Method and device for identifying damage of goods in parcel, electronic equipment and storage medium

Abstract

The invention discloses a damage identification method and device for goods in a package, electronic equipment and a storage medium, and the method comprises the steps: obtaining a current X-ray image of the package; the current X-ray image is input to an object detection model, corresponding detection results are obtained, the object detection model is obtained based on the historical X-ray image of the damaged goods and the target detection model, and the detection results comprise a first detection result used for representing that the goods in the package are damaged and a second detection result used for representing that the goods in the package are not damaged. According to the method, the damage identification of the goods in the parcel is realized based on the object detection model, and the identification accuracy of the damage identification of the goods in the parcel is improved.

Description

Technical Field

[0001] The present application belongs to the field of logistics technology, and in particular relates to a method, device, electronic device and storage medium for identifying damaged goods in a package. Background Art

[0002] With the rapid development of e-commerce, the volume of express delivery business has gradually increased, and more and more goods are packaged into parcels for transportation. During transportation, parcels are often damaged due to squeezing, collision, etc., which in turn causes damage to the goods inside the parcels. In order to prevent customers from receiving parcels with damaged goods, logistics companies often identify the damaged goods inside the parcels before delivery, and intercept the parcels when they identify that the goods inside the parcels are damaged.

[0003] At present, the damage identification of goods in the package is mainly carried out by the sorter's human eyes to observe whether the package packaging is damaged. If the sorting staff observes that the package packaging is not damaged, then the goods in the package are judged to be not damaged; if the sorting staff observes that the package packaging is damaged, then the goods in the package are judged to be broken.

[0004] However, when the goods in the package are fragile items, the package may be slightly bumped, the package packaging is intact, but the goods in the package are damaged. The inspectors observe that the package packaging is not damaged, so they mistakenly judge that the goods in the package are not damaged, which reduces the accuracy of damage identification of the goods in the package. Summary of the invention

[0005] In view of this, the embodiments of the present application provide a method, device, electronic device and storage medium for identifying damaged goods in a package to overcome or at least partially solve the above problems of the prior art.

[0006] In a first aspect, an embodiment of the present application provides a method for identifying damaged goods in a package, comprising: obtaining a current X-ray image of the package; inputting the current X-ray image into an object detection model to obtain a corresponding detection result, wherein the object detection model is obtained based on historical X-ray images of damaged goods and a target detection model, and the detection result includes a first detection result for characterizing that the goods in the package are damaged, and a second detection result for characterizing that the goods in the package are not damaged.

[0007] In a second aspect, an embodiment of the present application provides a device for identifying damaged goods in a package, including an image acquisition module and an image input module. The image acquisition module is used to acquire a current X-ray image of the package; the image input module is used to input the current X-ray image into an object detection model to obtain a corresponding detection result, the object detection model is obtained based on historical damaged goods X-ray images and a target detection model, and the detection result includes a first detection result for characterizing that the goods in the package are damaged, and a second detection result for characterizing that the goods in the package are not damaged.

[0008] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory; one or more processors coupled to the memory; and one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to execute the method for identifying damaged goods in a package as provided in the first aspect above.

[0009] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which a program code is stored. The program code can be called by a processor to execute the method for identifying damaged goods in a package as provided in the first aspect above.

[0010] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is executed on a computer device, the computer device executes the method for identifying damaged goods in a package provided in the first aspect above.

[0011] The solution provided in the present application obtains a current X-ray image of a package and inputs the current X-ray image into an object detection model to obtain a corresponding detection result. The object detection model is obtained based on historical X-ray images of damaged goods and a target detection model. The detection result includes a first detection result for characterizing that the goods in the package are damaged, and a second detection result for characterizing that the goods in the package are not damaged. This realizes damage identification of the goods in the package based on the object detection model, thereby improving the recognition accuracy of damage identification of the goods in the package. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0013] Figure 1 A schematic diagram of a scenario of a system for identifying damaged goods in a package provided in an embodiment of the present application is shown.

[0014] Figure 2 A schematic flow chart of a method for identifying damaged goods in a package provided in an embodiment of the present application is shown.

[0015] Figure 3 Another schematic flow chart of the method for identifying damaged goods in a package provided in an embodiment of the present application is shown.

[0016] Figure 4 A structural block diagram of a device for identifying damaged goods in a package provided in an embodiment of the present application is shown.

[0017] Figure 5 A functional block diagram of an electronic device provided in an embodiment of the present application is shown.

[0018] Figure 6 A computer-readable storage medium provided in an embodiment of the present application for storing or carrying a program code for implementing a method for identifying damaged goods in a package provided in an embodiment of the present application is shown.

[0019] Figure 7 A computer program product provided in an embodiment of the present application and used for storing or carrying program codes for implementing the method for identifying damaged goods in a package provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0020] In order to make the purpose, features, and advantages of the invention of this application more obvious and easy to understand, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the embodiments described below are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0021] It should be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0022] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, the singular forms "a", "an" and "the" are intended to include plural forms unless the context clearly indicates other working conditions.

[0023] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0024] As used in this specification and the appended claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0025] In addition, in the description of the present application, the terms "first", "second", "third", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0026] With the rapid development of e-commerce, the volume of express delivery business has gradually increased, and more and more goods are packaged into parcels for transportation. During transportation, parcels are often damaged due to squeezing, collision, etc., which in turn causes damage to the goods inside the parcels. In order to prevent customers from receiving parcels with damaged goods, logistics companies often identify the damaged goods inside the parcels before delivery, and intercept the parcels when they identify that the goods inside the parcels are damaged.

[0027] At present, the damage identification of goods in the package is mainly carried out by the sorter's human eyes to observe whether the package packaging is damaged. If the sorting staff observes that the package packaging is not damaged, then the goods in the package are judged to be not damaged; if the sorting staff observes that the package packaging is damaged, then the goods in the package are judged to be broken.

[0028] However, when the goods in the package are fragile items, the package may be slightly bumped, the package packaging is intact, but the goods in the package are damaged. The inspectors observe that the package packaging is not damaged, so they mistakenly judge that the goods in the package are not damaged, which reduces the accuracy of damage identification of the goods in the package.

[0029] In response to the above problems, the inventors have conducted a long period of research and proposed a method, device, electronic device and storage medium for identifying damaged goods in a package provided in the embodiments of the present application. The method, device, electronic device and storage medium are used to obtain a current X-ray image of the package and input the current X-ray image into an object detection model to obtain a corresponding detection result. The object detection model is obtained based on historical X-ray images of damaged goods and a target detection model. The detection result includes a first detection result for characterizing that the goods in the package are damaged, and a second detection result for characterizing that the goods in the package are not damaged. This realizes the identification of damaged goods in the package based on the object detection model, thereby improving the accuracy of identifying damaged goods in the package.

[0030] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0031] See also Figure 1 , which shows a schematic diagram of an application scenario of the system for identifying damaged goods in a package provided in an embodiment of the present application, which may include a security inspection machine 100 and a processing device 200, wherein the security inspection machine 100 is communicatively connected to the processing device 200 and performs data exchange with the processing device 200.

[0032] The security inspection machine 100 can emit X-rays, and capture images of the package through X-rays, obtain corresponding X-ray images, and send the X-ray images to the processing device 200 .

[0033] The processing device 200 can be used to receive the X-ray image sent by the security inspection machine 100, and identify damage to the goods in the package based on the X-ray image.

[0034] The processing device 200 may be a terminal device or a server, etc. The type of the processing device 200 is not limited here and may be specifically configured according to actual needs.

[0035] The terminal device can be a mobile terminal device (for example, any one of a mobile phone, a personal digital assistant (PDA), a tablet personal computer (Tablet PC), a laptop computer, a smart watch, a smart bracelet or a wearable device, etc.), or a fixed terminal device (desktop computer, smart panel, etc.), etc.

[0036] The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or any one of the cloud servers that provide basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDN), big data or artificial intelligence platforms, etc.

[0037] In some embodiments, the security inspection machine 100 can be integrated with the processing device 200 to form an integrated device. For example, the processing device 200 can be embedded in the security inspection machine 100 and form an integrated device with the security inspection machine 100. The integrated device can be used to capture images of packages, obtain corresponding X-ray images, and identify damage to goods in the packages based on the X-ray images.

[0038] See also Figure 2 , which shows a flow chart of a method for identifying damaged goods in a package provided by an embodiment of the present application. In a specific embodiment, the method for identifying damaged goods in a package can be applied to Figure 1 The processing device 200 in the package damage identification system is shown in FIG. Figure 2 The process shown is described in detail, and the method for identifying damaged goods in a package may include the following steps S110 to S120.

[0039] Step S110: Acquire the current X-ray image of the package.

[0040] In an embodiment of the present application, when a sorter needs to identify damage to goods in a package, an identification instruction can be sent to a processing device, and the processing device receives and responds to the identification instruction to obtain a current X-ray image of the package.

[0041] Specifically, when the sorter needs to identify damage to the goods in the package, he can send an image acquisition instruction to the security inspection machine. The security inspection machine receives and responds to the image acquisition instruction, performs an X-ray scan on the package, obtains the corresponding current X-ray image, and sends the current X-ray image to the processing device. The processing device receives the current X-ray image returned by the security inspection machine.

[0042] Among them, the imaging principle of X-ray images is: X-ray imaging uses the different degrees of absorption of X-rays by materials of different densities when they penetrate objects to obtain the internal structural information of objects. Due to the different densities of different materials, the attenuation of X-rays after penetrating different materials varies, and the receiver also receives different signals. According to the strength of these signals, the security inspection machine renders the corresponding signals in different colors for easy observation by the human eye. Generally speaking, the color of textiles is light yellow, the color of liquids is orange-yellow, the color of metals is blue, the color of glass, ceramics and other mixtures is green, and objects that cannot be penetrated by X-rays are black.

[0043] In some embodiments, the processing device may include an input panel. When the sorter needs to identify damage to the goods in the package, the sorter may input an identification instruction on the input panel, and the processing device receives the identification instruction through the input panel.

[0044] In some embodiments, the processing device may include a voice recognition module. When the sorter needs to identify damage to goods in a package, a voice message carrying a recognition instruction can be sent within the voice collection range of the voice recognition module. The processing device collects the voice information through the voice recognition module, performs voice recognition on the voice information, and obtains the recognition instruction.

[0045] In some embodiments, the system for identifying damaged goods in a package may further include a client, which is connected to the processing device via a network and exchanges data with the processing device via the network.

[0046] When the sorter needs to identify the damage of the goods in the package, he can send an identification instruction to the client. The client receives and responds to the identification instruction and forwards the identification instruction to the processing device through the network. The processing device receives the identification instruction forwarded by the client.

[0047] Among them, the client can be any one of a mobile client (for example, a mobile phone client, a personal digital assistant (PDA) client, a tablet computer (Tablet Personal Computer, Tablet PC) client, a laptop computer client, a smart watch client, a smart bracelet client or a wearable client, etc.) or a fixed client (for example, a desktop computer client, a smart panel client, etc.). The type of client is not limited here and can be set according to actual needs.

[0048] The network can be any one of a ZigBee network, a Bluetooth (BT) network, a Wireless Fidelity (Wi-Fi) network, a Thread network, a Long Range Radio (LoRa) network, a Low-Power Wide-Area Network (LPWAN), an infrared network, a Narrow Band Internet of Things (NB-IoT), a Controller Area Network (CAN), a Digital Living Network Alliance (DLNA) network, a Wide Area Network (WAN), a Local Area Network (LAN), a Metropolitan Area Network (MAN) or a Wireless Personal Area Network (WPAN), etc. The type of network is not limited here and can be set according to actual needs.

[0049] Step S120: Input the current X-ray image into the object detection model to obtain the corresponding detection result.

[0050] In an embodiment of the present application, after acquiring the current X-ray image of the package, the processing device can input the current X-ray image into the object detection model. The object detection model receives and responds to the current X-ray image, identifies damage to the goods in the package based on the current X-ray image, obtains corresponding detection results, and outputs the detection results to the processing device. The processing device receives the detection results output by the object detection model. The object detection model can be obtained based on historical X-ray images of damaged goods and a target detection model. The detection results may include a first detection result for characterizing that the goods in the package are damaged, and a second detection result for characterizing that the goods in the package are not damaged, thereby realizing damage identification of the goods in the package based on the object detection model, and improving the recognition accuracy of damage identification of the goods in the package.

[0051] Among them, the object detection model can be obtained by training the target detection model based on the historical X-ray images of damaged goods. The target detection model can be any one of the YOLO-v3 model, Faster-RCNN model or YOLOX model. The type of the target detection model is not limited here and can be set according to actual needs.

[0052] In some embodiments, after acquiring the current X-ray image of the package, the processing device can obtain the corresponding training set and test set based on the historical X-ray images of damaged goods, and input the training set to the target detection model. The target detection model receives and responds to the training set, performs training based on the training set, obtains the corresponding object detection model, and determines whether the object detection model converges based on the test set. When it is determined that the object detection model converges based on the test set, the current X-ray image is input to the object detection model. The object detection model receives and responds to the current X-ray image, identifies damage to the goods in the package based on the current X-ray image, obtains the corresponding detection result, and outputs the detection result to the processing device. The processing device receives the detection result output by the object detection model, and realizes damage identification of the goods in the package based on the object detection model when it is determined that the object detection model converges, thereby ensuring the stability of the object detection model and improving the recognition reliability of damage identification of the goods in the package.

[0053] As an implementation method, the processing device can obtain historical X-ray images of damaged goods, and annotate the historical X-ray images of damaged goods to obtain corresponding annotated X-ray images of damaged goods, and divide the annotated X-ray images of damaged goods according to preset division rules to obtain corresponding training sets and test sets, and input the training set into the target detection model. The target detection model receives and responds to the training set, performs training according to the training set, and obtains the corresponding object detection model.

[0054] The preset division rule may be an artificial division rule, for example, the preset division rule may be an artificial division rule of training set: test set = 9:2, when the X-ray image of the historical damaged goods is marked with 22,000, the training set is 18,000, and the test set is 4,000; the preset division rule may be an artificial division rule of training set: test set = 3:1, when the X-ray image of the historical damaged goods is marked with 40,000, the training set is 30,000, and the test set is 10,000. The division method of the preset division rule is not limited here, and can be set according to actual needs.

[0055] In one application scenario, the target detection model is a YOLOX model. The processing device can obtain historical X-ray images of damaged goods, and annotate the historical X-ray images of damaged goods to obtain corresponding annotated X-ray images of damaged goods. The annotated X-ray images of damaged goods are divided according to preset division rules to obtain corresponding training sets and test sets, and the training sets are input into the YOLOX model. The YOLOX model receives and responds to the training set, performs training according to the training set, and obtains the corresponding object detection model.

[0056] As an implementation mode, a processing device can obtain historical X-ray images of damaged goods, and annotate the historical X-ray images of damaged goods to obtain corresponding annotated X-ray images of damaged goods, and divide the annotated X-ray images of damaged goods according to preset division rules to obtain corresponding training sets and test sets, and perform data enhancement processing on the training set according to a preset data enhancement strategy to obtain a corresponding enhanced training set, and input the enhanced training set into a target detection model, the target detection model receives and responds to the enhanced training set, and performs training according to the enhanced training set to obtain a corresponding object detection model, thereby realizing training of the target detection model according to the enhanced training set, avoiding the low robustness of the object detection model obtained by training the target detection model with fewer X-ray images of damaged goods due to less X-ray image data of damaged goods, and increasing the robustness of the object detection model.

[0057] The preset data enhancement strategy may be a brightness change processing strategy, for example, the brightness of the historical damaged cargo X-ray image is changed to [0.7, 1.3] times the initial brightness of the historical damaged cargo X-ray image.

[0058] The preset data enhancement strategy may also be a contrast change processing strategy, for example, the contrast of the historical damaged cargo X-ray image is changed to [0.7, 1.3] times the initial contrast of the historical damaged cargo X-ray image.

[0059] The preset data enhancement strategy can also be an image scaling processing strategy. For example, for an edge of each historical X-ray image of damaged goods, a number x% is randomly displayed from -5% to 5%, and if the number is greater than zero, the edge is expanded and the expanded area is filled with pixels x% multiplied by the length of the edge. If the number is less than zero, the edge is cropped, and the cropping size is x% multiplied by the length of the edge. If the number is equal to zero, the length of the edge remains unchanged.

[0060] The preset data enhancement strategy can also be an image flipping processing strategy. For example, according to a preset percentage (e.g., 50%) probability of the historical X-ray image of damaged goods, the historical X-ray image of damaged goods is flipped up and down in a clockwise or counterclockwise direction, and the up and down flipping angle is 0-360°.

[0061] The preset data enhancement strategy can also be a transparency overlay processing strategy. For example, two images to be overlaid are randomly selected from historical damaged X-ray images, and the two images to be overlaid are overlaid with a transparency of 40%-60%, and the damage detection frame in the image is also overlaid.

[0062] The preset data enhancement strategy may also be other processing strategies. The type of the preset data enhancement strategy is not limited here and can be set according to actual needs.

[0063] As an implementation method, the processing device can input a test set into the object detection model, the object detection model receives and responds to the test set, performs testing according to the test set, obtains corresponding test results, and determines the test accuracy of the test results based on the test results and the test set, and determines whether the object detection model converges based on the test accuracy.

[0064] When the test accuracy is greater than or equal to the preset accuracy threshold, it is determined that the object detection model has converged; when the test accuracy is less than the preset accuracy threshold, it is determined that the object detection model has not converged.

[0065] Among them, the preset accuracy threshold can be used to characterize the minimum accuracy value corresponding to the convergence of the object detection model. The preset accuracy threshold can be an accuracy value pre-set by the sorter. The preset accuracy threshold can also be an accuracy value automatically generated by the processing equipment based on the recognition process of multiple damage identification of goods in the package, etc., which is not limited here.

[0066] The solution provided in this embodiment obtains a current X-ray image of the package and inputs the current X-ray image into an object detection model to obtain a corresponding detection result. The object detection model is obtained based on historical X-ray images of damaged goods and a target detection model. The detection result includes a first detection result for characterizing that the goods in the package are damaged, and a second detection result for characterizing that the goods in the package are not damaged. This realizes damage identification of the goods in the package based on the object detection model, thereby improving the recognition accuracy of damage identification of the goods in the package.

[0067] See also Figure 3 , which shows a flow chart of a method for identifying damaged goods in a package provided by another embodiment of the present application. In a specific embodiment, the method for identifying damaged goods in a package can be applied to Figure 1 The processing device 200 in the package damage identification system is shown in FIG. Figure 3 The process shown is described in detail, and the method for identifying damaged goods in a package may include the following steps S210 to S240.

[0068] Step S210: Acquire the current X-ray image of the package.

[0069] Step S220: Input the current X-ray image to the object detection model to obtain the corresponding detection result.

[0070] In this embodiment, step S210 and step S220 may refer to the contents of the corresponding steps in the aforementioned embodiments, which will not be described in detail here.

[0071] Step S230: When the first detection result output by the object detection model is received, the package number of the package is obtained.

[0072] In this embodiment, when the processing device receives the first detection result output by the object detection model, it indicates that the goods in the package are damaged, and the package number of the package can be obtained.

[0073] In some embodiments, the system for identifying damaged goods in a package may further include a six-sided barcode scanner, which is connected to the processing device via a network and exchanges data with the processing device via the network.

[0074] When the processing device receives the first detection result output by the object detection model, it can send an order number collection instruction to the six-sided barcode scanner through the network. The six-sided barcode scanner receives and responds to the order number collection instruction, performs six-sided barcode scanning on the package, obtains the corresponding package number, and sends the package number to the processing device through the network. The processing device receives the package number returned by the six-sided barcode scanner.

[0075] In some embodiments, when the processing device receives the first detection result output by the object detection model, it can generate corresponding first package number input prompt information, and the first package number input prompt information is used to prompt the sorter to input the package number of the package to the processing device, and when the sorter inputs the package number to the processing device, the processing device receives the package number input by the sorter.

[0076] Among them, the first package number input prompt information can be at least any one of the first text prompt information, the first sound prompt information or the first light prompt information, etc., which is not limited here.

[0077] In some embodiments, the system for identifying damaged goods in a package may further include a client. When the processing device receives the first detection result output by the object detection model, it may send a number acquisition instruction to the client via the network. The client receives the number acquisition instruction sent by the processing device and generates corresponding second package number input prompt information. The second package number input prompt information is used to prompt the sorter to enter the package number of the package to the client. When the sorter enters the package number to the client, the client receives the package number entered by the sorter and sends the package number to the processing device via the network. The processing device receives the package number returned by the client.

[0078] The second package number input prompt information may be at least any one of second text prompt information, second sound prompt information, or second light prompt information, which is not limited here.

[0079] Step S240: Generate interception prompt information including the package number.

[0080] In this embodiment, after the processing device obtains the parcel number of the package, it can generate an interception prompt message carrying the parcel number. The interception prompt message can be used to prompt the sorter to intercept the package according to the parcel number, thereby preventing customers from receiving damaged goods packages and improving the customer's logistics experience.

[0081] Among them, the interception prompt information can be at least any one of text interception prompt information, sound interception prompt information or light interception prompt information, etc. The type of interception prompt information is not limited here and can be set according to actual needs.

[0082] In some embodiments, after the processing device generates interception prompt information including the package number, a corresponding package interception record can be generated and stored, which facilitates logistics controllers to track historical package management records and improves the control experience of package control.

[0083] The solution provided in this embodiment obtains the current X-ray image of the package and inputs the current X-ray image into the object detection model to obtain the corresponding detection result. When receiving the first detection result output by the object detection model, the package number of the package is obtained, and interception prompt information including the package number is generated, thereby realizing damage identification of the goods in the package based on the object detection model, and improving the recognition accuracy of damage identification of the goods in the package.

[0084] Furthermore, when it is determined that the goods in the package are damaged based on the current X-ray image, the sorter is reminded to intercept the damaged goods package, thereby preventing the customer from receiving the damaged goods package and improving the customer's logistics experience.

[0085] See also Figure 4 , which shows a device 300 for identifying damaged goods in a package provided by an embodiment of the present application. The device 300 for identifying damaged goods in a package can be applied to Figure 1 The processing device 200 in the package damage identification system is shown in FIG. Figure 4 The device 300 for identifying damaged goods in a package is described in detail. The device 300 for identifying damaged goods in a package may include an image acquisition module 310 and an image input module 320 .

[0086] The image acquisition module 310 can be used to acquire the current X-ray image of the package; the image input module 320 can be used to input the current X-ray image into the object detection model to obtain the corresponding detection result. The object detection model can be obtained based on the historical X-ray images of damaged goods and the target detection model. The detection result may include a first detection result for characterizing that the goods in the package are damaged, and a second detection result for characterizing that the goods in the package are not damaged.

[0087] In some embodiments, the device for identifying damaged goods in a package 300 may further include a tracking number acquisition module and a generation module.

[0088] The order number acquisition module can be used to obtain the parcel order number of the package when receiving the first detection result output by the object detection model; the generation module can be used to generate interception prompt information containing the parcel order number, and the interception prompt information can be used to prompt the sorter to intercept the package according to the parcel order number.

[0089] In some implementations, the order number acquisition module may include a sending unit and a receiving unit.

[0090] The sending unit can be used to send an order number collection instruction to the six-sided barcode scanner when receiving the first detection result output by the object detection model. The order number collection instruction can be used to instruct the six-sided barcode scanner to scan the six sides of the package to obtain the corresponding package order number; the receiving unit can be used to receive the package number returned by the six-sided barcode scanner.

[0091] In some embodiments, the device 300 for identifying damaged goods in a package may further include a training set and a test set acquisition module, a training set input module, and a determination module.

[0092] The training set and test set acquisition module can be used for the image input module 320 to input the current X-ray image into the object detection model. Before obtaining the corresponding detection result, the corresponding training set and test set are obtained based on the historical X-ray images of damaged goods; the training set input module can be used to input the training set into the target detection model for training to obtain the corresponding object detection model; the determination module can be used to determine whether the object detection model converges based on the test set.

[0093] In some embodiments, the image input module 320 may include a first input unit.

[0094] The first input unit can be used to input the current X-ray image into the object detection model to obtain the corresponding detection result when it is determined that the object detection model converges according to the test set.

[0095] In some embodiments, the device for identifying damaged goods in a package 300 may further include an enhanced processing module.

[0096] The enhancement processing module can be used for the training set input module to input the training set to the target detection model for training. Before obtaining the corresponding object detection model, the training set is subjected to data enhancement processing according to the preset data enhancement strategy to obtain an enhanced training set.

[0097] In some implementations, the training set input module may include a second input unit.

[0098] The second input unit can be used to input the enhanced training set to the target detection model for training to obtain the corresponding object detection model.

[0099] In some implementations, the determination module may include a third input unit, a first determination unit, and a second determination unit.

[0100] The third input module can be used to input the test set into the object detection model for testing to obtain the corresponding test results; the first determination unit can be used to determine the test accuracy of the test results based on the test results and the test set; the second determination unit can be used to determine whether the object detection model converges based on the test accuracy.

[0101] In some embodiments, the first determining unit may include a first determining subunit and a second determining subunit.

[0102] The first determination subunit may be used to determine that the object detection model has converged when the test accuracy is greater than or equal to a preset accuracy threshold; the second determination subunit may be used to determine that the object detection model has not converged when the test accuracy is less than a preset accuracy threshold.

[0103] The solution provided in this embodiment obtains a current X-ray image of the package and inputs the current X-ray image into an object detection model to obtain a corresponding detection result. The object detection model is obtained based on historical X-ray images of damaged goods and a target detection model. The detection result includes a first detection result for characterizing that the goods in the package are damaged, and a second detection result for characterizing that the goods in the package are not damaged. This realizes damage identification of the goods in the package based on the object detection model, thereby improving the recognition accuracy of damage identification of the goods in the package.

[0104] It should be noted that each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the embodiments can be referred to each other. For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. Any processing method described in the method embodiment can be implemented by the corresponding processing module in the device embodiment, and will not be repeated one by one in the device embodiment.

[0105] In addition, each functional module in each embodiment of the present application can be integrated into a processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The above integrated modules can be implemented in the form of hardware or software functional modules.

[0106] See also Figure 5, which shows a functional block diagram of an electronic device 400 provided by an embodiment of the present application, the electronic device 400 may include one or more of the following components: a memory 410, a processor 420, and one or more applications, wherein the one or more applications may be stored in the memory 410 and configured to be executed by the one or more processors 420, and the one or more applications are configured to execute the method described in the aforementioned method embodiment.

[0107] The memory 410 may include a random access memory (RAM) or a read-only memory (ROM). The memory 410 may be used to store instructions, programs, codes, code sets or instruction sets. The memory 410 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as obtaining a current X-ray image, inputting a current X-ray image, obtaining a detection result, receiving a first detection result, outputting a first detection result, obtaining a parcel number, generating an interception prompt message, prompting a sorter, intercepting a parcel, sending a number collection instruction, six-sided code scanning recognition, obtaining a parcel number, returning a parcel number, receiving a parcel number, obtaining a training set, obtaining a test set, inputting a training set, performing training, obtaining an object detection model, determining whether the object detection model converges, determining that the object detection model converges, data enhancement processing, obtaining an enhanced training set, inputting an enhanced training set, inputting a test set, performing testing, obtaining a test result, determining a test accuracy, and determining that the object detection model does not converge, etc.), instructions for implementing the following various method embodiments, etc. The data storage area can also store data created by the electronic device 400 during use (such as packages, current X-ray images, object detection models, detection results, historical X-ray images of damaged goods, target detection models, first detection results, second detection results, package numbers, interception prompt information, sorters, number collection instructions, six-sided barcode scanners, training sets, test sets, preset data enhancement strategies, enhanced training sets, test results, test accuracy, and preset accuracy thresholds), etc.

[0108] The processor 420 may include one or more processing cores. The processor 420 uses various interfaces and lines to connect the various parts of the entire electronic device 400, and executes various functions and processes data of the electronic device 400 by running or executing instructions, programs, code sets or instruction sets stored in the memory 410, and calling data stored in the memory 410. Optionally, the processor 420 can be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 420 can integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. Among them, the CPU mainly processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing display content; and the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 420, but may be implemented separately through a communication chip.

[0109] Please refer to Figure 6 , which shows a structural block diagram of a computer-readable storage medium provided in an embodiment of the present application. The computer-readable storage medium 500 stores a program code 510, which can be called by a processor to execute the method described in the above method embodiment.

[0110] The computer-readable storage medium 500 may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read-only memory), an EPROM, a hard disk, or a ROM. Optionally, the computer-readable storage medium 500 includes a non-transitory computer-readable storage medium. The computer-readable storage medium 500 has storage space for program code 510 that performs any method steps in the above method. These program codes can be read from or written to one or more computer program products. The program code 510 can be compressed, for example, in an appropriate form.

[0111] Please refer to Figure 7, which shows a structural block diagram of a computer program product 600 provided in an embodiment of the present application. The computer program product 600 includes a computer program / instruction 610, and the computer program / instruction 610 is stored in a computer-readable storage medium of a computer device. When the computer program product 600 is run on a computer device, a processor of the computer device reads the computer program / instruction 610 from the computer-readable storage medium, and the processor executes the computer program / instruction 610, so that the computer device performs the method described in the above method embodiment.

[0112] The solution provided in this embodiment obtains a current X-ray image of the package and inputs the current X-ray image into an object detection model to obtain a corresponding detection result. The object detection model is obtained based on historical X-ray images of damaged goods and a target detection model. The detection result includes a first detection result for characterizing that the goods in the package are damaged, and a second detection result for characterizing that the goods in the package are not damaged. This realizes damage identification of the goods in the package based on the object detection model, thereby improving the recognition accuracy of damage identification of the goods in the package.

[0113] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for identifying damaged goods in a package, characterized in that: include: Get the current X-ray image of the package; The current X-ray image is input into an object detection model to obtain a corresponding detection result, wherein the object detection model is obtained based on a historical X-ray image of damaged goods and a target detection model, and the detection result includes a first detection result for characterizing that the goods in the package are damaged, and a second detection result for characterizing that the goods in the package are not damaged.

2. The method for identifying damaged goods in a package according to claim 1, characterized in that: Also includes: When receiving the first detection result output by the object detection model, obtaining the parcel number of the parcel; Generate interception prompt information including the parcel number, and the interception prompt information is used to prompt the sorter to intercept the parcel according to the parcel number.

3. The method for identifying damaged goods in a package according to claim 2, characterized in that: The step of obtaining the parcel number of the parcel upon receiving the first detection result output by the object detection model comprises: When the first detection result output by the object detection model is received, a tracking number collection instruction is sent to the six-sided barcode scanner, wherein the tracking number collection instruction is used to instruct the six-sided barcode scanner to scan and identify the six-sided barcodes of the package to obtain the corresponding package tracking number; Receive the parcel number returned by the six-sided barcode scanner.

4. The method for identifying damaged goods in a package according to any one of claims 1 to 3, characterized in that: Before inputting the current X-ray image into the object detection model to obtain the corresponding detection result, the method for identifying damaged goods in a package further includes: Based on the historical X-ray images of damaged goods, obtain the corresponding training set and test set; Input the training set into the target detection model for training to obtain the corresponding object detection model; Determining whether the object detection model converges according to the test set; The inputting the current X-ray image into the object detection model to obtain the corresponding detection result includes: When it is determined that the object detection model converges according to the test set, the current X-ray image is input into the object detection model to obtain a corresponding detection result.

5. The method for identifying damaged goods in a package according to claim 4, characterized in that: Before inputting the training set into the target detection model for training and obtaining the corresponding object detection model, the method for identifying damaged goods in a package further includes: According to a preset data enhancement strategy, data enhancement processing is performed on the training set to obtain an enhanced training set; The inputting the training set into the target detection model for training to obtain the corresponding object detection model includes: The enhanced training set is input into the target detection model for training to obtain the corresponding object detection model.

6. The method for identifying damaged goods in a package according to claim 4, characterized in that: The determining whether the object detection model converges according to the test set includes: Input the test set to the object detection model for testing to obtain corresponding test results; Determining the test accuracy of the test result according to the test result and the test set; Determine whether the object detection model converges according to the test accuracy.

7. The method for identifying damaged goods in a package according to claim 6, characterized in that: The determining whether the object detection model converges according to the test accuracy includes: When the test accuracy is greater than or equal to a preset accuracy threshold, it is determined that the object detection model has converged; When the test accuracy is less than a preset accuracy threshold, it is determined that the object detection model has not converged.

8. A device for identifying damaged goods in a package, characterized in that: include: An image acquisition module, used to acquire a current X-ray image of the package; An image input module is used to input the current X-ray image into an object detection model to obtain a corresponding detection result, wherein the object detection model is obtained based on historical X-ray images of damaged goods and a target detection model, and the detection result includes a first detection result for characterizing that the goods in the package are damaged, and a second detection result for characterizing that the goods in the package are not damaged.

9. An electronic device, characterized in that: include: Memory; One or more processors coupled to the memory; One or more applications, wherein the one or more applications are stored in the memory and are configured to be executed by one or more processors, and the one or more applications are configured to execute the method for identifying damaged goods in a package as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program code, and the program code can be called by a processor to execute the method for identifying damaged goods in a package as described in any one of claims 1 to 7.

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