101 lines
3.7 KiB
Python
101 lines
3.7 KiB
Python
import cv2
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import os
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import numpy as np
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from ultralytics import YOLO
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IMG_EXTENSIONS = {'.jpg', '.jpeg', '.png', '.bmp', '.tif', '.tiff', '.webp'}
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def process_obb_images_for_angle_distribution(model_path, image_dir, conf_thresh=0.15, imgsz=640):
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"""
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批量处理图像的 OBB 推理，计算每张图像检测目标的主方向和夹角，并统计夹角分布情况。
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输入：
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model_path: YOLO 权重路径
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image_dir: 图像文件夹路径
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conf_thresh: 置信度阈值
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imgsz: 输入图像大小
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输出：
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angle_distribution: {'<6': count, '6-20': count, '>20': count}
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"""
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results_dict = {}
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angle_distribution = {'<6': 0, '6-20': 0, '>20': 0}
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print("加载 YOLO 模型...")
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model = YOLO(model_path)
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print("✅ 模型加载完成")
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# 获取图像文件
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image_files = [f for f in os.listdir(image_dir) if os.path.splitext(f.lower())[1] in IMG_EXTENSIONS]
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if not image_files:
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print(f"❌ 未找到图像文件：{image_dir}")
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return angle_distribution
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print(f"发现 {len(image_files)} 张图像待处理")
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for img_filename in image_files:
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img_path = os.path.join(image_dir, img_filename)
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print(f"\n正在处理：{img_filename}")
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img = cv2.imread(img_path)
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if img is None:
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print(f"❌ 跳过：无法读取图像 {img_path}")
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continue
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# 推理 OBB
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results = model(img, save=False, imgsz=imgsz, conf=conf_thresh, mode='obb')
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result = results[0]
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# 提取旋转角
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boxes = result.obb
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angles_deg = []
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if boxes is None or len(boxes) == 0:
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print("❌ 该图像中未检测到任何目标")
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else:
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for i, box in enumerate(boxes):
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cx, cy, w, h, r_rad = box.xywhr.cpu().numpy()[0]
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direction = r_rad if w >= h else r_rad + np.pi / 2
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direction = direction % np.pi
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angle_deg = np.degrees(direction)
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angles_deg.append(angle_deg)
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# 两两夹角
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pairwise_angles_deg = []
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if len(angles_deg) >= 2:
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for i in range(len(angles_deg)):
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for j in range(i + 1, len(angles_deg)):
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diff_rad = abs(np.radians(angles_deg[i]) - np.radians(angles_deg[j]))
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min_diff_rad = min(diff_rad, np.pi - diff_rad)
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angle_deg_diff = np.degrees(min_diff_rad)
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pairwise_angles_deg.append(angle_deg_diff)
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# 更新角度分布统计
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if angle_deg_diff < 6:
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angle_distribution['<6'] += 1
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elif 6 <= angle_deg_diff <= 20:
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angle_distribution['6-20'] += 1
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else:
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angle_distribution['>20'] += 1
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print(f" Box {i + 1} 与 Box {j + 1} 夹角: {angle_deg_diff:.2f}°")
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# 保存每张图像结果
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results_dict[img_filename] = {
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"angles_deg": angles_deg,
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"pairwise_angles_deg": pairwise_angles_deg
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}
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print("\n所有图像处理完成！")
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return angle_distribution
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# ------------------- 测试调用 -------------------
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if __name__ == "__main__":
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MODEL_PATH = r'obb.pt'
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IMAGE_SOURCE_DIR = r"/media/hx/04e879fa-d697-4b02-ac7e-a4148876ebb0/dataset/obb3/train"
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distribution = process_obb_images_for_angle_distribution(MODEL_PATH, IMAGE_SOURCE_DIR)
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print("\n夹角分布统计:")
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print(f"小于6度的夹角数量: {distribution['<6']}")
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print(f"在6至20度之间的夹角数量: {distribution['6-20']}")
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print(f"大于20度的夹角数量: {distribution['>20']}") |