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| {{hidden | Z-depth to Euclidean Depth | | | {{hidden | Z-depth to Euclidean Depth | |
| | | See [https://github.com/carla-simulator/carla/issues/2287 https://github.com/carla-simulator/carla/issues/2287] for a formula to convert z-depth to euclidean depth. |
| Below is code to convert z-depth to euclidean depth for an equirectangular image stitched from cubemaps.
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| Adapt it accordingly.
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| <syntaxhighlight lang="python">
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| theta, phi = np.meshgrid((np.arange(width) + 0.5) * (2 * np.pi / width),
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| (np.arange(height) + 0.5) * (np.pi / height))
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| uvs, uv_sides = my_helpers.spherical_to_cubemap(theta.reshape(-1),
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| phi.reshape(-1))
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| cubemap_uvs = uvs.reshape(height, width, 2)
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| # cubemap_uv_sides = uv_sides.reshape(height, width)
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| world_coords = my_helpers.spherical_to_cartesian(
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| cubemap_uvs[:, :, 0] * np.pi / 2 + np.pi / 4,
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| cubemap_uvs[:, :, 1] * np.pi / 2 + np.pi / 4)
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| cos_angle = world_coords @ np.array([0, 0, 1], dtype=np.float32)
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| return depth_image / cos_angle[np.newaxis, :, :, np.newaxis]
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| </syntaxhighlight>
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| | |
| * Here <code>cubemap_uvs</code> are the UVs of each equirectangular pixel within the cubemap.
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| Spherical to cubemap is defined as follows:
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| <syntaxhighlight lang="python">
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| def spherical_to_cubemap(theta, phi):
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| """Converts spherical coordinates to cubemap coordinates.
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| Args:
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| theta: Longitude (azimuthal angle) in radians. [0, 2pi]
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| phi: Latitude (altitude angle) in radians. [0, pi]
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| Returns:
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| uv: UVS in channel_last format
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| idx: Side of the cubemap
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| """
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| u = np.zeros(theta.shape, dtype=np.float32)
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| v = np.zeros(theta.shape, dtype=np.float32)
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| side = np.zeros(theta.shape, dtype=np.float32)
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| side[:] = -1
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| for i in range(0, 4):
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| indices = np.logical_or(
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| np.logical_and(theta >= i * np.pi / 2 - np.pi / 4, theta <=
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| (i + 1) * np.pi / 2 - np.pi / 4),
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| np.logical_and(theta >= i * np.pi / 2 - np.pi / 4 + 2 * np.pi, theta <=
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| (i + 1) * np.pi / 2 - np.pi / 4 + 2 * np.pi))
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| u[indices] = np.tan(theta[indices] - i * np.pi / 2)
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| v[indices] = 1 / (
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| np.tan(phi[indices]) * np.cos(theta[indices] - i * np.pi / 2))
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| side[indices] = i + 1
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| top_indices = np.logical_or(phi < np.pi / 4, v >= 1)
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| u[top_indices] = -np.tan(phi[top_indices]) * np.sin(theta[top_indices] -
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| np.pi)
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| v[top_indices] = np.tan(phi[top_indices]) * np.cos(theta[top_indices] - np.pi)
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| side[top_indices] = 0
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| bottom_indices = np.logical_or(phi >= 3 * np.pi / 4, v <= -1)
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| u[bottom_indices] = -np.tan(phi[bottom_indices]) * np.sin(
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| theta[bottom_indices])
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| v[bottom_indices] = -np.tan(phi[bottom_indices]) * np.cos(
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| theta[bottom_indices])
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| side[bottom_indices] = 5
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| assert not np.any(side < 0), "Side less than 0"
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| return np.stack(((u + 1) / 2, (-v + 1) / 2), axis=-1), side
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| </syntaxhighlight>
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| }} | | }} |
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