Sample labeling method and computer storage medium

A sample labeling and sample image technology, applied in the computer field, can solve the problem of low labeling accuracy and achieve the effect of improving accuracy

Inactive Publication Date: 2019-08-16
BEIJING CENTURY TAL EDUCATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of this, an embodiment of the present invention provides a sample labeling method and a computer storage medium to solve the problem of low labeling accuracy of real samples in the prior art

Method used

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  • Sample labeling method and computer storage medium
  • Sample labeling method and computer storage medium

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Experimental program
Comparison scheme
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Embodiment 1

[0013] figure 1 It is a schematic flowchart of a sample labeling method provided in Embodiment 1 of the present invention. Such as figure 1 As shown, the sample labeling methods include:

[0014] S101: Obtain a sample image to be labeled.

[0015] The sample images to be labeled can be used for subsequent training of the machine learning model and used as training sample images. In the embodiment of the present invention, the training sample image is an image including characters, where the characters include but not limited to: characters, letters, numbers, and symbols.

[0016] S102: Perform character detection on the sample image to be labeled by using the character detection model, and obtain a character frame for indicating the character position of each character in the sample image to be labeled.

[0017] The character detection model is used to detect characters in the sample images to be annotated. The character detection model can be used by those skilled in the...

Embodiment 2

[0037] Such as figure 2 As shown, it shows a schematic flowchart of the sample labeling method according to Embodiment 2 of the present invention. The sample labeling methods include:

[0038] S201: Obtain a sample image to be labeled.

[0039] The sample images to be labeled can be used for subsequent training of the machine learning model and used as training sample images. In the embodiment of the present invention, the training sample image is an image including characters, where the characters include but not limited to: characters, letters, numbers, and symbols.

[0040] S202: Perform character detection on the sample image to be labeled by using the character detection model, and obtain a character frame for indicating the character position of each character in the sample image to be labeled.

[0041] The character detection model is used to detect characters in the sample images to be annotated. The character detection model can be used by those skilled in the ar...

Embodiment 3

[0081] According to an embodiment of the present invention, a computer storage medium is provided, and the computer storage medium stores: instructions for acquiring a sample image to be marked; for performing character detection on the sample image to be marked through a character detection model, and obtaining Instructions for character boxes indicating the character positions of each character in the sample image to be marked; for determining the average height of character boxes according to the number of character boxes and the height of each character box; for according to the average height of character boxes, from Instructions for screening out at least one first candidate character frame from all character frames; for each first candidate character frame, in the vertical direction, determine the character frame with the smallest distance from the current first candidate character frame as the current second character frame The candidate character frame, in the horizont...

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Abstract

The invention provides a sample labeling method and a computer storage medium. The sample labeling method comprises the following steps: carrying out character detection on a to-be-labeled sample image through a character detection model, and obtaining a character box; determining the average height of the character boxes according to the number of the character boxes and the height of each character box; screening out at least one first candidate character box from all character boxes according to the average height of the character boxes; for each first candidate character box, determining the character box with the minimum distance from the current first candidate character box as a current second candidate character box in the vertical direction, and determining a reference character box in the horizontal direction; if the horizontal center line of the current second candidate character box passes through the reference character box in the horizontal direction, determining the current first candidate character box and the current second candidate character box as candidate character boxes to be merged; and generating labeling information of the sample image according to the processing of the candidate character boxes to be merged. For the sample labeling method, the marking accuracy of the sample marking method is better.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a sample labeling method and a computer storage medium. Background technique [0002] With the development of artificial intelligence and machine learning technology, more and more fields have begun to use machine learning methods to train equipment to have a certain degree of intelligence. With this comes a growing demand for training samples. For example, when training optical character detection models and recognition models, a large number of labeled samples are required. Labeled samples refer to manually labeling character boxes and character categories used to indicate character positions on real samples. The existing method of using purely manual labeling when obtaining real samples has the problem of low efficiency, and because of manual labeling, there will be a certain loss of accuracy, such as manual errors that cause inaccurate character position labeling and chara...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/32
CPCG06V20/63G06V30/10
Inventor 兴百桥
Owner BEIJING CENTURY TAL EDUCATION TECH CO LTD
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