修正 mini_npz 深度数据职责

src/snapform/image_depth.py

@@ -9,7 +9,6 @@ DEPTH_KEY_CANDIDATES = ("depth", "depths")
 INTRINSICS_KEY_CANDIDATES = ("intrinsics", "ixts")
 DISPLACEMENT_STRENGTH = 1.0
 DISPLACEMENT_MIDLEVEL = 0.0
-REFERENCE_DEPTH_KEY = "snapform_reference_depth"
 ORIGINAL_DISPLACEMENT_STRENGTH = 1.0
 ORIGINAL_DISPLACEMENT_MIDLEVEL = 0.0
 BUMP_BASE_DISTANCE = 0.001
@@ -695,25 +694,6 @@ def extract_intrinsics_array(npz_path):
     return intrinsics
 
 
-def extract_reference_depth(npz_path):
-    try:
-        import numpy as np
-    except ImportError as error:
-        raise RuntimeError("Blender Python does not provide NumPy") from error
-
-    try:
-        with np.load(npz_path, allow_pickle=False) as archive:
-            if REFERENCE_DEPTH_KEY not in archive.files:
-                return None
-            reference_depth = float(archive[REFERENCE_DEPTH_KEY])
-    except OSError as error:
-        raise ValueError(f"Unable to read Mini NPZ: {npz_path}") from error
-
-    if not np.isfinite(reference_depth) or reference_depth <= 0.0:
-        raise ValueError("Mini NPZ has an invalid reference depth")
-    return reference_depth
-
-
 def prepare_depth_values(depth):
     import numpy as np
 
@@ -725,6 +705,13 @@ def prepare_depth_values(depth):
     return values
 
 
+def depth_displacement_values(depth):
+    """Convert raw DA3 camera distance to positive outward displacement."""
+    import numpy as np
+
+    return 1.0 - np.asarray(depth, dtype=np.float32)
+
+
 def camera_plane_bounds(
     source_object,
     depth,
@@ -1407,18 +1394,19 @@ def build_depth_plane(
     depth_frames_directory=None,
 ):
     source_name = source_object.name
-    depth_arrays = extract_depth_arrays(npz_path)
+    raw_depth_arrays = extract_depth_arrays(npz_path)
-    depth = depth_arrays[0]
+    raw_depth = raw_depth_arrays[0]
     intrinsics = extract_intrinsics_array(npz_path)
-    stored_reference_depth = extract_reference_depth(npz_path)
+    raw_depth_values = prepare_depth_values(raw_depth)
-    depth_values = prepare_depth_values(depth)
     bounds, reference_depth = camera_plane_bounds(
         source_object,
-        depth_values,
+        raw_depth_values,
         intrinsics,
         DISPLACEMENT_STRENGTH,
-        reference_depth=stored_reference_depth,
     )
+    depth_arrays = [
+        depth_displacement_values(frame) for frame in raw_depth_arrays
+    ]
     depth_name = depth_name or depth_data_name(source_object)
     frame_count = len(depth_arrays)
     foreground_image = (

src/snapform/worker.py

@@ -36,7 +36,6 @@ HF_ENDPOINT = "https://huggingface.co"
 MODELSCOPE_ENDPOINT = "https://modelscope.cn"
 MODELSCOPE_REVISION = "master"
 MODELSCOPE_TIMEOUT = 60.0
-REFERENCE_DEPTH_KEY = "snapform_reference_depth"
 
 
 class TaskCancelled(RuntimeError):
@@ -48,37 +47,6 @@ def check_cancelled(cancel_check):
         raise TaskCancelled("Task cancelled")
 
 
-def convert_ai_depth_for_displacement(prediction):
-    """Convert DA3 distance into Blender's positive displacement direction."""
-    import numpy as np
-
-    prediction.depth = 1.0 - np.asarray(prediction.depth)
-
-
-def depth_reference_value(depth):
-    """Return the unmasked depth used to size the imported camera plane."""
-    import numpy as np
-
-    values = np.asarray(depth)
-    valid = np.isfinite(values) & (values > 0.0)
-    if not valid.any():
-        raise ValueError("Depth array contains no positive finite values")
-    return float(np.median(values[valid]))
-
-
-def write_npz_reference_depth(npz_path, reference_depth):
-    """Add SnapForm metadata without changing exported prediction arrays."""
-    import numpy as np
-
-    npz_path = Path(npz_path)
-    temporary_path = npz_path.with_name(f"{npz_path.stem}.tmp.npz")
-    with np.load(npz_path, allow_pickle=False) as archive:
-        values = {key: archive[key] for key in archive.files}
-    values[REFERENCE_DEPTH_KEY] = np.asarray(reference_depth, dtype=np.float32)
-    np.savez_compressed(temporary_path, **values)
-    temporary_path.replace(npz_path)
-
-
 def write_status(
     path,
     progress,
@@ -1640,10 +1608,6 @@ def reconstruct(args, model_cache=None, cancel_check=None):
                 ref_view_strategy=args.ref_view_strategy,
             )
         check_cancelled(cancel_check)
-        reference_depth = None
-        if args.export_format == "mini_npz":
-            reference_depth = depth_reference_value(prediction.depth[0])
-            convert_ai_depth_for_displacement(prediction)
         write_status(args.status, 0.88, f"Exporting {args.export_format}")
         if args.export_format == "mesh":
             export_textured_mesh_glb(
@@ -1701,10 +1665,6 @@ def reconstruct(args, model_cache=None, cancel_check=None):
             result_paths,
             cancel_check=cancel_check,
         )
-        if args.export_format == "mini_npz":
-            result_path = output_directory / "results.npz"
-            if reference_depth is not None:
-                write_npz_reference_depth(result_path, reference_depth)
         check_cancelled(cancel_check)
         copy_frames(images, output_directory)
         write_status(

tests/test_image_depth.py

@@ -87,21 +87,6 @@ class ImageDepthTest(unittest.TestCase):
 
         self.assertEqual(depth.shape, (2, 3))
 
-    def test_extracts_optional_reference_depth(self):
-        with tempfile.TemporaryDirectory() as directory:
-            npz_path = Path(directory) / "results.npz"
-            np.savez_compressed(
-                npz_path,
-                depth=np.ones((1, 2, 2), dtype=np.float32),
-                snapform_reference_depth=np.float32(2.5),
-            )
-
-            reference_depth = self.image_depth.extract_reference_depth(
-                npz_path
-            )
-
-        self.assertEqual(reference_depth, 2.5)
-
     def test_is_animated_image_accepts_movie_and_sequence(self):
         self.assertTrue(
             self.image_depth.is_animated_image(
@@ -384,6 +369,23 @@ class ImageDepthTest(unittest.TestCase):
 
         self.assertEqual(depth.shape, (2, 3))
 
+    def test_raw_da3_depth_is_converted_only_for_displacement(self):
+        raw_depth = np.array(
+            ((0.25, 1.0), (1.5, 2.0)),
+            dtype=np.float32,
+        )
+
+        displacement = self.image_depth.depth_displacement_values(raw_depth)
+
+        np.testing.assert_array_equal(
+            displacement,
+            np.array(((0.75, 0.0), (-0.5, -1.0)), dtype=np.float32),
+        )
+        np.testing.assert_array_equal(
+            raw_depth,
+            np.array(((0.25, 1.0), (1.5, 2.0)), dtype=np.float32),
+        )
+
     def test_extracts_camera_intrinsics(self):
         expected = np.array(
             ((100.0, 0.0, 50.0), (0.0, 120.0, 40.0), (0.0, 0.0, 1.0)),

tests/test_worker.py

@@ -157,40 +157,6 @@ class WorkerTest(unittest.TestCase):
         )
         self.assertEqual(args.remove_background_model_dir, "ben2")
 
-    def test_ai_depth_is_converted_for_positive_displacement(self):
-        prediction = SimpleNamespace(
-            depth=np.array([[[0.25, 1.0], [1.5, 2.0]]]),
-            conf=np.array([[[0.1, 0.2], [0.3, 0.4]]]),
-        )
-
-        self.worker.convert_ai_depth_for_displacement(prediction)
-
-        np.testing.assert_array_equal(
-            prediction.depth,
-            [[[0.75, 0.0], [-0.5, -1.0]]],
-        )
-        np.testing.assert_array_equal(
-            prediction.conf,
-            [[[0.1, 0.2], [0.3, 0.4]]],
-        )
-
-    def test_npz_reference_depth_preserves_prediction_arrays(self):
-        with tempfile.TemporaryDirectory() as directory:
-            npz_path = Path(directory) / "results.npz"
-            depth = np.array([[[1.0, 2.0]]], dtype=np.float32)
-            confidence = np.array([[[0.2, 0.8]]], dtype=np.float32)
-            np.savez_compressed(npz_path, depth=depth, conf=confidence)
-
-            self.worker.write_npz_reference_depth(npz_path, 1.5)
-
-            with np.load(npz_path, allow_pickle=False) as archive:
-                np.testing.assert_array_equal(archive["depth"], depth)
-                np.testing.assert_array_equal(archive["conf"], confidence)
-                self.assertEqual(
-                    float(archive[self.worker.REFERENCE_DEPTH_KEY]),
-                    1.5,
-                )
-
     def test_prepares_a_single_image_file(self):
         with tempfile.TemporaryDirectory() as directory:
             image_path = Path(directory) / "input.png"
@@ -1013,12 +979,9 @@ class WorkerTest(unittest.TestCase):
             _export_dir,
             options,
         ) in export_calls:
-            expected_depth = (
-                -1.0 if export_format == "mini_npz" else 2.0
-            )
             np.testing.assert_array_equal(
                 _prediction.depth,
-                np.full((1, 2, 2), expected_depth, dtype=np.float32),
+                np.full((1, 2, 2), 2.0, dtype=np.float32),
             )
             if export_format == "glb":
                 self.assertEqual(