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print("hello world!")
""" | |
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
BSD License | |
""" | |
import numpy as np | |
# data I/O | |
data = open('input.txt', 'r').read() # should be simple plain text file | |
chars = list(set(data)) | |
data_size, vocab_size = len(data), len(chars) |
# | |
# ref https://github.com/tebeka/pythonwise/blob/master/docker-miniconda/Dockerfile | |
# | |
# miniconda vers: http://repo.continuum.io/miniconda | |
# sample variations: | |
# Miniconda3-latest-Linux-armv7l.sh | |
# Miniconda3-latest-Linux-x86_64.sh | |
# Miniconda3-py38_4.10.3-Linux-x86_64.sh | |
# Miniconda3-py37_4.10.3-Linux-x86_64.sh | |
# |
#!/bin/sh | |
# Sanity checks | |
if ! [ -x "$(command -v gs)" ]; then | |
echo "gs is not installed -> exit" | |
exit 1 | |
fi | |
# Define some handy options to use with ghostscript | |
export PDF2PDFFLAGS="-dCompatibilityLevel=1.5 -dPDFSETTINGS=/ebook -dPrinted=false -dColorConversionStrategy=/UseDeviceIndependentColor -dDownsampleColorImages=true -dDownsampleGrayImages=true -dDownsampleMonoImages=true -dMaxSubsetPct=100 -dSubsetFonts=true -dEmbedAllFonts=true -dOptimize=true -dUseFlateCompression=true -dNOPAUSE -dBATCH -sDEVICE=pdfwrite" |
# Load dry bone CT of skull into the scene and run this script to automatically segment endocranium | |
masterVolumeNode = slicer.mrmlScene.GetFirstNodeByClass("vtkMRMLScalarVolumeNode") | |
smoothingKernelSizeMm = 3.0 # this is used for closing small holes in the se | |
# Compute bone threshold value automatically | |
import vtkITK | |
thresholdCalculator = vtkITK.vtkITKImageThresholdCalculator() | |
thresholdCalculator.SetInputData(masterVolumeNode.GetImageData()) | |
thresholdCalculator.SetMethodToOtsu() |