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python/train-metrics.py 1.24 KB
5f3cba02   David Mayerich   initial public co...
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  import sys, string, os, subprocess
  
  os.system("cls")
  
  infile = sys.argv[1]
  
  A = "supervised-class/class_coll.png "
  B = "supervised-class/class_epith.png "
  C = "supervised-class/class_fibro.png "
  D = "supervised-class/class_lymph.png "
  E = "supervised-class/class_myo.png "
  F = "supervised-class/class_necrosis.png "
  G = "supervised-class/class_blood.png "
  
  Ca = "magenta "
  Cb = "lime "
  Cc = "pink "
  Cd = "purple "
  Ce = "yellow "
  Cf = "orange "
  Cg = "maroon "
  
  #project to metrics
  subprocess.call("hsiproc " + infile + " " + infile + "-met --metrics metrics.txt")
  
  #create a mask to remove bad pixels
  subprocess.call("hsiproc " + infile + "-met " + "finite.bmp --mask-finite")
  subprocess.call("hsiproc " + infile + "-met " + infile + "-mask --apply-mask finite.bmp")
  
  #Baseline correction using a set of wavenumber points specified in baseline.txt
  subprocess.call("hsiclass " + infile + "-mask classifier.rf --train " + A + B + C + D + E + F + G + "--verbose")
  
  #convert to BIP for speed
  subprocess.call("hsiproc " + infile + "-mask " + infile + "-bip --convert bip")
  
  #classify the entire image
  subprocess.call("hsiclass " + infile + "-bip " + infile + "-class.bmp " + "--classify classifier.rf --colors " + Ca + Cb + Cc + Cd + Ce + Cf + Cg + "--mask mask.bmp --verbose")