PSPNet in Chainer

Related tags

Deep Learningpythondeep-learningchainerimagenetconvolutional-neural-networkssemantic-segmentationpascal-voccityscapespspnetade20k
Overview

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
    • CuPy 2.0.0b1+
    • ChainerCV 0.6.0+
    • NumPy 1.12.0+
    • tqdm 4.11.0+
pip install chainer --pre
pip install cupy --pre
pip install git+git://github.com/chainer/chainermn
pip install git+git://github.com/chainer/chainercv
pip install tqdm

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. Run demo.py

Cityscapes

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

Pascal VOC2012

$ python demo.py -g 0 -m voc2012 -f 2008_000005.jpg

ADE20K

$ python demo.py -g 0 -m ade20k -f ADE_val_00000001.jpg

FAQ

If you get RuntimeError: Invalid DISPLAY variable, how about specifying the matplotlib's backend by an environment variable?

$ MPLBACKEND=Agg python demo.py -g 0 -m cityscapes -f aachen_000000_000019_leftImg8bit.png

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+
    • NumPy 1.12.0+

1. Download the original weights

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

and then put them into weights directory.

2. Convert weights

$ python convert.py

Reference

  • The original implementation by authors is: hszhao/PSPNet
  • The original paper is:
    • Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia, "Pyramid Scene Parsing Network", Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
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Comments
  • Training failes with ModuleNotFoundError when using train_mn.py

    Training failes with ModuleNotFoundError when using train_mn.py

    Hi, I got following error when I tried to train PSP net with your train_mn.py How can I train my PSPNet model?

    [email protected]:/yendo/oss/chainer-pspnet# python3 train_mn.py --result_dir result configs/cityscapes/pspnet.yml
Warning: using naive communicator because only naive supports CPU-only execution
==========================================
Num process (COMM_WORLD): 1
Using single_node communicator
Chainer version: 3.4.0
ChainerMN version: 1.2.0
cuda: True, cudnn: True
result_dir: result
Traceback (most recent call last):
  File "train_mn.py", line 504, in <module>
    trainer = get_trainer(args)
  File "train_mn.py", line 374, in get_trainer
    model = get_model_from_config(config, comm)
  File "train_mn.py", line 239, in get_model_from_config
    loss.module, loss.name, loss.args, comm)
  File "train_mn.py", line 219, in get_model
    mod = import_module(loss_module)
  File "/root/.pyenv/versions/anaconda3-5.0.1/lib/python3.6/importlib/__init__.py", line 126, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 994, in _gcd_import
  File "<frozen importlib._bootstrap>", line 971, in _find_and_load
  File "<frozen importlib._bootstrap>", line 941, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "<frozen importlib._bootstrap>", line 994, in _gcd_import
  File "<frozen importlib._bootstrap>", line 971, in _find_and_load
  File "<frozen importlib._bootstrap>", line 953, in _find_and_load_unlocked
ModuleNotFoundError: No module named 'loss'
    opened by jo7ueb 0
  • Training Fails with IndexError when using train.py

    Training Fails with IndexError when using train.py

    Hi, I got following error when I tried to train PSP net with your train.py How can I train my PSPNet model?

    [email protected]:/yendo/oss/chainer-pspnet# python3 train.py --gpu --result_dir result configs/cityscapes/pspnet.yml
==========================================
Chainer version: 3.4.0
CuPy version: 2.4.0
Traceback (most recent call last):
  File "train.py", line 483, in <module>
    trainer = get_trainer(args)
  File "train.py", line 339, in get_trainer
    chainer.cuda.available, chainer.cuda.cudnn_enabled, ))
IndexError: tuple index out of range
    opened by jo7ueb 0
  • could you actually train a new model?

    could you actually train a new model?

    Hi, I am currently trying to train the cityscapes dataset with your code, but the result is miserable: still 0.5263158 (=1/19) class accuracy after 120 epochs. Apparently, the loss of training data is converged correctly, so it seems like a perfect over fitting. Since I used the same settings as yours, i am wondering how you managed to reproduce the results(maybe i need less learning rate?). thanks in advance!

    opened by suzukikbp 0
Owner
Shunta Saito
Ph.D in Engineering, Researcher at Preferred Networks, Inc.
Shunta Saito
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