프로젝트 분리 이동

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

tools/merge_tiles_vis.py

@@ -0,0 +1,90 @@
+"""
+6×8 (또는 임의 그리드) 타일 라벨을 원본 이미지 좌표로 병합해 시각화.
+
+사용:
+    python tools/merge_tiles_vis.py \
+        --orig  data/역사이미지/slope/DJI_20260306113838_0004.JPG \
+        --labels output/autolabel/tile6x8/labels \
+        --output output/autolabel/tile6x8/merged_vis.jpg \
+        --cols 6 --rows 8
+"""
+import argparse
+import cv2
+import numpy as np
+from pathlib import Path
+
+CLASS_NAMES  = ["catenary_pole", "bracket"]
+CLASS_COLORS = [(0, 200, 255), (255, 130, 0)]
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--orig",   required=True)
+    parser.add_argument("--labels", required=True)
+    parser.add_argument("--output", required=True)
+    parser.add_argument("--cols",   type=int, default=6)
+    parser.add_argument("--rows",   type=int, default=8)
+    parser.add_argument("--alpha",  type=float, default=0.3)
+    args = parser.parse_args()
+
+    buf = np.fromfile(args.orig, dtype=np.uint8)
+    img = cv2.imdecode(buf, cv2.IMREAD_COLOR)
+    H, W = img.shape[:2]
+    tw, th = W // args.cols, H // args.rows
+
+    label_dir = Path(args.labels)
+    counts = [0] * len(CLASS_NAMES)
+
+    for r in range(args.rows):
+        for c in range(args.cols):
+            label_file = label_dir / f"tile_r{r+1:02d}_c{c+1:02d}.txt"
+            if not label_file.exists():
+                continue
+            x0 = c * tw
+            y0 = r * th
+            tile_w = tw if c < args.cols - 1 else W - x0
+            tile_h = th if r < args.rows - 1 else H - y0
+
+            text = label_file.read_text(encoding="utf-8").strip()
+            if not text:
+                continue
+            for line in text.splitlines():
+                parts = line.split()
+                if not parts:
+                    continue
+                cls_id = int(parts[0])
+                coords = list(map(float, parts[1:]))
+                pts = np.array(
+                    [[coords[i] * tile_w + x0, coords[i + 1] * tile_h + y0]
+                     for i in range(0, len(coords), 2)],
+                    dtype=np.int32,
+                )
+                color = CLASS_COLORS[cls_id % len(CLASS_COLORS)]
+                overlay = img.copy()
+                cv2.fillPoly(overlay, [pts], color)
+                cv2.addWeighted(overlay, args.alpha, img, 1 - args.alpha, 0, img)
+                cv2.polylines(img, [pts], True, color, 3)
+                if cls_id < len(counts):
+                    counts[cls_id] += 1
+
+    # 범례
+    for i, name in enumerate(CLASS_NAMES):
+        y = 30 + i * 50
+        cv2.rectangle(img, (15, y - 20), (55, y + 10), CLASS_COLORS[i], -1)
+        cv2.putText(img, f"{name}: {counts[i]}",
+                    (65, y), cv2.FONT_HERSHEY_SIMPLEX, 1.5, CLASS_COLORS[i], 3)
+
+    total = sum(counts)
+    print(f"총 {total}개  " + ", ".join(f"{CLASS_NAMES[i]}={counts[i]}" for i in range(len(counts))))
+
+    # 4096px 이하로 미리보기 저장
+    scale = min(1.0, 4096 / max(H, W))
+    vis = cv2.resize(img, (int(W * scale), int(H * scale)))
+    out_path = Path(args.output)
+    out_path.parent.mkdir(parents=True, exist_ok=True)
+    cv2.imencode(out_path.suffix, vis)[1].tofile(str(out_path))
+    print(f"저장: {out_path}")
+
+
+if __name__ == "__main__":
+    main()