Pointmap: kill mesh holes — morphological CLOSE on fg mask + loosen max_edge to 4cm

app.py

@@ -142,7 +142,12 @@ def _foreground_mask(image_pil: Image.Image, target_h: int, target_w: int) -> np
     with torch.no_grad():
         out = fg(inputs)
     out = F.interpolate(out, size=(target_h, target_w), mode="bilinear", align_corners=False)
-    return (out.argmax(dim=1)[0] > 0).cpu().numpy()
+    mask = (out.argmax(dim=1)[0] > 0).cpu().numpy().astype(np.uint8)
+    # Morphological closing fills small false-negative holes inside the figure
+    # (shadows, dark hair, between fingers) so the mesh doesn't show pinpricks.
+    kernel = np.ones((5, 5), np.uint8)
+    mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
+    return mask.astype(bool)
 
 
 def _depth_to_rgb(depth: np.ndarray, mask: np.ndarray) -> np.ndarray:
@@ -183,7 +188,7 @@ def _camera_marker(radius: float = 0.025, n_points: int = 600,
 
 
 def _triangulate_grid(pointmap_hwc: np.ndarray, mask_hw: np.ndarray,
-                      max_edge: float = 0.02):
+                      max_edge: float = 0.04):
     """Build a triangulated mesh from the (H, W) pointmap grid.
 
     Returns (verts, uvs, faces). Each valid pixel becomes a vertex; adjacent
@@ -221,7 +226,7 @@ def _triangulate_grid(pointmap_hwc: np.ndarray, mask_hw: np.ndarray,
 
 
 def _make_glb(image_pil_native: Image.Image, pointmap_hwc: np.ndarray,
-              mask_hw: np.ndarray, max_edge: float = 0.02) -> str:
+              mask_hw: np.ndarray, max_edge: float = 0.04) -> str:
     h, w = pointmap_hwc.shape[:2]
     image_native = image_pil_native.resize((w, h), Image.LANCZOS)