Merge branch 'Project-MONAI:dev' into 4980-get-wsi-at-mpp

Project-MONAI · Sep 21, 2024 · 6094ffd · 6094ffd
2 parents a8bb436 + fa1c1af
commit 6094ffd
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Showing 5 changed files with 40 additions and 5 deletions.
diff --git a/monai/data/image_reader.py b/monai/data/image_reader.py
@@ -1359,7 +1359,7 @@ def _get_affine(self, header: dict) -> np.ndarray:
         x, y = direction.shape
         affine_diam = min(x, y) + 1
         affine: np.ndarray = np.eye(affine_diam)
-        affine[:x, :y] = direction
+        affine[:x, :y] = direction.T
         affine[: (affine_diam - 1), -1] = origin  # len origin is always affine_diam - 1
         return affine
 

diff --git a/monai/transforms/utils.py b/monai/transforms/utils.py
@@ -582,7 +582,8 @@ def weighted_patch_samples(
     if not v[-1] or not isfinite(v[-1]) or v[-1] < 0:  # uniform sampling
         idx = r_state.randint(0, len(v), size=n_samples)
     else:
-        r, *_ = convert_to_dst_type(r_state.random(n_samples), v)
+        r_samples = r_state.random(n_samples)
+        r, *_ = convert_to_dst_type(r_samples, v, dtype=r_samples.dtype)
         idx = searchsorted(v, r * v[-1], right=True)  # type: ignore
     idx, *_ = convert_to_dst_type(idx, v, dtype=torch.int)  # type: ignore
     # compensate 'valid' mode

diff --git a/tests/test_bundle_download.py b/tests/test_bundle_download.py
@@ -89,7 +89,7 @@
 TEST_CASE_10 = [
     ["network.json", "test_output.pt", "test_input.pt", "large_files.yaml"],
     "test_bundle",
-    "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/test_bundle_v0.1.2.zip",
+    "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/test_bundle_v0.1.3.zip",
     {"model.pt": "27952767e2e154e3b0ee65defc5aed38", "model.ts": "97746870fe591f69ac09827175b00675"},
 ]
 

diff --git a/tests/test_nrrd_reader.py b/tests/test_nrrd_reader.py
@@ -40,8 +40,8 @@
         "dimension": 4,
         "space": "left-posterior-superior",
         "sizes": [3, 4, 4, 1],
-        "space directions": [[0.0, 0.0, 0.0], [1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]],
-        "space origin": [0.0, 0.0, 0.0],
+        "space directions": [[0.7, 0.0, 0.0], [0.0, 0.0, -0.8], [0.0, 0.9, 0.0]],
+        "space origin": [1.0, 5.0, 20.0],
     },
 ]
 
@@ -110,6 +110,10 @@ def test_read_with_header(self, data_shape, filename, expected_shape, dtype, ref
         np.testing.assert_allclose(image_array, test_image)
         self.assertIsInstance(image_header, dict)
         self.assertTupleEqual(tuple(image_header["spatial_shape"]), expected_shape)
+        np.testing.assert_allclose(
+            image_header["affine"],
+            np.array([[-0.7, 0.0, 0.0, -1.0], [0.0, 0.0, -0.9, -5.0], [0.0, -0.8, 0.0, 20.0], [0.0, 0.0, 0.0, 1.0]]),
+        )
 
     @parameterized.expand([TEST_CASE_8])
     def test_read_with_header_index_order_c(self, data_shape, filename, expected_shape, dtype, reference_header):

diff --git a/tests/test_rand_weighted_crop.py b/tests/test_rand_weighted_crop.py
@@ -90,6 +90,21 @@ def get_data(ndim):
                 [[63, 37], [31, 43], [66, 20]],
             ]
         )
+        im = SEG1_2D
+        weight_map = np.zeros_like(im, dtype=np.int32)
+        weight_map[0, 30, 20] = 3
+        weight_map[0, 45, 44] = 1
+        weight_map[0, 60, 50] = 2
+        TESTS.append(
+            [
+                "int w 2d",
+                dict(spatial_size=(10, 12), num_samples=3),
+                p(im),
+                q(weight_map),
+                (1, 10, 12),
+                [[60, 50], [30, 20], [45, 44]],
+            ]
+        )
         im = SEG1_3D
         weight = np.zeros_like(im)
         weight[0, 5, 30, 17] = 1.1
@@ -149,6 +164,21 @@ def get_data(ndim):
                 [[32, 24, 40], [32, 24, 40], [32, 24, 40]],
             ]
         )
+        im = SEG1_3D
+        weight_map = np.zeros_like(im, dtype=np.int32)
+        weight_map[0, 6, 22, 19] = 4
+        weight_map[0, 8, 40, 31] = 2
+        weight_map[0, 13, 20, 24] = 3
+        TESTS.append(
+            [
+                "int w 3d",
+                dict(spatial_size=(8, 10, 12), num_samples=3),
+                p(im),
+                q(weight_map),
+                (1, 8, 10, 12),
+                [[13, 20, 24], [6, 22, 19], [8, 40, 31]],
+            ]
+        )
 
 
 class TestRandWeightedCrop(CropTest):