AKASH2907 / fcn_semantic_segmentation

FCN

This code provides Pytorch implementation of FCN architecture on synthetic dataset and real world dataset from scratch as well as finetuning. There are some custom utils functions for joint transformation, evaluation, and average meter.

Requirements

Tested on Python 3.6.x and Keras 2.3.0 with TF backend version 1.14.0.

• Numpy
• Torchvision
• PyTorch
• Matplotlib
• Pillow

Codes running

• Install the required dependencies:

pip install -r requirements.txt

Description

fcn.py: Model architecture

train_games.py: Train on games dataset

train_cityscapes.py: Train on cityscapes dataset

ft_cityscapes.py: Finetuning on cityscapes

eval_cityscapes.py: Evaluate on test dataset of cityscapes

cityscapes.py: create dataloader for cityscapes dataset

games_data.py: create dataloader for games dataset

To train on games from scratch

python train_games.py 

To train on cityscapes from scratch

python train_cityscapes.py 

To train on cityscapes for finetuning

python ft_cityscapes.py 

Evaluate on cityscapes

 python eval_cityscapes.py