数据增强相关代码

扩大边缘像素.py

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+import os
+
+
+def expand_bbox(label_path, k=1.1):
+    """
+    扩大YOLO标签的边界框
+    :param label_path: 标签文件路径（.txt）
+    :param k: 扩大系数（k>1）
+    """
+    with open(label_path, 'r') as f:
+        lines = f.readlines()
+
+    new_lines = []
+    for line in lines:
+        line = line.strip()
+        if not line:
+            continue
+        # 解析标签
+        class_id, xc, yc, w, h = line.split()
+        xc = float(xc)
+        yc = float(yc)
+        w = float(w)
+        h = float(h)
+
+        # 计算新宽高
+        new_w = w * k
+        new_h = h * k
+
+        # 计算边界
+        x1 = xc - new_w / 2
+        y1 = yc - new_h / 2
+        x2 = xc + new_w / 2
+        y2 = yc + new_h / 2
+
+        # 截断超出图像的部分（0~1范围）
+        x1 = max(0.0, x1)
+        y1 = max(0.0, y1)
+        x2 = min(1.0, x2)
+        y2 = min(1.0, y2)
+
+        # 重新计算中心和宽高
+        new_xc = (x1 + x2) / 2
+        new_yc = (y1 + y2) / 2
+        new_w = x2 - x1
+        new_h = y2 - y1
+
+        # 保留6位小数，拼接新标签
+        new_line = f"{class_id} {new_xc:.6f} {new_yc:.6f} {new_w:.6f} {new_h:.6f}\n"
+        new_lines.append(new_line)
+
+    # 写入新标签（覆盖原文件，或改为新路径）
+    with open(label_path, 'w') as f:
+        f.writelines(new_lines)
+
+
+# 批量处理文件夹中的所有标签
+label_dir = r"D:\DataPreHandler\yuanshi_data\images\val\labels"  # 替换为你的标签文件夹路径
+k = 1.25  # 扩大系数，根据需求调整
+
+for filename in os.listdir(label_dir):
+    if filename.endswith('.txt'):
+        label_path = os.path.join(label_dir, filename)
+        expand_bbox(label_path, k)
+
+print("处理完成！")