Add tests for foreground preservation and refactor geometry node asset

- Implement test to ensure foreground preserves source RGB and Ben2 alpha in WorkerTest.
- Remove outdated tests related to background distance and original background depth.
- Update geometry node asset to reflect new naming conventions and structure.
- Introduce validation for depth plane asset, ensuring correct input/output configurations and attribute handling.
- Adjust confidence and edge parameters in geometry node asset to support a wider range of values.

tests/test_worker.py

@@ -30,6 +30,25 @@ class WorkerTest(unittest.TestCase):
     def setUpClass(cls):
         cls.worker = load_worker()
 
+    def test_foreground_preserves_source_rgb_and_ben2_alpha(self):
+        alpha = SimpleNamespace(size=(2, 1))
+        source_rgba = SimpleNamespace(size=(2, 1), applied_alpha=None)
+        source_rgba.putalpha = lambda value: setattr(
+            source_rgba,
+            "applied_alpha",
+            value,
+        )
+        source = SimpleNamespace(convert=lambda _mode: source_rgba)
+        foreground_rgba = SimpleNamespace(
+            getchannel=lambda _name: alpha,
+        )
+        foreground = SimpleNamespace(convert=lambda _mode: foreground_rgba)
+
+        result = self.worker.preserve_source_rgb(source, foreground)
+
+        self.assertIs(result, source_rgba)
+        self.assertIs(result.applied_alpha, alpha)
+
     def test_collect_images_is_sorted_and_filters_suffixes(self):
         with tempfile.TemporaryDirectory() as directory:
             root = Path(directory)
@@ -138,49 +157,6 @@ class WorkerTest(unittest.TestCase):
         )
         self.assertEqual(args.remove_background_model_dir, "ben2")
 
-    def test_background_distance_sets_fixed_background_depth(self):
-        prediction = SimpleNamespace(
-            depth=np.array(
-                [[
-                    [1.0, 2.0, 3.0, 4.0],
-                    [5.0, -9.0, -2.0, 8.0],
-                    [9.0, -3.0, 4.0, 12.0],
-                    [13.0, 14.0, 15.0, 16.0],
-                ]]
-            ),
-            conf=np.arange(16, dtype=np.float32).reshape(1, 4, 4),
-        )
-        foreground_mask = np.array(
-            [[
-                [True, True, True, True],
-                [True, True, False, True],
-                [True, True, True, True],
-                [True, True, True, True],
-            ]],
-            dtype=bool,
-        )
-        original_confidence = prediction.conf.copy()
-
-        self.worker.apply_depth_background_array(
-            prediction,
-            foreground_mask,
-            8.0,
-        )
-
-        np.testing.assert_array_equal(
-            prediction.depth,
-            [[
-                [-8.0, -8.0, -8.0, -8.0],
-                [-8.0, -8.0, -8.0, -8.0],
-                [-8.0, -3.0, 4.0, -8.0],
-                [-8.0, -8.0, -8.0, -8.0],
-            ]],
-        )
-        np.testing.assert_array_equal(
-            prediction.conf,
-            original_confidence,
-        )
-
     def test_ai_depth_is_converted_for_positive_displacement(self):
         prediction = SimpleNamespace(
             depth=np.array([[[0.25, 1.0], [1.5, 2.0]]]),
@@ -215,26 +191,6 @@ class WorkerTest(unittest.TestCase):
                     1.5,
                 )
 
-    def test_original_background_uses_fixed_negative_depth(self):
-        luminance = np.full((3, 3), 0.5, dtype=np.float32)
-        alpha = np.full((3, 3), 255, dtype=np.uint8)
-        alpha[1, 0] = 0
-
-        depth = self.worker.compose_original_background_depth(
-            luminance,
-            alpha,
-            3.0,
-        )
-
-        np.testing.assert_allclose(
-            depth,
-            [
-                [-3.0, -3.0, -3.0],
-                [-3.0, 0.5, -3.0],
-                [-3.0, -3.0, -3.0],
-            ],
-        )
-
     def test_prepares_a_single_image_file(self):
         with tempfile.TemporaryDirectory() as directory:
             image_path = Path(directory) / "input.png"
@@ -646,6 +602,8 @@ class WorkerTest(unittest.TestCase):
         save_options = []
 
         class FakeImage:
+            size = (1, 1)
+
             def __enter__(self):
                 return self
 
@@ -656,6 +614,12 @@ class WorkerTest(unittest.TestCase):
                 self.mode = mode
                 return self
 
+            def getchannel(self, _name):
+                return self
+
+            def putalpha(self, _alpha):
+                return None
+
             def save(self, path, **options):
                 save_options.append(options)
                 Path(path).touch()
@@ -726,6 +690,8 @@ class WorkerTest(unittest.TestCase):
         inference_options = []
 
         class FakeImage:
+            size = (1, 1)
+
             def __enter__(self):
                 return self
 
@@ -736,6 +702,12 @@ class WorkerTest(unittest.TestCase):
                 self.mode = mode
                 return self
 
+            def getchannel(self, _name):
+                return self
+
+            def putalpha(self, _alpha):
+                return None
+
             def save(self, path, **options):
                 Path(path).touch()