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