feat: unify reference depth calculation by using median-based range factor and baseline

src/anyimage/common/depth.py

@@ -11,7 +11,8 @@ from .image import depth_data_name, image_empty_bounds
 PLANE_VARIANCE_FLOOR_RATIO = 0.025
 REFERENCE_DEPTH_PERCENTILE = 95.0
 DEPTH_ALPHA_THRESHOLD = 0.95
-REFERENCE_DEPTH_LIMIT = 8.0
+REFERENCE_DEPTH_RANGE_FACTOR = 1.1
+REFERENCE_DEPTH_BASELINE = 8.0
 FLAT_DEPTH_DIRECTION = (0.0, 1.0, 0.0)
 
 
@@ -72,10 +73,10 @@ def reference_depth(image, mask=None):
     """Return the upper-percentile camera depth of a loaded Depth texture.
 
     Distances are in model meters. Samples farther than
-    ``REFERENCE_DEPTH_LIMIT`` are dropped so a distant background cannot push
-    the reference plane, and with it the whole reconstruction scale, out to
-    the far field. The limit itself is the reference when the selection leaves
-    no sample.
+    ``REFERENCE_DEPTH_RANGE_FACTOR`` times the median are dropped so a distant
+    background cannot push the reference plane, and with it the whole
+    reconstruction scale, out to the far field. A selection without usable
+    samples returns ``REFERENCE_DEPTH_BASELINE``.
     """
     import numpy as np
 
@@ -87,10 +88,12 @@ def reference_depth(image, mask=None):
             raise ValueError("Depth reference mask dimensions do not match")
         usable &= mask
     values = depth[usable]
-    values = values[values <= REFERENCE_DEPTH_LIMIT]
     if not values.size:
-        return REFERENCE_DEPTH_LIMIT
-    return float(np.percentile(values, REFERENCE_DEPTH_PERCENTILE))
+        return REFERENCE_DEPTH_BASELINE
+    near = values[
+        values <= REFERENCE_DEPTH_RANGE_FACTOR * float(np.median(values))
+    ]
+    return float(np.percentile(near, REFERENCE_DEPTH_PERCENTILE))
 
 
 def _weighted_depth_plane(coordinates, values, weights):