Zero-Shot Semantic Segmentation

• Princeton University Senior Thesis
• Advisor: Professor Olga Russakovsky, Princeton University Department of Computer Science
• Part of the Princeton VisualAI Lab

Project Overview

This is the PyTorch implementation of the seenmask zeroshot network (SZN) described in Rohan Doshi's senior thesis "Zero-shot Semantic Segmentation." Please reference this paper (rohan_doshi_senior_thesis.pdf) to understand the code.

Installation

** Requirements: ** Conda (with Python 3) and Linux

1. Install Conda

2. Clone repository

git clone https://github.com/RohanDoshi2018/ZeroshotSemanticSegmentation.git
cd ZeroshotSemanticSegmentation

3. Create new conda environment

conda create --name thesis_env

4. Install Dependencies

conda install pytorch torchvision -c pytorch
pip install pytz pyyaml scipy fcn jupyter tensorflow tensorboardX

5. Activate your conda environment source activate thesis_env

6. Run code

./train.py -c 4 -g 0

7. [Optional] Run Tensorboard Server. Use Ngrok tunnel to access server remotely.

tensorboard --logdir /opt/visualai/rkdoshi/ZeroshotSemanticSegmentation/tb