cv2.remap cannot handle float16; ensure output of sampler matches input dtype.

py360convert/e2p.py

@@ -14,7 +14,7 @@
 
 def e2p(
     e_img: NDArray[DType],
-    fov_deg: Union[float, int, tuple[float | int, float | int]],
+    fov_deg: Union[float, int, tuple[Union[float, int], Union[float, int]]],
     u_deg: float,
     v_deg: float,
     out_hw: tuple[int, int],
@@ -65,7 +65,18 @@ def e2p(
     u = -float(np.deg2rad(u_deg))
     v = float(np.deg2rad(v_deg))
     in_rot = float(np.deg2rad(in_rot_deg))
-    sampler = EquirecSampler.from_perspective(h_fov, v_fov, u, v, in_rot, h, w, order)
+    sampler = EquirecSampler.from_perspective(
+        h_fov,
+        v_fov,
+        u,
+        v,
+        in_rot,
+        h,
+        w,
+        out_hw[0],
+        out_hw[0],
+        order,
+    )
     pers_img = np.stack([sampler(e_img[..., i]) for i in range(e_img.shape[2])], axis=-1)
 
     return pers_img[..., 0] if squeeze else pers_img

py360convert/utils.py

@@ -376,16 +376,29 @@ def __init__(
             self._order = order
 
     def __call__(self, img: NDArray[DType]) -> NDArray[DType]:
+        if img.dtype == np.float16:
+            source_dtype = np.float16
+        else:
+            source_dtype = None
+
+        if source_dtype:
+            img = img.astype(np.float32)  # pyright: ignore
+
         padded = self._pad(img)
         if self._use_cv2:
+            # cv2.remap can handle uint8, float32, float64
             out = cv2.remap(padded, self._coor_x, self._coor_y, interpolation=self._order)  # pyright: ignore
         else:
+            # map_coordinates can handle uint8, float32, float64
             out = map_coordinates(
                 padded,
                 (self._coor_y, self._coor_x),
                 order=self._order,
             )[..., 0]
 
+        if source_dtype:
+            out = out.astype(source_dtype)
+
         return out  # pyright: ignore[reportReturnType]
 
     def _pad(self, img: NDArray[DType]) -> NDArray[DType]:
@@ -419,7 +432,9 @@ def from_cubemap(cls, face_w: int, h: int, w: int, order: int):
 
     @classmethod
     @lru_cache(_CACHE_SIZE)
-    def from_perspective(cls, h_fov: float, v_fov: float, u, v, in_rot: float, h: int, w: int, order: int):
+    def from_perspective(
+        cls, h_fov: float, v_fov: float, u, v, in_rot: float, in_h: int, in_w: int, out_h, out_w, order: int
+    ):
         """Construct a EquirecSampler from perspective specs.
 
         Parameters
@@ -434,16 +449,20 @@ def from_perspective(cls, h_fov: float, v_fov: float, u, v, in_rot: float, h: in
             Vertical viewing angle in radians
         in_rot: float
             Inplane rotation in radians.
-        h: int
+        in_h: int
             Height of input equirec image.
-        w: int
+        in_w: int
             Width of input equirec image.
+        out_h: int
+            Height of output perspective image.
+        out_w: int
+            Width of output perspective image.
         order: int
             The order of the spline interpolation. See ``scipy.ndimage.map_coordinates``.
         """
-        xyz = xyzpers(h_fov, v_fov, u, v, (h, w), in_rot)
+        xyz = xyzpers(h_fov, v_fov, u, v, (out_h, out_w), in_rot)
         u, v = xyz2uv(xyz)
-        coor_x, coor_y = uv2coor(u, v, h, w)
+        coor_x, coor_y = uv2coor(u, v, in_h, in_w)
         return cls(coor_x, coor_y, order=order)
 
 
@@ -530,13 +549,28 @@ def __call__(self, cube_faces: NDArray[DType]) -> NDArray[DType]:
         if w != self._w:
             raise ValueError("Input width {w} doesn't match expected height {self._w}.")
 
+        if cube_faces.dtype == np.float16:
+            source_dtype = np.float16
+        else:
+            source_dtype = None
+
+        if source_dtype:
+            cube_faces = cube_faces.astype(np.float32)  # pyright: ignore
+
         padded = self._pad(cube_faces)
         if self._use_cv2:
             w = padded.shape[-1]
             v_img = padded.reshape(-1, w)
+
+            # cv2.remap can handle uint8, float32, float64
             out = cv2.remap(v_img, self._coor_x, self._coor_y, interpolation=self._order)  # pyright: ignore
         else:
+            # map_coordinates can handle uint8, float32, float64
             out = map_coordinates(padded, (self._tp, self._coor_y, self._coor_x), order=self._order)
+
+        if source_dtype:
+            out = out.astype(source_dtype)
+
         return out  # pyright: ignore[reportReturnType]
 
     def _pad(self, cube_faces: NDArray[DType]) -> NDArray[DType]:

pyproject.toml

@@ -102,6 +102,7 @@ ignore = [
     "E501",
     "F401",
     "N806",
+    "SIM108",  # Use ternary operator
     "PGH003",  # Use specific rule codes when ignoring type issues
     "TRY003",  # Avoid specifying messages outside exception class; overly strict, especially for ValueError
 ]

tests/test_main.py

@@ -124,3 +124,24 @@ def test_e2c_list_mono(equirec_image_mono, list_image_mono):
     assert list_diff[3].mean() < AVG_DIFF_THRESH
     assert list_diff[4].mean() < AVG_DIFF_THRESH
     assert list_diff[5].mean() < AVG_DIFF_THRESH
+
+
+@pytest.mark.parametrize("dtype", [np.float16, np.float32, np.float64])
+def test_e2c_dtype(equirec_image, dtype):
+    equirec_image = equirec_image.astype(dtype)
+    actual = py360convert.e2c(equirec_image, cube_format="horizon")
+    assert actual.dtype == dtype
+
+
+@pytest.mark.parametrize("dtype", [np.float16, np.float32, np.float64])
+def test_e2p_dtype(equirec_image, dtype):
+    equirec_image = equirec_image.astype(dtype)
+    actual = py360convert.e2p(equirec_image, 90, 50, 120, (512, 512))
+    assert actual.dtype == dtype
+
+
+@pytest.mark.parametrize("dtype", [np.float16, np.float32, np.float64])
+def test_c2e_dtype(dice_image, dtype):
+    dice_image = dice_image.astype(dtype)
+    actual = py360convert.c2e(dice_image, 512, 1024, cube_format="dice")
+    assert actual.dtype == dtype