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fix(ldm3d): return uint16/int32 from rgblike_to_depthmap instead of casting back to uint8 #14424

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fix(ldm3d): return uint16/int32 from rgblike_to_depthmap instead of casting back to uint8 #14424

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20 changes: 4 additions & 16 deletions src/diffusers/image_processor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1048,28 +1048,16 @@ def rgblike_to_depthmap(image: np.ndarray | torch.Tensor) -> np.ndarray | torch.
# for return value from a library function.

if isinstance(image, torch.Tensor):
# Cast to a safe dtype (e.g., int32 or int64) for the calculation
original_dtype = image.dtype
image_safe = image.to(torch.int32)

# Calculate the depth map
depth_map = image_safe[:, :, 1] * 256 + image_safe[:, :, 2]

# You may want to cast the final result to uint16, but casting to a
# larger int type (like int32) is sufficient to fix the overflow.
# depth_map = depth_map.to(torch.uint16) # Uncomment if uint16 is strictly required
return depth_map.to(original_dtype)
# Return int32 — the 16-bit value does not fit back in the uint8 input dtype.
return depth_map

elif isinstance(image, np.ndarray):
# NumPy equivalent: Cast to a safe dtype (e.g., np.int32)
original_dtype = image.dtype
image_safe = image.astype(np.int32)

# Calculate the depth map
depth_map = image_safe[:, :, 1] * 256 + image_safe[:, :, 2]

# depth_map = depth_map.astype(np.uint16) # Uncomment if uint16 is strictly required
return depth_map.astype(original_dtype)
# uint16 matches the mode="I;16" consumer in numpy_to_depth.
return depth_map.astype(np.uint16)
else:
raise TypeError("Input image must be a torch.Tensor or np.ndarray")

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