Example Analysis of Hitachi Open Source semantic Segmentation dataset Annotation tool Semantic Segmentation Editor

In this issue, the editor will bring you an example analysis of the Hitachi open source semantic segmentation dataset annotation tool Semantic Segmentation Editor. The article is rich in content and analyzes and describes it from a professional point of view. I hope you can get something after reading this article.

Hitachi Automotive And Industry Lab has just opened up the Web-based semantic object Annotation Editor (Semantic Segmentation Editor), a tool designed to create training data for machine learning semantic segmentation.

The tool was developed for autopilot research, but has also been used to annotate other types of semantic target databases. It not only supports 2D images (.jpg and .png files) taken by ordinary cameras, but also supports the annotation of targets in 3D point clouds (.pcd files) generated by LIDAR. It is a Meteor application developed using React, Paper.js and three.js.

2D picture object annotation

Bitmap image editor marks the target by marking polygons on the image

3D point cloud object annotation

Point cloud editor creates objects by dimensioning a subset of 3D points

The above is the example of Hitachi open source semantic segmentation dataset annotation tool Semantic Segmentation Editor shared by Xiaobi. if you happen to have similar doubts, please refer to the above analysis to understand. If you want to know more about it, you are welcome to follow the industry information channel.