Initial Dansori character workspace

2026-07-04 10:34:46 +09:00
commit 5a419816ff
2480 changed files with 38692 additions and 0 deletions
@@ -0,0 +1,107 @@
+from __future__ import annotations
+
+from collections import deque
+from pathlib import Path
+import sys
+
+import numpy as np
+from PIL import Image, ImageFilter
+
+
+def connected_components(mask: np.ndarray) -> np.ndarray:
+    h, w = mask.shape
+    labels = np.zeros((h, w), dtype=np.int32)
+    current = 0
+
+    for y in range(h):
+        for x in range(w):
+            if not mask[y, x] or labels[y, x] != 0:
+                continue
+            current += 1
+            queue: deque[tuple[int, int]] = deque([(x, y)])
+            labels[y, x] = current
+            while queue:
+                cx, cy = queue.popleft()
+                for nx, ny in (
+                    (cx + 1, cy),
+                    (cx - 1, cy),
+                    (cx, cy + 1),
+                    (cx, cy - 1),
+                ):
+                    if nx < 0 or ny < 0 or nx >= w or ny >= h:
+                        continue
+                    if mask[ny, nx] and labels[ny, nx] == 0:
+                        labels[ny, nx] = current
+                        queue.append((nx, ny))
+    return labels
+
+
+def main() -> None:
+    if len(sys.argv) != 3:
+        raise SystemExit("usage: make_hairmask.py <input-head.png> <output-mask.png>")
+
+    src = Path(sys.argv[1])
+    out = Path(sys.argv[2])
+
+    image = Image.open(src).convert("RGBA")
+    arr = np.asarray(image)
+    rgb = arr[:, :, :3].astype(np.int16)
+    alpha = arr[:, :, 3]
+    r, g, b = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
+
+    opaque = alpha > 32
+    brown_hair = (
+        opaque
+        & (r > 34)
+        & (g > 18)
+        & (r >= g - 8)
+        & (g >= b - 4)
+        & ((r - b) > 22)
+        & ((r < 205) | (g < 138) | (b < 105))
+    )
+    dark_hair_lines = opaque & (r > 18) & (r < 115) & (g < 100) & (b < 85) & ((r - b) > 8)
+    mask = brown_hair | dark_hair_lines
+
+    labels = connected_components(mask)
+    keep = np.zeros_like(mask)
+    for label in range(1, labels.max() + 1):
+        ys, xs = np.where(labels == label)
+        if xs.size == 0:
+            continue
+        area = xs.size
+        width = int(xs.max() - xs.min() + 1)
+        height = int(ys.max() - ys.min() + 1)
+        left = int(xs.min())
+        right = int(xs.max())
+        top = int(ys.min())
+        bottom = int(ys.max())
+        h, w = arr.shape[:2]
+        touches_hair_zone = (
+            left < w * 0.25
+            or right > w * 0.75
+            or top < h * 0.32
+            or bottom > h * 0.78
+        )
+        if area >= 5000 or (
+            area >= 1200
+            and touches_hair_zone
+            and (width >= 45 or height >= 45)
+        ):
+            keep[ys, xs] = True
+
+    mask_img = Image.fromarray((keep.astype(np.uint8) * 255), "L")
+    mask_img = mask_img.filter(ImageFilter.MaxFilter(5))
+    mask_arr = np.asarray(mask_img) > 0
+    mask_arr &= opaque
+
+    out_arr = np.zeros_like(arr)
+    out_arr[:, :, :3] = 255
+    out_arr[:, :, 3] = (mask_arr.astype(np.uint8) * 255)
+
+    out.parent.mkdir(parents=True, exist_ok=True)
+    Image.fromarray(out_arr, "RGBA").save(out)
+    print(f"Wrote {out}")
+
+
+if __name__ == "__main__":
+    main()