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- # Deep Extreme Cut (DEXTR)
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- [ ![ Binder] ( https://mybinder.org/badge.svg )] ( https://mybinder.org/v2/gh/4QuantOSS/DEXTR-KerasTensorflow/master )
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+ # Deep Extreme Cut (DEXTR) [ ![ Binder] ( https://mybinder.org/badge.svg )] ( https://mybinder.org/v2/gh/4QuantOSS/DEXTR-KerasTensorflow/master )
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+ [ ![ Demo] ( https://img.shields.io/badge/launch-interactive_demo-yellow.svg )] ( https://mybinder.org/v2/gh/4QuantOSS/DEXTR-KerasTensorflow/master?urlpath=%2Fapps%2Fnotebooks%2FDemo.ipynb )
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Visit our [ project page] ( http://www.vision.ee.ethz.ch/~cvlsegmentation/dextr ) for accessing the paper, and the pre-computed results.
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- torchvision
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- opencv3>=3.0
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- tensorflow==1.4.0
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+ - appmode
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- pip :
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- keras==2.1.3
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- plotly==2.1.0
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cd models
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- . download_dextr_model.sh
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+ sh download_dextr_model.sh
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cd ..
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+ mkdir $HOME/.jupyter
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+ echo "c.NotebookApp.iopub_data_rate_limit=1e22" >> $HOME/.jupyter/jupyter_notebook_config.py
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class Path (object ):
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@staticmethod
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def models_dir ():
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- return os .path .join (os .path .dirname (___file___ ), 'models/' )
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+ return os .path .join (os .path .dirname (__file__ ), 'models/' )
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