feat(perception): vectorised IR→RGB depth alignment

Forward-project IR depth pixels into the RGB pixel grid with a z-buffer.
Output uint16 mm at RGB resolution, ready to feed SAM21.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

src/presa_mano/perception/depth_align.py

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+"""Forward-project an IR depth image into RGB pixel coordinates.
+
+Vectorised equivalent of librealsense `rs.align(stream.color)`. Each IR pixel
+with valid depth is back-projected to 3D in the IR camera frame, transformed to
+the RGB camera frame via the rigid extrinsics, and projected with RGB
+intrinsics. On collisions the closest point wins (z-buffer).
+
+Output is a uint16 array in millimeters, shape (rgb_height, rgb_width), with 0
+on pixels that received no IR projection.
+"""
+from __future__ import annotations
+
+import numpy as np
+
+from .depth_to_rgb import CameraRegistration
+
+_SENTINEL = np.iinfo(np.uint32).max
+
+
+def align_depth_to_rgb(
+    depth_ir_mm: np.ndarray,
+    reg: CameraRegistration,
+) -> np.ndarray:
+    """Forward-project IR depth → RGB pixel grid.
+
+    Parameters
+    ----------
+    depth_ir_mm : (H_ir, W_ir) uint16
+        Depth in millimeters, IR camera frame. Zero means "no depth".
+    reg : CameraRegistration
+        IR and RGB intrinsics + IR→RGB rigid transform (translation in meters).
+
+    Returns
+    -------
+    (reg.rgb_height, reg.rgb_width) uint16
+        Depth in millimeters in RGB pixel coordinates; 0 where no IR pixel
+        projected.
+    """
+    if depth_ir_mm.ndim != 2:
+        raise ValueError(f"depth_ir_mm must be 2D, got shape {depth_ir_mm.shape}")
+    if depth_ir_mm.shape != (reg.ir_height, reg.ir_width):
+        raise ValueError(
+            f"depth_ir_mm shape {depth_ir_mm.shape} ≠ IR resolution "
+            f"({reg.ir_height}, {reg.ir_width}) from registration"
+        )
+
+    H_rgb, W_rgb = reg.rgb_height, reg.rgb_width
+    H_ir, W_ir = reg.ir_height, reg.ir_width
+
+    valid = depth_ir_mm > 0
+    if not valid.any():
+        return np.zeros((H_rgb, W_rgb), dtype=np.uint16)
+
+    v_idx, u_idx = np.where(valid)
+    z_ir_m = depth_ir_mm[v_idx, u_idx].astype(np.float64) / 1000.0
+
+    # Back-project IR pixel → 3D point in IR camera frame.
+    K_ir_inv = np.linalg.inv(reg.K_ir)
+    pixels_h = np.vstack([u_idx.astype(np.float64),
+                          v_idx.astype(np.float64),
+                          np.ones_like(u_idx, dtype=np.float64)])
+    rays_ir = K_ir_inv @ pixels_h
+    P_ir = rays_ir * z_ir_m
+
+    # IR camera frame → RGB camera frame.
+    P_rgb = reg.R_ir_to_rgb @ P_ir + reg.t_ir_to_rgb.reshape(3, 1)
+
+    z_rgb = P_rgb[2]
+    in_front = z_rgb > 1e-6
+    P_rgb = P_rgb[:, in_front]
+    if P_rgb.shape[1] == 0:
+        return np.zeros((H_rgb, W_rgb), dtype=np.uint16)
+
+    z_rgb = P_rgb[2]
+    u_rgb = reg.K_rgb[0, 0] * P_rgb[0] / z_rgb + reg.K_rgb[0, 2]
+    v_rgb = reg.K_rgb[1, 1] * P_rgb[1] / z_rgb + reg.K_rgb[1, 2]
+
+    u_int = np.round(u_rgb).astype(np.int64)
+    v_int = np.round(v_rgb).astype(np.int64)
+    z_mm = np.round(z_rgb * 1000.0).astype(np.int64)
+
+    in_bounds = (
+        (u_int >= 0) & (u_int < W_rgb)
+        & (v_int >= 0) & (v_int < H_rgb)
+        & (z_mm > 0) & (z_mm < 65535)
+    )
+    u_int = u_int[in_bounds]
+    v_int = v_int[in_bounds]
+    z_mm = z_mm[in_bounds].astype(np.uint32)
+    if z_mm.size == 0:
+        return np.zeros((H_rgb, W_rgb), dtype=np.uint16)
+
+    # Z-buffer: initialise to sentinel, reduce-min, then sentinel→0.
+    zbuf = np.full(H_rgb * W_rgb, _SENTINEL, dtype=np.uint32)
+    flat_idx = v_int * W_rgb + u_int
+    np.minimum.at(zbuf, flat_idx, z_mm)
+    zbuf[zbuf == _SENTINEL] = 0
+    return zbuf.reshape(H_rgb, W_rgb).astype(np.uint16)