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2026-08-20 18:00:47 +08:00
parent b9934c996d
commit 45d55028d7
17 changed files with 500 additions and 1520 deletions
@@ -0,0 +1,79 @@
+#!/usr/bin/env python3
+"""标注预览图生成: 动物红色实线框 + 生境 cover 黄色虚线框
+
+用法:
+  venv/bin/python visualize_labels.py --input datasets/images --labels datasets/labels --output datasets/pheasant_label
+"""
+import argparse
+from pathlib import Path
+
+from PIL import Image, ImageDraw
+
+CLASSES = ["pheasant", "cover"]
+LABELS = {"pheasant": "野鸡", "cover": "疑似区域"}
+
+
+def draw_dashed(draw, box, outline, width, dash=12, gap=8):
+    x1, y1, x2, y2 = box
+    for (ax, ay, bx, by) in [(x1, y1, x2, y1), (x2, y1, x2, y2),
+                             (x2, y2, x1, y2), (x1, y2, x1, y1)]:
+        length = max(abs(bx - ax), abs(by - ay))
+        steps = max(int(length / (dash + gap)), 1)
+        for i in range(steps):
+            s = i / steps
+            e = min((i * (dash + gap) + dash) / length, 1.0)
+            if e <= s:
+                continue
+            draw.line([ax + (bx - ax) * s, ay + (by - ay) * s,
+                       ax + (bx - ax) * e, ay + (by - ay) * e],
+                      fill=outline, width=width)
+
+
+def main():
+    ap = argparse.ArgumentParser(description="标注预览图生成")
+    ap.add_argument("--input", default="datasets/images")
+    ap.add_argument("--labels", default="datasets/labels")
+    ap.add_argument("--output", default="datasets/pheasant_label")
+    args = ap.parse_args()
+
+    img_dir = Path(args.input)
+    lab_dir = Path(args.labels)
+    out_dir = Path(args.output)
+    out_dir.mkdir(parents=True, exist_ok=True)
+
+    count = 0
+    for img_path in sorted(img_dir.rglob("*")):
+        if img_path.suffix.lower() not in (".jpg", ".jpeg", ".png", ".webp", ".bmp"):
+            continue
+        rel = img_path.relative_to(img_dir)
+        lab_path = lab_dir / rel.with_suffix(".txt")
+        if not lab_path.exists():
+            continue
+        im = Image.open(img_path).convert("RGB")
+        W, H = im.size
+        d = ImageDraw.Draw(im)
+        for line in lab_path.read_text().splitlines():
+            parts = line.split()
+            if not parts:
+                continue
+            cid, cx, cy, w, h = map(float, parts)
+            box = ((cx - w / 2) * W, (cy - h / 2) * H,
+                   (cx + w / 2) * W, (cy + h / 2) * H)
+            if int(cid) == 1:  # cover 生境: 黄色虚线
+                draw_dashed(d, box, (255, 200, 0), width=5)
+                d.text((box[0] + 6, max(box[1] - 28, 4)), "疑似区域",
+                       fill=(255, 200, 0))
+            else:              # 动物: 红色实线
+                d.rectangle(box, outline=(255, 0, 0), width=6)
+                label = LABELS.get(CLASSES[int(cid)], CLASSES[int(cid)])
+                d.text((box[0] + 6, max(box[1] - 28, 4)), label,
+                       fill=(255, 0, 0))
+        out = out_dir / (img_path.stem + ".jpg")
+        im.save(out, quality=92)
+        count += 1
+        print(out.name)
+    print(f"共生成 {count} 张")
+
+
+if __name__ == "__main__":
+    main()