python version of tan_specular_highlights removed.

bob/ip/qualitymeasure/__init__.py

@@ -5,8 +5,6 @@ from .galbally_iqm_features import compute_quality_features
 from .msu_iqa_features import compute_msu_iqa_features
 
 from ._library import remove_highlights
-from . import tan_specular_highlights as tsh
-
 
 def get_config():
     """

bob/ip/qualitymeasure/msu_iqa_features.py

@@ -10,12 +10,10 @@ import bob.ip.base
 import bob.ip.color
 from . import galbally_iqm_features as iqm
 
-#from . import tan_specular_highlights as tsh
 from ._library import remove_highlights
 
 ''' Utility functions '''
 
-
 def matlab_rgb2hsv(rgbImage):
     # first normalize the range of values to 0-1
 

bob/ip/qualitymeasure/script/highlights_histogram.py

@@ -5,6 +5,8 @@
 Created on 28 Jun 2017
 
 @author: dgeissbuhler
+
+Compute average specular histogram of an entire picture folder.
 '''
 from __future__ import print_function
 
@@ -13,21 +15,15 @@ import sys
 import argparse
 import time
 
-
 import bob.io.base
 import bob.io.image
 import bob.io.video
 import bob.ip.base
 import numpy as np
 
-from bob.ip.qualitymeasure import remove_highlights_orig
 from bob.ip.qualitymeasure import remove_highlights
-from bob.ip.qualitymeasure import tsh
 
 def main(command_line_parameters=None):
-    """Remove the specular component of the input image and write result to
-    a file.
-    """
 
     argParser = argparse.ArgumentParser(
         description=__doc__,
@@ -44,17 +40,15 @@ def main(command_line_parameters=None):
         '--output',
         dest='output',
         default=None,
-        help='output file.')
+        help='output text file.')
 
     args = argParser.parse_args(command_line_parameters)
 
     num_hist = 0.0
-    hist_v0  = np.zeros(256, dtype='uint64')
-    hist_v1  = np.zeros(256, dtype='uint64')
-    hist_v2  = np.zeros(256, dtype='uint64')
+    hist     = np.zeros(256, dtype='uint64')
 
     f = open(args.output, 'w')
-    print('# i v0 v1 v2', file=f)
+    print('# i bin_value', file=f)
 
     # 1. open input image
     print("Opening dir: %s" % args.path)
@@ -63,35 +57,24 @@ def main(command_line_parameters=None):
     # 2. compute
     for file in files:
         print('processing file: %s' % file)
+
         video = bob.io.video.reader(args.path + file)
         frame = video[0]
 
-        sfi, diff, residue = tsh.remove_highlights(frame.astype(np.float32), 0.06)
-        residue[np.where(np.isinf(residue))] = 0
-        residue[np.where(np.isnan(residue))] = 0
-        residue[np.where(residue < 0)] = 0
-        residue[np.where(residue > 255)] = 255
-        hist_v0 = hist_v0 + bob.ip.base.histogram(residue[0], (0.0, 255.0), 256)
+        sfi, diff, residue = remove_highlights(frame.astype(np.float32), 0.06)
 
-        sfi, diff, residue = remove_highlights_orig(frame.astype(np.float32), 0.06)
         residue[np.where(np.isinf(residue))] = 0
         residue[np.where(np.isnan(residue))] = 0
         residue[np.where(residue < 0)] = 0
         residue[np.where(residue > 255)] = 255
-        hist_v1 = hist_v1 + bob.ip.base.histogram(residue[0], (0.0, 255.0), 256)
 
-        sfi, diff, residue = remove_highlights(frame.astype(np.float32), 0.06)
-        residue[np.where(np.isinf(residue))] = 0
-        residue[np.where(np.isnan(residue))] = 0
-        residue[np.where(residue < 0)] = 0
-        residue[np.where(residue > 255)] = 255
-        hist_v2 = hist_v2 + bob.ip.base.histogram(residue[0], (0.0, 255.0), 256)
+        hist = hist + bob.ip.base.histogram(residue[0], (0.0, 255.0), 256)
 
 
     # 1. save output image
 
     for i in range(256):
-        print(i, hist_v0[i], hist_v1[i], hist_v2[i], file= f)
+        print(i, hist[i], file= f)
 
 
 

bob/ip/qualitymeasure/script/remove_highlights.py

@@ -15,9 +15,7 @@ import bob.io.base
 import bob.io.image
 import numpy as np
 
-from bob.ip.qualitymeasure import remove_highlights_orig
 from bob.ip.qualitymeasure import remove_highlights
-from bob.ip.qualitymeasure import tsh
 
 def main(command_line_parameters=None):
     """Remove the specular component of the input image and write result to
@@ -55,13 +53,6 @@ def main(command_line_parameters=None):
         default=0.5,
         help='value of epsilon parameter.')
 
-    argParser.add_argument(
-        '-a',
-        '--algorithm',
-        dest='algorithm',
-        default=0,
-        help='version of the algoritm used.')
-
     args = argParser.parse_args(command_line_parameters)
 
     if not args.inpImg:
@@ -76,15 +67,7 @@ def main(command_line_parameters=None):
     # 2. compute
     print("Extracting diffuse component...")
 
-    if int(args.algorithm) == 0:
-        print('v0')
-        sfi, diff, residue = tsh.remove_highlights(img.astype(np.float32), float(args.epsilon))
-    elif int(args.algorithm) == 1:
-        print('v1')
-        sfi, diff, residue = remove_highlights_orig(img.astype(np.float32), float(args.epsilon))
-    else:
-        print('v2')
-        sfi, diff, residue = remove_highlights(img.astype(np.float32), float(args.epsilon))
+    sfi, diff, residue = remove_highlights(img.astype(np.float32), float(args.epsilon))
 
     # 1. save output image
     print("Saving output file: %s" % args.outImg)