Power grid image intelligent annotation crowdsourcing platform and working method

Abstract

The invention relates to a power grid image intelligent annotation crowdsourcing platform and a working method, and belongs to the technical field of power grid image data processing. The working method comprises the following steps: collecting to-be-annotated picture collection, performing initial annotation, performing manual adjustment annotation, performing difference re-annotation and data storage. The power grid image intelligent annotation crowdsourcing platform comprises a to-be-annotated image collection module, an initial annotation module, a manual adjustment annotation module, a difference re-annotation module and a data storage module, and is used for executing the power grid image intelligent annotation crowdsourcing platform working method. According to the invention, the preset model is used to carry out initial annotation on the data; meanwhile, platform crowdsourcing is used for manually adjusting annotation; multi-person cooperation is achieved, the annotation efficiency is improved, the unqualified annotation result is modified according to IOU parameters, the annotation quality is effectively improved, meanwhile, the data classification and arrangement functionmeets the requirement for specific model training for a certain hidden danger, and powerful data support is provided for model training and model precision improvement in the future.

Description

technical field

[0001] The invention relates to a power grid image intelligent tagging crowdsourcing platform and a working method, belonging to the technical field of power grid image data processing. Background technique

[0002] With the rapid development of big data and artificial intelligence, the application of artificial intelligence in various fields of the power grid has taken root, such as: detection of hidden dangers in transmission channels, detection of wear of substation construction personnel, temperature detection of distribution tower heads, etc. The realization of the above functions is far from Without high-precision recognition model support, a good model not only requires excellent algorithm support, but also requires a large amount of labeled data for training.

[0003] At present, manual labeling is still the mainstream of data labeling, and its labeling process is roughly as follows: through issuing labeling tasks, manual labeling, and finally submitt...

Examples

Embodiment Construction

[0037] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0038] Such as figure 1 As shown, the grid image intelligent labeling crowdsourcing platform working method of the present invention includes:

[0039] Step S1, collection of pictures to be marked: the data to be marked includes monitoring pictures in the process of power transmission, power transformation and power distribution of the power grid;

[0040] Step S2, initial annotation: call the corresponding preset model for each type of image to be annotated to perform prediction analysis and adopt the corresponding annotation method to annotate, and obtain the initial annotated data and the initial annotated image;

[0041] Step S3, manually adjust labeling: use crowdsourcing distribution method to distribute each batch of initial la...

technical field

[0001] The invention relates to a power grid image intelligent tagging crowdsourcing platform and a working method, belonging to the technical field of power grid image data processing. Background technique

[0002] With the rapid development of big data and artificial intelligence, the application of artificial intelligence in various fields of the power grid has taken root, such as: detection of hidden dangers in transmission channels, detection of wear of substation construction personnel, temperature detection of distribution tower heads, etc. The realization of the above functions is far from Without high-precision recognition model support, a good model not only requires excellent algorithm support, but also requires a large amount of labeled data for training.

[0003] At present, manual labeling is still the mainstream of data labeling, and its labeling process is roughly as follows: through issuing labeling tasks, manual labeling, and finally submitt...

Examples

Embodiment Construction

[0037] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0038] Such as figure 1 As shown, the grid image intelligent labeling crowdsourcing platform working method of the present invention includes:

[0039] Step S1, collection of pictures to be marked: the data to be marked includes monitoring pictures in the process of power transmission, power transformation and power distribution of the power grid;

[0040] Step S2, initial annotation: call the corresponding preset model for each type of image to be annotated to perform prediction analysis and adopt the corresponding annotation method to annotate, and obtain the initial annotated data and the initial annotated image;

[0041] Step S3, manually adjust labeling: use crowdsourcing distribution method to distribute each batch of initial la...

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