CN111737509A - Information processing method, apparatus, system, and computer-readable storage medium - Google Patents

Abstract

The present disclosure provides an information processing method, including: acquiring a plurality of images related to an accommodating space, wherein each of the images has an image identifier, the accommodating space comprises a plurality of areas, the areas can be used for accommodating a specific object, and the image identifiers represent areas where the specific object in the images is located; acquiring a location file, wherein the location file comprises location information of the plurality of areas; and generating a plurality of position subfiles respectively corresponding to the plurality of images based on the plurality of image identifications and the position files, wherein each position subfile comprises position information of an area where a specific object in the corresponding image is located.

Description

Information processing method, apparatus, system, and computer-readable storage medium

technical field

The present disclosure relates to the field of computer technology, and more particularly, to an information processing method, an information processing apparatus, an information processing system, and a computer-readable storage medium.

Background technique

In the physical store of commodity sales, the clerk usually needs to periodically check and inspect the commodities on the shelves to ensure that there are enough salable commodities on the shelves, the commodities are neatly arranged, and the arrangement is standardized, so as to improve the shopping experience of customers. and sales. With the development of artificial intelligence technology and image recognition technology, it is possible to use cameras to shoot shelves and use object detection to identify the goods on the shelves, so as to complete the inventory of goods on the shelves, shelf inspection and other solutions are getting more and more attention. Usually, multiple images of the shelf can be collected by the camera, and the images are manually labeled in the later stage, and a corresponding label file is generated for each image, and the label file includes the position information of the target object to be recognized in the image. Manual labeling requires a lot of manpower and time costs. Therefore, how to improve the efficiency of image annotation to save manpower and time has become an urgent problem to be solved.

In the process of realizing the concept of the present disclosure, the inventor found that the prior art has at least the following problems. The prior art requires a lot of manpower and time costs by manually labeling images.

SUMMARY OF THE INVENTION

In view of this, the present disclosure provides an optimized information processing method and information processing system.

One aspect of the present disclosure provides an information processing method, comprising: acquiring a plurality of images about a accommodating space, wherein each of the plurality of images has an image identification, the accommodating space includes a plurality of regions, and the The area can be used to accommodate a specific object, the image identifier represents the area where the specific object in the image is located, and a location file is obtained, wherein the location file includes the location information of the multiple areas, based on the multiple image identifiers and the position file to generate a plurality of position sub-files respectively corresponding to the plurality of images, wherein each position sub-file includes position information of a region where a specific object in the corresponding image is located.

According to an embodiment of the present disclosure, the above-mentioned generating multiple location sub-files corresponding to the multiple images based on the multiple image identifiers and the location file includes: determining, based on the image identifiers, to which the image identifiers belong. The region where the specific object is located in the image, the location information of the region where the specific object is located is determined from the location file, and a location sub-file corresponding to the image is generated based on the location information of the region where the specific object is located.

According to an embodiment of the present disclosure, the above-mentioned accommodating space includes: a plurality of sub-accommodating spaces, and each sub-accommodating space includes a plurality of regions. The acquiring the location file includes: acquiring location information of multiple areas in each sub-accommodating space, and generating the location file based on the location information of the multiple areas in each sub-accommodating space.

According to an embodiment of the present disclosure, acquiring the location information of multiple areas of each sub-accommodating space includes: acquiring the location information of a specific area in the sub-accommodating space, and determining the corresponding sub-accommodating space based on the location information of the specific area location information for other regions in .

According to an embodiment of the present disclosure, multiple images of the above-mentioned accommodating space are obtained through multiple cameras from different viewing angles, and the image identifier of each image includes corresponding camera information.

According to an embodiment of the present disclosure, the above-mentioned location file includes: a plurality of location files, and each location file includes the camera information. The acquiring a location file includes: acquiring a corresponding location file from the plurality of location files based on the camera information in the image identification.

Another aspect of the present disclosure provides an information processing apparatus, including: a first acquisition module, a second acquisition module, and a generation module. Wherein, the first acquisition module acquires a plurality of images about the accommodating space, wherein each of the plurality of images has an image identification, the accommodating space includes a plurality of areas, and the areas can be used to accommodate a specific object, so The image identifier represents the area where the specific object in the image is located, and the second acquisition module acquires a location file, wherein the location file includes the location information of the multiple areas, and the generation module is based on the multiple image identifiers and the The location file generates a plurality of location sub-files respectively corresponding to the plurality of images, wherein each location sub-file includes location information of a region where a specific object in the corresponding image is located.

According to an embodiment of the present disclosure, the above-mentioned generating multiple location sub-files corresponding to the multiple images based on the multiple image identifiers and the location file includes: determining, based on the image identifiers, to which the image identifiers belong. The region where the specific object is located in the image, the location information of the region where the specific object is located is determined from the location file, and a location sub-file corresponding to the image is generated based on the location information of the region where the specific object is located.

According to an embodiment of the present disclosure, the above-mentioned accommodating space includes: a plurality of sub-accommodating spaces, and each sub-accommodating space includes a plurality of regions. The acquiring the location file includes: acquiring location information of multiple areas in each sub-accommodating space, and generating the location file based on the location information of the multiple areas in each sub-accommodating space.

According to an embodiment of the present disclosure, acquiring the location information of multiple areas of each sub-accommodating space includes: acquiring the location information of a specific area in the sub-accommodating space, and determining the corresponding sub-accommodating space based on the location information of the specific area location information for other regions in .

According to an embodiment of the present disclosure, multiple images of the above-mentioned accommodating space are obtained through multiple cameras from different viewing angles, and the image identifier of each image includes corresponding camera information.

According to an embodiment of the present disclosure, the above-mentioned location file includes: a plurality of location files, and each location file includes the camera information. The acquiring a location file includes: acquiring a corresponding location file from the plurality of location files based on the camera information in the image identification.

Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, which when executed, are used to implement the method as described above.

Another aspect of the present disclosure provides a computer program comprising computer-executable instructions, which when executed, are used to implement the method as described above.

According to the embodiments of the present disclosure, the problem in the prior art that a large amount of manpower and time costs are required for manually annotating images can be at least partially solved, and thus a technology that improves the efficiency of image annotation and saves manpower and time costs can be realized. Effect.

Description of drawings

The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments of the present disclosure with reference to the accompanying drawings, in which:

FIG. 1 schematically shows a system architecture of an information processing method and a processing system according to an embodiment of the present disclosure;

FIG. 2 schematically shows an application scenario of an information processing method and a processing system according to an embodiment of the present disclosure;

FIG. 3 schematically shows a flowchart of an information processing method according to an embodiment of the present disclosure;

FIG. 4 schematically shows a schematic diagram of a plurality of images according to an embodiment of the present disclosure;

FIG. 5 schematically shows a schematic diagram of a location file according to an embodiment of the present disclosure;

6 schematically shows a schematic diagram of generating a location subfile according to an embodiment of the present disclosure;

FIG. 7 schematically shows a schematic diagram of an accommodating space according to an embodiment of the present disclosure;

FIG. 8 schematically shows a block diagram of an information processing apparatus according to an embodiment of the present disclosure; and

9 schematically shows a block diagram of a computer system suitable for information processing according to an embodiment of the present disclosure.

Detailed ways

Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood, however, that these descriptions are exemplary only, and are not intended to limit the scope of the present disclosure. In the following detailed description, for convenience of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It will be apparent, however, that one or more embodiments may be practiced without these specific details. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concepts of the present disclosure.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the present disclosure. The terms "comprising", "comprising" and the like as used herein indicate the presence of stated features, steps, operations and/or components, but do not preclude the presence or addition of one or more other features, steps, operations or components.

All terms (including technical and scientific terms) used herein have the meaning as commonly understood by one of ordinary skill in the art, unless otherwise defined. It should be noted that terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly rigid manner.

Where expressions like "at least one of A, B, and C, etc.," are used, they should generally be interpreted in accordance with the meaning of the expression as commonly understood by those skilled in the art (eg, "has A, B, and C") At least one of the "systems" shall include, but not be limited to, systems with A alone, B alone, C alone, A and B, A and C, B and C, and/or A, B, C, etc. ). Where expressions like "at least one of A, B, or C, etc.," are used, they should generally be interpreted in accordance with the meaning of the expression as commonly understood by those skilled in the art (eg, "has A, B, or C, etc." At least one of the "systems" shall include, but not be limited to, systems with A alone, B alone, C alone, A and B, A and C, B and C, and/or A, B, C, etc. ).

An embodiment of the present disclosure provides an information processing method, including: acquiring a plurality of images about a accommodating space, wherein each of the plurality of images has an image identification, the accommodating space includes a plurality of regions, and the regions can be used to accommodate a specific Object, the image identifier represents the area where a specific object in the image is located, and a location file is obtained, wherein the location file includes location information of multiple areas, and multiple locations corresponding to multiple images are generated based on multiple image identifiers and location files. sub-files, wherein each location sub-file includes the location information of the region where the specific object in the corresponding image is located.

FIG. 1 schematically shows a system architecture of an information processing method and an information processing system according to an embodiment of the present disclosure. It should be noted that FIG. 1 is only an example of a system architecture to which the embodiments of the present disclosure can be applied, so as to help those skilled in the art to understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used for other A device, system, environment or scene.

As shown in FIG. 1 , the system architecture 100 according to this embodiment may include terminal devices 101 , 102 , and 103 , a network 104 and a server 105 . The network 104 is a medium used to provide a communication link between the terminal devices 101 , 102 , 103 and the server 105 . The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

The user can use the terminal devices 101, 102, 103 to interact with the server 105 through the network 104 to receive or send messages and the like. Various communication client applications may be installed on the terminal devices 101 , 102 and 103 , such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only examples).

The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

The server 105 may be a server that provides various services, such as a background management server (just an example) that provides support for websites browsed by users using the terminal devices 101 , 102 , and 103 . The background management server can analyze and process the received user requests and other data, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

It should be noted that, the information processing method provided by the embodiments of the present disclosure may generally be executed by the server 105 . Correspondingly, the information processing apparatus provided by the embodiments of the present disclosure may generally be provided in the server 105 . The information processing method provided by the embodiments of the present disclosure may also be executed by a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101 , 102 , 103 and/or the server 105 . Correspondingly, the information processing apparatus provided by the embodiments of the present disclosure may also be provided in a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101 , 102 , 103 and/or the server 105 .

For example, the multiple images and location files related to the accommodation space acquired by the embodiments of the present disclosure may be stored in the terminal devices 101 , 102 , and 103 , and the multiple images and location files related to the accommodation space can be stored in the terminal devices 101 , 102 , and 103 through the terminal devices 101 , 102 , and 103 Sent to the server 105, the server 105 can generate multiple location sub-files corresponding to the multiple images based on the multiple image identifiers and location files, or the terminal devices 101, 102, 103 can also directly based on the multiple image identifiers and locations. The file generates multiple location sub-files corresponding to multiple images respectively. In addition, the multiple images and location files related to the storage space may also be directly stored in the server 105, and the server 105 directly generates multiple location sub-files corresponding to the multiple images based on the multiple image identifiers and the location files.

It should be understood that the numbers of terminal devices, networks and servers in FIG. 1 are merely illustrative. There can be any number of terminal devices, networks and servers according to implementation needs.

FIG. 2 schematically shows an application scenario of an information processing method and an information processing system according to an embodiment of the present disclosure. It should be noted that FIG. 2 is only an example of a scene to which the embodiments of the present disclosure can be applied, so as to help those skilled in the art to understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be applied to other devices , system, environment or scene.

As shown in FIG. 2 , the application scenario 200 may include, for example, multiple images 211 , 212 , and 213 .

According to an embodiment of the present disclosure, the plurality of images 211 , 212 , and 213 may be, for example, images about a shelf collected by a camera, for example, the shelf is used for placing items. Therein, the shelf includes, for example, a plurality of areas for placing items. For example, FIG. 2 schematically shows that the shelf has three areas for placing items, and the three areas are a first area A, a second area B, and a third area C, respectively.

According to an embodiment of the present disclosure, each image includes, for example, a specific object. For example, the specific object in the image 211 is located in the first area A, the specific object in the image 212 is located in the second area B, and the specific object in the image 213 is located in the third area C.

Wherein, each image has an image identification, and the image identification can be the file name of the image. For example, the image identification of image 211 is Fig.a, the image identification of image 212 is Fig.b, and the image identification of image 213 is Fig.c.

In the embodiment of the present disclosure, the image identification can, for example, represent a region where a specific object in the image is located. For example, Fig.a can indicate that a specific object in image 211 is located in the first area A, Fig.b can indicate that a specific object in image 212 is located in the second area B, and Fig.c can indicate that a specific object in image 213 is located in the third area area C.

Among them, for example, the collection methods of the multiple images 211 , 212 , and 213 are consistent, that is, the positions of the shelves in different images are consistent. Therefore, the position information of each area of the shelf in different images is consistent. For example, the position information of the first region A in the multiple images 211 , 212 and 213 is [(a ₁ , a ₂ ), (a ₃ , a ₄ )], where (a ₁ , a ₂ ) is, for example, The position coordinates of the upper left corner of the first area A, (a ₃ , a ₄ ) are, for example, the position coordinates of the lower right corner of the first area A. Similarly, the position information of the second area B is, for example, [(b ₁ , b ₂ ), (b ₃ , b ₄ )], and the position information of the third area C is, for example, [(c ₁ , c ₂ ), (c ₃ , c4 ₎ ].

In the embodiment of the present disclosure, the location information of a plurality of regions is, for example, combined into a location file 220, that is, the location file 220 includes the location information of each region. According to each image and the location file 220, a location sub-file corresponding to each image can be automatically generated, and the location sub-file includes region location information of a region where a specific object is located in each image. For example, the position sub-file 231 of the image 211 is automatically generated according to the position file 220, and the position sub-file 231 includes the position information of the first area A where the specific object in the image 211 is located [(a ₁ , a ₂ ), (a ₃ , a4 ₎ ]. Similarly, the embodiment of the present disclosure can automatically generate the position sub-file 232 corresponding to the image 212 , and automatically generate the position sub-file 233 corresponding to the image 213 .

Through the embodiments of the present disclosure, the location sub-file of the image can be automatically generated, the efficiency of image labeling is improved, and labor and time costs are saved. In addition, the labeled images can be used as a training set for machine learning, for example, a training set for an object detection model for deep learning, and the trained model can be used to automatically detect and identify specific object information on the shelf.

FIG. 3 schematically shows a flowchart of an information processing method according to an embodiment of the present disclosure.

FIG. 4 schematically shows a schematic diagram of a plurality of images according to an embodiment of the present disclosure.

As shown in FIG. 3, the method includes operations S310-S330.

In operation S310, a plurality of images about the accommodating space are acquired, wherein each of the plurality of images has an image identifier, the accommodating space includes a plurality of areas, the areas can be used to accommodate a specific object, and the image identifier represents the specific object in the image the area in which it is located.

According to an embodiment of the present disclosure, the accommodating space is, for example, used for placing items, and the accommodating space may be, for example, a shelf for placing items. Wherein, the accommodating space includes a plurality of areas, and each area can be used for placing items.

As shown in FIG. 4 , for example, a plurality of images 410 , 420 , and 430 regarding the accommodation space are acquired. Each image has an image ID, which can be the filename of the corresponding image. For example, the image identification of the image 410 is Fig_1, the image identification of the image 420 is Fig_2, and the image identification of the image 430 is Fig_3.

In the embodiment of the present disclosure, for example, the accommodating space includes 6 regions (as shown in FIG. 4 , the accommodating space includes 3 upper regions and 3 lower regions) as an example. Wherein, in each image, a specific object (for example, the specific object is a large volume cylinder in FIG. 4 ) is placed in different regions, for example, and the regions where the specific objects of different images are located have certain rules. For example, a particular object in image 410 may be located in all regions. Based on the image 410, starting from the specific object located in the left area, each time the specific object located in the even position is removed, for example, the specific object located in the even number 2 position is removed for the first time (the upper and lower areas are the same), and the image 420 is obtained, and the specific object is removed. Walking in the area of a specific object can place other interfering objects (for example, small-sized objects in Figure 4). Secondly, based on the image 420, the specific object located at the position of the even number 2 is removed for the second time (the area where the disturbing object in the image 420 is located is not within the calculation range of the position parity), and the image 430 is obtained. In this way it is possible to acquire multiple images in which a particular object is in different regions.

In the embodiment of the present disclosure, the image identification can represent the region where the specific object is located in the corresponding image. For example, the image identification Fig_1 of the image 410 can indicate that a specific object is located in all areas in the image 410, the image identification Fig_2 of the image 420 can indicate that the specific object is located in the left and right areas in the image 420, and the image identification Fig_3 of the image 430 can indicate that the specific object in the image 430 is located in the area. Objects are located in the left area.

Or, the multiple images are arranged in a certain order in the folder where the images are stored according to the image identification, for example, the images are arranged in the folder according to the image identification order as Fig_1, Fig_2, Fig_3, and the area where the specific object is located in the multiple images is arranged in a certain order. The rules correspond to the order in which the images are arranged in the folder. Based on the arrangement of the images in the folder, the area where a specific object is located in each image can also be known. That is, when the images are arranged in a folder according to the image identification order as Fig_1, Fig_2, Fig_3, based on this arrangement, it can be known that the area where the specific object is located in the image 410 is all areas, and the area where the specific object is located in the image 420 is the left side. and the right area, the area where the specific object is located in the image 430 is the left area.

It can be understood that the above examples of the rules of the regions where the specific objects are located in different images are only exemplary examples made to facilitate the understanding of the present disclosure, and those skilled in the art can specifically set the rules of the regions where the specific objects are located according to the actual application situation, as long as It is sufficient to ensure that the region where the specific object in the corresponding image is located can be determined based on the image identification.

In operation S320, a location file is obtained, wherein the location file includes location information of a plurality of regions.

According to an embodiment of the present disclosure, the location file includes, for example, location information of all areas of the accommodation space in the image. The collection methods of the multiple images 410 , 420 , and 430 are, for example, the same, so as to ensure the same location information of the same area in the accommodating space in different images.

FIG. 5 schematically shows a schematic diagram of a location file according to an embodiment of the present disclosure.

As shown in FIG. 5 , the location file 510 includes, for example, the location information of all areas in the image, and the location information of the upper area of the accommodating space from left to right is [(a ₁ , a ₂ ), (a ₃ , a ₄ ). )], [(b ₁ , b ₂ ), (b ₃ , b ₄ )], [(c ₁ , a ₂ ), (c ₃ , c ₄ )]; the position information of the lower area of the accommodation space is from left to On the right are [(d ₁ , d ₂ ), (d ₃ , d ₄ )], [(e ₁ , e ₂ ), (e ₃ , e ₄ )], [(f ₁ , f ₂ ), (f ₃ , _f4 )].

In operation S330, a plurality of position sub-files respectively corresponding to the plurality of images are generated based on the plurality of image identifiers and the position files, wherein each position sub-file includes position information of a region where a specific object in the corresponding image is located.

According to the embodiment of the present disclosure, since the image identifier can represent the area where the specific object is located in the image, the location sub-file corresponding to each image can be automatically generated based on the image identifier and the location file.

FIG. 6 schematically shows a schematic diagram of generating a location subfile according to an embodiment of the present disclosure.

First, the region where the specific object is located in the image to which the image identification belongs is determined based on the image identification.

As shown in FIGS. 4 to 6 , for example, the image identification characterizes the region in the image where the specific object is located. Taking the image 410 as an example, according to the image identifier Fig_1, it is determined that the specific object in the image 410 to which the image identifier Fig_1 belongs is located in all areas (for example, the specific object is located in the upper 3 areas and the lower 3 areas in the accommodation space).

Second, the location information of the region where the particular object is located is determined from the location file. For example, the location file 510 includes the location information of all regions. After the region where the specific object is located in the image 410 is determined, the location information of the region where the specific object is located is determined from the location file 510 .

Finally, a location subfile corresponding to the image is generated based on the location information of the region where the specific object is located. For example, the location sub-file 610 corresponding to the image 410 is obtained from the location file 510 . The location subfile 610 includes, for example, location information of the region where the specific object is located in the image 410 . For example, if a specific object in the image 410 is in all areas of the accommodation space, a position sub-file 610 corresponding to the image 410 is automatically generated based on the position file 510, and the position sub-file 610 includes, for example, the following position information: [(a ₁ , a ₂ ), (a ₃ , a ₄ )], [(b ₁ , b ₂ ), (b ₃ , b ₄ )], [(c ₁ , a ₂ ), (c ₃ , c ₄ )], [(d ₁ , d ₂ ), (d ₃ , d ₄ )], [(e ₁ , e ₂ ), (e ₃ , e ₄ )], [(f ₁ , f ₂ ), (f ₃ , f ₄ )].

Similarly, the image identifier Fig_2 of the image 420 indicates that the specific object in the image 420 is located in the left and right regions. At this time, a position sub-file 620 corresponding to the image 420 is automatically generated according to the position file 510 , and the position sub-file 620 includes, for example, the image 420 Location information for the area where a specific object is located. Similarly, the location sub-file 630 of the image 430 is automatically generated according to the location file 510, and the specific process is not repeated here.

This embodiment of the present disclosure automatically generates a location sub-file corresponding to each image based on the image identifiers of multiple images and a location file including location information of multiple regions, where the location sub-file includes location information of the region where a specific object in the corresponding image is located, to This implementation automatically generates the location sub-file of the image, improves the efficiency of image annotation, and saves manpower and time costs.

The specific method of obtaining the location file is described below.

FIG. 7 schematically shows a schematic diagram of an accommodating space according to an embodiment of the present disclosure.

As shown in FIG. 7 , the accommodating space includes a plurality of sub-accommodating spaces, and each sub-accommodating space includes a plurality of regions. For example, the accommodating space includes sub-accommodating spaces 710 and 720 , and the sub-accommodating space 710 includes, for example, a plurality of areas 711 , 712 and 713 . The sub-accommodating space 720 includes, for example, a plurality of areas 721 , 722 and 723 .

Wherein, acquiring the location file includes: acquiring location information of multiple areas in each sub-accommodating space, and generating a location file based on the location information of the multiple areas in each sub-accommodating space.

According to an embodiment of the present disclosure, during the process of acquiring an image by a camera, due to the angle of view of the camera, the positions of different sub-accommodating spaces in the image are deformed (not only the distance difference). Therefore, in order to ensure the accuracy of the region location information in the acquired location file, by separately acquiring the location information of the multiple sub-accommodating spaces, the combination of the location information of the multiple sub-accommodating spaces is the location file.

Among them, the following takes the acquisition of the location information of multiple regions in a sub-accommodating space as an example.

First, position information of a specific area in the sub-accommodating space is acquired.

According to an embodiment of the present disclosure, the specific area in the sub-accommodating space is, for example, one of a plurality of areas in the sub-accommodating space. Taking the sub-accommodating space 710 as an example, the specific area may be, for example, an area 711, where the location information of the area 711 is, for example, [(a ₁ , a ₂ ), (a ₃ , a ₄ )]. Among them, a1 is, for example, the _x -axis coordinate of the upper left corner of the area 711, a2 is, for example, the y _- axis coordinate of the upper left corner of the area 711, a3 is, for example, the x _- axis coordinate of the lower right corner of the area 711, and a4 is, for example, the y-axis coordinate of the lower right corner of the area 711 axis coordinates.

Second, the location information of other areas in the corresponding sub-accommodating space is determined based on the location information of the specific area.

For example, the location information of other areas in the sub-accommodating space is automatically generated based on the location information of a specific area. For example, the position information [(a ₁ +m, a ₂ ), (a ₃ +m, a ) of the area 712 is automatically generated based on the position information [(a ₁ , a ₂ ), (a ₃ , a ₄ )] of the area 711 ₄ )], where, for example, each of the multiple regions 711, 712, and 713 has the same size, and m is, for example, the length of each region in the x-direction. Similarly, the position information [(a ₁ +2*m, a ₂ ), (a ₃ +2*m, a ₄ )] of the area 713 is automatically generated.

Similarly, for example, by acquiring the position information of a specific area of the sub-accommodating space 720 (for example, the specific area is the area 721 ), and automatically generating the position information of the area 722 and the area 723 according to the position information of the area 721 .

Of course, within the range that the precision of the location information of each area in the location file meets the accuracy requirements, the location file may also be obtained without separately acquiring the location information of the sub-accommodating spaces. For example, the location information of a specific area in the accommodation space can also be acquired, and the location information of other areas in the accommodation space can be automatically acquired through the location information of the specific area. For example, a specific area in the accommodation space is, for example, area 711, the position information of area 711 is [(a ₁ , a2), (a ₃ , a4)], and the position information of area 712 is automatically generated based on the position information of area 711 [(a ₁ +m, a ₂ ), (a ₃ +m, a ₄ )], the position information of the area 713 [(a ₁ +2*m, a ₂ ), (a ₃ +2*m, a ₄ )], The position information of the area 721 [(a ₁ , a ₂ +n), (a ₃ , a ₄ +n)], the position information of the area 722 [(a ₁ +m, a ₂ +n), (a ₃ +m , a ₄ +n)], the position information of the area 723 [(a ₁ +2*m, a ₂ +n), (a ₃ +2*m, a ₄ +n)]. Wherein, n is, for example, the width of each region in the y direction.

According to the embodiment of the present disclosure, multiple images of the accommodating space are obtained from different viewing angles through multiple cameras, and the image identifier of each image includes corresponding camera information.

That is, by acquiring multiple images from different viewing angles through multiple cameras, rich image samples can be acquired. The image identification of each image may also include information about the camera that acquired the image.

The location file includes, for example, multiple location files, and each location file includes camera information. That is, each location file includes location information of multiple regions in an image acquired by the same camera based on the same viewing angle. Therefore, each location file includes corresponding camera information, so that the corresponding location file is obtained from the plurality of location files based on the camera information in the image identification. That is, when a sub-location file of multiple images is automatically generated based on the location file, the camera corresponding to the location file is the same as the camera that acquires the multiple images. For example, the multiple images are acquired by a camera, and the location file is the location information of multiple regions in the images acquired by the camera.

FIG. 8 schematically shows a block diagram of an information processing apparatus according to an embodiment of the present disclosure.

As shown in FIG. 8 , the information processing apparatus 800 includes a first obtaining module 810 , a second obtaining module 820 and a generating module 830 .

The first acquisition module 810 can be used to acquire a plurality of images about the accommodating space, wherein each of the plurality of images has an image identification, the accommodation space includes a plurality of regions, the regions can be used to accommodate a specific object, and the image identification characterizes the image. The area where a particular object in the . According to an embodiment of the present disclosure, the first obtaining module 810 may, for example, perform the operation S310 described above with reference to FIG. 3 , which will not be repeated here.

The second obtaining module 820 may be configured to obtain a location file, wherein the location file includes location information of multiple regions. According to an embodiment of the present disclosure, the second obtaining module 820 may, for example, perform the operation S320 described above with reference to FIG. 3 , which will not be repeated here.

The generating module 830 may be configured to generate a plurality of position sub-files corresponding to the plurality of images based on the plurality of image identifiers and the position files, wherein each position sub-file includes the position information of the region where the specific object in the corresponding image is located. . According to an embodiment of the present disclosure, the generating module 830 may, for example, perform the operation S330 described above with reference to FIG. 3 , which will not be repeated here.

According to an embodiment of the present disclosure, the above-mentioned generation of multiple location sub-files corresponding to multiple images based on multiple image identifiers and location files includes: determining, based on the image identifiers, a region where a specific object is located in an image to which the image identifier belongs, and from The location information of the area where the specific object is located is determined in the location file, and a location sub-file corresponding to the image is generated based on the location information of the area where the specific object is located.

According to an embodiment of the present disclosure, the above-mentioned accommodating space includes: a plurality of sub-accommodating spaces, and each sub-accommodating space includes a plurality of regions. Acquiring a location file includes: acquiring location information of multiple areas in each sub-accommodating space, and generating a location file based on the location information of the multiple areas in each sub-accommodating space.

According to an embodiment of the present disclosure, obtaining the location information of multiple areas in each sub-accommodating space includes: acquiring the location information of a specific area in the sub-accommodating space, and determining other areas in the corresponding sub-accommodating space based on the location information of the specific area location information.

According to an embodiment of the present disclosure, multiple images of the above-mentioned accommodating space are obtained through multiple cameras from different viewing angles, and the image identifier of each image includes corresponding camera information.

According to an embodiment of the present disclosure, the above-mentioned location files include: a plurality of location files, and each location file includes camera information. Acquiring a location file includes: acquiring a corresponding location file from multiple location files based on the camera information in the image identification.

Any of the modules, sub-modules, units, sub-units, or at least part of the functions of any of them according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be divided into multiple modules for implementation. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least in part as hardware circuits, such as field programmable gate arrays (FPGA), programmable logic arrays (PLA), A system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or any other reasonable means of hardware or firmware that integrates or packages circuits, or can be implemented in software, hardware, and firmware Any one of these implementations or an appropriate combination of any of them is implemented. Alternatively, one or more of the modules, sub-modules, units, and sub-units according to embodiments of the present disclosure may be implemented at least in part as computer program modules that, when executed, may perform corresponding functions.

For example, any one of the first obtaining module 810, the second obtaining module 820, and the generating module 830 may be combined into one module for implementation, or any one of the modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the first acquisition module 810, the second acquisition module 820, and the generation module 830 may be implemented at least partially as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), system-on-chip, system-on-substrate, system-on-package, application specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging circuits, etc. in hardware or firmware, or in software, It can be implemented in any one of the three implementation manners of hardware and firmware or in an appropriate combination of any of them. Alternatively, at least one of the first acquisition module 810, the second acquisition module 820, and the generation module 830 may be implemented at least in part as a computer program module that, when executed, may perform corresponding functions.

9 schematically shows a block diagram of a computer system suitable for information processing according to an embodiment of the present disclosure. The computer system shown in FIG. 9 is only an example, and should not impose any limitation on the function and scope of use of the embodiments of the present disclosure.

As shown in FIG. 9 , a computer system 900 according to an embodiment of the present disclosure includes a processor 901 that can be loaded into a random access memory (RAM) 903 according to a program stored in a read only memory (ROM) 902 or from a storage section 908 program to perform various appropriate actions and processes. The processor 901 may include, for example, a general-purpose microprocessor (eg, a CPU), an instruction set processor and/or a related chipset, and/or a special-purpose microprocessor (eg, an application-specific integrated circuit (ASIC)), among others. The processor 901 may also include on-board memory for caching purposes. The processor 901 may include a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiments of the present disclosure.

In the RAM 903, various programs and data necessary for the operation of the system 900 are stored. The processor 901 , the ROM 902 and the RAM 903 are connected to each other through a bus 904 . The processor 901 performs various operations of the method flow according to the embodiment of the present disclosure by executing the programs in the ROM 902 and/or the RAM 903 . Note that the program may also be stored in one or more memories other than the ROM 902 and the RAM 903 . The processor 901 may also perform various operations of the method flow according to the embodiments of the present disclosure by executing programs stored in the one or more memories.

According to embodiments of the present disclosure, the system 900 may also include an input/output (I/O) interface 905 that is also connected to the bus 904 . System 900 may also include one or more of the following components connected to I/O interface 905: input portion 906 including keyboard, mouse, etc.; including components such as cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers An output section 907 including a hard disk, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, a modem, and the like. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the I/O interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is mounted on the drive 910 as needed so that a computer program read therefrom is installed into the storage section 908 as needed.

According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the method illustrated in the flowchart. In such an embodiment, the computer program may be downloaded and installed from the network via the communication portion 909, and/or installed from the removable medium 911. When the computer program is executed by the processor 901, the above-described functions defined in the system of the embodiment of the present disclosure are performed. According to embodiments of the present disclosure, the above-described systems, apparatuses, apparatuses, modules, units, etc. can be implemented by computer program modules.

The present disclosure also provides a computer-readable storage medium. The computer-readable storage medium may be included in the device/apparatus/system described in the above embodiments; it may also exist alone without being assembled into the device/system. device/system. The above-mentioned computer-readable storage medium carries one or more programs, and when the above-mentioned one or more programs are executed, implement the method according to the embodiment of the present disclosure.

According to an embodiment of the present disclosure, the computer-readable storage medium may be a computer non-volatile computer-readable storage medium, for example, it may include, but is not limited to, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), erasable programmable read only memory (EPROM or flash memory), portable compact disk read only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. In this disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

For example, according to embodiments of the present disclosure, a computer-readable storage medium may include one or more memories other than ROM 902 and/or RAM 903 and/or ROM 902 and RAM 903 described above.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code that contains one or more logical functions for implementing the specified functions executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It is also noted that each block of the block diagrams or flowchart illustrations, and combinations of blocks in the block diagrams or flowchart illustrations, can be implemented in special purpose hardware-based systems that perform the specified functions or operations, or can be implemented using A combination of dedicated hardware and computer instructions is implemented.

Those skilled in the art will appreciate that various combinations and/or combinations of features recited in various embodiments and/or claims of the present disclosure are possible, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments of the present disclosure and/or in the claims may be made without departing from the spirit and teachings of the present disclosure. All such combinations and/or combinations fall within the scope of this disclosure.

Embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only, and are not intended to limit the scope of the present disclosure. Although the various embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the appended claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art can make various substitutions and modifications, and these substitutions and modifications should all fall within the scope of the present disclosure.

Claims (14)

1. An information processing method comprising:

acquiring a plurality of images related to an accommodating space, wherein each of the images has an image identifier, the accommodating space comprises a plurality of areas, the areas can be used for accommodating a specific object, and the image identifiers represent areas where the specific object in the images is located;

acquiring a location file, wherein the location file comprises location information of the plurality of areas; and

and generating a plurality of position subfiles respectively corresponding to the plurality of images based on the plurality of image identifications and the position files, wherein each position subfile comprises position information of an area where a specific object in the corresponding image is located.

2. The method of claim 1, wherein the generating a plurality of location subfiles corresponding to the plurality of images, respectively, based on the plurality of image identifications and the location file comprises:

determining the area of a specific object in the image to which the image identifier belongs based on the image identifier;

determining the position information of the area where the specific object is located from the position file;

and generating a position subfile corresponding to the image based on the position information of the area where the specific object is located.

3. The method of claim 1, wherein:

the accommodating space includes: a plurality of sub-receiving spaces, each of which includes a plurality of regions;

the acquiring the location file comprises:

acquiring position information of a plurality of areas in each sub-accommodation space;

and generating the position file based on the position information of the plurality of areas in each sub accommodation space.

4. The method of claim 3, wherein said obtaining location information for a plurality of regions of each sub-accommodation space comprises:

acquiring position information of a specific area in the sub-accommodation space;

and determining the position information of other areas in the corresponding sub-accommodation spaces based on the position information of the specific area.

5. The method of claim 1, wherein the plurality of images of the accommodation space are obtained from different perspectives by a plurality of cameras, the image identification of each image comprising corresponding camera information.

6. The method of claim 5, wherein:

the location file includes: a plurality of location files, each location file including the camera information;

the acquiring the location file comprises: and acquiring corresponding position files from the plurality of position files based on the camera information in the image identification.

7. An information processing apparatus comprising:

the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module acquires a plurality of images related to an accommodating space, each image of the plurality of images has an image identifier, the accommodating space comprises a plurality of areas, the areas can be used for accommodating a specific object, and the image identifiers represent the areas where the specific object is located in the images;

a second obtaining module, configured to obtain a location file, where the location file includes location information of the plurality of areas; and

and the generating module is used for generating a plurality of position subfiles respectively corresponding to the images based on the image identifications and the position files, wherein each position subfile comprises position information of an area where a specific object in the corresponding image is located.

8. The apparatus of claim 7, wherein the generating a plurality of location subfiles corresponding to the plurality of images, respectively, based on the plurality of image identifications and the location file comprises:

determining the area of a specific object in the image to which the image identifier belongs based on the image identifier;

determining the position information of the area where the specific object is located from the position file;

and generating a position subfile corresponding to the image based on the position information of the area where the specific object is located.

9. The apparatus of claim 7, wherein:

the accommodating space includes: a plurality of sub-receiving spaces, each of which includes a plurality of regions;

the acquiring the location file comprises:

acquiring position information of a plurality of areas in each sub-accommodation space;

and generating the position file based on the position information of the plurality of areas in each sub accommodation space.

10. The apparatus of claim 9, wherein said obtaining location information for a plurality of regions of each sub-accommodation space comprises:

acquiring position information of a specific area in the sub-accommodation space;

and determining the position information of other areas in the corresponding sub-accommodation spaces based on the position information of the specific area.

11. The apparatus of claim 7, wherein the plurality of images of the receiving space are obtained from different perspectives by a plurality of cameras, the image identification of each image comprising corresponding camera information.

12. The apparatus of claim 11, wherein:

the location file includes: a plurality of location files, each location file including the camera information;

the acquiring the location file comprises: and acquiring corresponding position files from the plurality of position files based on the camera information in the image identification.

13. An information processing system comprising:

one or more processors;

a storage device for storing one or more programs,

wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method of any of claims 1-6.

14. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 6.

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