DA3-GIANT — CoreML (.mlpackage) for monocular depth

• Input: image, RGB, 504×504, [0,1] (CoreML ImageType; ImageNet norm baked in).
• Output: depth, shape (1, 504, 504), single-channel relative depth.
• Weights: FP16, ~2.2 GB. Only the backbone → depth head is converted (camera / sky / Gaussian-splat heads bypassed).
• Conversion notes: the full DA3-GIANT backbone uses RoPE + multi-view camera tokens + qk-norm + SwiGLU FFN. Five things were handled for coremltools: the four DA3-LARGE RoPE/cam-token/meshgrid rewrites, plus a converter-side cast shim (numpy 2.x refuses int() on size-1 non-0-dim arrays, which breaks the const-cast of H//patch_size). Single-image behaviour is unchanged.

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