Annotation object control device

A technology of object control and target object, which is applied in the direction of instruments, electrical digital data processing, character and pattern recognition, etc., can solve the problems of time-consuming and cumbersome labeling process, reduce the number of interactions, simplify the labeling process, and save labeling time Effect

Inactive Publication Date: 2018-02-16
FAFA AUTOMOBILE (CHINA) CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In the process of labeling in the existing method, when multiple labeling boxes overlap, multiple interactions with the labeling application program are required to determine the target object to be selected, which makes the labeling process more cumbersome and time-consuming. The present invention The embodiment proposes a labeling object control device

Method used

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Embodiment Construction

[0025] The specific embodiments of the invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0026] figure 1 It shows a schematic flowchart of a method for controlling a marked object provided in this embodiment, including:

[0027] S101. After marking an object in an image with a label frame, obtain a control point of the label frame, and establish a corresponding relationship between the control point and the object;

[0028] Specifically, after the tagging application program of the terminal recognizes the object in the image, it uses a tagging frame to tag the identified object, obtains control points on the tagging frame, and establishes a corresponding relationship between each control point and the identified object .

[0029] Wherein, the labeling applicat...

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Abstract

The embodiment of the invention discloses an annotation object control device. According to the device, after annotation boxes are adopted to annotate objects in an image, control points of the annotation boxes are acquired, and a corresponding relation between the control points and the objects is established; if a mouse clicking event is monitored, a mouse position is acquired; and if it is known that the mouse position is in at least two annotation boxes through judgment, target control points closest to the mouse position in the annotation boxes are acquired, and target objects corresponding to the target control points are obtained according to the corresponding relation. According to the embodiment, the mouse position is acquired after the mouse clicking event is monitored, the target control points closest to the mouse position are calculated, and the target objects corresponding to the target control points are obtained according to the corresponding relation between the control points and the objects. Therefore, the target objects can be determined according to the mouse clicking position, the number of interactions between an annotation tool and a user is reduced, the annotation process is simpler, and meanwhile annotation time is saved.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of smart cars, and in particular to a control device for labeling objects. Background technique [0002] With the deepening of the research on smart cars and the continuous improvement of their intelligence, more and more smart cars have introduced smart modules, which can meet the personalized customization requirements of different drivers while improving the driver's driving experience, so more and more more popular with users. [0003] The automatic driving perception module is a very important functional module in the smart car, which is used to automatically recognize the objects around the car during the driving process, including: people, cars, obstacles and buildings, etc., which involves a large number of deep learning algorithms , these deep learning algorithms require a large number of annotated training samples, therefore, it is necessary to annotate different objects thro...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F3/0484G06F3/0487G06K9/62
CPCG06F3/04842G06F3/0487G06F18/40G06F18/214
Inventor 黄立宏
Owner FAFA AUTOMOBILE (CHINA) CO LTD
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