A commodity weighing method, device, equipment and storage medium

Abstract

The application discloses a commodity weighing method, device, equipment and storage medium. The method comprises the following steps: acquiring target commodity information on a weighing disc, wherein the target commodity information comprises target commodity image information and target commodity weight information; identifying the target commodity information to determine target commodity value information corresponding to the highest confidence of the target commodity; and generating a target commodity label based on the target commodity value information. Through the technical scheme, the timeliness and accuracy of commodity weighing can be improved, and thus the service quality can be improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method, apparatus, device and storage medium for weighing goods. Background Technology

[0002] With the increasing prevalence of technologies such as artificial intelligence and deep learning, image recognition technology can significantly improve the work efficiency of staff. Currently, in various shopping malls and supermarkets, when weighing bulk goods, staff need to input different product codes to weigh the goods, which increases the supermarket's operating costs and reduces the timeliness and accuracy of product weighing. Summary of the Invention

[0003] This invention provides a method, apparatus, equipment, and storage medium for weighing goods, in order to solve the problem of goods not being automatically identified and weighed.

[0004] According to one aspect of the present invention, a method for weighing goods is provided, the method comprising:

[0005] Obtain target product information from the weighing pan, the target product information including target product image information and target product weight information;

[0006] The target product information is identified to determine the target product value information with the highest confidence level corresponding to the target product;

[0007] A target product label is generated based on the target product value information.

[0008] According to another aspect of the present invention, a commodity weighing device is provided, the device comprising:

[0009] The target product information acquisition module is used to acquire target product information on the weighing pan, the target product information including target product image information and target product weight information;

[0010] The target product value information determination module is used to identify the target product information in order to determine the target product value information with the highest confidence level corresponding to the target product;

[0011] The target product label generation module is used to generate target product labels based on the target product value information.

[0012] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0013] At least one processor; and

[0014] A memory communicatively connected to the at least one processor; wherein,

[0015] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the commodity weighing method according to any embodiment of the present invention.

[0016] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the commodity weighing method according to any embodiment of the present invention.

[0017] The technical solution of this invention acquires target product information from a weighing pan, including target product image information and target product weight information. Then, the target product information is identified to determine the target product value information with the highest confidence level. Finally, a target product tag is generated based on the target product value information, solving the current problem of inaccurate product identification. This technical solution improves the timeliness and accuracy of product weighing, thereby enhancing service quality.

[0018] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of a commodity weighing method provided in Embodiment 1 of the present invention;

[0021] Figure 2 This is a flowchart of a commodity weighing method applicable to Embodiment 2 of the present invention;

[0022] Figure 3 This is a schematic diagram of the structure of a commodity weighing device according to Embodiment 3 of the present invention;

[0023] Figure 4 This is a schematic diagram of the structure of an electronic device that implements an embodiment of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "comprising" and "having" and any variations thereof in the specification, claims and accompanying drawings of this invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such processes, methods, products or devices.

[0026] Example 1

[0027] Figure 1 This invention provides a flowchart of a product weighing method according to Embodiment 1. This embodiment is applicable to self-service product weighing. The method can be executed by a product weighing device, which can be implemented in hardware and / or software and can be configured in a smart electronic scale. Figure 1 As shown, the method includes:

[0028] S110. Obtain target product information from the weighing pan, wherein the target product information includes target product image information and target product weight information.

[0029] The target product information refers to the information of the product that the user needs to weigh, i.e., the information of the product to be weighed. Target product information may include target product image information and target product weight information, etc.

[0030] Specifically, images of the target product can be taken using a camera, or video frames can be selected from a recorded video stream. The camera can be fixed above or to the side of the weighing pan, at a distance sufficient to capture a complete image of the target product. The weight of the target product on the weighing pan can be obtained using a load cell and used as the product's weight information.

[0031] S120. Identify the target product information to determine the target product value information with the highest confidence level corresponding to the target product.

[0032] Among them, the target product value information is the price corresponding to the target product.

[0033] For example, the step of identifying the target product information to determine the target product value information with the highest confidence level may include:

[0034] Based on the target product display information, the confidence level of multiple pending products in the product database is determined; based on the confidence level, all pending products are sorted in descending order to determine and display the target product value information corresponding to the pending product with the highest confidence level.

[0035] Specifically, image recognition technology can be used to process the target product image information to obtain the confidence level information corresponding to the target product image, and to determine the confidence level of the candidate product corresponding to the product in the product database and the target product image information. After obtaining the confidence level of the corresponding candidate product, the confidence level values ​​of each candidate product are sorted in descending order from largest to smallest, and the candidate product corresponding to the candidate product with the largest confidence level value is determined as the target product. Based on the determined target product, the target product medium information is obtained.

[0036] For example, if the confidence level of the target product information is lower than the confidence level threshold, the step of obtaining the target product information on the weighing pan is re-executed.

[0037] If the confidence level of the target product image obtained after processing is lower than the preset confidence threshold, it indicates that the following situations may occur: the target product image does not contain the complete target product, the target product is not stationary when the target product image is acquired, or the target product is obscured. The target product image information on the weighing pan can be reacquired by adjusting the position of the target product or the position and distance of the camera device.

[0038] S130. Generate a target product label based on the target product value information.

[0039] The target product label can refer to the label on the weighed target product. The target product label can be made of waterproof material. The information contained on the target product label may include: the name of the target product, unit price, total price, quantity of the target product, and the corresponding barcode information.

[0040] Specifically, after obtaining the value information of the target product, a target product tag can be generated based on the value information of the target product and the corresponding information of the target product stored in the product database.

[0041] The technical solution of this invention improves the timeliness and accuracy of weighing goods by acquiring target product information on a weighing pan, identifying the target product information to determine the target product value information with the highest confidence level, and generating a target product label based on the target product value information. This can improve service quality.

[0042] Based on the above embodiments, the step of identifying the target product information to determine the target product value information with the highest confidence level may further include: obtaining the unit price value information of the target product based on the target product confidence level; and determining the target product value information by multiplying the target product weight information and the target product unit price value information according to the target product weight information.

[0043] Specifically, based on the confidence level information and weight information of the target product, the unit price information of the target product is queried in the product database, and the product of the unit price information and the weight information of the target product is used as the medium information of the target product, that is, the price information of the weighed target product.

[0044] Optionally, after determining the target product value information with the highest confidence level corresponding to the target product, the method further includes:

[0045] If the value information of the pending product with the highest confidence level does not match the target product, the value information of the pending product with the second highest confidence level is determined as the value information of the target product and the value information of the target product is displayed.

[0046] Specifically, if the target product value information with the highest confidence level does not match the actual product, the second-highest confidence level product can be selected as the target product value information, and the latest target product value information will be displayed to the user. If the second-highest confidence level target product value information still does not match the actual product, the third-highest confidence level product can be selected as the target product value information, and the latest target product value information will be displayed to the user. This process continues until the actual product value information is determined and displayed.

[0047] Based on the above embodiments, after the step of re-executing the step of obtaining the target product information on the weighing pan if the confidence level is lower than the confidence level threshold, the method further includes:

[0048] If the confidence level of the target product image is still lower than the confidence level threshold, then image optimization processing is performed on the target product image. The image optimization processing includes white balance, sharpening, occlusion removal, and noise reduction.

[0049] Specifically, after re-acquiring and recognizing the target product image, if the confidence score of the target product image is still lower than the preset confidence threshold, image optimization processing can be performed on the target product image information. This image optimization processing can include, but is not limited to, white balance adjustments, sharpening, occlusion removal, and noise reduction, which can effectively improve the recognition rate of the target product image information and enhance the user experience.

[0050] Example 2

[0051] Figure 2 This is a flowchart of a commodity weighing method according to Embodiment 2 of the present invention. This embodiment further optimizes the method before the step "obtaining target commodity information on the weighing pan" based on the above embodiments. Explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here. See also Figure 2 The commodity weighing method based on a commodity weighing device provided in this embodiment may include the following steps:

[0052] S210. Determine whether the acceleration of the change in the weight of the target product tends to a stable state. If so, obtain the weight information of the target product.

[0053] Specifically, to determine the accuracy of target product identification, the identification effect is optimal when the target product is in a stable state. This can be achieved by determining whether the acceleration of the weight change of the target product is in a stable state. A stable state can be represented by the following formula:

[0054]

[0055] Where Is_s represents whether the current target product is in a stable state, and a is the acceleration of the change in the weight of the current target product. max It is the maximum acceleration when the weight of the target product just begins to change, and n is a preset threshold. When the acceleration changes to 1 / n of the maximum acceleration, it can be preliminarily judged that the acceleration of the weight change of the target product tends to a stable state. The setting of this threshold can be flexibly adjusted according to the needs of the site and the configuration of the hardware equipment.

[0056] S220. Determine whether the video stream of the target product is in a stable state. If so, obtain the image information of the target product from the video stream.

[0057] Once the acceleration of the weight change of the target product has stabilized, N frames of target product image information can be continuously acquired from the video stream captured by the camera device. The N-frame difference method can be used to determine whether the current target product image information contains a moving object. Preferably, N can be 3.

[0058] Specifically, taking the second frame of the continuously acquired target product image information as n, the images of the (n+1)th, nth, and (n-1)th frames are fn+1, fn, and fn-1, respectively. The grayscale values ​​corresponding to the three frames of target product image information are denoted as fn+1(x,y), fn(x,y), and fn-1(x,y). Then, the difference images Dn+1 and Dn are calculated respectively. Then, an AND operation is performed on the difference images Dn+1 and Dn to obtain the image Dn`. Then, thresholding is performed, and the number of pixel values ​​greater than 0 remaining in the final target product image frame is used to determine whether the image of that frame is in a stable state. If it is not in a stable state, the next frame image is acquired and the judgment process is repeated. If it is in a stable state, the n+1th frame image is acquired as the target product image information.

[0059] S230. Obtain target product information from the weighing pan, wherein the target product information includes target product image information and target product weight information.

[0060] S240. Identify the target product information to determine the target product value information with the highest confidence level corresponding to the target product.

[0061] S250. Generate a target product label based on the target product value information.

[0062] The technical solution of this invention improves the quality of acquiring target product information by determining whether the acceleration of the change in the weight of the target product tends to a stable state, and if so, acquiring the weight information of the target product; and by determining whether the video stream of the target product is in a stable state, and if so, acquiring the image information of the target product from the video stream. This can further improve the accuracy of product recognition and thus improve service quality.

[0063] Based on the above embodiments, the step of determining whether the video stream of the target product is in a stable state further includes:

[0064] Determine whether the weighing time has reached the predetermined time; if so, obtain the target product image information at the time the predetermined time is reached, and identify the target product image information.

[0065] Specifically, if the target product in the video stream cannot be in a stable state within a predetermined time, the video frame corresponding to the time when the preset duration is reached is obtained as the target product image information and processed for recognition. This can reduce the time consumption of shooting and further improve the user experience.

[0066] Example 3

[0067] Figure 3 This is a schematic diagram of a commodity weighing device provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes: a target product information acquisition module 310, a target product value information determination module 320, and a target product label generation module 330.

[0068] The target product information acquisition module 310 is used to acquire target product information on the weighing pan, including target product image information and target product weight information.

[0069] The target product value information determination module 320 is used to identify the target product information to determine the target product value information with the highest confidence level corresponding to the target product.

[0070] The target product label generation module 330 is used to generate target product labels based on the target product value information.

[0071] This invention discloses a method, apparatus, device, and storage medium for weighing goods. The method includes: acquiring target product information from a weighing pan, the target product information including target product image information and target product weight information; identifying the target product information to determine the target product value information with the highest confidence level corresponding to the target product; and generating a target product label based on the target product value information. This embodiment of the technical solution can improve the timeliness and accuracy of goods weighing, thereby improving service quality.

[0072] Optionally, the product weighing device further includes:

[0073] The target product weight information determination module is used to determine whether the acceleration of the change in the weight of the target product tends to a stable state; if so, the target product weight information is obtained.

[0074] The target product image information judgment module is also used to determine whether the video stream of the target product is in a stable state; if so, the target product image information is obtained from the video stream.

[0075] Optionally, the target image information determination module is further configured to:

[0076] Determine whether the weighing time has reached the predetermined time;

[0077] If so, obtain the target product image at the time when the predetermined time period arrives, and identify the target product image.

[0078] Optionally, the target commodity value information determination module 320 includes:

[0079] The confidence level determination unit for pending products is used to determine the confidence level of multiple pending products in the product database based on the target product display information;

[0080] The target product value information determination unit is used to sort all pending products in descending order based on their confidence level, so as to determine and display the target product value information corresponding to the pending product with the highest confidence level.

[0081] Optionally, if the confidence level of the target product information is lower than the confidence level threshold, the target product information acquisition module 310 re-executes the step of acquiring the target product information on the weighing pan.

[0082] Optionally, the target commodity value information determination module 320 further includes:

[0083] The target product unit price acquisition unit is used to obtain the unit price value information of the target product based on the confidence level of the target product.

[0084] The target commodity value information determination unit is further configured to determine the target commodity value information by multiplying the target commodity weight information and the target commodity unit price information based on the target commodity weight information.

[0085] The target commodity value information determination module 320 is also used for:

[0086] If the value information of the pending product with the highest confidence level does not match the target product, the value information of the pending product with the second highest confidence level is determined as the value information of the target product and the value information of the target product is displayed.

[0087] Example 4

[0088] Figure 4 A schematic diagram of the structure of a weighing electronic device 10 that can be used to implement an embodiment of the present invention is shown. Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0089] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0090] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a product weighing method.

[0091] In some embodiments, the product weighing method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the product weighing method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured by any other suitable means (e.g., by means of firmware) to perform the product weighing method of any of the above embodiments.

[0092] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0093] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0094] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0095] To provide interaction with the user, the systems and techniques described herein can be implemented on a weighing electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the weighing electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0096] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0097] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0098] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0099] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for weighing goods, characterized in that, include: Obtain target product information from the weighing pan, the target product information including target product image information and target product weight information; The target product information is identified to determine the target product value information with the highest confidence level corresponding to the target product; Generate a target product tag based on the target product value information; Before obtaining the target product information from the weighing pan, the following steps are included: Determine whether the acceleration of the change in the weight of the target product tends to a stable state; if so, obtain the weight information of the target product. Determine whether the video stream of the target product is in a stable state; if so, obtain the image information of the target product from the video stream. The steady state of acceleration is represented by the following formula: Where Is_s represents whether the target product is in a stable state, a is the acceleration of the change in the weight of the target product, and a max It is the maximum acceleration when the weight of the target product just begins to change, and n is a preset threshold. When the acceleration changes to 1 / n of the maximum acceleration, it is determined that the acceleration of the weight change of the target product tends to a stable state. The step of determining whether the video stream of the target product is in a stable state includes: Acquire three consecutive frames of the target product image, and determine the first difference image and the second difference image between each pair of the three consecutive frames of the target product image; The first difference image and the second difference image are ANDed to obtain the target image, and the target image is thresholded to obtain the target judgment image. Based on the number of pixel values ​​greater than 0 in the target image, it is determined whether the video stream of the target product is in a stable state.

2. The method according to claim 1, characterized in that, After determining whether the video stream of the target product is in a stable state, the method further includes: Determine whether the weighing time has reached the predetermined time; If so, obtain the target product image information at the time when the predetermined time period arrives, and identify the target product image information.

3. The method according to claim 1, characterized in that, The step of identifying the target product information to determine the target product value information with the highest confidence level includes: Based on the target product display information, determine the confidence level of multiple undetermined products in the product database; All pending products are sorted in descending order based on their confidence level to identify and display the target product value information corresponding to the pending product with the highest confidence level.

4. The method according to claim 2, characterized in that, If the confidence level of the target product information is lower than the confidence level threshold, the step of obtaining the target product information on the weighing pan is repeated.

5. The method according to claim 1, characterized in that, The step of identifying the target product information to determine the target product value information with the highest confidence level includes: Based on the confidence level of the target product, obtain the unit price value information of the target product; Based on the target product's weight information, the product of the target product's weight information and the target product's unit price information is determined as the target product's value information.

6. The method according to claim 2, characterized in that, After determining the target product value information with the highest confidence level corresponding to the target product, the process further includes: If the value information of the pending product with the highest confidence level does not match the target product, the value information of the pending product with the second highest confidence level is determined as the value information of the target product and the value information of the target product is displayed.

7. A commodity weighing device, characterized in that, include: The target product information acquisition module is used to acquire target product information on the weighing pan, the target product information including target product image information and target product weight information; The target product value information determination module is used to identify the target product information in order to determine the target product value information with the highest confidence level corresponding to the target product; The target product label generation module is used to generate target product labels based on the target product value information. The target product weight information determination module is used to determine whether the acceleration of the change in the weight of the target product tends to a stable state before acquiring the target product information on the weighing pan; if so, the target product weight information is acquired. The target product image information judgment module is used to determine whether the video stream of the target product is in a stable state before acquiring the target product information on the weighing pan; if so, the target product image information is acquired from the video stream. The steady state of acceleration is represented by the following formula: Where Is_s represents whether the target product is in a stable state, a is the acceleration of the change in the weight of the target product, and a max It is the maximum acceleration when the weight of the target product just begins to change, and n is a preset threshold. When the acceleration changes to 1 / n of the maximum acceleration, it is determined that the acceleration of the weight change of the target product tends to a stable state. The target product image information judgment module is used for: Acquire three consecutive frames of the target product image, and determine the first difference image and the second difference image between each pair of the three consecutive frames of the target product image; The first difference image and the second difference image are ANDed to obtain the target image, and the target image is thresholded to obtain the target judgment image. Based on the number of pixel values ​​greater than 0 in the target image, it is determined whether the video stream of the target product is in a stable state.

8. A weighing electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor to enable the at least one processor to perform the commodity weighing method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the commodity weighing method according to any one of claims 1-6.

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