def test_3d(self): """tests the detection of maxima in 3D.""" img = np.zeros((8, 8, 8), dtype=np.uint8) local_maxima = np.zeros((8, 8, 8), dtype=np.uint64) # first maximum: only one pixel img[1, 1:3, 1:3] = 100 img[2, 2, 2] = 200 img[3, 1:3, 1:3] = 100 local_maxima[2, 2, 2] = 1 # second maximum: three pixels in z-direction img[5:8, 1, 1] = 200 local_maxima[5:8, 1, 1] = 1 # third: two maxima in 0 and 3. img[0, 5:8, 5:8] = 200 img[1, 6, 6] = 100 img[2, 5:7, 5:7] = 200 img[0:3, 5:8, 5:8] += 50 local_maxima[0, 5:8, 5:8] = 1 local_maxima[2, 5:7, 5:7] = 1 # four : one maximum in the corner of the square img[6:8, 6:8, 6:8] = 200 img[7, 7, 7] = 255 local_maxima[7, 7, 7] = 1 out = max_tree_local_maxima(img) out_bin = out > 0 assert_array_equal(local_maxima, out_bin) assert np.max(out) == 5
def test_3d(self): """tests the detection of maxima in 3D.""" img = np.zeros((8, 8, 8), dtype=np.uint8) local_maxima = np.zeros((8, 8, 8), dtype=np.uint64) # first maximum: only one pixel img[1, 1:3, 1:3] = 100 img[2, 2, 2] = 200 img[3, 1:3, 1:3] = 100 local_maxima[2, 2, 2] = 1 # second maximum: three pixels in z-direction img[5:8, 1, 1] = 200 local_maxima[5:8, 1, 1] = 1 # third: two maxima in 0 and 3. img[0, 5:8, 5:8] = 200 img[1, 6, 6] = 100 img[2, 5:7, 5:7] = 200 img[0:3, 5:8, 5:8] += 50 local_maxima[0, 5:8, 5:8] = 1 local_maxima[2, 5:7, 5:7] = 1 # four : one maximum in the corner of the square img[6:8, 6:8, 6:8] = 200 img[7, 7, 7] = 255 local_maxima[7, 7, 7] = 1 out = max_tree_local_maxima(img) out_bin = out > 0 assert_array_equal(local_maxima, out_bin) assert np.max(out) == 5
def test_extrema_float(self): "specific tests for float type" data = np.array( [[0.10, 0.11, 0.13, 0.14, 0.14, 0.15, 0.14, 0.14, 0.13, 0.11], [0.11, 0.13, 0.15, 0.16, 0.16, 0.16, 0.16, 0.16, 0.15, 0.13], [0.13, 0.15, 0.40, 0.40, 0.18, 0.18, 0.18, 0.60, 0.60, 0.15], [0.14, 0.16, 0.40, 0.40, 0.19, 0.19, 0.19, 0.60, 0.60, 0.16], [0.14, 0.16, 0.18, 0.19, 0.19, 0.19, 0.19, 0.19, 0.18, 0.16], [0.15, 0.182, 0.18, 0.19, 0.204, 0.20, 0.19, 0.19, 0.18, 0.16], [0.14, 0.16, 0.18, 0.19, 0.19, 0.19, 0.19, 0.19, 0.18, 0.16], [0.14, 0.16, 0.80, 0.80, 0.19, 0.19, 0.19, 4.0, 1.0, 0.16], [0.13, 0.15, 0.80, 0.80, 0.18, 0.18, 0.18, 1.0, 1.0, 0.15], [0.11, 0.13, 0.15, 0.16, 0.16, 0.16, 0.16, 0.16, 0.15, 0.13]], dtype=np.float32) expected_result = np.array( [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 0, 0, 0, 1, 1, 0], [0, 0, 1, 1, 0, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 0, 0, 0, 1, 0, 0], [0, 0, 1, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.uint8) # test for local maxima out = max_tree_local_maxima(data, connectivity=1) out_bin = out > 0 assert_array_equal(expected_result, out_bin) assert np.max(out) == 6
def test_local_maxima(self): "local maxima for various data types" data = np.array([[10, 11, 13, 14, 14, 15, 14, 14, 13, 11], [11, 13, 15, 16, 16, 16, 16, 16, 15, 13], [13, 15, 40, 40, 18, 18, 18, 60, 60, 15], [14, 16, 40, 40, 19, 19, 19, 60, 60, 16], [14, 16, 18, 19, 19, 19, 19, 19, 18, 16], [15, 16, 18, 19, 19, 20, 19, 19, 18, 16], [14, 16, 18, 19, 19, 19, 19, 19, 18, 16], [14, 16, 80, 80, 19, 19, 19, 100, 100, 16], [13, 15, 80, 80, 18, 18, 18, 100, 100, 15], [11, 13, 15, 16, 16, 16, 16, 16, 15, 13]], dtype=np.uint8) expected_result = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 0, 0, 0, 1, 1, 0], [0, 0, 1, 1, 0, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 0, 0, 0, 1, 1, 0], [0, 0, 1, 1, 0, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.uint64) for dtype in [np.uint8, np.uint64, np.int8, np.int64]: test_data = data.astype(dtype) out = max_tree_local_maxima(test_data, connectivity=1) out_bin = out > 0 assert_array_equal(expected_result, out_bin) assert out.dtype == expected_result.dtype assert np.max(out) == 5 P, S = max_tree(test_data) out = max_tree_local_maxima(test_data, parent=P, tree_traverser=S) assert_array_equal(expected_result, out_bin) assert out.dtype == expected_result.dtype assert np.max(out) == 5
def test_local_maxima(self): "local maxima for various data types" data = np.array([[10, 11, 13, 14, 14, 15, 14, 14, 13, 11], [11, 13, 15, 16, 16, 16, 16, 16, 15, 13], [13, 15, 40, 40, 18, 18, 18, 60, 60, 15], [14, 16, 40, 40, 19, 19, 19, 60, 60, 16], [14, 16, 18, 19, 19, 19, 19, 19, 18, 16], [15, 16, 18, 19, 19, 20, 19, 19, 18, 16], [14, 16, 18, 19, 19, 19, 19, 19, 18, 16], [14, 16, 80, 80, 19, 19, 19, 100, 100, 16], [13, 15, 80, 80, 18, 18, 18, 100, 100, 15], [11, 13, 15, 16, 16, 16, 16, 16, 15, 13]], dtype=np.uint8) expected_result = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 0, 0, 0, 1, 1, 0], [0, 0, 1, 1, 0, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 0, 0, 0, 1, 1, 0], [0, 0, 1, 1, 0, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.uint64) for dtype in [np.uint8, np.uint64, np.int8, np.int64]: test_data = data.astype(dtype) out = max_tree_local_maxima(test_data, connectivity=1) out_bin = out > 0 assert_array_equal(expected_result, out_bin) assert out.dtype == expected_result.dtype assert np.max(out) == 5 P, S = max_tree(test_data) out = max_tree_local_maxima(test_data, parent=P, tree_traverser=S) assert_array_equal(expected_result, out_bin) assert out.dtype == expected_result.dtype assert np.max(out) == 5
def maksimum_tree(image): image = color.rgb2gray(image) max_tree = max_tree_local_maxima(image) fig, axes = plt.subplots(nrows=1, ncols=2,figsize=(8, 8)) ax = axes.ravel() ax[0].imshow(image, cmap='gray') ax[0].set_title("Original image") ax[1].imshow(max_tree, cmap='gray') ax[1].set_title("Max tree ") plt.tight_layout() plt.show()
def test_extrema_float(self): "specific tests for float type" data = np.array([[0.10, 0.11, 0.13, 0.14, 0.14, 0.15, 0.14, 0.14, 0.13, 0.11], [0.11, 0.13, 0.15, 0.16, 0.16, 0.16, 0.16, 0.16, 0.15, 0.13], [0.13, 0.15, 0.40, 0.40, 0.18, 0.18, 0.18, 0.60, 0.60, 0.15], [0.14, 0.16, 0.40, 0.40, 0.19, 0.19, 0.19, 0.60, 0.60, 0.16], [0.14, 0.16, 0.18, 0.19, 0.19, 0.19, 0.19, 0.19, 0.18, 0.16], [0.15, 0.182, 0.18, 0.19, 0.204, 0.20, 0.19, 0.19, 0.18, 0.16], [0.14, 0.16, 0.18, 0.19, 0.19, 0.19, 0.19, 0.19, 0.18, 0.16], [0.14, 0.16, 0.80, 0.80, 0.19, 0.19, 0.19, 4.0, 1.0, 0.16], [0.13, 0.15, 0.80, 0.80, 0.18, 0.18, 0.18, 1.0, 1.0, 0.15], [0.11, 0.13, 0.15, 0.16, 0.16, 0.16, 0.16, 0.16, 0.15, 0.13]], dtype=np.float32) expected_result = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 0, 0, 0, 1, 1, 0], [0, 0, 1, 1, 0, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 0, 0, 0, 1, 0, 0], [0, 0, 1, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.uint8) # test for local maxima out = max_tree_local_maxima(data, connectivity=1) out_bin = out > 0 assert_array_equal(expected_result, out_bin) assert np.max(out) == 6