CN110516628A - Shelf vacant locations merchandise news acquisition methods, system, equipment and storage medium - Google Patents
Shelf vacant locations merchandise news acquisition methods, system, equipment and storage medium Download PDFInfo
- Publication number
- CN110516628A CN110516628A CN201910812733.8A CN201910812733A CN110516628A CN 110516628 A CN110516628 A CN 110516628A CN 201910812733 A CN201910812733 A CN 201910812733A CN 110516628 A CN110516628 A CN 110516628A
- Authority
- CN
- China
- Prior art keywords
- shelf
- vacant
- commodity
- information
- image
- 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
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000012549 training Methods 0.000 claims description 11
- 238000004590 computer program Methods 0.000 claims description 10
- 238000003709 image segmentation Methods 0.000 claims description 9
- 230000011218 segmentation Effects 0.000 claims description 4
- 230000010365 information processing Effects 0.000 claims description 3
- 238000013507 mapping Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 abstract description 9
- 230000000875 corresponding effect Effects 0.000 description 28
- 238000010586 diagram Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 4
- 239000000463 material Substances 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 239000003086 colorant Substances 0.000 description 2
- 238000002372 labelling Methods 0.000 description 2
- 239000013307 optical fiber Substances 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000005022 packaging material Substances 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000011514 reflex Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Economics (AREA)
- General Business, Economics & Management (AREA)
- Life Sciences & Earth Sciences (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Human Resources & Organizations (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Finance (AREA)
- Accounting & Taxation (AREA)
- Marketing (AREA)
- Artificial Intelligence (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention relates to technical field of image processing, in particular to a kind of shelf vacant locations merchandise news acquisition methods, system, equipment and storage medium.The acquisition methods of the shelf vacant locations merchandise news include the shelf image for obtaining arrangement commodity；The shelf image is identified using identification model；To obtain, there are the vacant locations of commodity vacancy on shelf；The vacant locations and scheduled placement information on the shelf are compared, to obtain the corresponding merchandise news of the vacant locations.In the information acquisition method of vacancy commodity provided by the invention, by the shelf image for obtaining arrangement commodity, and then it is identified using image information of the identification model to acquisition, to obtain on shelf, there are the vacant locations of commodity vacancy, and then it is compared according to merchandise news scheduled on shelf, corresponding merchandise news in vacant locations is finally obtained, the working strength of staff can be largely reduced, accelerates the renewal frequency of commodity on shelf information.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a method, a system, equipment and a storage medium for acquiring commodity information at a vacant position of a shelf.
Background
In the retail industry, whether the position of the goods is correctly placed and whether the goods are sufficiently supplied can have a great influence on the sales volume of the goods.
No matter large-scale business surpasses or small-size convenience stores, when selling goods, can put goods on goods shelves usually, can make things convenient for the consumer to choose and purchase like this, also make things convenient for the trade company in time to master the goods on the goods shelves and manage.
In the process of selling commodities, a merchant usually arranges personnel to regularly check the goods shelf so as to obtain the quantity information of the commodities on the goods shelf, so that different kinds of commodities are placed at preset positions on the goods shelf, even the commodities lacking the commodities are supplemented in time, and the timely and sufficient supply of the corresponding commodities is ensured.
Disclosure of Invention
The invention provides a method for acquiring commodity information of a vacant position of a shelf. The method for acquiring the commodity information of the vacant positions of the shelves comprises the following steps:
acquiring a shelf image of the arranged commodities;
identifying the shelf image by using an identification model to obtain the vacant positions of commodity vacancies on the shelf; wherein,
the identification model is obtained by utilizing the shelf image training in advance;
and comparing the vacant positions with preset arrangement information on the shelf to obtain commodity information corresponding to the vacant positions.
Preferably, the recognizing the shelf image by using the recognition model to obtain the vacant positions where the commodity vacancy exists on the shelf includes:
identifying the area ranges occupied by the commodities and the vacant positions on the shelf image by using an identification model;
marking the area range occupied by the commodity and the area range occupied by the vacant position by adopting a closed wire frame;
carrying out image segmentation on the shelf image to obtain a characteristic picture of which the commodity characteristics are different from the shelf characteristics;
mapping the closed wireframe on the shelf image onto the feature map;
calculating the ratio of the area occupied by the shelf features in the closed wire frame to the corresponding area of the closed wire frame;
comparing the ratio with a preset threshold, and when the ratio exceeds the preset threshold, taking the position of the corresponding closed wire frame as the vacant position where the commodity is vacant; otherwise, the position of the corresponding closed wire frame is abandoned.
Preferably, the image segmentation of the shelf image to obtain the feature picture of the product feature difference and the shelf feature includes:
and segmenting the image by utilizing an edge segmentation mode to obtain the characteristic picture which reflects the characteristics of the commodity and reflects the characteristics of the goods shelf to be different.
Preferably, the closed wire frame is a rectangular frame.
Preferably, the predetermined threshold is 0.8.
Preferably, the comparing the vacant position with the predetermined arrangement information on the shelf to obtain the commodity information corresponding to the vacant position includes:
acquiring commodity information at a position adjacent to the vacant position;
and taking the commodity information on the adjacent positions as the corresponding commodity information on the vacant positions.
Preferably, the comparing the vacant position with the predetermined arrangement information on the shelf to obtain the commodity information corresponding to the vacant position includes:
setting the commodity arrangement history information on the shelf as the predetermined commodity information;
and comparing the vacant position with the preset commodity information to obtain the commodity information corresponding to the vacant position.
Another aspect of the invention is to provide a system for acquiring commodity information of a vacant position on a shelf. The system for acquiring goods information at the vacant shelf positions is used for realizing the steps of the method for acquiring the goods information at the vacant shelf positions. The system for acquiring commodity information of the vacant positions on the shelves comprises:
the image acquisition module is used for acquiring a shelf image of the arranged commodities;
the image identification module is used for identifying the shelf image by utilizing an identification model; to obtain the vacant positions of commodity vacancy on the shelf; wherein,
the identification model is obtained by utilizing the shelf image training in advance;
and the information processing module is used for comparing the preset position information of the vacant position on the goods shelf to obtain the commodity information corresponding to the vacant position.
The invention further provides equipment for acquiring the commodity information of the vacant positions of the goods shelves. The equipment for acquiring commodity information of the vacant positions on the goods shelf comprises:
a memory for storing a computer program;
a processor for implementing the steps of the method for acquiring information on goods at empty positions on shelves according to the previous aspect of the present invention when the computer program is executed.
A final aspect of the invention provides a computer-readable storage medium. The computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the method of acquiring information on an item of goods at a shelf empty position as described above.
According to the method, the system, the equipment and the storage medium for acquiring the information of the vacant commodities, the shelf images for arranging the commodities are acquired, the acquired image information is identified by using an identification model so as to obtain the vacant positions where the commodities are vacant on the shelf, and then the commodity information corresponding to the vacant positions is finally obtained by comparing according to the preset commodity information on the shelf.
On the other hand, the merchant can also reduce the manpower and material resources invested for obtaining the commodity information on the goods shelf, thereby reducing the operating cost and improving the profit margin.
On the last hand, the invention uses machine vision to identify the goods shelf and compares the obtained final vacant commodity information, thereby greatly improving the accuracy of obtaining the commodity information on the goods shelf.
Drawings
Fig. 1 is a flowchart illustrating steps of a method for acquiring information about goods at vacant shelves according to an embodiment of the present invention;
FIG. 2 is a flow chart of the steps provided by an embodiment of the present invention for vacant location identification;
fig. 3 and fig. 4 are flowcharts of steps of comparing information of commodities at vacant positions according to an embodiment of the present invention;
fig. 5 is a schematic diagram of module connections of a system for acquiring information on goods in vacant shelves according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an apparatus for acquiring commodity information at a vacant shelf position according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present invention.
Detailed Description
According to the description, in the commodity selling process, in order to obtain the quantity and the type information of commodities on the goods shelf, a merchant can arrange a worker to manually count the goods shelf, so that different types of commodities are placed at the preset positions on the goods shelf, and even the goods shortage commodities are supplemented in time, and the corresponding commodities can be supplied fully all the time. The shelf is periodically checked manually, so that information on the goods on the shelf (for example, whether a certain type of goods is sold out (or is vacant), whether the type and the position of the goods correspond to each other, and the type and the number of the placed goods) can be accurately grasped, and the method is widely used by retail enterprises. Obviously, the mode of manually checking the commodities on the shelves is a main and even only commodity information acquisition mode for the retail enterprises.
However, although the accurate commodity information of whether the commodity on the shelf is empty can be obtained by manual counting, enormous manpower and material resources are required, and a long time is required to obtain the result. For large-scale business surpasses, the size of the shelf inside is huge, the variety of the placed goods is various, and the checking work of one shelf can be finished by one to two workers within tens of minutes. In addition, when the worker checks the product, if the worker finds that there is a product vacancy on the shelf, the product information of the vacancy position cannot be reflected in the first time, and the worker must check and compare the product information with the product information list in which the product information of each position on the shelf is recorded, and then confirm the product information of the vacancy position. Therefore, even if only the commodity information of whether the goods shelf is empty or not and the empty position is checked, much time and energy are needed, and the timeliness of commodity supply is seriously influenced. The merchant will use more manpower to quickly acquire the information of the goods on the shelf. Clearly, this will increase the investment costs of the merchant.
Aiming at the problem that the prior art acquires the information whether goods on the goods shelf are vacant or not, the inventor of the invention conducts repeated research and analysis to make more creative labor, and provides a method, a system, equipment and a storage medium for acquiring the goods information of the vacant positions of the goods shelf.
The method, system, device and storage medium for acquiring information of a vacant commodity according to the present invention will be described in detail with reference to the accompanying drawings and specific embodiments. The advantages and features of the present invention will become more fully apparent from the appended claims and the following description. It is to be noted that the drawings are in a very simplified form and are not to precise scale, which is merely for the purpose of facilitating and distinctly claiming the embodiments of the present invention.
It is to be understood that the terminology used in the description is for the purpose of describing particular embodiments only, and is not intended to be limiting of the disclosure. All terms (including technical and scientific terms) used in the specification have the meaning commonly understood by one of ordinary skill in the art unless otherwise defined. Well-known functions or constructions may not be described in detail for brevity and/or clarity.
It should be noted that, the acquiring of the commodity information at the vacant position provided in this embodiment mainly refers to information that can help the staff to determine what kind of commodity is specific, and the information may include contents such as names, volumes, and packaging materials representing the commodities. Of course, the contents can be adjusted according to actual application conditions and actual commodities, and the purpose of the contents is to help workers to uniquely determine specific commodities corresponding to the vacant positions.
As shown in fig. 1, fig. 1 is a flowchart illustrating steps of a method for acquiring commodity information at a vacant shelf position according to the present embodiment. The splicing method provided by the embodiment comprises the following steps:
s1: acquiring a shelf image of the arranged commodities;
it should be noted that the shelf image acquired in step S1 is an image normally used for selling goods and may or may already contain goods. As will be readily understood by those skilled in the art, the shelf image may be an image captured by a mobile terminal with camera function (e.g., a smart phone), an image captured by a professional camera (e.g., a single lens reflex camera), or may be obtained by other hardware devices with camera function, which is not listed here.
S2: identifying the shelf image by using an identification model; to obtain the vacant positions of commodity vacancy on the shelf;
the recognition model in step S2 is a model obtained by training in advance using the above-mentioned shelf image. In training the recognition model, the acquired shelf images may be labeled with some existing labeling systems for the goods, shelves, etc. in the images, so as to "inform" the model which labeled features in the shelf images are goods and which labeled features are shelves. Of course, a large number of shelf images (images of different shelves, images of the same shelf taken at different angles, and the like) are required in the training process, so that the model can recognize the goods and the shelves in the images of various scenes, angles, and the like, and the accuracy of the recognition model is further improved.
Also, the skilled person can select a suitable image marking system tool according to the actual requirements. Of course, it is also possible to use his rational approach for model training. Regardless of the training method, as long as the requirement of the recognition model defined in step S2 is satisfied, it can be considered that the model can be applied to the method for acquiring the commodity information at the vacant shelf position provided in the present embodiment.
S3: and comparing the vacant positions with preset arrangement information on the shelf to obtain commodity information corresponding to the vacant positions.
Here, the "predetermined arrangement information" on the shelf means information that includes a placement position on the shelf, a type of a product, a model number, and the like, and that can uniquely identify the product and its position.
According to the method for acquiring the information of the vacant commodities, the shelf images of the arranged commodities are acquired, the acquired image information is identified by using an identification model, so that the vacant positions of the commodities on the shelf, which are vacant, are obtained, the commodity information is compared according to the preset commodity information on the shelf, and the corresponding commodity information on the vacant positions is finally obtained.
When the commodity information of the vacant positions on the shelves is obtained by the method, the final result is difficult to achieve high accuracy due to possible factors such as the accuracy of the identification model. For this reason, the present embodiment further provides a preferred scheme for vacant position identification, please refer to fig. 2, and fig. 2 is a flowchart of the steps for vacant position identification provided in the present embodiment. Namely, step S2 includes:
s201: identifying the area ranges occupied by the commodities and the vacant positions on the shelf image by using an identification model;
s202: marking the area range occupied by the commodity and the area range occupied by the vacant position by adopting a closed wire frame;
the closed wire frame mentioned in step S202 preferably uses a rectangular frame in this embodiment, so as to reduce the performance requirement of the hardware system running the method provided in this embodiment, thereby reducing the marking difficulty and improving the marking efficiency.
S203: carrying out image segmentation on the shelf image to obtain a characteristic picture of which the commodity characteristics are different from the shelf characteristics;
more specifically, in step S203, the image is segmented by edge segmentation to obtain a feature picture reflecting that the features of the product are different from the features of the shelf.
In addition, the shelf characteristics in the step are image centroids displayed in the characteristic pictures of the shelf after image segmentation; similarly, the term "commodity feature" refers to image information that is presented in a feature picture after image segmentation.
S204: mapping the closed wireframe on the shelf image onto the feature map;
s205: calculating the ratio of the area occupied by the shelf features in the closed wire frame to the corresponding area of the closed wire frame;
s206: comparing the ratio with a preset threshold, and when the ratio exceeds the preset threshold, taking the position of the corresponding closed wire frame as the vacant position where the commodity is vacant; otherwise, the position of the corresponding closed wire frame is abandoned.
In step S206, the predetermined threshold should be set to a value that is beneficial to improve the accuracy of the final acquired vacant position, and although the accuracy is not significantly and positively correlated with the size of the value in the actual verification process, the present embodiment provides a value of 0.8. The vacant position finally obtained by utilizing the numerical value is more in line with the actual verification condition, and the accuracy of the obtained vacant position is obviously improved.
It should be noted that, in the feature picture obtained by segmentation, there is a distinction between the shelf feature and the product feature because there is a distinct boundary (or may be expressed as a color contrast) between the area occupied by the product and the shelf, and just because of this feature, the feature picture mentioned in the above preferred embodiment can be obtained by image segmentation. In addition, not all of the shelf features and product features can be converted into corresponding "features" after image segmentation. Due to various possible or potential reasons such as shooting angles, light, commodity colors, frame colors and the like, part of the content which is easily regarded as non-commodity characteristics may appear in the area occupied by the commodity characteristics, and part of the content which is easily regarded as non-commodity characteristics may also appear in the area occupied by the shelf characteristics. It is determined that the content of non-shelf features present in the area occupied by shelf features is a lesser portion, and the content of non-merchandise features present in the area occupied by merchandise features is a lesser portion. Therefore, whether the area belongs to the shelf area or not can be further confirmed by utilizing the area calculation mode, and the vacant position of the shelf can be found. In the above description, it is mentioned that the obtained image may be labeled first in the training process to obtain the recognition model, and in the implementation process of the above preferred embodiment, the region occupied by the commodity and the region occupied by the vacant position may be labeled (depicted) by using a closed wire frame in the above labeling manner. Therefore, each closed wire frame can be mapped onto the feature map according to a uniform coordinate system, and when the ratio of the area occupied by the shelf features in each wire frame to the area occupied by the corresponding closed wire frame exceeds a preset threshold, the vacant positions on the shelf can be further screened out.
Therefore, the preferred scheme for identifying the vacant positions provided by the embodiment can more accurately screen out the vacant positions on the shelf, so that the accuracy of acquiring the vacant positions by using the method for acquiring commodity information of the vacant positions on the shelf is further improved.
For this reason, the embodiment further provides two preferred schemes for obtaining the commodity information corresponding to the vacant position by comparison, please refer to fig. 3 and 4 for reading together, and fig. 3 and 4 are flowcharts of steps for obtaining the commodity information at the vacant position by comparison provided in this embodiment.
In fig. 3, the steps involved are as follows:
s311: acquiring commodity information at a position adjacent to the vacant position;
s312: and taking the commodity information on the adjacent positions as the corresponding commodity information on the vacant positions.
It can be seen that in steps S311 and S312, the product information at the position adjacent to the vacant position is defined as the predetermined product information. In this case, the product information corresponding to the vacant position is identical to the product information of the adjacent position. In the conventional commercial shelf, a plurality of commodities of the same type are arranged side by side so as to meet a certain marketing strategy, so that the steps can more conveniently and efficiently acquire commodity information on vacant positions in practical application.
In fig. 4, the steps involved are as follows:
s321: setting the commodity arrangement history information on the shelf as the predetermined commodity information;
s322: and comparing the vacant position with the preset commodity information to obtain the commodity information corresponding to the vacant position.
Here, the product placement history information refers to product information that has been placed at the same position in the past. The mode can always keep a consistent commodity arrangement mode, and further can accurately know that the commodity is correctly arranged on the corresponding shelf position by a worker.
In addition, the preset commodity information can be flexibly adjusted according to the actual commodity arrangement requirement (such as changing commodity suppliers, updating commodity replacement and the like) so as to meet different requirements.
Fig. 5 is a schematic diagram illustrating module connections of the system for acquiring information on goods at vacant shelves according to this embodiment. The system for acquiring the commodity information of the vacant positions on the shelves can be used for realizing the steps of the method for acquiring the commodity information of the vacant positions on the shelves. The system comprises:
an image acquisition module 501, configured to acquire shelf images of arranged commodities;
an image recognition module 502 for recognizing the shelf image using a recognition model; to obtain the vacant positions of commodity vacancy on the shelf; wherein,
the identification model is obtained by utilizing the shelf image training in advance;
the information processing module 503 is configured to compare the predetermined position information of the vacant position on the shelf to obtain the commodity information corresponding to the vacant position.
Another aspect of this embodiment also provides an acquisition device for goods information at a vacant shelf position. The image stitching apparatus includes:
a memory for storing a computer program;
and a processor for implementing the steps of the method for acquiring commodity information at a vacant shelf position when executing the computer program.
As will be appreciated by one skilled in the art, aspects of the present embodiments may be embodied as a system, method or program product. Thus, aspects of the present embodiments may be embodied in the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" platform.
Fig. 6 is a schematic structural diagram of an acquisition apparatus for commodity information at a vacant shelf position according to the present embodiment. An electronic device 600 implemented according to an embodiment of the invention is described in detail below with reference to fig. 6. The electronic device 600 shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 6, the electronic device 600 is embodied in the form of a general purpose computing device. The set-up of the electronic device 600 may include, but is not limited to: at least one processing unit 610, at least one memory unit 620, a bus 630 connecting the different platform components (including the memory unit 620 and the processing unit 610), a display unit 640, etc.
Wherein the storage unit stores a program code, which can be executed 610 by the processing unit, so that the processing unit 610 performs the implementation steps according to the present embodiment described in the above-mentioned image stitching method section in the present embodiment. For example, processing unit 610 may perform the steps as shown in fig. 1.
The storage unit 620 may include readable media in the form of volatile storage units, such as a random access unit (RAM) and/or cache memory unit, and may further include a read only memory unit (ROM) 6203.
The memory unit 620 may also include a program/utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
Bus 630 may represent one or more of any of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an image acceleration port, a processing unit, or a local bus using any of a variety of bus architectures.
The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 600, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 650. Also, the electronic device 600 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via the bus 630. It should be appreciated that although not shown in FIG. 7, other hardware and/or software modules may be used in conjunction with electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, to name a few.
A final aspect of the present embodiment provides a computer-readable storage medium, which stores thereon a computer program, which, when being executed by a processor, is capable of implementing the steps of the above-mentioned method for acquiring information on goods at empty positions on shelves. Although this embodiment does not exhaustively enumerate other specific embodiments, in some possible embodiments, the various aspects of the present invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the present invention as described in the image stitching method section above in this embodiment, when the program product is run on the terminal device.
As described above, when the computer program stored in the computer-readable storage medium provided in this embodiment is executed, the shelf image of the arranged goods is obtained, and then the obtained image information is identified by using an identification model, so as to obtain the vacant positions where the goods are vacant on the shelf, and then the comparison is performed according to the predetermined goods information on the shelf, and finally the goods information corresponding to the vacant positions is obtained, so that the working method of manual inventory in the prior art can be replaced to a greater extent, the working intensity of the staff is reduced, the speed of the merchant for obtaining the goods information on the shelf is increased, and the update frequency of the goods information on the shelf is increased.
Fig. 7 is a schematic structural diagram of a computer-readable storage medium provided in this embodiment. As shown in fig. 7, there is depicted a program product 800 for implementing the above method according to an embodiment of the present invention, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. Of course, the program product produced in accordance with the present embodiments is not limited in this regard, as a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the C language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In summary, in the method, the system, the device, and the storage medium for acquiring information of empty commodities provided in this embodiment, the shelf image of the arranged commodities is acquired, and then the acquired image information is identified by using an identification model, so as to obtain the empty positions where the commodities are empty on the shelf, and then the comparison is performed according to the preset commodity information on the shelf, so as to finally obtain the corresponding commodity information on the empty positions, which can replace the manual counting mode in the prior art to a greater extent, reduce the working intensity of the staff, further improve the speed of the merchant for acquiring the commodity information on the shelf, and accelerate the update frequency of the commodity information on the shelf.
On the other hand, the merchant can also reduce the manpower and material resources invested for obtaining the commodity information on the goods shelf, thereby reducing the operating cost and improving the profit margin.
On the last hand, the invention uses machine vision to identify the goods shelf and compares the obtained final vacant commodity information, thereby greatly improving the accuracy of obtaining the commodity information on the goods shelf.
The above description is only for the purpose of describing the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention, and any variations and modifications made by those skilled in the art based on the above disclosure are within the scope of the appended claims.
Claims (10)
1. A method for acquiring commodity information of a vacant position on a shelf is characterized by comprising the following steps:
acquiring a shelf image of the arranged commodities;
identifying the shelf image by using an identification model to obtain the vacant positions of commodity vacancies on the shelf; wherein,
the identification model is obtained by utilizing the shelf image training in advance;
and comparing the vacant positions with preset arrangement information on the shelf to obtain commodity information corresponding to the vacant positions.
2. The method for acquiring commodity information on a shelf vacant position according to claim 1, wherein the recognizing the shelf image by the recognition model to acquire a vacant position on the shelf where a commodity vacancy exists includes:
identifying the area ranges occupied by the commodities and the vacant positions on the shelf image by using an identification model;
marking the area range occupied by the commodity and the area range occupied by the vacant position by adopting a closed wire frame;
carrying out image segmentation on the shelf image to obtain a characteristic picture of which the commodity characteristics are different from the shelf characteristics;
mapping the closed wireframe on the shelf image onto the feature map;
calculating the ratio of the area occupied by the shelf features in the closed wire frame to the corresponding area of the closed wire frame;
comparing the ratio with a preset threshold, and when the ratio exceeds the preset threshold, taking the position of the corresponding closed wire frame as the vacant position where the commodity is vacant; otherwise, the position of the corresponding closed wire frame is abandoned.
3. The method for acquiring commodity information at a shelf vacant position according to claim 2, wherein the image segmentation of the shelf image to obtain a characteristic picture of the commodity characteristic difference and the shelf characteristic comprises:
and segmenting the image by utilizing an edge segmentation mode to obtain the characteristic picture which reflects the characteristics of the commodity and reflects the characteristics of the goods shelf to be different.
4. The method for acquiring commodity information on a vacant shelf position according to claim 2, wherein the closed wire frame is a rectangular frame.
5. The shelf empty position commodity information acquisition method according to claim 2, wherein the predetermined threshold value is 0.8.
6. The method for acquiring commodity information of a vacant position on a shelf according to claim 1, wherein the step of comparing the vacant position with predetermined arrangement information on the shelf to obtain commodity information corresponding to the vacant position includes:
acquiring commodity information at a position adjacent to the vacant position;
and taking the commodity information on the adjacent positions as the corresponding commodity information on the vacant positions.
7. The method for acquiring commodity information of a vacant position on a shelf according to claim 1, wherein the step of comparing the vacant position with predetermined arrangement information on the shelf to obtain commodity information corresponding to the vacant position includes:
setting the commodity arrangement history information on the shelf as the predetermined commodity information;
and comparing the vacant position with the preset commodity information to obtain the commodity information corresponding to the vacant position.
8. A shelf vacant position commodity information acquisition system for realizing the steps of the shelf vacant position commodity information acquisition method according to any one of claims 1 to 7, characterized by comprising:
the image acquisition module is used for acquiring a shelf image of the arranged commodities;
the image identification module is used for identifying the shelf image by utilizing an identification model; to obtain the vacant positions of commodity vacancy on the shelf; wherein,
the identification model is obtained by utilizing the shelf image training in advance;
and the information processing module is used for comparing the preset position information of the vacant position on the goods shelf to obtain the commodity information corresponding to the vacant position.
9. A shelf vacant position commodity information acquisition apparatus characterized by comprising:
a memory for storing a computer program;
a processor for implementing the steps of the method for acquiring shelf empty position merchandise information according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that a computer program is stored thereon, which, when being executed by a processor, carries out the steps of the method for acquiring information on articles at a shelf vacant position according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910812733.8A CN110516628A (en) | 2019-08-29 | 2019-08-29 | Shelf vacant locations merchandise news acquisition methods, system, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910812733.8A CN110516628A (en) | 2019-08-29 | 2019-08-29 | Shelf vacant locations merchandise news acquisition methods, system, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110516628A true CN110516628A (en) | 2019-11-29 |
Family
ID=68629277
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910812733.8A Pending CN110516628A (en) | 2019-08-29 | 2019-08-29 | Shelf vacant locations merchandise news acquisition methods, system, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110516628A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111161388A (en) * | 2019-12-31 | 2020-05-15 | 上海扩博智能技术有限公司 | Method, system, equipment and storage medium for generating retail commodity shelf image |
| CN111783627A (en) * | 2020-06-29 | 2020-10-16 | 杭州海康威视数字技术股份有限公司 | Commodity stock determining method, device and equipment |
| CN111881894A (en) * | 2019-12-09 | 2020-11-03 | 上海扩博智能技术有限公司 | Method, system, equipment and storage medium for collecting goods selling information of container |
| CN112434584A (en) * | 2020-11-16 | 2021-03-02 | 浙江大华技术股份有限公司 | Shelf commodity surplus calculation method and device, computer equipment and storage medium |
| CN113674049A (en) * | 2021-06-24 | 2021-11-19 | 杭州碑石数据技术有限公司 | Commodity shelf position identification method and system based on picture search and storage medium |
| CN114253253A (en) * | 2020-09-24 | 2022-03-29 | 科沃斯商用机器人有限公司 | Target identification method and device based on artificial intelligence and robot |
| CN114999060A (en) * | 2022-06-27 | 2022-09-02 | 河南云迹智能技术有限公司 | Container identification system and method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180060803A1 (en) * | 2016-08-23 | 2018-03-01 | Wal-Mart Stores, Inc. | System and method for managing retail products |
| CN108960038A (en) * | 2018-05-04 | 2018-12-07 | 广州图匠数据科技有限公司 | A kind of shopping cart and its recognition methods based on image recognition technology |
| CN108986357A (en) * | 2018-08-21 | 2018-12-11 | 深圳码隆科技有限公司 | Merchandise news determines method, system and self-service system |
| CN109446883A (en) * | 2018-09-05 | 2019-03-08 | 北京三快在线科技有限公司 | Condition of merchandise recognition methods, device, electronic equipment and readable storage medium storing program for executing |
| CN109977886A (en) * | 2019-03-29 | 2019-07-05 | 京东方科技集团股份有限公司 | Shelf vacancy rate calculation method and device, electronic equipment, storage medium |
-
2019
- 2019-08-29 CN CN201910812733.8A patent/CN110516628A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180060803A1 (en) * | 2016-08-23 | 2018-03-01 | Wal-Mart Stores, Inc. | System and method for managing retail products |
| CN108960038A (en) * | 2018-05-04 | 2018-12-07 | 广州图匠数据科技有限公司 | A kind of shopping cart and its recognition methods based on image recognition technology |
| CN108986357A (en) * | 2018-08-21 | 2018-12-11 | 深圳码隆科技有限公司 | Merchandise news determines method, system and self-service system |
| CN109446883A (en) * | 2018-09-05 | 2019-03-08 | 北京三快在线科技有限公司 | Condition of merchandise recognition methods, device, electronic equipment and readable storage medium storing program for executing |
| CN109977886A (en) * | 2019-03-29 | 2019-07-05 | 京东方科技集团股份有限公司 | Shelf vacancy rate calculation method and device, electronic equipment, storage medium |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111881894A (en) * | 2019-12-09 | 2020-11-03 | 上海扩博智能技术有限公司 | Method, system, equipment and storage medium for collecting goods selling information of container |
| CN111161388A (en) * | 2019-12-31 | 2020-05-15 | 上海扩博智能技术有限公司 | Method, system, equipment and storage medium for generating retail commodity shelf image |
| CN111161388B (en) * | 2019-12-31 | 2023-10-13 | 上海扩博智能技术有限公司 | Method, system, device and storage medium for generating retail commodity shelf images |
| CN111783627A (en) * | 2020-06-29 | 2020-10-16 | 杭州海康威视数字技术股份有限公司 | Commodity stock determining method, device and equipment |
| CN111783627B (en) * | 2020-06-29 | 2023-10-27 | 杭州海康威视数字技术股份有限公司 | Commodity stock determining method, device and equipment |
| CN114253253A (en) * | 2020-09-24 | 2022-03-29 | 科沃斯商用机器人有限公司 | Target identification method and device based on artificial intelligence and robot |
| CN112434584A (en) * | 2020-11-16 | 2021-03-02 | 浙江大华技术股份有限公司 | Shelf commodity surplus calculation method and device, computer equipment and storage medium |
| CN112434584B (en) * | 2020-11-16 | 2024-04-30 | 浙江大华技术股份有限公司 | Goods shelf allowance calculation method, device, computer equipment and storage medium |
| CN113674049A (en) * | 2021-06-24 | 2021-11-19 | 杭州碑石数据技术有限公司 | Commodity shelf position identification method and system based on picture search and storage medium |
| CN114999060A (en) * | 2022-06-27 | 2022-09-02 | 河南云迹智能技术有限公司 | Container identification system and method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110516628A (en) | Shelf vacant locations merchandise news acquisition methods, system, equipment and storage medium | |
| US10664692B2 (en) | Visual task feedback for workstations in materials handling facilities | |
| CN108416403B (en) | Method, system, equipment and storage medium for automatically associating commodity with label | |
| US8527325B1 (en) | System and method for allocating labor to units processed in a materials handling facility | |
| CN112100425B (en) | Label labeling method and device based on artificial intelligence, electronic equipment and medium | |
| US11328250B2 (en) | Inventory management server, inventory management system, inventory management program, and inventory management method | |
| CN108629318B (en) | Shelf display identification method, device and system based on image identification technology | |
| CN110796416B (en) | Industrial networking based order processing method and computer storage medium | |
| US8423432B1 (en) | System and method for authoritative item identification based on facility operations | |
| CN112465032A (en) | Distribution method and device of training data labeling tasks and computing equipment | |
| CN111124863A (en) | Intelligent equipment performance testing method and device and intelligent equipment | |
| CN112001664B (en) | Method, device, equipment and storage medium for generating return tasks | |
| CN111753614A (en) | Commodity shelf monitoring method and device | |
| CN114969040A (en) | Data display method and device, electronic equipment and storage medium | |
| CN113268478A (en) | Big data analysis method and device, electronic equipment and storage medium | |
| CN113627415A (en) | Method and device for determining target object placement information | |
| CN107341632A (en) | A kind of data capture method and device based on user's request | |
| CN108446693B (en) | Marking method, system, equipment and storage medium of target to be identified | |
| WO2023280098A1 (en) | Weighing processing method and apparatus, and electronic device | |
| WO2023050504A1 (en) | Artificial intelligence identification scale management system with multiple weighing platforms | |
| CN108453050A (en) | Electric energy meter method for sorting, device and system | |
| US20200126013A1 (en) | Microcomponents for data integration and methods thereof | |
| CN112131511A (en) | Method and device for displaying negotiation information in matching activities | |
| CN112488318A (en) | Self-service cash registering system and method | |
| US11556891B2 (en) | Operations system for combining independent product monitoring systems to automatically manage product inventory and product pricing and automate store processes |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20191129 |
|
| RJ01 | Rejection of invention patent application after publication |