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Semi-automatic labeling method, equipment, medium and device

A semi-automated, storage medium technology, applied in the field of image labeling, can solve problems such as low efficiency and manual labeling errors

Pending Publication Date: 2020-10-23
HANGZHOU KEDU TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the deficiencies of the prior art, one of the purposes of the present invention is to provide a semi-automatic labeling method, which can solve the problems of errors and low efficiency in manual labeling

Method used

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  • Semi-automatic labeling method, equipment, medium and device
  • Semi-automatic labeling method, equipment, medium and device
  • Semi-automatic labeling method, equipment, medium and device

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0046] This embodiment provides a semi-automatic labeling method, aiming at labeling tasks, after using the semi-automatic labeling method to generate label candidate boxes, the manual only needs to select the appropriate candidate box, thereby saving labeling time and improving labeling. efficiency. At the same time, the candidate area is automatically generated according to the edge information of the object, so the accuracy will be higher than manual labeling. And it is not limited to the detection of specific objects, but the area automatically generated according to the edge information, so it can be applied to the labeling of most scenes and has good applicability.

[0047] According to the above principles, a semi-automatic labeling method is introduced, such as figure 1 As shown, a semi-automatic labeling method specifically includes the following steps:

[0048] Initialize each pixel generation area for the picture, as a candidate area, pair all adjacent candidate a...

Embodiment 2

[0073] Embodiment 2 discloses a semi-automatic labeling device corresponding to the above embodiment, which is the virtual device structure of Embodiment 1. Please refer to image 3 shown, including:

[0074] The initialization module 210 initializes each pixel generation area for the picture as a candidate area, and performs pairwise pairing of all adjacent candidate areas to generate a calculation list;

[0075] The similarity calculation module 220 performs similarity calculation according to the calculation list, including color similarity calculation and texture value similarity calculation, and obtains the first score and the second score respectively;

[0076] The score calculation module 230 calculates the score according to the calculation list to obtain the third score;

[0077] The merging module 240 adds the calculated similarities according to the first score, the second score and the third score, and performs pairwise merging of those in the list that reach the ...

Embodiment 3

[0095] Figure 4 A schematic structural diagram of an electronic device provided in Embodiment 3 of the present invention, such as image 3 As shown, the electronic device includes a processor 310, a memory 320, an input device 330, and an output device 340; the number of processors 310 in a computer device may be one or more, image 3 Take a processor 310 as an example; the processor 310, the memory 320, the input device 330 and the output device 340 in the electronic device can be connected through a bus or other methods, image 3 Take connection via bus as an example. As a computer-readable storage medium, the memory 320 can be used to store software programs, computer-executable programs and modules, such as program instructions / modules corresponding to a semi-automatic labeling method in Embodiment 2 of the present invention (for example, a semi-automatic labeling method) initialization module 210, similarity calculation module 220, score module 230, merging module 240,...

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Abstract

The invention discloses a semi-automatic labeling method, which belongs to the technical field of image labeling, and comprises the following steps of: initializing each pixel generation region of a picture as a candidate region, and pairing all adjacent candidate regions in pairs to generate a calculation list; similarity calculation is carried out according to the calculation list, including color similarity calculation and texture value similarity calculation, and a first score and a second score are obtained respectively; score calculation is carried out according to the calculation list to obtain a third score; and according to the first score, the second score and the third score, adding the calculated similarities, and combining every two similarities reaching a similarity combination threshold in the list until all candidate regions are combined. After the label candidate boxes are generated by adopting the semi-automatic labeling method, only the proper candidate boxes need tobe manually selected, so that the labeling time is greatly saved, and the labeling efficiency is improved. The invention further discloses a semi-automatic labeling device, electronic equipment and acomputer storage medium.

Description

technical field [0001] The invention relates to the technical field of image labeling, in particular to a semi-automatic labeling method, equipment, medium and device. Background technique [0002] With the vigorous development of machine learning, the field of artificial intelligence has become increasingly inseparable from machine learning. However, machine learning requires a large amount of training data, and the training data needs to be manually labeled. However, the training data is usually tens of thousands or even hundreds of pieces. Ten thousand. However, pure manual labeling requires manual strokes, and the workload is very heavy. [0003] And manual labeling will cause large errors, which will cause unnecessary impact on the machine learning model. However, the existing algorithm itself is specialized and only targets a specific object detection, so it cannot be used as a general object labeling aid. Contents of the invention [0004] In order to overcome th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/33G06T7/187G06T7/11G06T7/44G06T7/62G06T5/50G06T5/40G06K9/62
CPCG06T7/337G06T7/187G06T7/11G06T5/50G06T5/40G06T7/44G06T7/62G06T2207/20221G06F18/22Y02D10/00
Inventor 赵鑫王伟吴鹏
Owner HANGZHOU KEDU TECH
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