CNN v2 training: Fix float64/float32 dtype mismatch in depth feature

Cast depth array to float32 when provided, preventing torch Double/Float
dtype mismatch during forward pass.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

1 files changed, 1 insertions, 1 deletions

diff --git a/training/train_cnn_v2.py b/training/train_cnn_v2.py
index 70229ce..134a5ae 100755
--- a/training/train_cnn_v2.py
+++ b/training/train_cnn_v2.py
@@ -61,7 +61,7 @@ def compute_static_features(rgb, depth=None, mip_level=0):
     p0 = mip_rgb[:, :, 0].astype(np.float32)
     p1 = mip_rgb[:, :, 1].astype(np.float32)
     p2 = mip_rgb[:, :, 2].astype(np.float32)
-    p3 = depth if depth is not None else np.ones((h, w), dtype=np.float32)  # Default 1.0 = far plane
+    p3 = depth.astype(np.float32) if depth is not None else np.ones((h, w), dtype=np.float32)  # Default 1.0 = far plane
 
     # UV coordinates (normalized [0, 1])
     uv_x = np.linspace(0, 1, w)[None, :].repeat(h, axis=0).astype(np.float32)