An example of semantic segmentation using tensorflow in eager execution.

Last update: Sep 29, 2022

Overview

Semantic segmentation using Tensorflow eager execution

Requirement

Python 2.7+
Tensorflow-gpu
OpenCv
H5py
Scikit-learn
Numpy
Imgaug

Train with eager execution

Train a semantic segmentation model on the Camvid dataset! just execute:

python train_eager.py

Owner

Iñigo Alonso Ruiz

PhD student (University of Zaragoza)

GitHub Repository

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An example of semantic segmentation using tensorflow in eager execution.

Related tags

Overview

Semantic segmentation using Tensorflow eager execution

Requirement

Train with eager execution

Owner

Iñigo Alonso Ruiz

A pytorch implementation of the ACL2019 paper "Simple and Effective Text Matching with Richer Alignment Features".

Official implementation for paper: Feature-Style Encoder for Style-Based GAN Inversion

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