coderzbx / chainer-pspnet

PSPNet in Chainer

PSPNet

This is an unofficial implementation of Pyramid Scene Parsing Network (PSPNet) in Chainer.

Training

Requirement

• Python 3.4.4+
  • Chainer 3.0.0b1+
  • ChainerMN master@distributed-batch-normalization
    • pip install git+git://github.com/chainer/chainermn.git@distributed-batch-normalization
  • CuPy 2.0.0b1+
  • ChainerCV 0.6.0+
  • NumPy 1.12.0+
  • tqdm 4.11.0+

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Inference using converted weights

Requirement

• Python 3.4.4+
  • Chainer 3.0.0b1+
  • ChainerCV 0.6.0+
  • Matplotlib 2.0.0+
  • CuPy 2.0.0b1+
  • tqdm 4.11.0+

1. Download converted weights

$ bash download.sh

2. Run demo.py

$ python demo.py -g 0 -m Cityscapes -f aachen_000000_000019_leftImg8bit.png

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Convert weights by yourself

Caffe is NOT needed to convert .caffemodel to Chainer model. Use caffe_pb2.py.

Requirement

• Python 3.4.4+
  • protobuf 3.2.0+
  • Chainer 3.0.0b1+

1. Download the original weights

Please download the weights below from the author's repository:

• pspnet50_ADE20K.caffemodel: GoogleDrive
• pspnet101_VOC2012.caffemodel: GoogleDrive
• pspnet101_cityscapes.caffemodel: GoogleDrive

and then put them into weights directory.

2. Convert weights

$ python convert.py