Fcn Pytorch

🚘 Easiest Fully Convolutional Networks
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Readme

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🚘 The easiest implementation of fully convolutional networks

Results

Trials

Training Procedures

Performance

I train with two popular benchmark dataset: CamVid and Cityscapes

dataset n_class pixel accuracy
Cityscapes 20 96%
CamVid 32 93%

Training

Install packages

pip3 install -r requirements.txt

and download pytorch 0.2.0 from pytorch.org

and download CamVid dataset (recommended) or Cityscapes dataset

Run the code

  • default dataset is CamVid

create a directory named "CamVid", and put data into it, then run python codes:

python3 python/CamVid_utils.py 
python3 python/train.py CamVid
  • or train with CityScapes

create a directory named "CityScapes", and put data into it, then run python codes:

python3 python/CityScapes_utils.py 
python3 python/train.py CityScapes

Author

Po-Chih Huang / @pochih

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Python
Deep Learning
Network
Dataset
Pytorch
Convolutional Networks
Computer Vision
Segmentation
Semantic Segmentation
Cityscapes
Fully Convolutional Networks