NF: Initial commit of greylevel co-occurance (pure python)

2026-09-10 12:35:06 +08:00 · 2011-11-21 09:51:20 +00:00
parent 4fbdeb4b41
commit 4fe7965f69
3 changed files with 204 additions and 1 deletions
@@ -0,0 +1,90 @@
+import numpy as np
+from skimage.feature import glcm
+
+class TestGLCM():
+    def test_output_angles(self):
+        image = np.array([[0, 0, 1, 1],
+                          [0, 0, 1, 1],
+                          [0, 2, 2, 2],
+                          [2, 2, 3, 3]], dtype=np.uint8)        
+        result = glcm(image, [1], [0, np.pi/2], 4)
+        assert result.shape == (4, 4, 1, 2)
+        expected1 = np.array([[2, 2, 1, 0],
+                             [0, 2, 0, 0],
+                             [0, 0, 3, 1],
+                             [0, 0, 0, 1]], dtype=np.uint32)
+        np.testing.assert_array_equal(result[:, :, 0, 0], expected1)
+        expected2 = np.array([[3, 0, 2, 0],
+                             [0, 2, 2, 0],
+                             [0, 0, 1, 2],
+                             [0, 0, 0, 0]], dtype=np.uint32)
+        np.testing.assert_array_equal(result[:, :, 0, 1], expected2)        
+    
+    def test_output_symmetric_1(self):
+        image = np.array([[0, 0, 1, 1],
+                          [0, 0, 1, 1],
+                          [0, 2, 2, 2],
+                          [2, 2, 3, 3]], dtype=np.uint8)        
+        result = glcm(image, [1], [np.pi/2], 4, symmetric=True)
+        assert result.shape == (4, 4, 1, 1)
+        expected = np.array([[6, 0, 2, 0],
+                             [0, 4, 2, 0],
+                             [2, 2, 2, 2],
+                             [0, 0, 2, 0]], dtype=np.uint32)
+        np.testing.assert_array_equal(result[:, :, 0, 0], expected)    
+
+    def test_result_symmetric_2(self):
+        image = np.array([[0, 0, 1, 1],
+                          [0, 0, 1, 1],
+                          [0, 2, 2, 2],
+                          [2, 2, 3, 3]], dtype=np.uint8)        
+        result = glcm(image, [1], [0], 4, symmetric=True)[:, :, 0, 0]
+        np.testing.assert_array_equal(result, result.transpose())
+
+    def test_output_distance(self):
+        image = np.array([[0, 0, 0, 0],
+                          [1, 0, 0, 1],
+                          [2, 0, 0, 2],
+                          [3, 0, 0, 3]], dtype=np.uint8)        
+        result = glcm(image, [3], [0], 4, symmetric=False)
+        expected = np.array([[1, 0, 0, 0],
+                             [0, 1, 0, 0],
+                             [0, 0, 1, 0],
+                             [0, 0, 0, 1]], dtype=np.uint32)
+        np.testing.assert_array_equal(result[:, :, 0, 0], expected)           
+
+    def test_output_combo(self):
+        image = np.array([[0],
+                          [1],
+                          [2],
+                          [3]], dtype=np.uint8)
+        result = glcm(image, [1, 2], [0, np.pi/2], 4)
+        assert result.shape == (4, 4, 2, 2)
+        
+        z = np.zeros((4, 4), dtype=np.uint32)
+        e1 = np.array([[0, 1, 0, 0],
+                       [0, 0, 1, 0],
+                       [0, 0, 0, 1],
+                       [0, 0, 0, 0]], dtype=np.uint32)
+        e2 = np.array([[0, 0, 1, 0],
+                       [0, 0, 0, 1],
+                       [0, 0, 0, 0],
+                       [0, 0, 0, 0]], dtype=np.uint32)
+        
+        np.testing.assert_array_equal(result[:, :, 0, 0], z)
+        np.testing.assert_array_equal(result[:, :, 1, 0], z)
+        np.testing.assert_array_equal(result[:, :, 0, 1], e1)
+        np.testing.assert_array_equal(result[:, :, 1, 1], e2)
+
+    def test_normed(self):
+        image = np.array([[0, 0, 1, 1],
+                          [0, 0, 1, 1],
+                          [0, 2, 2, 2],
+                          [2, 2, 3, 3]], dtype=np.uint8)        
+        result = glcm(image, [1], [0], 4, normal=True)
+        np.testing.assert_almost_equal(result.sum(), 1.0)
+    
+    
+if __name__ == '__main__':
+    np.testing.run_module_suite()
+