def test_05_02_otsu_entropy(self):
     '''Test the entropy version of Otsu'''
     np.random.seed(0)
     image = np.hstack((np.random.exponential(1.5, size=600),
                        np.random.poisson(15, size=300)))
     image.shape = (30, 30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     threshold = entropy(limage)
     threshold = T.inverse_log_transform(threshold, d)
     expected = image > threshold
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_scope.value = I.TS_GLOBAL
     module.threshold_method.value = T.TM_OTSU
     module.use_weighted_variance.value = I.O_ENTROPY
     module.two_class_otsu.value = I.O_TWO_CLASS
     module.run(workspace)
     output = workspace.image_set.get_image(OUTPUT_IMAGE_NAME)
     self.assertTrue(np.all(output.pixel_data == expected))
 def test_05_02_otsu_entropy(self):
     '''Test the entropy version of Otsu'''
     np.random.seed(0)
     image = np.hstack((np.random.exponential(1.5,size=600),
                        np.random.poisson(15,size=300)))
     image.shape=(30,30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     threshold = entropy(limage)
     threshold = T.inverse_log_transform(threshold, d)
     expected = image > threshold
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_scope.value = I.TS_GLOBAL
     module.threshold_method.value = T.TM_OTSU
     module.use_weighted_variance.value = I.O_ENTROPY
     module.two_class_otsu.value = I.O_TWO_CLASS
     module.run(workspace)
     output = workspace.image_set.get_image(OUTPUT_IMAGE_NAME)
     self.assertTrue(np.all(output.pixel_data == expected))
 def test_05_06_otsu3_entropy_high(self):
     '''Test the three-class otsu, entropy, middle = background'''
     np.random.seed(0)
     image = np.hstack((np.random.exponential(1.5, size=300),
                        np.random.poisson(15, size=300),
                        np.random.poisson(30, size=300)))
     image.shape = (30, 30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     t1, t2 = entropy3(limage)
     threshold = T.inverse_log_transform(t1, d)
     expected = image > threshold
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_scope.value = I.TS_GLOBAL
     module.threshold_method.value = T.TM_OTSU
     module.use_weighted_variance.value = I.O_ENTROPY
     module.two_class_otsu.value = I.O_THREE_CLASS
     module.assign_middle_to_foreground.value = I.O_FOREGROUND
     module.run(workspace)
     output = workspace.image_set.get_image(OUTPUT_IMAGE_NAME)
     self.assertTrue(np.all(output.pixel_data == expected))
 def test_05_04_otsu3_wv_high(self):
     '''Test the three-class otsu, weighted variance middle = foreground'''
     np.random.seed(0)
     image = np.hstack((np.random.exponential(1.5, size=300),
                        np.random.poisson(15, size=300),
                        np.random.poisson(30, size=300)))
     image.shape = (30, 30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     t1, t2 = otsu3(limage)
     threshold = T.inverse_log_transform(t1, d)
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_scope.value = I.TS_GLOBAL
     module.threshold_method.value = T.TM_OTSU
     module.use_weighted_variance.value = I.O_WEIGHTED_VARIANCE
     module.two_class_otsu.value = I.O_THREE_CLASS
     module.assign_middle_to_foreground.value = I.O_FOREGROUND
     module.run(workspace)
     m = workspace.measurements
     m_threshold = m[cpmeas.IMAGE, I.FF_ORIG_THRESHOLD % module.get_measurement_objects_name()]
     self.assertAlmostEqual(m_threshold, threshold)
示例#5
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 def test_05_06_otsu3_entropy_high(self):
     '''Test the three-class otsu, entropy, middle = background'''
     np.random.seed(0)
     image = np.hstack(
         (np.random.exponential(1.5, size=300),
          np.random.poisson(15, size=300), np.random.poisson(30, size=300)))
     image.shape = (30, 30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     t1, t2 = entropy3(limage)
     threshold = T.inverse_log_transform(t1, d)
     expected = image > threshold
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_scope.value = I.TS_GLOBAL
     module.threshold_method.value = T.TM_OTSU
     module.use_weighted_variance.value = I.O_ENTROPY
     module.two_class_otsu.value = I.O_THREE_CLASS
     module.assign_middle_to_foreground.value = I.O_FOREGROUND
     module.run(workspace)
     output = workspace.image_set.get_image(OUTPUT_IMAGE_NAME)
     self.assertTrue(np.all(output.pixel_data == expected))
 def test_05_04_otsu3_wv_high(self):
     '''Test the three-class otsu, weighted variance middle = foreground'''
     np.random.seed(0)
     image = np.hstack((np.random.exponential(1.5,size=300),
                        np.random.poisson(15,size=300),
                        np.random.poisson(30,size=300)))
     image.shape=(30,30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     t1,t2 = otsu3(limage)
     threshold = T.inverse_log_transform(t1, d)
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_scope.value = I.TS_GLOBAL
     module.threshold_method.value = T.TM_OTSU
     module.use_weighted_variance.value = I.O_WEIGHTED_VARIANCE
     module.two_class_otsu.value = I.O_THREE_CLASS
     module.assign_middle_to_foreground.value = I.O_FOREGROUND
     module.run(workspace)
     m = workspace.measurements
     m_threshold = m[cpmeas.IMAGE, I.FF_ORIG_THRESHOLD % module.get_measurement_objects_name()]
     self.assertAlmostEqual(m_threshold, threshold)
 def test_05_05_otsu3_entropy_low(self):
     '''Test the three-class otsu, entropy, middle = background'''
     np.random.seed(0)
     image = np.hstack((np.random.exponential(1.5, size=300),
                        np.random.poisson(15, size=300),
                        np.random.poisson(30, size=300)))
     image.shape = (30, 30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     t1, t2 = entropy3(limage)
     threshold = T.inverse_log_transform(t2, d)
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_scope.value = I.TS_GLOBAL
     module.threshold_method.value = T.TM_OTSU
     module.use_weighted_variance.value = I.O_ENTROPY
     module.two_class_otsu.value = I.O_THREE_CLASS
     module.assign_middle_to_foreground.value = I.O_BACKGROUND
     module.run(workspace)
     output = workspace.image_set.get_image(OUTPUT_IMAGE_NAME)
     m = workspace.measurements
     m_threshold = m[cpmeas.IMAGE, I.FF_ORIG_THRESHOLD % module.get_measurement_objects_name()]
     self.assertAlmostEqual(m_threshold, threshold)
 def test_05_05_otsu3_entropy_low(self):
     '''Test the three-class otsu, entropy, middle = background'''
     np.random.seed(0)
     image = np.hstack((np.random.exponential(1.5,size=300),
                        np.random.poisson(15,size=300),
                        np.random.poisson(30,size=300)))
     image.shape=(30,30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     t1,t2 = entropy3(limage)
     threshold = T.inverse_log_transform(t2, d)
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_scope.value = I.TS_GLOBAL
     module.threshold_method.value = T.TM_OTSU
     module.use_weighted_variance.value = I.O_ENTROPY
     module.two_class_otsu.value = I.O_THREE_CLASS
     module.assign_middle_to_foreground.value = I.O_BACKGROUND
     module.run(workspace)
     output = workspace.image_set.get_image(OUTPUT_IMAGE_NAME)
     m = workspace.measurements
     m_threshold = m[cpmeas.IMAGE, I.FF_ORIG_THRESHOLD % module.get_measurement_objects_name()]
     self.assertAlmostEqual(m_threshold, threshold)