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63 lines
1.9 KiB
Markdown
63 lines
1.9 KiB
Markdown
# Keras implementation of [PSPNet(caffe)](https://github.com/hszhao/PSPNet)
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Implemented Architecture of Pyramid Scene Parsing Network in Keras.
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Converted trained weights are needed to run the network.
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Weights of the original caffemodel can be converted with weight_converter.py as follows:
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```bash
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python weight_converter.py <path to .prototxt> <path to .caffemodel>
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```
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Running this needs the compiled original PSPNet caffe code and pycaffe.
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Already converted weights can be downloaded here:
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[pspnet50_ade20k.npy](https://www.dropbox.com/s/ms8afun494dlh1t/pspnet50_ade20k.npy?dl=0)
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[pspnet101_cityscapes.npy](https://www.dropbox.com/s/b21j6hi6qql90l0/pspnet101_cityscapes.npy?dl=0)
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[pspnet101_voc2012.npy](https://www.dropbox.com/s/xkjmghsbn6sfj9k/pspnet101_voc2012.npy?dl=0)
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npy weights should be placed in the directory weights/npy.
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The interpolation layer is implemented as custom layer "Interp"
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## Keras result:
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## Pycaffe result:
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## Dependencies:
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1. Tensorflow (-gpu)
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2. Keras
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3. numpy
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4. scipy
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4. pycaffe(PSPNet)(optional for converting the weights)
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```bash
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pip install -r requirements.txt --upgrade
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```
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## Usage:
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```bash
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python pspnet.py
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python pspnet.py -m pspnet101_cityscapes -i example_images/cityscapes.png -o example_results/cityscapes.jpg
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python pspnet.py -m pspnet101_voc2012 -i example_images/pascal_voc.jpg -o example_results/pascal_voc.jpg
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```
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