TuSimple/TuSimple-DUC
Understanding Convolution for Semantic Segmentation
This project helps developers and researchers working with computer vision tasks like autonomous driving or medical image analysis. It takes raw images (e.g., from a car's camera or medical scans) and outputs a detailed, pixel-by-pixel map where each pixel is labeled with the type of object it represents (e.g., road, car, pedestrian, tumor). This is specifically for those building or evaluating image segmentation models.
611 stars. No commits in the last 6 months.
Use this if you are a computer vision engineer or researcher focused on developing and evaluating state-of-the-art semantic segmentation models for visual scene understanding.
Not ideal if you need an out-of-the-box application for general image editing or object detection without delving into the underlying model architecture and training.
Stars
611
Forks
112
Language
Python
License
Apache-2.0
Category
Last pushed
Oct 26, 2021
Commits (30d)
0
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