.
Mapping the colors according to the temperature values: one color is matched for each temperature progression under each color mapping logic to express the same temperature range. For example, the two main temperature ranges are 20 degrees to 220 degrees and 500 degrees to 800 degrees, and 100 temperature levels and 30 temperature levels need to be displayed respectively. For the first temperature interval, a color system a is assigned, and each temperature level corresponds to 2 degrees. 20 degrees to 22 degrees are the first level, mapping color A1, 22 degrees to 24 degrees are the second level, mapping color A2, and so on. For the second temperature interval, a color system B is assigned, each temperature level representing 3 degrees. 500 degrees to 510 degrees are the first level, mapping color B1, 510 degrees to 520 degrees are the second level, mapping color B2, and so on.
Generating a color heat map: the color heat map is produced in a layer mode, one layer is created for each color system, namely each temperature distribution interval, and a user can display and hide different layers according to ROI (Range of Interest), namely the temperature distribution concerned by the user. In a fire scene, a firefighter needs to obtain key information of relatively low temperature but still important, and the layer Gao Wenxian can be hidden, namely, large flame and smoke particles with high temperature are filtered out from an image, so that influence on rescue work is reduced.
Object recognition and labeling based on the color heat map are carried out through an object recognition pre-training model: and respectively carrying out targeted identification on each layer by adopting an identification model such as YOLO. And frame extraction and category labeling are carried out, different recognition objects are preset on different temperature layers, so that the recognition efficiency and accuracy are greatly enhanced (for example, only open fire is recognized on a high-temperature layer, the possibility of recognizing flames of different shapes into temperature-mismatched objects such as adults is avoided while the efficiency is increased, and the accuracy is greatly enhanced).
Overlapping the temperature layer and object identification and labeling categories according to requirements: under the holding of the multi-layer scheme, the layers to be displayed and the labeling objects to be displayed can be combined at will. If the object identification of high temperature and low temperature is overlapped by adopting the display low temperature diagram, the interference of large high temperature flame and smoke can be avoided on the picture, the states of people and building structures can be seen more clearly, and meanwhile, the specific positions of objects which interfere with the sight but are still important, such as flame, high temperature smoke and the like, can be known through marked objects.
And finally outputting the color heat map with the mark and after the optimized imaging.
Example III
Fig. 3 is a block diagram of an infrared image generation device according to a third embodiment of the present invention; the infrared image generating device provided by the embodiment of the invention can be suitable for strengthening the thermal imaging signal acquired by the infrared thermal imaging sensor to obtain a more accurate and effective infrared image, can be realized in a hardware and/or software form and is configured in equipment with an infrared image generating function, as shown in fig. 3, and specifically comprises:
the value determining module 301 is configured to determine a temperature region in the detection region and a quantized value of a temperature of each temperature region according to an original thermal imaging signal acquired by the infrared thermal imaging sensor;
the relationship determining module 302 is configured to determine a mapping relationship between the temperature level and the color system according to the quantized value of the temperature in each temperature area, the number of the temperature levels, and a preset color system;
the information determining module 303 is configured to perform color mapping according to the quantized value of the temperature of each temperature region and the mapping relationship between the temperature level and the color system, generate a candidate infrared image, and determine labeling information of the candidate infrared image based on a preset object recognition model;
the image generating module 304 is configured to process the candidate infrared image according to the target display layer, the target display object category, and the labeling information, and generate a target infrared image.
According to the technical scheme, according to the original thermal imaging signals acquired by the infrared thermal imaging sensor, temperature areas in the detection area and quantized values of temperatures of the temperature areas are determined; determining the mapping relation between the temperature grade and the color system according to the quantized value of the temperature of each temperature area, the number of the temperature grade and the preset color system; performing color mapping according to quantized values of temperatures of all temperature areas and mapping relations between temperature levels and color systems to generate candidate infrared images, and determining labeling information of the candidate infrared images based on a preset object recognition model; and processing the candidate infrared images according to the target display layers, the target display object types and the labeling information to generate target infrared images. Through processing the signals collected by the infrared thermal imaging sensor, the available information in the signals can be extracted more comprehensively, accurate and effective infrared images are generated, and related personnel are assisted to evaluate and judge the fire scene environment more accurately.
Further, the relationship determination module 302 may include:
the interval determining unit is used for classifying the temperature areas according to the distance relation among the temperature areas in the detection area based on a preset clustering algorithm and determining a distribution interval according to a clustering result;
a first range determining unit, configured to determine a temperature range of the distribution interval according to a quantized value of a temperature region included in the distribution interval;
a second range determining unit, configured to determine a temperature range of each temperature level according to a temperature range of the distribution interval and a preset number of temperature levels;
and the relation determining unit is used for determining the mapping relation between the temperature grade and the color system according to the preset color system, the temperature range of each temperature grade and the number of the temperature grades.
Further, the relationship determination unit is specifically configured to:
determining a corresponding number of target colors from a preset color system according to the number of the temperature levels, and matching the corresponding target colors for each temperature level;
and generating a mapping relation between the temperature grade and the color system according to the corresponding condition of each temperature grade and the target color and the temperature range of each temperature grade.
Further, the relationship determination module 302 is further configured to:
if the number of the determined distribution intervals is at least two, determining a mapping relation between the temperature level and the color system for each distribution interval;
if the number of the determined distribution intervals is one, the mapping relation between the temperature level and the color system is directly determined.
Further, the device is also used for:
determining a region belonging to a preset dark color range under a color system in the candidate infrared image as a high-temperature image layer of the candidate infrared image;
and determining the low-temperature image layer of the candidate infrared image according to the region belonging to the preset light color range under the color system in the candidate infrared image.
Further, the information determining module 303 is specifically configured to:
performing object recognition processing on the candidate infrared images by adopting a pre-trained object recognition model, marking according to recognition results, and determining marking information of the candidate infrared images; the object recognition model is a YOLO target detection model.
Further, the target display layer is a low-temperature layer and/or a high-temperature layer; the target display object type is flame, corridor or door and window.
Example IV
Fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention. Fig. 4 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 4, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as an infrared image generation method.
In some embodiments, the infrared image generation method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the infrared image generation method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the infrared image generation method in any other suitable way (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method of generating an infrared image, comprising:
determining temperature areas in the detection areas and quantitative values of temperatures of the temperature areas according to original thermal imaging signals acquired by the infrared thermal imaging sensor;
determining the mapping relation between the temperature grade and the color system according to the quantized value of the temperature of each temperature area, the number of the temperature grade and the preset color system;
performing color mapping according to quantized values of temperatures of all temperature areas and mapping relations between temperature levels and color systems to generate candidate infrared images, and determining labeling information of the candidate infrared images based on a preset object recognition model;
and processing the candidate infrared images according to the target display layers, the target display object types and the labeling information to generate target infrared images.
2. The method of claim 1, wherein determining the mapping between the temperature level and the color system based on the quantized value of the temperature in each temperature zone, the number of temperature levels, and the preset color system comprises:
classifying the temperature areas according to the distance relation among the temperature areas in the detection area based on a preset clustering algorithm, and determining a distribution interval according to a clustering result;
determining the temperature range of the distribution interval according to the quantized value of the temperature area contained in the distribution interval;
determining the temperature range of each temperature grade according to the temperature range of the distribution interval and the number of preset temperature grades;
and determining the mapping relation between the temperature grade and the color system according to the preset color system, the temperature range of each temperature grade and the number of the temperature grades.
3. The method of claim 2, wherein determining the mapping between the temperature level and the color system based on the preset color system, the temperature range of each temperature level, and the number of temperature levels comprises:
determining a corresponding number of target colors from a preset color system according to the number of the temperature levels, and matching the corresponding target colors for each temperature level;
and generating a mapping relation between the temperature grade and the color system according to the corresponding condition of each temperature grade and the target color and the temperature range of each temperature grade.
4. The method of claim 2, wherein after the determining the distribution interval, further comprising:
if the number of the determined distribution intervals is at least two, determining a mapping relation between the temperature level and the color system for each distribution interval;
if the number of the determined distribution intervals is one, the mapping relation between the temperature level and the color system is directly determined.
5. The method of claim 1, further comprising, after generating the candidate infrared image:
determining a region belonging to a preset dark color range under a color system in the candidate infrared image as a high-temperature image layer of the candidate infrared image;
and determining the low-temperature image layer of the candidate infrared image according to the region belonging to the preset light color range under the color system in the candidate infrared image.
6. The method of claim 1, wherein determining labeling information for the candidate infrared image based on a predetermined object recognition model comprises:
performing object recognition processing on the candidate infrared images by adopting a pre-trained object recognition model, marking according to recognition results, and determining marking information of the candidate infrared images; the object recognition model is a YOLO target detection model.
7. The method of claim 1, wherein the target presentation layer is a low temperature layer and/or a high temperature layer; the target display object type is flame, corridor or door and window.
8. An infrared image generation apparatus, comprising:
the numerical value determining module is used for determining temperature areas in the detection areas and quantized numerical values of temperatures of the temperature areas according to original thermal imaging signals acquired by the infrared thermal imaging sensor;
the relation determining module is used for determining the mapping relation between the temperature grade and the color system according to the quantized value of the temperature of each temperature area, the number of the temperature grade and the preset color system;
the information determining module is used for carrying out color mapping according to the quantized value of the temperature of each temperature region and the mapping relation between the temperature level and the color system, generating a candidate infrared image, and determining the labeling information of the candidate infrared image based on a preset object identification model;
and the image generation module is used for processing the candidate infrared images according to the target display layer, the target display object category and the labeling information to generate target infrared images.
9. An electronic device, the electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the infrared image generation method of any one of claims 1-7.
10. A computer readable storage medium storing computer instructions for causing a processor to perform the method of generating an infrared image according to any one of claims 1-7.
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| CN117455119B (en) * | 2023-11-24 | 2024-04-09 | 佛山市盈科工程造价咨询事务所有限公司 | Night engineering project cost progress supervision method, system, equipment and medium |
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