Utils for ROI annotations and more

MANIFEST.in

 include README.rst bootstrap-buildout.py buildout.cfg COPYING
 recursive-include doc *.py *.rst
-recursive-include bob/bio/vein/tests *.png *.mat
+recursive-include bob/bio/vein/tests *.png *.mat *.txt *.npy

bob/bio/vein/preprocessor/utils/__init__.py

+from .utils import ManualRoiCut
+from .utils import ConstructVeinImage
+from .utils import RotateImage
+
+# gets sphinx autodoc done right - don't remove it
+__all__ = [_ for _ in dir() if not _.startswith('_')]

bob/bio/vein/tests/preprocessors/0019_3_1_120509-160517.txt

+26 0
+27 7
+29 24
+31 38
+40 80
+45 104
+50 124
+58 156
+61 171
+65 187
+67 194
+69 205
+71 223
+74 251
+76 274
+79 298
+81 324
+83 341
+83 358
+86 385
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+284 482
+280 413
+280 358
+281 309
+286 277
+288 238
+288 195
+285 165
+285 138
+285 111
+288 49
+291 20
+294 0

bob/bio/vein/tests/preprocessors/ConstructAnnotations.txt

+11 91
+8 322
+76 320
+114 307
+140 300
+176 292
+225 292
+269 288
+330 287
+405 288
+436 290
+456 288
+468 276
+473 242
+472 208
+470 184
+466 146
+455 116
+440 93
+424 77
+397 69
+358 64
+298 60
+247 52
+201 38
+160 25
+130 7
+106 7
+81 16
+46 46
+22 71

bob/bio/vein/tests/test.py

@@ -14,6 +14,7 @@ the generated sphinx documentation)
 
 import os
 import numpy
+import numpy as np
 import nose.tools
 
 import pkg_resources
@@ -186,3 +187,59 @@ def test_miura_match():
 
   score_imp = MM.score(template_vein, probe_imp_vein)
   assert numpy.isclose(score_imp, 0.172906739278421)
+  
+def test_manualRoiCut():
+    from bob.bio.vein.preprocessors.utils.utils import ManualRoiCut
+    image_path      = F(('preprocessors', '0019_3_1_120509-160517.png'))
+    annotation_path  = F(('preprocessors', '0019_3_1_120509-160517.txt'))
+
+    c = ManualRoiCut(annotation_path, image_path)
+    mask_1 = c.roi_mask()
+    image_1 = c.roi_image()
+    # create mask using size:
+    c = ManualRoiCut(annotation_path, sizes=(672,380))
+    mask_2 = c.roi_mask()
+    
+    # loading image:
+    image = bob.io.base.load(image_path)
+    c = ManualRoiCut(annotation_path, image)
+    mask_3 = c.roi_mask()
+    image_3 = c.roi_image()
+    # load text file:
+    with open(annotation_path,'r') as f:
+        retval = numpy.loadtxt(f, ndmin=2)
+        
+    # carefully -- this is BOB format --- (x,y)
+    annotation = list([tuple([k[0], k[1]]) for k in retval])
+    c = ManualRoiCut(annotation, image)
+    mask_4 = c.roi_mask()
+    image_4 = c.roi_image()
+    
+    assert (mask_1 == mask_2).all()
+    assert (mask_1 == mask_3).all()
+    assert (mask_1 == mask_4).all()
+    assert (image_1 == image_3).all()
+    assert (image_1 == image_4).all()
+    
+def test_ConstructAnnotations():
+  """
+  Test ConstructAnnotations preprocessor
+  """
+  image_filename = "/idiap/home/teglitis/Desktop/REFACTOR_ALL/src/bob.bio.vein/bob/bio/vein/tests/preprocessors/ConstructAnnotations.png"
+  roi_annotations_filename = "/idiap/home/teglitis/Desktop/REFACTOR_ALL/src/bob.bio.vein/bob/bio/vein/tests/preprocessors/ConstructAnnotations.txt"
+  vein_annotations_filename = "/idiap/home/teglitis/Desktop/REFACTOR_ALL/src/bob.bio.vein/bob/bio/vein/tests/preprocessors/ConstructAnnotations.npy"
+  
+  image = bob.io.base.load( image_filename )
+  roi_annotations = np.loadtxt(roi_annotations_filename, dtype='uint16')
+  roi_annotations =  [tuple([point[0], point[1]]) for point in roi_annotations]
+  fp = open(vein_annotations_filename, 'rt')
+  vein_annotations = np.load(fp)
+  vein_annotations = vein_annotations['arr_0'].tolist()
+  fp.close()
+  vein_annotations = [[tuple([point[0], point[1]]) for point in line] for line in vein_annotations]
+  
+  annotation_dictionary = {"image" : image, "roi_annotations" : roi_annotations, "vein_annotations" : vein_annotations}
+  from bob.bio.vein.preprocessors import ConstructAnnotations
+  preprocessor = ConstructAnnotations(center = True, rotate = True)
+  output = preprocessor(annotation_dictionary)
+  assert np.array_equal(output, image)

doc/api.rst

@@ -24,6 +24,11 @@ Pre-processors
 .. automodule:: bob.bio.vein.preprocessor
 
 
+Pre-processor utilities
+-----------------------
+
+.. automodule:: bob.bio.vein.preprocessor.utils
+
 Feature Extractors
 ------------------