CN115665542A - Picture processing method based on scene self-recognition and related device - Google Patents
Picture processing method based on scene self-recognition and related device Download PDFInfo
- Publication number
- CN115665542A CN115665542A CN202211356125.9A CN202211356125A CN115665542A CN 115665542 A CN115665542 A CN 115665542A CN 202211356125 A CN202211356125 A CN 202211356125A CN 115665542 A CN115665542 A CN 115665542A
- Authority
- CN
- China
- Prior art keywords
- picture
- scene
- processing
- photographing
- acquiring
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Studio Devices (AREA)
Abstract
The application discloses a picture processing method based on scene self-recognition and a related device, comprising the following steps: when the shooting task is detected to be started, the ambient environment information is acquired through a preset sensing device; determining a photographing scene according to the ambient environment information, and judging whether the photographing scene meets a preset condition; if so, acquiring a picture processing strategy according to the photographing scene; when an instruction for completing a shooting task is received, a shooting result is obtained according to the instruction; when the shooting result is a single target picture, processing the target picture by using the picture processing strategy; when the shooting result is a target picture set, acquiring a picture with the highest weight in the target picture set as a second target picture, and processing the second target picture through the picture processing strategy; the technical effect of automatically adjusting the shot picture according to the scene under the condition that the shooting processing is not required by the camera is achieved.
Description
Technical Field
The present application relates to the field of image processing, and in particular, to a method and an apparatus for processing an image based on scene self-recognition.
Background
With the rapid development of information technology, many electronic devices have a picture taking function, and a user can take a picture of a target scene or person through a camera on the electronic device. At present along with the upgrading of camera technique, can realize the modification to the picture in the shooting process, for example the camera of shooing will be automatic configures according to self hardware evening, also can realize shooing out steady photo under the condition that anti-shake mode was opened. However, the above-mentioned effects are to be achieved without expensive equipment in the current state of the art.
Therefore, how to adjust the scene of the photo by using the software processing technology to reduce the hardware cost becomes a technical problem to be solved urgently.
Disclosure of Invention
In order to perform scene adjustment on a photo by using a software processing technology so as to reduce hardware cost, the application provides a picture processing method based on scene self-recognition and a related device.
In a first aspect, the present application provides a method for processing an image based on scene self-recognition, which adopts the following technical solutions:
a picture processing method based on scene self-recognition comprises the following steps:
when the shooting task is detected to be started, acquiring surrounding environment information through a preset sensing device;
determining a photographing scene according to the ambient environment information, and judging whether the photographing scene meets a preset condition;
if so, acquiring a picture processing strategy according to the photographing scene;
when an instruction for completing a shooting task is received, a shooting result is obtained according to the instruction;
when the shooting result is a single target picture, processing the target picture by using the picture processing strategy;
and when the shooting result is a target picture set, acquiring a picture with the highest weight in the target picture set as a second target picture, and processing the second target picture through the picture processing strategy.
Optionally, the step of determining a photographing scene according to the ambient environment information and determining whether the photographing scene meets a preset condition includes:
determining the current photographing time according to the time information in the ambient environment information;
determining a current shooting subject according to role information in the surrounding environment information;
acquiring a strategy factor in the ambient environment information, and matching the current shooting atmosphere according to the strategy factor;
determining a current photographing scene according to the photographing moment, the photographing subject and the photographing atmosphere;
and judging whether the photographing scene meets a preset condition or not.
Optionally, the step of determining the current photographing scene according to the photographing time, the photographing subject and the photographing atmosphere includes:
determining the current photographing time period according to the photographing time;
determining the weight of the current photographed object according to the photographing subject;
and acquiring a scene set, and determining the current photographing scene in the scene set according to the photographing time period, the partial weight of the photographing object and the photographing atmosphere.
Optionally, the step of determining whether the shooting scene meets a preset condition includes:
acquiring a historical scene record, and acquiring a target comparison element in the historical scene record by combining scene elements in the photographing scene information;
acquiring a scene generation log corresponding to the target comparison element;
and judging whether the shooting scene meets a preset condition or not according to the scene generation log.
Optionally, the step of processing the target picture by using the picture processing policy includes:
acquiring photo adjustment basic information corresponding to the picture processing strategy;
adjusting the basic information of the target picture according to the picture adjustment basic information;
and processing the target picture after the basic information adjustment according to a photo effect strategy in the picture processing strategies.
Optionally, before the step of obtaining the photo with the highest weight in the target picture set as a second target picture and processing the second target picture through the picture policy, the method further includes:
acquiring all picture information in the target picture set;
and acquiring the film-out effect score corresponding to each picture in all the picture information, and performing weight distribution according to the film-out effect scores.
Optionally, after the step of acquiring, when the shooting result is a target picture set, a picture with the highest weight in the target picture set as a second target picture, and processing the second target picture through the picture processing policy, the method further includes:
acquiring a current processing record, and acquiring use feedback of the current processing record from a preset port;
and when the use feedback meets the recording condition, storing the current processing record into a historical picture processing record, and performing data cleaning on the historical picture processing record.
In a second aspect, the present application provides a picture processing apparatus based on scene self-recognition, including:
the information acquisition module is used for acquiring surrounding environment information through a preset sensing device when the shooting task is detected to be started;
the condition judgment module is used for determining a photographing scene according to the ambient environment information and judging whether the photographing scene meets a preset condition or not;
the strategy acquisition module is used for acquiring a picture processing strategy according to the photographing scene if the picture processing strategy is the same as the photographing scene;
the result acquisition module is used for acquiring a shooting result according to an instruction when the instruction for completing the shooting task is received;
the single picture processing module is used for processing the target picture by using the picture processing strategy when the shooting result is a single target picture;
and the picture set processing module is used for acquiring the picture with the highest weight in the target picture set as a second target picture when the shooting result is the target picture set, and processing the second target picture through the picture processing strategy.
In a third aspect, the present application provides a computer apparatus, the apparatus comprising: a memory, a processor that, when executing computer instructions stored by the memory, performs a method as in any one of the above.
In a fourth aspect, the present application provides a computer-readable storage medium comprising instructions which, when executed on a computer, cause the computer to perform the method as described above.
In summary, the present application includes the following advantageous technical effects:
when the shooting task is detected to be started, the surrounding environment information is acquired through a preset sensing device; determining a photographing scene according to the ambient environment information, and judging whether the photographing scene meets a preset condition; if so, acquiring a picture processing strategy according to the photographing scene; when an instruction for completing a shooting task is received, a shooting result is obtained according to the instruction; when the shooting result is a single target picture, processing the target picture by using the picture processing strategy; when the shooting result is a target picture set, obtaining a picture with the highest weight in the target picture set as a second target picture, and processing the second target picture through the picture processing strategy; the technical effect of automatically adjusting the shot picture according to the scene under the condition that the shooting processing is not required by the camera is achieved.
Drawings
FIG. 1 is a schematic diagram of a computer device architecture of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a first embodiment of a method for processing a picture based on scene self-recognition according to the present invention;
FIG. 3 is a flowchart illustrating a second embodiment of a picture processing method based on scene self-recognition according to the present invention;
fig. 4 is a block diagram of a first embodiment of the picture processing device based on scene self-recognition according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is further described in 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.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a computer device in a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the computer device may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in FIG. 1 does not constitute a limitation of a computer device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a storage medium, may include therein an operating system, a network communication module, a user interface module, and a scene-based self-recognition picture processing program.
In the computer device shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 of the computer device of the present invention may be disposed in a computer device, and the computer device calls the picture processing program based on scene self-recognition stored in the memory 1005 through the processor 1001 and executes the picture processing method based on scene self-recognition provided by the embodiment of the present invention.
An embodiment of the present invention provides a picture processing method based on scene self-recognition, and referring to fig. 2, fig. 2 is a schematic flow diagram of a first embodiment of the picture processing method based on scene self-recognition according to the present invention.
In this embodiment, the picture processing method based on scene self-recognition includes the following steps:
step S10: when the shooting task is detected to be started, the surrounding environment information is acquired through a preset sensing device.
It should be noted that the execution main body of the embodiment may be a mobile phone, a computer, or other electronic devices with a camera function, which is not limited in this embodiment, and in this embodiment, a device based on scene self-recognition is used as the execution main body of the embodiment.
It should be understood that the detection of the shooting task being turned on in this embodiment refers to the detection of the command of turning on the camera or the turning on of other shooting devices.
It can be understood that, in this embodiment, the preset sensing device refers to a sensing device that can obtain various items of target information, for example, a camera can obtain image information around the current picture taking time, and a built-in clock can obtain current time information.
In specific implementation, when it is detected that a shooting task is started, acquiring ambient environment information through a preset sensing device is that a current work process of an execution main body of the implementation is acquired, judging whether the shooting task is started according to the current work process, and after it is detected that the shooting task is started, acquiring ambient environment information through the preset sensing device, wherein the ambient environment information includes: time, scene image information, application scene information, and sound information.
It should be noted that a sensor (english name: transducer/sensor) is a detection device, which can sense the measured information and convert the sensed information into an electrical signal according to a certain rule or output information in other required forms, so as to meet the requirements of information transmission, processing, storage, display, recording, control, etc. The sensor features include: miniaturization, digitalization, intellectualization, multifunction, systematization and networking. The method is the first link for realizing automatic detection and automatic control. The existence and development of the sensor enable the object to have the senses of touch, taste, smell and the like, and the object slowly becomes alive. Generally, the sensor is classified into ten categories, such as a thermosensitive element, a photosensitive element, a gas-sensitive element, a force-sensitive element, a magnetic-sensitive element, a humidity-sensitive element, a sound-sensitive element, a radiation-sensitive element, a color-sensitive element, and a taste-sensitive element, according to their basic sensing functions.
Step S20: and determining a photographing scene according to the ambient environment information, and judging whether the photographing scene meets a preset condition.
In specific implementation, the time, scene image information, application scene information, and sound information in the ambient environment information are analyzed, and a photo scene is determined according to the ambient environment information, where the photo scene is one of a preset scene set, and may be defined by using requirements in the preset scene set, for example: romantic scenes, serious scenes, learning scenes, and the like.
It is understood that the corresponding scene corresponds to preset factors, and different factors set different criteria, for example, in the determination of serious scenes, the current sound information sets the lowest threshold.
In a specific implementation, the determining whether the photographing scene meets the preset condition refers to whether the photographing scene can be matched with the corresponding picture processing policy in this embodiment.
Step S30: if so, acquiring a picture processing strategy according to the shooting scene.
In specific implementation, if not, generating corresponding reminding information, feeding back factors which cannot realize picture processing specifically, and generating a guide on a photographing interface or reminding in a voice playing mode.
It can be understood that the picture processing policy, that is, a policy for performing special effect adjustment on a picture, includes: and adjusting the contrast and brightness of the picture and the picture frame. The processing strategies of the pictures are integrated in the strategy processing set, and the basic steps in the strategies can be orderly arranged through the strategy processing set. Different processing strategy effects are achieved by combining different basic adjustment steps.
Step S40: and when receiving an instruction for finishing the shooting task, acquiring a shooting result according to the instruction.
In specific implementation, when the shooting task is received to be completed, the shooting result corresponding to the current shooting task is obtained. The shooting result can be a single picture or a picture set.
Step S50: and when the shooting result is a single target picture, processing the target picture by using a picture processing strategy.
Further, in order to improve the processing effect of a single picture, the step of processing the target picture by using the picture processing policy includes: acquiring photo adjustment basic information corresponding to a picture processing strategy; carrying out basic information adjustment on the target picture according to the picture adjustment basic information; and processing the target picture after the basic information adjustment according to a photo effect strategy in the picture processing strategy.
It should be noted that the picture processing policy includes adjusting the overall proportion and size of the picture, so basic information adjustment needs to be performed on the picture first.
Step S60: and when the shooting result is the target picture set, acquiring the picture with the highest weight in the target picture set as a second target picture, and processing the second target picture through a picture processing strategy.
Further, in order to accurately acquire a second target picture, before the step of acquiring the picture with the highest weight in the target picture set as the second target picture and processing the second target picture through the picture policy, the method further includes: acquiring all picture information in a target picture set; and acquiring the film-out effect score corresponding to each picture in all the picture information, and performing weight distribution according to the film-out effect scores.
It should be noted that the score of the film-out effect in this embodiment refers to performing resolution analysis on all the pictures in the target picture set, and the resolution is directly proportional to the score of the film-out effect.
It can be understood that the score of the picture-out effect in this embodiment is set through a mapping relationship between the picture definition and the score.
Further, in order to improve the processing efficiency of the picture, after the step of acquiring, when the shooting result is the target picture set, the picture with the highest weight in the target picture set as the second target picture, and processing the second target picture through the picture processing policy, the method further includes: acquiring a current processing record, and acquiring use feedback of the current processing record from a preset port; and when the use feedback meets the recording condition, storing the current processing record into the historical picture processing record, and cleaning the historical picture processing record.
In the embodiment, when the shooting task is detected to be started, the surrounding environment information is acquired through the preset sensing device; determining a photographing scene according to the ambient environment information, and judging whether the photographing scene meets a preset condition; if so, acquiring a picture processing strategy according to the photographing scene; when an instruction for completing a shooting task is received, a shooting result is obtained according to the instruction; when the shooting result is a single target picture, processing the target picture by using the picture processing strategy; when the shooting result is a target picture set, acquiring a picture with the highest weight in the target picture set as a second target picture, and processing the second target picture through the picture processing strategy; the technical effect of automatically adjusting the shot picture according to the scene under the condition that the shooting processing is not required by the camera is achieved.
Referring to fig. 3, a flowchart of a second embodiment of the method for processing a picture based on scene self-recognition according to the present invention is shown.
Based on the first embodiment, the step S20 of the picture processing method based on scene self-recognition in this embodiment further includes:
step S201; and determining the current photographing time according to the time information in the ambient environment information.
In a specific implementation, the current photographing time is determined by the internal clock of the execution subject of the embodiment.
Step S202: and determining the current shooting subject according to the role information in the surrounding environment information.
It is understood that by acquiring image information in the surrounding environment information at the time of photographing, the person or article information within the current shot is acquired by the image recognition technology.
Step S203: and acquiring a strategy factor in the ambient environment information, and matching the current shooting atmosphere according to the strategy factor.
It should be noted that the policy factors are preset factors that can affect the judgment of the environmental mode, and the policy factors include keywords, types of target persons, and target articles. After identifying the policy factor, the corresponding detailed impact pattern will be matched according to the policy factor, for example, when a keyword appears: when the wedding is matched, the wedding mode corresponding to the keyword is matched, after the wedding mode is matched, the picture processing strategy is switched to the romantic mode, and laces and love are given to the shot pictures.
Step S204: and determining the current photographing scene according to the photographing moment, the photographing subject and the photographing atmosphere.
In specific implementation, key contents in the current photographing moment, the photographing subject and the photographing atmosphere are obtained, matching is performed in the photographing scene set according to the key contents, and when scenes meeting all the key contents are matched, the scenes are used as matching results.
Step S205: and judging whether the photographing scene meets a preset condition or not.
The embodiment determines the current photographing time according to the time information in the ambient environment information; determining a current shooting subject according to role information in the surrounding environment information; acquiring a strategy factor in the ambient environment information, and matching the current shooting atmosphere according to the strategy factor; determining a current photographing scene according to the photographing moment, the photographing subject and the photographing atmosphere; and judging whether the shooting scene meets the preset conditions or not, thereby realizing the technical effect of accurately determining the shooting scene according to the surrounding environment information.
Furthermore, an embodiment of the present invention further provides a computer-readable storage medium, where the storage medium stores a program for picture processing based on scene self-recognition, and the program for picture processing based on scene self-recognition, when executed by a processor, implements the steps of the method for picture processing based on scene self-recognition as described above.
Referring to fig. 4, fig. 4 is a block diagram illustrating a first embodiment of a picture processing apparatus based on scene self-recognition according to the present invention.
As shown in fig. 4, the picture processing apparatus based on scene self-recognition according to the embodiment of the present invention includes:
and the information acquisition module 10 is configured to acquire the ambient environment information through a preset sensing device when detecting that the shooting task is started.
And the condition judgment module 20 is configured to determine a shooting scene according to the ambient environment information, and judge whether the shooting scene meets a preset condition.
And the strategy acquisition module 30 is configured to acquire a picture processing strategy according to the photographing scene if the picture processing strategy is determined to be correct.
And the result acquiring module 40 is used for acquiring a shooting result according to the instruction when the instruction for completing the shooting task is received.
And the single picture processing module 50 is configured to process the target picture by using the picture processing policy when the shooting result is a single target picture.
And the picture set processing module 60 is configured to, when the shooting result is the target picture set, acquire a picture with the highest weight in the target picture set as a second target picture, and process the second target picture through the picture processing policy.
It should be understood that the above is only an example, and the technical solution of the present invention is not limited in any way, and in a specific application, a person skilled in the art may set the technical solution as needed, and the present invention is not limited thereto.
In the embodiment, when the starting of a shooting task is detected, the surrounding environment information is acquired through a preset sensing device; determining a photographing scene according to the ambient environment information, and judging whether the photographing scene meets a preset condition; if so, acquiring a picture processing strategy according to the photographing scene; when an instruction for completing a shooting task is received, a shooting result is obtained according to the instruction; when the shooting result is a single target picture, processing the target picture by using the picture processing strategy; when the shooting result is a target picture set, acquiring a picture with the highest weight in the target picture set as a second target picture, and processing the second target picture through the picture processing strategy; the technical effect that the shot pictures can be automatically adjusted according to the scene under the condition that the shooting processing is not required by the camera is achieved.
In an embodiment, the condition determining module 20 is further configured to determine a current photographing time according to time information in the ambient environment information; determining a current shooting subject according to role information in the surrounding environment information; acquiring a strategy factor in the ambient environment information, and matching the current shooting atmosphere according to the strategy factor; determining a current photographing scene according to the photographing moment, the photographing subject and the photographing atmosphere; and judging whether the photographing scene meets a preset condition or not.
In an embodiment, the condition determining module 20 is further configured to determine a current photographing time period according to the photographing time; determining the weight of the current photographed object according to the photographing subject; and acquiring a scene set, and determining the current photographing scene in the scene set according to the photographing time period, the partial weight of the photographing object and the photographing atmosphere.
In an embodiment, the condition determining module 20 is further configured to obtain a historical scene record, and obtain a target contrast element in the historical scene record by combining with a scene element in the photographing scene information; acquiring a scene generation log corresponding to the target comparison element; and judging whether the shooting scene meets a preset condition or not according to the scene generation log.
In an embodiment, the single picture processing module 50 is further configured to obtain basic information of photo adjustment corresponding to the picture processing policy; performing basic information adjustment on the target picture according to the picture adjustment basic information; and processing the target picture after the basic information adjustment according to a photo effect strategy in the picture processing strategies.
In an embodiment, the picture set processing module 60 is further configured to obtain information of all pictures in the target picture set; and acquiring the film-out effect score corresponding to each picture in all the picture information, and performing weight distribution according to the film-out effect scores.
In an embodiment, the picture set processing module 60 is further configured to obtain a current processing record, and obtain a use feedback of the current processing record from a preset port; and when the use feedback meets the recording condition, storing the current processing record into a historical picture processing record, and performing data cleaning on the historical picture processing record.
It should be noted that the above-described work flows are only exemplary, and do not limit the scope of the present invention, and in practical applications, a person skilled in the art may select some or all of them to achieve the purpose of the solution of the embodiment according to actual needs, and the present invention is not limited herein.
In addition, the technical details that are not described in detail in this embodiment may refer to the method for processing the picture based on the scene self-recognition provided in any embodiment of the present invention, and are not described herein again.
Further, it is to be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention or portions thereof that contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g. Read Only Memory (ROM)/RAM, magnetic disk, optical disk), and includes several instructions for enabling a terminal device (e.g. a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all equivalent structures or equivalent processes performed by the present invention or directly or indirectly applied to other related technical fields are also included in the scope of the present invention.
Claims (10)
1. A picture processing method based on scene self-recognition is characterized by comprising the following steps:
when the shooting task is detected to be started, acquiring surrounding environment information through a preset sensing device;
determining a photographing scene according to the ambient environment information, and judging whether the photographing scene meets a preset condition;
if so, acquiring a picture processing strategy according to the photographing scene;
when an instruction for completing a shooting task is received, a shooting result is obtained according to the instruction;
when the shooting result is a single target picture, processing the target picture by using the picture processing strategy;
and when the shooting result is a target picture set, acquiring a picture with the highest weight in the target picture set as a second target picture, and processing the second target picture through the picture processing strategy.
2. The picture processing method based on scene self-recognition as claimed in claim 1, wherein the step of determining the photographed scene according to the ambient environment information and determining whether the photographed scene meets a preset condition includes:
determining the current photographing time according to the time information in the ambient environment information;
determining a current shooting subject according to role information in the surrounding environment information;
acquiring a strategy factor in the ambient environment information, and matching the current shooting atmosphere according to the strategy factor;
determining a current photographing scene according to the photographing moment, the photographing subject and the photographing atmosphere;
and judging whether the photographing scene meets a preset condition or not.
3. The picture processing method based on scene self-recognition as claimed in claim 2, wherein the step of determining the current photographing scene according to the photographing time, the subject and the photographing atmosphere comprises:
determining the current photographing time period according to the photographing time;
determining the weight of the current photographed object according to the photographing subject;
and acquiring a scene set, and determining the current photographing scene in the scene set according to the photographing time period, the partial weight of the photographing object and the photographing atmosphere.
4. The picture processing method based on scene self-recognition as claimed in claim 2, wherein the step of determining whether the photographed scene meets a preset condition comprises:
acquiring a historical scene record, and acquiring a target comparison element in the historical scene record by combining scene elements in the photographing scene information;
acquiring a scene generation log corresponding to the target comparison element;
and judging whether the shooting scene meets a preset condition or not according to the scene generation log.
5. The method for processing pictures based on scene self-recognition according to claim 1, wherein the step of processing the target picture by using the picture processing policy comprises:
acquiring photo adjustment basic information corresponding to the picture processing strategy;
performing basic information adjustment on the target picture according to the picture adjustment basic information;
and processing the target picture after the basic information adjustment according to a photo effect strategy in the picture processing strategies.
6. The method as claimed in claim 1, wherein the step of obtaining the highest weighted photo in the target set of pictures as a second target picture, and processing the second target picture through the picture policy further comprises:
acquiring all picture information in the target picture set;
and acquiring the film-out effect score corresponding to each picture in all the picture information, and performing weight distribution according to the film-out effect scores.
7. The method for processing pictures based on scene self-recognition according to any one of claims 1 to 6, wherein when the shooting result is a target picture set, the method for acquiring the picture with the highest weight in the target picture set as a second target picture, and after the step of processing the second target picture by the picture processing policy, further comprises:
acquiring a current processing record, and acquiring use feedback of the current processing record from a preset port;
and when the use feedback meets the recording condition, storing the current processing record into a historical picture processing record, and performing data cleaning on the historical picture processing record.
8. A picture processing device based on scene self-recognition, comprising:
the information acquisition module is used for acquiring surrounding environment information through a preset sensing device when the shooting task is detected to be started;
the condition judgment module is used for determining a photographing scene according to the ambient environment information and judging whether the photographing scene meets a preset condition or not;
the strategy acquisition module is used for acquiring a picture processing strategy according to the photographing scene if the picture processing strategy is the same as the photographing scene;
the result acquisition module is used for acquiring a shooting result according to an instruction when the instruction for completing the shooting task is received;
the single picture processing module is used for processing the target picture by using the picture processing strategy when the shooting result is a single target picture;
and the picture set processing module is used for acquiring the picture with the highest weight in the target picture set as a second target picture when the shooting result is the target picture set, and processing the second target picture through the picture processing strategy.
9. A computer device, the device comprising: a memory, a processor that, when executing computer instructions stored by the memory, performs the method of any of claims 1-7.
10. A computer-readable storage medium comprising instructions that, when executed on a computer, cause the computer to perform the method of any of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211356125.9A CN115665542A (en) | 2022-11-01 | 2022-11-01 | Picture processing method based on scene self-recognition and related device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211356125.9A CN115665542A (en) | 2022-11-01 | 2022-11-01 | Picture processing method based on scene self-recognition and related device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115665542A true CN115665542A (en) | 2023-01-31 |
Family
ID=84994914
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211356125.9A Pending CN115665542A (en) | 2022-11-01 | 2022-11-01 | Picture processing method based on scene self-recognition and related device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115665542A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116401401A (en) * | 2023-05-26 | 2023-07-07 | 深圳市致尚信息技术有限公司 | Song recommendation method and device based on user preference for intelligent K song system |
-
2022
- 2022-11-01 CN CN202211356125.9A patent/CN115665542A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116401401A (en) * | 2023-05-26 | 2023-07-07 | 深圳市致尚信息技术有限公司 | Song recommendation method and device based on user preference for intelligent K song system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111476306B (en) | Object detection method, device, equipment and storage medium based on artificial intelligence | |
| CN106547744B (en) | Image retrieval method and system | |
| CN107820020A (en) | Method of adjustment, device, storage medium and the mobile terminal of acquisition parameters | |
| WO2018120460A1 (en) | Image focal length detection method, apparatus and device, and computer-readable storage medium | |
| CN111126573A (en) | Model distillation improvement method and device based on individual learning and storage medium | |
| CN103617432A (en) | Method and device for recognizing scenes | |
| CN110060213A (en) | Image processing method, device, storage medium and electronic equipment | |
| CN113837257B (en) | Target detection method and device | |
| CN111597884A (en) | Facial action unit identification method and device, electronic equipment and storage medium | |
| US20190087736A1 (en) | Information processing apparatus, artificial intelligence selection method, and artificial intelligence selection program | |
| CN111209970A (en) | Video classification method and device, storage medium and server | |
| CN111737573A (en) | Resource recommendation method, device, equipment and storage medium | |
| CN107748615B (en) | Screen control method and device, storage medium and electronic equipment | |
| CN111506758A (en) | Method and device for determining article name, computer equipment and storage medium | |
| CN112672145B (en) | Camera shooting function detection method and device | |
| CN111324352A (en) | Code generation method of application page and related equipment | |
| CN115665542A (en) | Picture processing method based on scene self-recognition and related device | |
| CN111124863B (en) | Intelligent device performance testing method and device and intelligent device | |
| CN111209947A (en) | Image recognition method, device, storage medium and apparatus | |
| US20050276483A1 (en) | Person image retrieval apparatus | |
| EP3865993A1 (en) | System and method for dynamic device user interface generation based on user characteristics | |
| CN107688623A (en) | A kind of search method in kind, device, equipment and storage medium | |
| WO2023142396A1 (en) | Test method and apparatus for relocation module, device, system, medium, computer program, and computer program product | |
| CN113032560B (en) | Sentence classification model training method, sentence processing method and equipment | |
| CN116797954A (en) | Image processing method, device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |