From f6859cfa79a134cbed976c50653824c4278afc59 Mon Sep 17 00:00:00 2001
From: crosstyan <crosstyan@outlook.com>
Date: Mon, 2 Mar 2026 16:45:20 +0800
Subject: [PATCH] fix(demo): harden mask hole-filling for border-touching cases

---
 opengait/demo/preprocess.py   | 24 ++++++++++++++++++++++++
 tests/demo/test_preprocess.py | 28 ++++++++++++++++++++++++++++
 2 files changed, 52 insertions(+)

diff --git a/opengait/demo/preprocess.py b/opengait/demo/preprocess.py
index 9801cc7..4977d2a 100644
--- a/opengait/demo/preprocess.py
+++ b/opengait/demo/preprocess.py
@@ -64,6 +64,29 @@ def _to_numpy_array(value: object) -> NDArray[np.generic]:
     return cast(NDArray[np.generic], np.asarray(current))
 
 
+def _fill_binary_holes(mask_u8: UInt8Array) -> UInt8Array:
+    mask_bin = np.where(mask_u8 > 0, np.uint8(255), np.uint8(0)).astype(np.uint8)
+    h, w = cast(tuple[int, int], mask_bin.shape)
+    if h <= 2 or w <= 2:
+        return mask_bin
+
+    seed_candidates = [(0, 0), (w - 1, 0), (0, h - 1), (w - 1, h - 1)]
+    seed: tuple[int, int] | None = None
+    for x, y in seed_candidates:
+        if int(mask_bin[y, x]) == 0:
+            seed = (x, y)
+            break
+    if seed is None:
+        return mask_bin
+
+    flood = mask_bin.copy()
+    flood_mask = np.zeros((h + 2, w + 2), dtype=np.uint8)
+    _ = cv2.floodFill(flood, flood_mask, seed, 255)
+    holes = cv2.bitwise_not(flood)
+    filled = cv2.bitwise_or(mask_bin, holes)
+    return cast(UInt8Array, filled)
+
+
 def _bbox_from_mask(mask: UInt8[ndarray, "h w"]) -> BBoxXYXY | None:
     """Extract bounding box from binary mask in XYXY format.
 
@@ -248,6 +271,7 @@ def mask_to_silhouette(
         or None if conversion fails.
     """
     mask_u8 = np.where(mask > 0, np.uint8(255), np.uint8(0)).astype(np.uint8)
+    mask_u8 = _fill_binary_holes(mask_u8)
     if int(np.count_nonzero(mask_u8)) < MIN_MASK_AREA:
         return None
 
diff --git a/tests/demo/test_preprocess.py b/tests/demo/test_preprocess.py
index 9d58c39..7290db6 100644
--- a/tests/demo/test_preprocess.py
+++ b/tests/demo/test_preprocess.py
@@ -95,6 +95,34 @@ class TestMaskToSilhouette:
         np.testing.assert_array_equal(result1, result2)
         np.testing.assert_array_equal(result2, result3)
 
+    def test_hole_inside_mask_is_filled(self) -> None:
+        h, w = 200, 160
+        mask = np.zeros((h, w), dtype=np.uint8)
+        mask[30:170, 40:120] = 255
+        mask[80:120, 70:90] = 0
+        bbox = (40, 30, 120, 170)
+
+        result = mask_to_silhouette(mask, bbox)
+
+        assert result is not None
+        result_arr = cast(NDArray[np.float32], result)
+        hole_patch = result_arr[26:38, 18:26]
+        assert float(np.mean(hole_patch)) > 0.8
+
+    def test_hole_fill_works_when_mask_touches_corner(self) -> None:
+        h, w = 220, 180
+        mask = np.zeros((h, w), dtype=np.uint8)
+        mask[0:180, 0:130] = 255
+        mask[70:120, 55:95] = 0
+        bbox = (0, 0, 130, 180)
+
+        result = mask_to_silhouette(mask, bbox)
+
+        assert result is not None
+        result_arr = cast(NDArray[np.float32], result)
+        hole_patch = result_arr[24:40, 16:28]
+        assert float(np.mean(hole_patch)) > 0.75
+
     def test_tall_narrow_mask_valid_output(self) -> None:
         """Tall narrow mask should produce valid silhouette."""
         h, w = 400, 50