Method for automatically establishing artificial intelligent image recognizing training materials and annotation files

An artificial intelligence, automatic creation technology, applied in special data processing applications, instruments, electrical and digital data processing, etc., can solve the problems of low overall quality, long time, labeling speed, and reduced accuracy, and achieve high overall quality and generation. The effect of fast speed and saving time of labeling

Active Publication Date: 2018-09-21
王海军
View PDF9 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] overall low quality
In the shooting stage, it is difficult to accurately take a large number of photos that meet expectations, so the overall number of photos is relatively small and the time is long
The labeling stage mainly relies on manual w

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for automatically establishing artificial intelligent image recognizing training materials and annotation files

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0022] Example 1. Such as figure 1 As shown, the method for automatically creating artificial intelligence image recognition training materials and annotation files includes the following steps:

[0023] Step S1: 3D model and scene design, use CAD software for digital 3D modeling, and then use 3D MAX software for material production and rendering, simulate various scenes, light and shadow effects in various periods, and combine the model, material and background The information is stored separately for combined use; the step 1 includes a three-dimensional modeling module, a material production module, and a rendering module. In the step S1, when modeling, the important parts are firstly modeled separately, and finally the parts are assembled into a whole. Taking the lightning arrester as an example, at least the components such as the equalizing ring, the insulating ceramic column, the flange, the bolt, the equipment pillar, the cement foundation, and the grounding strap must be...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a method for automatically establishing artificial intelligent image recognizing training materials and annotation files. The method is characterized by comprising the following steps of S1, designing a 3D model and scene, and conducting three-dimensional modeling through CAD type software numbers; S2, synthesizing training images, reading the 3D model, materials and background information in the step S1 through tool software, conducting simulating camera shooting on the 3D model, materials and background to obtain shot images with different distances, angles, time durations and scenes, combining the images obtained through simulation and the object materials, synthesizing and outputting the training images, and recording the model space positions of all focused objects under current states during outputting; S3, establishing the object annotation files, and conducting annotation on the model space position information, recorded in the step S3, of all the focused objects to generate the annotation files; S4, storing the annotation files. By means of the method, the high-quality training materials and annotation files can be rapidly generated.

Description

Technical field [0001] The invention relates to a method for automatically creating artificial intelligence image recognition training materials and annotation files, and belongs to the technical field of artificial intelligence. Background technique [0002] The artificial intelligence platform software is relatively mature, and can form a specific picture recognition model by automatically learning a large number of training materials (pre-labeled pictures). Then apply this model to identify whether there is an object of interest in the new picture, and describe the exact position of the object in the picture. However, the current difficulties in obtaining training materials are as follows: [0003] Difficult to shoot. The existing training photo data is usually collected by manual or aerial photography. Due to various restrictions on safety, distance, angle, shooting equipment, time, climate, etc., the number of training pictures formed is small, and it is difficult to form t...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F17/30
Inventor 王海军王海涛吕博钰吕钢
Owner 王海军
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap