CN111866394A - Photographing method, photographing device, terminal and computer-readable storage medium - Google Patents
Photographing method, photographing device, terminal and computer-readable storage medium Download PDFInfo
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Abstract
The present application belongs to the field of photographing technologies, and in particular, to a photographing method, apparatus, terminal, and computer-readable storage medium, where the method includes: acquiring a preview frame image, and detecting a target object contained in the preview frame image; acquiring characteristic information of the target object, and calculating shooting parameters of a shooting frame image according to the characteristic information; receiving a photographing instruction, wherein the photographing instruction carries the photographing parameters; acquiring a picture corresponding to the shooting parameter according to the shooting instruction; the acquiring of the characteristic information of the target object and the calculating of the shooting parameters of the shooting frame image according to the characteristic information comprise: and acquiring the chromaticity of the target object, and calculating the saturation of the photographed frame image according to the chromaticity of the target object. By the method, the technical problem that the picture meeting the user requirement cannot be obtained through the post processing of the picture in the later shooting period is effectively solved, and the shooting quality of the picture is improved.
Description
Technical Field
The present application belongs to the field of photographing technologies, and in particular, to a photographing method, apparatus, terminal, and computer-readable storage medium.
Background
With the continuous development of image processing technology, post-processing of images has become mature, such as image denoising, resolution reconstruction, background blurring, style transformation, and the like.
However, image post-processing still has certain limitations, for example, for underexposed photos or out-of-focus photos, photos meeting the requirements of users can not be obtained by processing the photos usually.
Disclosure of Invention
The embodiment of the application provides a photographing method, a photographing device, a terminal and a computer-readable storage medium, which can solve the technical problem that a photo meeting the requirements of a user cannot be obtained by processing the photo.
A first aspect of an embodiment of the present application provides a photographing method, including:
acquiring a preview frame image, and detecting a target object contained in the preview frame image;
acquiring characteristic information of the target object, and calculating shooting parameters of a shooting frame image according to the characteristic information;
receiving a photographing instruction, wherein the photographing instruction carries the photographing parameters;
acquiring a picture corresponding to the shooting parameter according to the shooting instruction;
the obtaining of the feature information of the target object and the calculating of the shooting parameters of the shot frame image according to the feature information include: and acquiring the chromaticity of the target object, and calculating the saturation of the photographed frame image according to the chromaticity of the target object.
A second aspect of the embodiments of the present application provides a photographing apparatus, including:
a detection unit for acquiring a preview frame image and detecting a target object included in the preview frame image;
the calculating unit is used for acquiring the characteristic information of the target object and calculating the shooting parameters of the shooting frame image according to the characteristic information;
a receiving unit, configured to receive a photographing instruction, where the photographing instruction carries the photographing parameters;
the photographing unit is used for acquiring a photo corresponding to the photographing parameter according to the photographing instruction;
the calculating unit is specifically configured to:
and acquiring the chromaticity of the target object, and calculating the saturation of the photographed frame image according to the chromaticity of the target object.
A third aspect of the embodiments of the present application provides a terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method when executing the computer program.
A fourth aspect of the embodiments of the present application provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the above method.
In the embodiment of the application, in the shooting process before shooting, the target object contained in the preview frame image is detected in real time, and the characteristic information of the target object is obtained, so that the shooting parameters of the shooting frame image are calculated according to the characteristic information, when a shooting instruction is received, shooting can be performed according to the shooting parameters, when the picture is shot, shooting is performed according to the characteristic information of the target object in real time, the picture with the best shooting effect is obtained, the technical problem that the picture meeting the requirements of a user cannot be obtained through post-processing of the picture in the later shooting period is effectively solved, and the shooting quality of the picture is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a schematic flowchart of a first implementation of a photographing method provided in an embodiment of the present application;
fig. 2 is a schematic flowchart of a second implementation of a photographing method according to an embodiment of the present application;
fig. 3 is a schematic flowchart of a first specific implementation of step 102 of a photographing method according to an embodiment of the present application;
fig. 4 is a schematic flowchart of a second specific implementation of step 102 of the photographing method provided in the embodiment of the present application;
fig. 5 is a schematic diagram of a saturation label picture provided in an embodiment of the present application;
fig. 6 is a schematic structural diagram of a photographing device according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a terminal according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
In addition, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not intended to indicate or imply relative importance.
In order to explain the technical solution of the present application, the following description will be given by way of specific examples.
Before android 5.0, manual control of camera shooting parameters can be realized only by changing a system, an application program interface API (application program interface) Camera1.0 of a camera is not friendly, and the Camera1.0 is similar to a black box with an advanced control function and is not concerned about the shooting parameters of each frame of image shot by the camera. Starting from android 5.0, a new application program interface API Camera2.0 capable of completely controlling the android device camera is introduced, so that the shooting parameters of each frame of image shot by the camera are controlled, and the camera has stronger flexibility.
In the embodiment of the application, in the shooting process before shooting, the target object contained in the preview frame image is detected in real time, and the characteristic information of the target object is obtained, so that the shooting parameters of the shooting frame image are calculated according to the characteristic information, meanwhile, when a shooting instruction is received, the shooting parameters of the camera are set to be the shooting parameters calculated according to the characteristic information, when the picture is shot, the shooting parameters of the frame image shot by the camera at the next moment can be adjusted in real time according to the characteristic information of the target object, so that the picture with the best shooting effect is obtained, the technical problem that the picture meeting the requirements of a user cannot be obtained through post-processing of the picture in the later shooting stage is effectively solved, and the shooting quality of the picture is improved.
Fig. 1 shows a schematic flow chart of a photographing method implemented by an embodiment of the present application, where the method is applied to a terminal, can be executed by a photographing device configured on the terminal, and is suitable for a situation where a quality of a photo needs to be improved, and includes steps 101 to 104.
The terminal comprises terminal equipment such as a smart phone, a tablet personal computer and a learning machine, wherein the terminal equipment is provided with a photographing device. The terminal device can be provided with applications such as a photographing application, a browser and a WeChat.
In step 101, a preview frame image is acquired, and a target object included in the preview frame image is detected.
The preview frame image refers to a frame image generated by a camera collecting an external optical signal when the photographing application is in a preview state. The method comprises the steps that data output by an external optical signal collected by a camera each time are called frame data, a user enters a preview mode after starting a photographing application on a terminal, and the terminal obtains frame data collected by the camera and displays the frame data to obtain a preview frame image.
Generally, the frame data is captured at a frequency of 30 frames per 1 second, and is generally divided into a preview frame and a photographing frame for previewing and photographing, respectively.
In the embodiment of the application, the preview frame image is acquired in real time in the preview state, and the target object contained in the preview frame image is detected, so that the characteristic information of the target object in the current state is acquired in real time.
The target object refers to a target object currently being photographed, for example, when the target object currently belongs to a person for photographing, the target object is a person, and when the target object currently belongs to a building for photographing, the target object is a building. It should be noted that one or more target objects may be present in the preview frame image, and the types of the target objects may be one or more.
The detection of the target object contained in the preview frame image includes performing target detection on the preview frame image, classifying the foreground and the background at a pixel level, removing the background, and retaining one or more target objects, i.e., one or more target objects.
In some embodiments of the present application, the target object in the preview frame image may be detected by a target detection algorithm, and common target detection algorithms include a Local Binary Pattern (LBP) algorithm, a directional gradient feature combination support vector machine model, a Convolutional Neural Network (CNN) model, and the like. Compared with other target detection algorithms, the convolutional neural network model can realize more accurate and rapid detection of the target object, so that the trained convolutional neural network model can be selected to detect the target object in the preview frame image.
Before the trained convolutional neural network model is used for detecting the target object in the preview frame image, the trained convolutional neural network model needs to be obtained first. The trained convolutional neural network model is obtained by training according to each sample image and the detection result corresponding to each sample image, wherein the detection result corresponding to each sample image is used for indicating all target objects contained in the sample image.
Optionally, the training step of the convolutional neural network model may include: acquiring a sample image and a detection result corresponding to the sample image; and detecting the sample image by using a convolutional neural network model, adjusting parameters of the convolutional neural network model according to a detection result until the adjusted convolutional neural network model can detect all target objects in the sample image, or detecting that the accuracy rate of the target objects in the sample image is greater than a preset value, and taking the adjusted convolutional neural network model as a trained convolutional neural network model. The parameters of the convolutional neural network model may include the weight, deviation, and coefficient of the regression function of each convolutional layer in the convolutional neural network model, and may further include a learning rate, iteration times, the number of neurons in each layer, and the like. At present, the conventional Convolutional Neural Network models include an RCNN (region based Convolutional Neural Network) model, a Fast-RCNN model, and the like. The fast-RCNN model is evolved on the basis of the RCNN model and the fast-RCNN model, and compared with the RCNN model and the fast-RCNN model, the fast-RCNN model still cannot realize real-time detection of the target object, but has higher target detection precision and target detection speed compared with the RCNN model and the fast-RCNN model, so that in some embodiments of the application, the fast-RCNN model is preferred to the convolutional neural network model.
It should be noted that, the method for detecting the target object is only illustrated here, and is not meant to limit the scope of the present application, and other methods that can achieve target object detection are also applicable to the present application, and are not listed here.
the obtaining of the feature information of the target object and the calculating of the shooting parameters of the shot frame image according to the feature information include: and acquiring the chromaticity of the target object, and calculating the saturation of the photographed frame image according to the chromaticity of the target object.
The feature information of the target object is used to determine what shooting parameters are required to be used for shooting to achieve a good shooting effect. The photographing frame image is a frame image generated by a camera according to a photographing instruction and used for generating a final photo.
The feature information of the target object may include a chromaticity of the target object, and the shooting parameter of the shot frame image may include a saturation of the shot frame image. In addition, in some optional embodiments, the feature information of the target object may include position information of the target object in the preview frame image, and motion state information of the target object and chromaticity of the target object, and is used for calculating a photometric area, a focal length, an exposure parameter and saturation of the photographing frame image according to the position information, the motion state information and the chromaticity of the target object, so as to achieve an optimal photographing effect. It should be noted that, this is merely an example, and in some embodiments of the present application, the feature information of the target object may further include other more feature information. For example, facial expression information and height information.
In step 103, a photographing instruction is received, where the photographing instruction carries the photographing parameters.
In this embodiment of the application, the triggering manner of the photographing instruction may be triggered by using an existing triggering manner, for example, by clicking a photo shooting selection control in a photographing interface or by pressing a volume key, which is not described herein again.
In step 104, a photo corresponding to the shooting parameter is obtained according to the shooting instruction.
In the embodiment of the application, when a user starts a photographing application, the terminal obtains a target object contained in a preview frame image by acquiring the preview frame image in real time, and obtains photographing parameters of the photographing frame image according to characteristic information of the target object, so that after a photographing instruction is received, a photo corresponding to the photographing parameters can be obtained according to the photographing parameters.
In the embodiment of the application, in the shooting process before shooting, the target object contained in the preview frame image is detected in real time, and the characteristic information of the target object is obtained, so that the shooting parameters of the shooting frame image are calculated according to the characteristic information, meanwhile, when a shooting instruction is received, the shooting parameters of the camera are set to be the shooting parameters calculated according to the characteristic information, when the picture is shot, the shooting parameters of the frame image shot by the camera at the next moment can be adjusted in real time according to the characteristic information of the target object, so that the picture with the best shooting effect is obtained, the technical problem that the picture meeting the requirements of a user cannot be obtained through post-processing of the picture in the later shooting stage is effectively solved, and the shooting quality of the picture is improved.
Optionally, in some embodiments of the application, as shown in fig. 2, when the target object is a person, the method may include: step 201 to step 204.
In step 201, a preview frame image is obtained, and a target face included in the preview frame image is detected.
In step 202, feature information of the target face is obtained, and a shooting parameter of a shooting frame image is calculated according to the feature information, where the feature information of the target face includes a chromaticity of the target face, or the feature information of the target face includes the chromaticity of the target face, and position information and/or motion state information of the target face.
In step 203, a photographing instruction is received, where the photographing instruction carries the photographing parameters.
In step 204, a photo of the person corresponding to the shooting parameters is obtained according to the shooting instruction.
For example, a target face included in the preview frame image is obtained by face feature point recognition, and then the chromaticity of the target face in the preview frame image, or the chromaticity of the target face in the preview frame image, and the position information and/or the motion state information of the target face in the preview frame image are obtained, and then the saturation of the photographed frame image is calculated according to the chromaticity of the target face, or the saturation of the photographed frame image is calculated according to the chromaticity of the target face, and the photometric area and the focal length of the photographed frame image are calculated according to the position information of the target face, so as to avoid the blurred or dark picture face caused by the error of the focusing and photometric positions, and/or the exposure parameter of the photographed frame image is calculated according to the motion state of the target face, so as to avoid the blurred picture face caused by the shutter speed not being right when a person runs, the best face shooting effect is realized.
In some embodiments of the present application, when the photographic subject is a person, the detection of the target object included in the preview frame image may be to detect a plurality of target objects included in the preview frame image, for example, target objects such as a human face, clothes, and arm movements.
In the above-described embodiment, the step 102 of acquiring the feature value information of the target object and calculating the shooting parameters of the shooting frame image according to the feature information may include: acquiring the position information of the target object in the preview frame image, and calculating a light metering area and a focal length of the photographing frame image according to the position information; and/or acquiring the motion state information of the target object, and calculating the exposure parameter of the photographing frame image according to the motion speed of the characteristic point in the motion state information.
The selection of the light measuring area is one of the important bases for accurately selecting the shutter and aperture values. The photometry system of the camera is generally used to measure the brightness of light reflected by a subject, and is also called reflective photometry. The camera automatically assumes that the light reflectance of the photometric area is 18%, and the photometry is performed by this ratio, and then the values of the aperture and the shutter, which are related, are determined, and under the same illumination condition, if the same exposure amount is obtained, the larger the aperture value is, the smaller the shutter value is required, and if the aperture value is smaller, the larger the shutter value is required. The 18% value is derived from the appearance of neutral (grey) shades in natural scenes, where there is more white in the viewfinder, and more than 18% reflected light, which reflects about 90% of the incident light in the case of a completely white scene, and perhaps only a few percent of the reflectance in the case of a black scene. The standard gray card is an 8 x 10 inch card, the gray card is placed on the same light measuring source of a subject, the obtained light measuring region overall reflection rate is 18% of the standard, and then only the shot needs to be carried out according to the aperture shutter value given by the camera, and the shot picture is accurate in exposure. If the total reflectance of the entire photometric area is greater than 18%, for example, the background of the photometric area is mainly white, and if the image is taken according to the aperture shutter value automatically measured by the camera, the image will be an underexposed image, and the white background will appear grayed out, and if the image is a white paper, the image will become a black paper. Therefore, when a scene with a light reflection rate of more than 18% is photographed, the exposure compensation value EV of the camera needs to be increased. Conversely, if a scene with a light reflectance of less than 18% is taken, such as a black background, the taken picture tends to be overexposed and the black background becomes gray. Therefore, scenes with a light reflectance of less than 18% are photographed, and it is necessary to reduce EV exposure.
The current photometry methods mainly include central average photometry, central local photometry, spot photometry, multi-spot photometry and evaluative photometry. The embodiment of the present application exemplifies the selection of the light metering region by means of the center average light metering.
The center averaging metering is mainly in consideration of the fact that a general photographer is accustomed to placing a subject, that is, a target subject to be accurately exposed, in the middle of a viewfinder, and therefore the shooting contents are the most important. Therefore, the sensing element responsible for metering can organically divide the whole metering value of the camera, the metering data of the central part occupies most proportion, and the metering data outside the center of the picture plays an auxiliary role of metering as a small proportion. And obtaining photometric data shot by the camera through the proportion obtained by weighted and averaged two grid values by a processor of the camera. For example, it is set that the photometry data of the central portion of the camera occupies 75% of the entire photometry proportion, and the photometry data of the other non-central portion gradually extending to the edge occupies 25% of the proportion.
It can be seen that after the position of the target object is determined, the photometric area needs to be selected, for example, the position of the target object is set as the central part of the photometric area.
In addition, the focal length of the camera is generally selected by emitting a group of infrared rays or other rays by the camera head, determining the distance of the shot object after the rays are reflected by the shot object, and then adjusting the lens combination according to the measured distance to realize automatic focusing. Therefore, it is also necessary to obtain the focal length of the photographed frame image after the position of the target object is determined.
Optionally, in some embodiments of the application, as shown in fig. 3, the acquiring motion state information of the target object, and calculating an exposure parameter of the photo frame image according to a motion speed of a feature point in the motion state information includes: step 301 to step 303.
In step 301, obtaining preview frame images of a first preset frame number, and calculating the position change of a target object feature point in each adjacent preview frame image;
in step 302, calculating an average movement speed of the target object according to the position change and the acquisition period of the preview frame image;
in step 303, the shutter speed and the aperture parameter corresponding to the average moving speed of the target object are acquired.
For example, the first preset frame number is 30 frames, the target object is a human face, the human face feature points include eye feature points, nose feature points, mouth feature points and eyebrow feature points, and the acquisition period of the preview frame image is 30 frames/second. The method comprises the steps of obtaining 30 frames of preview frame images continuously shot by a camera, calculating the position change of a eyebrow center characteristic point in each adjacent preview frame image, accumulating the position change, obtaining the average motion speed of a human face, and obtaining the shutter speed and the aperture parameter of the shot frame image by searching a corresponding relation list of the shutter speed and the aperture parameter and the motion speed of an object.
The first preset frame number may be a frame number set by a user in a self-defined manner according to different shooting scenes, or may be a frame number set by default in factory, for example, 20 frames, 30 frames, 40 frames, or 50 frames, which is only illustrated here and is not meant to limit the scope of the present application.
Optionally, in some embodiments of the present application, as shown in fig. 4, the obtaining of the chromaticity of the target object and the calculating of the saturation of the photo frame image according to the chromaticity includes steps 401 to 402.
In step 401, a first chromaticity of the target object and a second chromaticity of a comparison picture selected by a user are obtained;
in step 402, the saturation of the photographed frame image is calculated according to the difference between the first chromaticity and the second chromaticity.
Color is commonly represented by lightness and chroma, which are properties of a color excluding lightness that reflects the hue and saturation of the color. And calculating the difference value of the first chroma and the second chroma by acquiring the first chroma of the target object and the second chroma of the comparison picture selected by the user, and obtaining the saturation adjustment size of the photographing frame image.
As shown in fig. 5, the comparison picture selected by the user may be saturation label pictures 50 pre-stored by the terminal, each saturation label picture representing a saturation value of a hue;
for example, when the image belongs to a person shooting currently, the target object may be a person's clothing, and the difference between the first chromaticity and the second chromaticity is calculated by obtaining the first chromaticity of the clothing and the second chromaticity of the comparison picture selected by the user, so as to obtain the saturation of the photographed frame image.
Optionally, the selected picture is a photograph arbitrarily selected by the user, and the second chroma of the reference picture may be the chroma of a certain area selected by the user in the photograph.
In the embodiment of the photographing method described in fig. 1 to fig. 5, in step 104, acquiring the photo corresponding to the photographing parameter according to the photographing instruction may include: and acquiring a second preset frame number of photographing frame images corresponding to the photographing parameters, and synthesizing the second preset frame number of photographing frame images into a photo corresponding to the photographing parameters.
For example, average fusion is carried out on pixel values of corresponding positions of the photographed frame images with a second preset frame number to obtain a picture corresponding to the photographing parameters; or taking the middle value of the pixel value of the corresponding position of the photographed frame image with the second preset frame number to synthesize the pixel value into a photo corresponding to the photographing parameter so as to optimize the photographing effect of the photo.
The second preset frame number may be a frame number set by a user in a self-defined manner, or may be a frame number set by a factory default, for example, 10 frames, 15 frames, 20 frames, or 30 frames, which is only an example and is not meant to limit the scope of the present application.
Fig. 6 shows a schematic structural diagram of a photographing apparatus 600 provided in an embodiment of the present application, which includes a detection unit 601, a calculation unit 602, a receiving unit 603, and a photographing unit 604.
A detection unit 601 configured to acquire a preview frame image and detect a target object included in the preview frame image;
a calculating unit 602, configured to obtain feature information of the target object, and calculate a shooting parameter of the shooting frame image according to the feature information;
a receiving unit 603, configured to receive a photographing instruction, where the photographing instruction carries the photographing parameters;
a photographing unit 604, configured to obtain a photo corresponding to the photographing parameter according to the photographing instruction;
the calculating unit 602 is specifically configured to:
and acquiring the chromaticity of the target object, and calculating the saturation of the photographed frame image according to the chromaticity of the target object.
In some embodiments of the present application, the detecting unit is specifically configured to acquire a preview frame image and detect a target face included in the preview frame image; correspondingly, the obtaining of the feature information of the target object and the calculating of the shooting parameters of the shot frame image according to the feature information includes: and acquiring feature information of the target face, and calculating shooting parameters of a shooting frame image according to the feature information, wherein the feature information of the target face comprises the chromaticity of the target face, or the feature information of the target face comprises the chromaticity of the target face, and position information and/or motion state information of the target face.
In some embodiments of the present application, the calculating unit is specifically configured to acquire position information of the target object in the preview frame image, and calculate a light metering area and a focal length of the photo frame image according to the position information; and/or acquiring the motion state information of the target object, and calculating the exposure parameter of the photographing frame image according to the motion speed of the characteristic point in the motion state information.
In some embodiments of the present application, the calculating unit is further specifically configured to acquire preview frame images of a first preset number of frames, and calculate a position change of a target object feature point in each adjacent preview frame image; calculating the average movement speed of the target object according to the position change and the acquisition period of the preview frame image; and acquiring the shutter speed and the aperture parameter corresponding to the average motion speed of the target object.
In some embodiments of the present application, the calculating unit is further specifically configured to obtain a first chromaticity of the target object and a second chromaticity of a user-selected comparison picture; and calculating the saturation of the photographed frame image according to the difference value of the first chroma and the second chroma.
Optionally, the detection unit is specifically configured to detect a target object included in the preview frame image by using a trained convolutional neural network model.
Optionally, the photographing unit is further specifically configured to acquire a second preset frame number of photographing frame images corresponding to the photographing parameters, and synthesize the photographing frame images with the preset frame number into a photo corresponding to the photographing parameters.
It should be noted that, for convenience and brevity of description, the specific working process of the photographing apparatus 600 described above may refer to the corresponding process of the method described in fig. 1 to fig. 5, and is not described herein again.
As shown in fig. 7, the present application provides a terminal for implementing the above-mentioned photographing method, where the terminal may be a mobile terminal, and the mobile terminal may be a terminal such as a smart phone, a tablet computer, a Personal Computer (PC), a learning machine, and includes: one or more input devices 73 (only one shown in fig. 7) and one or more output devices 74 (only one shown in fig. 7). The processor 71, memory 72, input device 73, output device 74, and camera 75 are connected by a bus 76. The camera is used for generating a preview frame image and a photographing frame image according to the collected external light signals.
It should be understood that, in the embodiment of the present Application, the Processor 71 may be a Central Processing Unit (CPU), and the Processor may also be other general processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The input device 73 may include a virtual keyboard, a touch pad, a fingerprint sensor (for collecting fingerprint information of a user and direction information of the fingerprint), a microphone, etc., and the output device 74 may include a display, a speaker, etc.
The memory 72 stores a computer program that is executable on the processor 71, for example, a program of a photographing method. The processor 71 implements the steps of the photographing method embodiment, such as the steps 101 to 104 shown in fig. 1, when executing the computer program. Alternatively, the processor 71, when executing the computer program, implements the functions of the modules/units in the device embodiments, such as the functions of the units 601 to 604 shown in fig. 6.
The computer program may be divided into one or more modules/units, which are stored in the memory 72 and executed by the processor 71 to complete the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used for describing the execution process of the computer program in the terminal for taking pictures. For example, the computer program may be divided into a detection unit, a calculation unit, a reception unit, and a photographing unit, and each unit functions specifically as follows: a detection unit for acquiring a preview frame image and detecting a target object included in the preview frame image; the calculating unit is used for acquiring the characteristic information of the target object and calculating the shooting parameters of the shooting frame image according to the characteristic information; a receiving unit, configured to receive a photographing instruction, where the photographing instruction carries the photographing parameters; the photographing unit is used for acquiring a photo corresponding to the photographing parameter according to the photographing instruction; the calculating unit is specifically configured to: and acquiring the chromaticity of the target object, and calculating the saturation of the photographed frame image according to the chromaticity of the target object.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned functions may be distributed as different functional units and modules according to needs, that is, the internal structure of the apparatus may be divided into different functional units or modules to implement all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal are merely illustrative, and for example, the division of the above-described modules or units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units described above, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above may be implemented by a computer program, which may be stored in a computer readable storage medium and used by a processor to implement the steps of the embodiments of the methods described above. The computer program includes computer program code, and the computer program code may be in a source code form, an object code form, an executable file or some intermediate form. The computer readable medium may include: any entity or device capable of carrying the above-described computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier signal, telecommunications signal, software distribution medium, and the like. It should be noted that the computer readable medium described above may include content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media that does not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A method of taking a picture, comprising:
acquiring a preview frame image, and detecting a target object contained in the preview frame image;
acquiring characteristic information of the target object, and calculating shooting parameters of a shooting frame image according to the characteristic information;
receiving a photographing instruction, wherein the photographing instruction carries the photographing parameters;
acquiring a picture corresponding to the shooting parameter according to the shooting instruction;
the acquiring of the characteristic information of the target object and the calculating of the shooting parameters of the shooting frame image according to the characteristic information comprise: and acquiring the chromaticity of the target object, and calculating the saturation of the photographed frame image according to the chromaticity of the target object.
2. The photographing method of claim 1, wherein the acquiring a preview frame image and detecting a target object included in the preview frame image comprises:
acquiring a preview frame image, and detecting a target face contained in the preview frame image;
correspondingly, the obtaining of the feature information of the target object and the calculating of the shooting parameters of the shooting frame image according to the feature information include:
and acquiring the feature information of the target face, and calculating shooting parameters of a shooting frame image according to the feature information, wherein the feature information of the target face comprises the chromaticity of the target face, or the feature information of the target face comprises the chromaticity of the target face, and the position information and/or the motion state information of the target face.
3. The photographing method according to claim 1 or 2, wherein the acquiring feature value information of the target object and calculating the photographing parameters of the photographing frame image according to the feature information comprises:
acquiring the position information of the target object in the preview frame image, and calculating a light metering area and a focal length of the photographing frame image according to the position information; and/or the presence of a gas in the gas,
and acquiring the motion state information of the target object, and calculating the exposure parameters of the photographing frame image according to the motion speed of the characteristic points in the motion state information.
4. The photographing method of claim 3, wherein the acquiring of the motion state information of the target object and the calculating of the exposure parameter of the photographed frame image according to the motion speed of the feature point in the motion state information comprises:
acquiring preview frame images with a first preset frame number, and calculating the position change of target object feature points in each adjacent preview frame image;
calculating the average movement speed of the target object according to the position change and the acquisition period of the preview frame image;
and acquiring a shutter speed and an aperture parameter corresponding to the average movement speed of the target object.
5. The photographing method of claim 1, wherein the obtaining of the chromaticity of the target object and the calculating of the saturation of the photographing frame image according to the chromaticity of the target object comprises:
acquiring a first chromaticity of the target object and a second chromaticity of a comparison picture selected by a user;
and calculating the saturation of the photographed frame image according to the difference value of the first chromaticity and the second chromaticity.
6. The photographing method of claim 1, wherein the acquiring a preview frame image and detecting a target object included in the preview frame image comprises:
and detecting a target object contained in the preview frame image by using the trained convolutional neural network model.
7. The photographing method of claim 1, wherein the obtaining of the picture corresponding to the photographing parameter according to the photographing instruction comprises:
and acquiring a photographing frame image with a second preset frame number corresponding to the photographing parameter, and synthesizing the photographing frame image with the second preset frame number into a photo corresponding to the photographing parameter.
8. A photographing apparatus, comprising:
the device comprises a detection unit, a processing unit and a display unit, wherein the detection unit is used for acquiring a preview frame image and detecting a target object contained in the preview frame image;
the calculating unit is used for acquiring the characteristic information of the target object and calculating the shooting parameters of the shooting frame image according to the characteristic information;
the receiving unit is used for receiving a photographing instruction, and the photographing instruction carries the photographing parameters;
the photographing unit is used for acquiring a photo corresponding to the photographing parameters according to the photographing instruction;
the computing unit is specifically configured to:
and acquiring the chromaticity of the target object, and calculating the saturation of the photographed frame image according to the chromaticity of the target object.
9. A terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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| CN202010785958.1A CN111866394A (en) | 2018-06-15 | 2018-06-15 | Photographing method, photographing device, terminal and computer-readable storage medium |
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| CN201810626707.1A CN108495050B (en) | 2018-06-15 | 2018-06-15 | Photographing method, photographing device, terminal and computer-readable storage medium |
| CN202010785958.1A CN111866394A (en) | 2018-06-15 | 2018-06-15 | Photographing method, photographing device, terminal and computer-readable storage medium |
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| CN201810626707.1A Division CN108495050B (en) | 2018-06-15 | 2018-06-15 | Photographing method, photographing device, terminal and computer-readable storage medium |
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| CN108495050A (en) | 2018-09-04 |
| WO2019237992A1 (en) | 2019-12-19 |
| CN108495050B (en) | 2020-09-04 |
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