yl-jiang/UPerNet
Pytorch Implement of UPerNet
This project helps machine learning engineers or researchers working with computer vision tasks. It takes a collection of images and their corresponding ground truth segmentation masks as input. The output is a trained segmentation model capable of accurately identifying and outlining objects or regions within new images.
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Use this if you are a machine learning practitioner looking to train and evaluate a UPerNet model for semantic segmentation on your own datasets.
Not ideal if you are an end-user without programming or machine learning experience, as it requires setting up a Python environment and configuring training scripts.
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31
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3
Language
Python
License
MIT
Category
Last pushed
Jan 17, 2023
Commits (30d)
0
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