Dumb resource image distribution method, device, equipment, storage medium and program product

Abstract

The present disclosure relates to the technical field of information processing, and particularly provides a dumb resource image distribution method, device, equipment, storage medium and program product. The dumb resource image distribution method comprises: acquiring a dumb resource image to be distributed; acquiring a channel rule model, the channel rule model being used to indicate a dumb resource feature combination supported by each dumb resource capability module; determining a dumb resource feature of the dumb resource image; determining a distribution channel of the dumb resource image based on the channel rule model and the dumb resource feature matched with the dumb resource image, and distributing the dumb resource image according to the distribution channel. The technical solution of the present disclosure can improve the distribution efficiency of the dumb resource image.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of information processing, and in particular to a dumb resource image distribution method, device, equipment, storage medium and program product. BACKGROUND

[0002] With the development of information processing technology, the processing mode of dumb resource images also varies with different application scenarios, resulting in nearly one hundred kinds of dumb resource capability modules such as optical cross-connect box identification, flange identification, terminal identification, process detection, connectivity analysis, compliance analysis, and idle rate calculation for daily operation and inspection, system interface, data verification and other scenarios.

[0003] In the prior art, in order to facilitate the use of front-line personnel, the R&D personnel will provide a plug-in type capability calling interface, the user installs the capability calling software in the portable terminal, selects the required interface channel, and distributes the obtained dumb resource image to the corresponding interface channel, so as to trigger the data processing logic of the server side to generate the processing result of the capability module. The deficiency is that the dumb resource image distribution efficiency is low and the labor cost is high. SUMMARY

[0004] The present disclosure is proposed in view of the above problems. The present disclosure provides a dumb resource image distribution method, device, equipment, storage medium and program product.

[0005] According to one aspect of the present disclosure, a dumb resource image distribution method is provided, comprising:

[0006] obtaining a dumb resource image to be distributed;

[0007] obtaining a channel rule model, the channel rule model being used to indicate a dumb resource feature combination supported by each dumb resource capability module;

[0008] determining a dumb resource feature of the dumb resource image;

[0009] determining a distribution channel of the dumb resource image based on the channel rule model and the dumb resource feature of the dumb resource image, and distributing the dumb resource image according to the distribution channel, wherein the distribution channel is an interface channel of a target dumb resource capability module, and the target dumb resource capability module is a dumb resource capability module whose dumb resource feature combination matches the dumb resource feature of the dumb resource image. In addition, according to the dumb resource image distribution method of one aspect of the present disclosure, the channel rule model uses a rule expression based on dumb resource features to indicate the dumb resource feature combination supported by each dumb resource capability module.

[0010] Further, according to an aspect of the present disclosure, a method for distributing a dumb resource image, each dumb resource feature combination supported by the dumb resource capability module comprises a plurality of or gate chains, each or gate chain comprises a plurality of and gate chains in or operation combination, and each and gate chain comprises a plurality of dumb resource features in and operation combination. If all dumb resource features of any and gate chain in the dumb resource feature combination are contained in the dumb resource features of the dumb resource image, the dumb resource feature combination matches the dumb resource features of the dumb resource image.

[0011] Further, according to an aspect of the present disclosure, a method for distributing a dumb resource image, the method further comprises:

[0012] Generating a channel rule model based on the dumb resource information description that can be processed by each dumb resource capability module.

[0013] Further, according to an aspect of the present disclosure, a method for distributing a dumb resource image, generating a channel rule model based on the dumb resource information description that can be processed by each dumb resource capability module comprises:

[0014] Determining dumb resource features that can be processed by each dumb resource capability module based on the dumb resource information description that can be processed by each dumb resource capability module, and constructing dumb resource feature combinations supported by each dumb resource capability module.

[0015] Generating the channel rule model according to the dumb resource feature combinations supported by each dumb resource capability module.

[0016] Further, according to an aspect of the present disclosure, a method for distributing a dumb resource image, the determining dumb resource features of the dumb resource image comprises:

[0017] Determining all dumb resource features matching the dumb resource image based on a label dictionary to obtain dumb resource features of the dumb resource image, wherein the label dictionary contains all dumb resource features involved in the channel rule model.

[0018] Further, according to an aspect of the present disclosure, a method for distributing a dumb resource image, the determining all dumb resource features matching the dumb resource image based on the label dictionary comprises:

[0019] Obtaining image features of the dumb resource image.

[0020] Determining all dumb resource features matching the dumb resource image according to the image features of the dumb resource image and each dumb resource feature of the label dictionary.

[0021] Further, according to an aspect of the present disclosure, a dumb resource image distribution method is provided. The distribution channel of the dumb resource image is determined based on the channel rule model and the dumb resource features of the dumb resource image, comprising:

[0022] According to the dumb resource feature combination supported by each dumb resource capability module indicated by the channel rule model and the dumb resource features of the dumb resource image, the interface channel of the dumb resource capability module supporting the dumb resource image is determined;

[0023] According to the interface channel of the dumb resource capability module supporting the dumb resource image, the distribution channel of the dumb resource image is determined.

[0024] According to another aspect of the present disclosure, a dumb resource image distribution device is provided, comprising:

[0025] A first obtaining module is configured to obtain a dumb resource image to be distributed;

[0026] A second obtaining module is configured to obtain a channel rule model, which is used to indicate the dumb resource feature combination supported by each dumb resource capability module;

[0027] A determining module is configured to determine all dumb resource features of the dumb resource image;

[0028] An image distribution module is configured to determine the distribution channel of the dumb resource image based on the channel rule model and the dumb resource features of the dumb resource image, and distribute the dumb resource image according to the distribution channel, wherein the distribution channel is the interface channel of a target dumb resource capability module, and the target dumb resource capability module is a dumb resource capability module whose dumb resource feature combination matches the dumb resource features of the dumb resource image.

[0029] According to yet another aspect of the present disclosure, an electronic device is provided, comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any of the above-mentioned methods.

[0030] According to yet another aspect of the present disclosure, a computer readable storage medium is provided, which stores a computer program / instruction, wherein the computer program / instruction is executed by a processor to implement the steps of any of the above-mentioned methods.

[0031] According to yet another aspect of the present disclosure, a computer program product is provided, comprising a computer program / instruction, wherein the computer program / instruction is executed by a processor to implement the steps of any of the above-mentioned methods.

[0032] As will be described in detail below, according to the dumb resource image distribution method, device, equipment, storage medium and program product of the embodiments of the present disclosure, by acquiring the channel rule model, determining the dumb resource features matched with the dumb resource image based on the label dictionary, determining the distribution channel of the dumb resource image based on the channel rule model and the dumb resource features of the dumb resource image, and distributing the dumb resource image according to the distribution channel, the distribution channel of the dumb resource image is automatically determined, and the distribution efficiency of the dumb resource image is improved.

[0033] It is to be understood that both the foregoing general description and the following detailed description are exemplary, and are intended to provide further explanation of the subject technology claimed. BRIEF DESCRIPTION OF DRAWINGS

[0034] The foregoing and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description, which proceeds with reference to the accompanying drawings. The drawings are provided to illustrate embodiments of the present disclosure and are not intended to limit the present disclosure. In the drawings, like reference numerals refer to like elements throughout.

[0035] Figure 1 is a flowchart illustrating a dumb resource image distribution method according to an embodiment of the present disclosure.

[0036] Figure 2 is a flowchart further illustrating generation of a channel rule model in the dumb resource image distribution method of the embodiments of the present disclosure.

[0037] Figure 3 is a schematic diagram further illustrating a channel rule model in the dumb resource image distribution method of the embodiments of the present disclosure.

[0038] Figure 4 is a flowchart further illustrating determination of dumb resource features matched with a dumb resource image in the dumb resource image distribution method of the embodiments of the present disclosure.

[0039] Figure 5 is a flowchart further illustrating determination of a distribution channel of a dumb resource image in the dumb resource image distribution method of the embodiments of the present disclosure.

[0040] Figure 6 is a block diagram illustrating a dumb resource image distribution device according to an embodiment of the present disclosure.

[0041] Figure 7 is a schematic diagram illustrating a computer program product according to an embodiment of the present disclosure.

[0042] Figure 8 is a hardware block diagram illustrating an electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0043] In order to make the objectives, technical solutions and advantages of the present disclosure more obvious, the following will describe the example embodiments according to the present disclosure in detail with reference to the drawings. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, and are not all the embodiments of the present disclosure, and it should be understood that the present disclosure is not limited to the example embodiments described herein.

[0044] Referring to Figure 1 A dumb resource image distribution method comprises:

[0045] S101, acquiring a dumb resource image to be distributed.

[0046] In step S101 of the present disclosure, the dumb resource image to be distributed can be uploaded by a user or transmitted by other systems. For example, when a user is preparing to initiate an interface call request of a dumb resource capability module, the user uploads a dumb resource image or a dumb resource video, and the system performing the present step acquires the dumb resource image uploaded by the user as the dumb resource image to be distributed or extracts a video frame of the dumb resource video as the dumb resource image to be distributed. When extracting the video frame of the dumb resource video, a feature frame of the dumb resource video can be extracted to facilitate better determination of a distribution channel.

[0047] S102, acquiring a channel rule model, the channel rule model being used to indicate a dumb resource feature combination supported by each dumb resource capability module.

[0048] In the present disclosure, a label dictionary can also be acquired, the label dictionary containing all dumb resource features involved in the channel rule model. The label dictionary can be used to determine dumb resource features of the dumb resource image. The channel rule model and the label dictionary can be preset. Each dumb resource capability module refers to each dumb resource capability module that can be called, and which dumb resource capability modules are used can be set according to actual conditions. If the dumb resource capability modules that can be called are changed and updated (for example, dumb resource features supported by the dumb resource capability modules are changed or new dumb resource capability modules that can be called appear), then the channel rule model and the label dictionary are also updated accordingly.

[0049] In step S102 of the embodiment of the present disclosure, the supported dummy resource feature combination of each dummy resource capability module can include or combine, and so on. Taking the dummy resource information description that the first dummy resource capability module can handle as an example, which is "stainless steel material optical cross-connect box, or optical cross-connect box with fiber core number between 48 and 144", the supported dummy resource feature combination of the first dummy resource capability module is: the first and combination of the first dummy resource feature "stainless steel" and the second dummy resource feature "optical cross-connect box", and the first or combination of the first and combination and the third dummy resource feature "fiber core number 48 to 144", and the channel rule model of the first dummy resource capability module can contain the first or combination. If the dummy resource features of the dummy resource image contain the first dummy resource feature "stainless steel" and the second dummy resource feature "optical cross-connect box", then the dummy resource image matches the channel rule model of the first dummy resource capability module; if the dummy resource features of the dummy resource image contain the third dummy resource feature "fiber core number 48 to 144", then the dummy resource image matches the channel rule model of the first dummy resource capability module; if the dummy resource features of the dummy resource image only contain the first dummy resource feature "stainless steel" and the fourth dummy resource feature "optical fiber distribution box", then the dummy resource features of the dummy resource image do not contain the first dummy resource feature and the second dummy resource feature at the same time, and do not contain the third dummy resource feature, so the dummy resource image does not match the channel rule model of the first dummy resource capability module.

[0050] In step S102 of the embodiment of the present disclosure, the channel rule model can indicate the supported dummy resource feature combination of each dummy resource capability module by using a rule expression based on dummy resource features. For example, the supported dummy resource feature combination of each dummy resource capability module can be indicated by using a NAND expression, can be indicated by using a regular expression, and can be indicated by using a postfix expression. Taking the NAND expression as an example, the supported dummy resource feature combination of each dummy resource capability module contains multiple OR gate chains, each OR gate chain contains the OR operation combination of multiple AND gate chains, and each AND gate chain contains the AND operation combination of a plurality of dummy resource features. If all dummy resource features of any AND gate chain in the dummy resource feature combination are contained in the dummy resource features of the dummy resource image, then the dummy resource feature combination matches the dummy resource features of the dummy resource image.

[0051] In the embodiment of the present disclosure, the label dictionary is a set of dummy resource features involved in all channel rule models, and the label set of the dummy resource features involved in all channel rule models can be obtained to obtain the label dictionary under the current external capability cluster present situation.

[0052] In the embodiments of the present disclosure, if the system already has the channel rule model or the label dictionary of all dummy resource capability modules to which the interface calling request is directed, the channel rule model or the label dictionary can be directly obtained. In this case, before step S102, the method comprises generating the channel rule model and the label dictionary based on the dummy resource information description that each dummy resource capability module can process. When the system does not have the channel rule model and the label dictionary of all dummy resource capability modules to which the interface calling request is directed, for example, when the dummy resource capability modules are updated, when the interface is called for the first time (when the channel rule model and the label dictionary have not been generated), and the like, the channel rule model and the label dictionary can be updated or generated based on the dummy resource information description that each dummy resource capability module can process.

[0053] As an implementation manner of generating the channel rule model, referring to Figure 2 , step S102 comprises:

[0054] S201, determining the dummy resource features that each dummy resource capability module can process based on the dummy resource information description that each dummy resource capability module can process, and constructing the dummy resource feature combination supported by each dummy resource capability module.

[0055] Taking the dummy resource information description that a certain first dummy resource capability module can process as "stainless steel material optical cross-connect box, or optical cross-connect box with fiber core number between 48 and 144" for example. It is determined that the dummy resource features that the first dummy resource capability module can process are the first dummy resource feature "stainless steel", the second dummy resource feature "optical cross-connect box", and the third dummy resource feature "fiber core number 48 to 144", and the dummy resource feature combination supported by the first dummy resource capability module can be the first and combination of the first dummy resource feature and the second dummy resource feature, and the first or combination of the first and combination and the third dummy resource feature.

[0056] Taking the dummy resource information description that a certain second dummy resource capability module can process as "wall-mounted optical distribution box, or upright optical cross-connect box" for example. It is determined that the dummy resource features that the second dummy resource capability module can process are the fifth dummy resource feature "wall-mounted", the fourth dummy resource feature "optical distribution box", the sixth dummy resource feature "upright", and the second dummy resource feature "optical cross-connect box", and the dummy resource feature combination supported by the second dummy resource capability module can be the second and combination of the fifth dummy resource feature and the fourth dummy resource feature, the third and combination of the sixth dummy resource feature and the second dummy resource feature, and the second or combination of the second and combination and the third and combination.

[0057] S202, generating the channel rule model according to the dummy resource feature combination supported by each dummy resource capability module.

[0058] For example, the description of the dumb resource information that can be processed by a first dumb resource capability module is "stainless steel optical cross-connect box or optical cross-connect box with fiber core number between 48 and 144", and the description of the dumb resource information that can be processed by a second dumb resource capability module is "wall-mounted optical distribution box or upright optical cross-connect box". The generated channel rule model includes a first or combination corresponding to the first dumb resource capability module and a second or combination corresponding to the second dumb resource capability module. It can be understood that the first or combination can be used as the dumb resource feature combination of the first channel rule model, and the second or combination can be used as the dumb resource feature combination of the second channel rule model. The generated channel rule model includes a first channel rule model corresponding to the first dumb resource capability module and a second channel rule model corresponding to the second dumb resource capability module.

[0059] In one embodiment, a label dictionary can be generated according to the dumb resource features involved in all channel rule models.

[0060] For example, the description of the dumb resource information that can be processed by a third dumb resource capability module is "non-stainless steel optical cross-connect box or optical cross-connect box with fiber core number between 48 and 144", and the channel rule model uses a rule expression based on the dumb resource feature to indicate the dumb resource feature combination supported by each dumb resource capability module.

[0061] The rule expression of the dumb resource feature combination supported by the dumb resource capability module of the channel rule model is:

[0062]

[0063] Suppose the optical cross-connect box is element A (i.e. dumb resource feature A), the stainless steel material is element B (i.e. dumb resource feature B), and the fiber core number (48, 144) is element C (i.e. dumb resource feature C). The above rule expression can be abstracted as:

[0064]

[0065] In the same way, for all dumb resource capability modules, corresponding rule expressions can be generated, for example:

[0066] Channel number Supported dummy resource information description Rule expression Abstract model ring1 Wall-mounted optical distribution box Optical distribution box ∧ wall-mounted A ∧ B ring2 Optical distribution box other than upright type Optical distribution box ∧ ¬ upright A ∧ ¬ B ... ringN Pole or manhole Pole ∨ manhole A ∨ B

[0067] The and-or operation satisfies the distributive law and the associative law, that is, the abstract model of any channel can be transformed into the following form:

[0068] Primitive 1 V … V primitive N (N = 1, 2, 3, 4, …);

[0069] Each group of primitives can be represented as:

[0070] Element 1 A … A element M (M = 1, 2, 3, 4, …);

[0071] Each element is a dumb resource feature.

[0072] Each element can carry attribute labels, feature descriptions, range limits, and negative signs, for example:

[0073]

[0074] All dumb resource capability module generation rule models are generated, and thus the full amount of channel rule models can be obtained, see Figure 3 , Figure 3 is an exemplary channel rule model. The channel rule model is a channel rule set, including a plurality of channel rule models. The channel rule model 1 includes an OR gate chain formed by primitives 1 V … V primitives N. The primitive 1 includes element 11. The primitive 2 includes an AND gate chain formed by elements 21, 22, …, 2M. The primitive N includes an AND gate chain formed by elements N1 and N2. Each element can carry attribute labels, feature descriptions, range limits, and negative signs.

[0075] S103, determining the dumb resource features of the dumb resource image.

[0076] In step S103 of the embodiments of the present disclosure, related technical means can be used to determine the dumb resource features of the dumb resource image.

[0077] In one embodiment, all dumb resource features matching the dumb resource image can be determined based on a label dictionary to obtain the dumb resource features of the dumb resource image, wherein the label dictionary contains all dumb resource features involved in the channel rule model. When determining all dumb resource features matching the dumb resource image, it can be determined whether each dumb resource feature in the label dictionary matches the dumb resource image, and all dumb resource features matching the dumb resource image are determined. For dumb resource feature matching in the label dictionary, it can be prevented that the vector dimension is too large to consume a large amount of computing resources. In one embodiment, see Figure 4 , based on the label dictionary, all dumb resource features matching the dumb resource image are determined, including:

[0078] S401, obtaining image features of the dumb resource image.

[0079] In step S401 of the embodiments of the present disclosure, the ORB (Oriented Fast and Rotated Brief, for quickly creating feature vectors for key points in images) feature extraction technology can be used to obtain the image features of the dumb resource image. It should be understood that other methods can also be used to obtain the image features of the dumb resource image.

[0080] S402, determine all dummy resource features matched with the dummy resource image according to the image feature of the dummy resource image and each dummy resource feature of the label dictionary.

[0081] The image feature of the dummy resource image corresponds to each dummy resource feature of the label dictionary. For example, the image feature of the dummy resource image includes the image feature of stainless steel and the image feature of an optical cross-connect box. Then, all dummy resource features matched with the dummy resource image include the dummy resource feature “stainless steel” and the dummy resource feature “optical cross-connect box”.

[0082] Exemplarily, the dummy resource sample image and the dummy resource feature label (the label of the dummy resource feature in the label dictionary) of the corresponding dummy resource sample image can be acquired, and the neural network model is trained to obtain the matching model. The neural network model can be a convolutional neural network model, a residual neural network model, etc. The matching model determines all dummy resource features matched with the dummy resource image by using the input dummy resource image.

[0083] S104, determine the distribution channel of the dummy resource image based on the channel rule model and the dummy resource feature of the dummy resource image, and distribute the dummy resource image according to the distribution channel. The distribution channel is the interface channel of the target dummy resource capability module, and the target dummy resource capability module is the dummy resource capability module whose dummy resource feature combination matches the dummy resource feature of the dummy resource image.

[0084] In step S104 of the embodiment of the present disclosure, the dummy resource feature of the dummy resource image can be matched with the dummy resource feature combination in the channel rule model to determine which dummy resource capability module has the capability to process the dummy resource image, determine the distribution channel of the dummy resource image, and distribute the dummy resource image according to the distribution channel.

[0085] It should be understood that the distribution channel of the dummy resource image can be one or more. Therefore, the determined distribution channel of the dummy resource image can be a channel list.

[0086] In the embodiment of the present disclosure, the dummy resource image can be distributed to the capability interface of the corresponding dummy resource capability module according to the distribution channel, so as to realize the automatic calling of the external capability cluster. Since the field construction personnel may call the same capability interface multiple times in a short time, the rule model and the label dictionary can be temporarily stored locally after the initialization is completed, so as to accelerate the system preloading rate.

[0087] In one embodiment, referring to Figure 5 , determining the distribution channel of the dummy resource image based on the channel rule model and the dummy resource feature of the dummy resource image includes:

[0088] S501, determine the interface channel of the dummy resource capability module supporting the dummy resource image according to the dummy resource feature combination supported by each dummy resource capability module indicated by the channel rule model and the dummy resource feature of the dummy resource image.

[0089] In step S501 of the embodiment of the present disclosure, if the dummy resource feature of the dummy resource image matches a dummy resource feature combination of the channel rule model, the interface channel of the dummy resource capability module corresponding to the dummy resource feature combination is the channel of the dummy resource capability module supporting the dummy resource image.

[0090] S502, determine the distribution channel of the dummy resource image according to the interface channel of the dummy resource capability module supporting the dummy resource image.

[0091] In step S502 of the embodiment of the present disclosure, the interface channel of the dummy resource capability module supporting the dummy resource image is used as the distribution channel of the dummy resource image, or the interface channel of the dummy resource capability module supporting the dummy resource image can be manually intervened to be selected as the distribution channel of the dummy resource image.

[0092] For example, the dummy resource feature combination supported by each dummy resource capability module contains multiple or chains, each or chain contains multiple and chains combined by or operation, and each and chain contains a plurality of dummy resource features combined by and operation. When matching, the dummy resource image can be distributed to the interface channels of multiple dummy resource capability modules, and the matching results of the interface channels do not affect each other; see Figure 3 For convenience of description, the and chain containing the dummy resource feature in the or chain is recorded as a primitive, and the dummy resource feature in the and chain is recorded as an element. The channel rule model is composed of multiple or chains. As long as the dummy resource feature of the dummy resource image meets any one primitive in each primitive in the or chain, it is considered that the dummy resource image matches the corresponding channel. The interface channel is added to the distribution list of the corresponding dummy resource image as the distribution channel of the dummy resource image. As for whether the dummy resource feature of the dummy resource image meets the primitive, the primitive is composed of multiple elements connected by and chains. If all elements of the and chain are contained in the dummy resource feature of the dummy resource image, it is considered that the dummy resource feature of the dummy resource image meets the primitive in the or chain. Then, the dummy resource image matches the corresponding interface channel. Otherwise, the dummy resource feature of the dummy resource image does not meet the primitive, and the next primitive can be determined. As can be known, if the element contains a negative sign, when judging whether the element is contained in the dummy resource feature of the dummy resource image, the result is negated. For example, the element is stainless steel containing a negative sign, and the dummy resource feature of the dummy resource image is stainless steel. Since the element contains a negative sign, the dummy resource feature of the dummy resource image does not meet the primitive at this time. The matching logic of the dummy resource image and the interface channel is looped until the last channel matching is completed, and the system outputs the channel list of the image matching successfully.

[0093] Referring to Figure 6 The exemplary embodiments of the present disclosure also provide a dumb resource image distribution device, comprising:

[0094] The first acquisition module 601 is configured to acquire a dumb resource image to be distributed.

[0095] The second acquisition module 602 is configured to acquire a channel rule model, which is used to indicate a dumb resource feature combination supported by each dumb resource capability module.

[0096] The determination module 603 is configured to determine a dumb resource feature of the dumb resource image.

[0097] The image distribution module 604 is configured to determine a distribution channel of the dumb resource image based on the channel rule model and the dumb resource feature of the dumb resource image, and distribute the dumb resource image according to the distribution channel, wherein the distribution channel is an interface channel of a target dumb resource capability module, and the target dumb resource capability module is a dumb resource capability module whose dumb resource feature combination matches the dumb resource feature of the dumb resource image.

[0098] In one embodiment, the channel rule model indicates the dumb resource feature combination supported by each dumb resource capability module by using a rule expression based on the dumb resource feature.

[0099] In one embodiment, the dumb resource feature combination supported by each dumb resource capability module comprises a plurality of OR gate chains, each OR gate chain comprises a plurality of AND gate chains combined by OR operation, and each AND gate chain comprises a plurality of AND operations of dumb resource features, wherein the dumb resource feature combination matches the dumb resource feature of the dumb resource image if all dumb resource features of any AND gate chain in the dumb resource feature combination are contained in the dumb resource feature of the dumb resource image.

[0100] In one embodiment, the dumb resource image distribution device further comprises:

[0101] The generation module is configured to generate the channel rule model based on the dumb resource information description that can be processed by each dumb resource capability module.

[0102] In one embodiment, when the generation module generates the channel rule model based on the dumb resource information description that can be processed by each dumb resource capability module, the generation module is specifically configured to:

[0103] determine the dumb resource feature that can be processed by each dumb resource capability module based on the dumb resource information description that can be processed by each dumb resource capability module, and construct the dumb resource feature combination supported by each dumb resource capability module;

[0104] generate the channel rule model according to the dumb resource feature combination supported by each dumb resource capability module.

[0105] In an embodiment, the determining module 603 is configured to determine the dummy resource features of the dummy resource image, and specifically configured to:

[0106] determine all dummy resource features matching the dummy resource image based on the label dictionary, to obtain the dummy resource features of the dummy resource image, wherein the label dictionary contains all dummy resource features involved in the channel rule model.

[0107] The determining module 603 is configured to determine all dummy resource features matching the dummy resource image based on the label dictionary, and specifically configured to:

[0108] obtain the image features of the dummy resource image;

[0109] determine all dummy resource features matching the dummy resource image according to the image features of the dummy resource image and each dummy resource feature of the label dictionary.

[0110] In an embodiment, the image distribution module 604 is configured to determine the distribution channel of the dummy resource image based on the channel rule model and the dummy resource features of the dummy resource image, and specifically configured to:

[0111] determine the interface channel of the dummy resource capability module supporting the dummy resource image according to the dummy resource feature combination supported by each dummy resource capability module indicated by the channel rule model and the dummy resource features of the dummy resource image;

[0112] determine the distribution channel of the dummy resource image according to the interface channel of the dummy resource capability module supporting the dummy resource image.

[0113] The exemplary embodiments of the present disclosure further provide an electronic device, including at least one processor, and a memory connected with the at least one processor in communication. The memory stores a computer program capable of being executed by the at least one processor, and the computer program, when executed by the at least one processor, is configured to cause the electronic device to perform the method according to the embodiments of the present disclosure.

[0114] The exemplary embodiments of the present disclosure further provide a non-transitory computer readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is configured to cause the computer to perform the method according to the embodiments of the present disclosure.

[0115] Reference Figure 7 The exemplary embodiments of the present disclosure further provide a computer program product 700 including a computer program 701, wherein the computer program, when executed by a processor of a computer, is configured to cause the computer to perform the method according to the embodiments of the present disclosure.

[0116] Reference Figure 8An example of a hardware device that can be employed in the implementation of the present disclosure will now be described with reference to FIG. 8, which is a block diagram of an electronic device 800 that can be used as a server or a client of the present disclosure, and which is an example of a hardware device that can be employed in various aspects of the present disclosure. The electronic device is intended to represent various forms of digital electronic computer devices such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices such as personal digital assistants, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present disclosure described and / or claimed in this document.

[0117] The electronic device 800 includes a computing unit 801 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. Various programs and data required for device operation can also be stored in the RAM 803. The computing unit 801, the ROM 802, and the RAM 803 are connected to each other through a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0118] Various components in the electronic device 800 are connected to the I / O interface 805, including an input unit 806, an output unit 807, the storage unit 808, and a communication unit 809. The input unit 806 can be any type of device that can input information to the electronic device 800, and can receive inputted digital or character information, and generate key signal inputs related to user settings and / or function controls of the electronic device. The output unit 807 can be any type of device that can present information, and can include, but is not limited to, a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 808 can include, but is not limited to, a magnetic disk, an optical disk. The communication unit 809 allows the electronic device 800 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and can include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth™ device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0119] The computing unit 801 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 801 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 computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 801 performs various methods and processes described above. For example, in some embodiments, the methods of the embodiments of the present disclosure can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 800 via the ROM 802 and / or the communication unit 809. In some embodiments, the computing unit 801 can be configured to perform the methods of the embodiments of the present disclosure by any other appropriate means, such as by means of firmware.

[0120] In the above, the method, device, equipment, storage medium and program product for distributing dumb resource images according to the embodiments of the present disclosure are described with reference to the drawings. By obtaining a channel rule model and a label dictionary, determining all dumb resource features matching the dumb resource image based on the label dictionary, determining a distribution channel of the dumb resource image based on each of the channel rule models and the dumb resource features matching the dumb resource image, and distributing the dumb resource image according to the distribution channel, the distribution channel of the dumb resource image is automatically determined, and the technical effect of improving the distribution efficiency of the dumb resource image is achieved.

[0121] The basic principles of the present disclosure are described above in combination with specific embodiments, but it should be pointed out that the advantages, advantages, effects, etc. mentioned in the present disclosure are only examples and are not limiting, and these advantages, advantages, effects, etc. cannot be considered as the must-have of each embodiment of the present disclosure. In addition, the specific details of the above disclosure are only for the purpose of example and for the purpose of understanding, and are not limiting, and the above details do not limit the present disclosure to the above specific details.

[0122] The block diagrams of the devices, apparatuses, equipment, systems involved in the present disclosure are only illustrative examples and are not intended to require or imply that the connection, arrangement, configuration must be as shown in the block diagram. As those skilled in the art will recognize, these devices, apparatuses, equipment, systems can be connected, arranged, configured in any manner. Words such as "include", "contain", "have", etc. are open-ended words, mean "include but not limited to", and can be used interchangeably. The words "or" and "and" used herein mean the word "and / or", and can be used interchangeably unless the context clearly indicates otherwise. The word "such as" used herein means the phrase "such as but not limited to", and can be used interchangeably.

[0123] Also, as used in the description herein, the term "or" as used in the

[0124] It is also important to note that the systems and methods of the disclosure can be embodied in a variety of forms including, but not limited to, application specific integrated circuits, program control modules, and the like.

[0125] Various changes, modifications, and improvements in the technologies described herein can be made without departing from the teachings of the disclosure as indicated by the appended claims. Moreover, the scope of the claims should not be limited to the particular aspects described in the above description and drawings. Rather, the scope of the claims should be understood to include any aspect that is within the scope of the claims and that falls within the equivalents thereof.

[0126] The above description of the disclosed aspects is given for illustrative purposes and is not intended to limit the scope of the disclosure. Although the foregoing discussion has discussed various example aspects and embodiments, those of skill in the art will recognize that certain variations, modifications, changes, additions and subcombinations can be made without departing from the scope of the disclosure. Accordingly, the disclosure is intended to embrace all such variations, modifications, changes, additions and subcombinations.

[0127] The above description has been given for illustrative purposes and is not intended to limit the embodiments of the disclosure. Although the above has discussed a plurality of example aspects and embodiments, those skilled in the art will recognize that certain variations, modifications, changes, additions and subcombinations can be made without departing from the scope of the disclosure. Accordingly, the disclosure is intended to embrace all such variations, modifications, changes, additions and subcombinations.

Claims

1. A method for distributing dumb resource images, characterized in that, include: Obtain the dumb resource image to be distributed; Obtain the channel rule model, which is used to indicate the combination of dummy resource features supported by each dummy resource capability module; Determine the dummy resource features of the dummy resource image; Based on the channel rule model and the dumb resource features of the dumb resource image, the distribution channel of the dumb resource image is determined, and the dumb resource image is distributed according to the distribution channel. The distribution channel is the interface channel of the target dumb resource capability module, and the target dumb resource capability module is a dumb resource capability module whose dumb resource feature combination matches the dumb resource features of the dumb resource image. The method further includes: Based on the description of the dummy resource information that each dummy resource capability module can process, the dummy resource features that each dummy resource capability module can process are determined, and the combination of dummy resource features supported by each dummy resource capability module is constructed. The channel rule model is generated based on the combination of dummy resource features supported by each of the dummy resource capability modules.

2. The method according to claim 1, characterized in that, The channel rule model uses rule expressions based on dummy resource features to indicate the combinations of dummy resource features supported by each of the dummy resource capability modules.

3. The method according to claim 1 or 2, characterized in that, Each of the dummy resource capability modules supports a combination of dummy resource features that includes multiple OR gate chains. Each OR gate chain includes multiple AND gate chains in combination with OR operations. Each AND gate chain includes a combination of several dummy resource features in combination with AND operations. If all the dummy resource features of any AND gate chain in the dummy resource feature combination are included in the dummy resource features of the dummy resource image, then the dummy resource feature combination matches the dummy resource features of the dummy resource image.

4. The method according to claim 1, characterized in that, Determining the dummy resource features of the dummy resource image includes: Based on the label dictionary, all dummy resource features that match the dummy resource image are determined to obtain the dummy resource features of the dummy resource image, wherein the label dictionary contains all dummy resource features involved in the channel rule model.

5. The method according to claim 4, characterized in that, The step of determining all dummy resource features that match the dummy resource image based on the label dictionary includes: Obtain the image features of the dumb resource image; Based on the image features of the dummy resource image and the various dummy resource features of the tag dictionary, all dummy resource features that match the dummy resource image are determined.

6. The method according to claim 1, characterized in that, Based on the channel rule model and the dummy resource features of the dummy resource image, the distribution channel of the dummy resource image is determined, including: Based on the combination of dummy resource features supported by each dummy resource capability module indicated by the channel rule model and the dummy resource features of the dummy resource image, determine the interface channel of the dummy resource capability module that supports the dummy resource image; The distribution channel of the dumb resource image is determined based on the interface channel of the dumb resource capability module that supports the dumb resource image.

7. A dumb resource image distribution device, characterized in that, include: The first acquisition module is used to acquire the dumb resource image to be distributed; The second acquisition module is used to acquire the channel rule model, which is used to indicate the combination of dummy resource features supported by each dummy resource capability module; The determination module is used to determine the dummy resource features of the dummy resource image; An image distribution module is used to determine the distribution channel of the dumb resource image based on the channel rule model and the dumb resource features of the dumb resource image, and to distribute the dumb resource image according to the distribution channel. The distribution channel is an interface channel of a target dumb resource capability module, and the target dumb resource capability module is a dumb resource capability module whose dumb resource feature combination matches the dumb resource features of the dumb resource image. The generation module is used to determine the dummy resource characteristics that each dummy resource capability module can process based on the description of dummy resource information that each dummy resource capability module can process, construct the combination of dummy resource characteristics supported by each dummy resource capability module, and generate a channel rule model based on the combination of dummy resource characteristics supported by each dummy resource capability module.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instruction is executed by the processor, it implements the steps of the method described in any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the steps of the method described in any one of claims 1 to 6.

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