【目标检测】旋转目标检测COCO格式标注转DOTAv1格式

DOTAv1数据集格式：

'imagesource':imagesource
'gsd':gsd
x1, y1, x2, y2, x3, y3, x4, y4, category, difficult
x1, y1, x2, y2, x3, y3, x4, y4, category, difficult
...

imagesource: 图片来源  
gsd: 分辨率
x1, y1, x2, y2, x3, y3, x4, y4：四边形的四个顶点的坐标 顶点按顺时针顺序排列，第一个起点为左上第一个点
category:实例类别
difficult：表示该实例是否难以检测（1表示困难，0表示不困难）

COCO转DOTA：

import json
import cv2
import numpy as np
import osdef calculate_rotated_bbox(poly):"""将多边形坐标转换为旋转边界框"""contour = np.array(poly).reshape((-1, 1, 2)).astype(np.float32)rect = cv2.minAreaRect(contour)box = cv2.boxPoints(rect)return np.int0(box)def coco_to_dota(coco_annotation_path, dota_annotation_folder, imagesource="Unknown", gsd="Unknown"):"""将COCO格式的标注转换为DOTA格式，包括imagesource和gsd信息"""# 类别ID到名称的映射category_map = {1: 'Class1',2: 'Class2',}# 确保输出目录存在if not os.path.exists(dota_annotation_folder):os.makedirs(dota_annotation_folder)# 读取COCO格式的JSON文件with open(coco_annotation_path, 'r') as f:coco_data = json.load(f)# 遍历每个图像的标注for image in coco_data['images']:image_id = image['id']image_filename = image['file_name']dota_filename = os.path.splitext(image_filename)[0] + '.txt'  # 去掉原始扩展名，添加.txtdota_filepath = os.path.join(dota_annotation_folder, dota_filename)with open(dota_filepath, 'w') as dota_file:# 写入imagesource和gsd信息# dota_file.write(f"'imagesource':{imagesource}\n'gsd':{gsd}\n")# 找到当前图像的所有标注for annotation in filter(lambda x: x['image_id'] == image_id, coco_data['annotations']):if 'segmentation' in annotation:for seg in annotation['segmentation']:if type(seg[0]) is list:  # 检查是否是多边形格式seg = seg[0]box = calculate_rotated_bbox(seg)# 从映射中获取类别名称category_name = category_map.get(annotation['category_id'], 'Unknown')# 格式化DOTA标注box_str = ' '.join(map(str, box.flatten().tolist()))dota_annotation = f"{box_str} {category_name} 0\n"dota_file.write(dota_annotation)# 调用函数，转换COCO到DOTA
coco_annotation_path = 'instances.json'
dota_annotation_folder = 'dota'
coco_to_dota(coco_annotation_path, dota_annotation_folder)

标注可视化：

import cv2
import numpy as np
import osdef draw_rotated_box(img, box, label):"""在图像上绘制旋转的边界框和标签。"""points = np.int0(box)cv2.drawContours(img, [points], 0, (0, 255, 0), 2)  # 绘制旋转框cv2.putText(img, label, tuple(points[0]), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 1)  # 添加文本标签def visualize_dota_annotations(image_folder, annotation_folder, output_folder):"""批量处理图像和DOTA标注文件，绘制旋转边界框和标签"""# 确保输出文件夹存在if not os.path.exists(output_folder):os.makedirs(output_folder)# 遍历图像文件for img_filename in os.listdir(image_folder):img_path = os.path.join(image_folder, img_filename)if os.path.isfile(img_path) and img_filename.endswith(('.jpg', '.png')):annot_filename = os.path.splitext(img_filename)[0] + '.txt'annot_path = os.path.join(annotation_folder, annot_filename)output_img_path = os.path.join(output_folder, img_filename)img = cv2.imread(img_path)if img is None:continueif os.path.isfile(annot_path):with open(annot_path, 'r') as f:lines = f.readlines()  # Skip imagesource and gsd linesfor line in lines:parts = line.strip().split(' ')if len(parts) < 9:continuebox = np.array([float(part) for part in parts[:8]]).reshape(4, 2)label = parts[8]draw_rotated_box(img, box, label)cv2.imwrite(output_img_path, img)# 路径配置
image_folder = 'images'
annotation_folder = 'dota'
output_folder = 'visual'visualize_dota_annotations(image_folder, annotation_folder, output_folder)