zjsh_yolov11/angle_base_obb/angle_caculate.py

import cv2
import os
import numpy as np
from ultralytics import YOLO

def predict_obb_best_angle(model_path, image_path, save_path=None):
    """
    输入：
        model_path: YOLO 权重路径
        image_path: 图片路径
        save_path: 可选，保存带标注图像
    输出：
        angle_deg: 置信度最高两个框的主方向夹角（度），如果检测少于两个目标返回 None
        annotated_img: 可视化图像
    """
    # 1. 加载模型
    model = YOLO(model_path)

    # 2. 读取图像
    img = cv2.imread(image_path)
    if img is None:
        print(f"无法读取图像: {image_path}")
        return None, None

    # 3. 推理 OBB
    results = model(img, save=False, imgsz=640, conf=0.3, mode='obb')
    result = results[0]
    print(result)

    # 4. 可视化
    annotated_img = result.plot()
    if save_path:
        os.makedirs(os.path.dirname(save_path), exist_ok=True)
        cv2.imwrite(save_path, annotated_img)
        print(f"推理结果已保存至: {save_path}")

    # 5. 提取旋转角度和置信度
    boxes = result.obb
    if boxes is None or len(boxes) < 2:
        print("检测到少于两个目标，无法计算夹角。")
        return None, annotated_img

    box_info = []
    for box in boxes:
        conf = box.conf.cpu().numpy()[0]
        cx, cy, w, h, r_rad = box.xywhr.cpu().numpy()[0]
        direction = r_rad if w >= h else r_rad + np.pi/2
        direction = direction % np.pi
        box_info.append((conf, direction))

    # 6. 取置信度最高两个框
    box_info = sorted(box_info, key=lambda x: x[0], reverse=True)
    dir1, dir2 = box_info[0][1], box_info[1][1]

    # 7. 计算夹角（最小夹角，0~90°）
    diff = abs(dir1 - dir2)
    diff = min(diff, np.pi - diff)
    angle_deg = np.degrees(diff)

    print(f"置信度最高两个框主方向夹角: {angle_deg:.2f}°")
    return angle_deg, annotated_img


# ------------------- 测试 -------------------
if __name__ == "__main__":
    weight_path = r'obb.pt'
    #weight_path = r'obb.pt'
    image_path = r"1.png"
    save_path = "./inference_results/detected_3.jpg"

    #angle_deg, annotated_img = predict_obb_best_angle(weight_path, image_path, save_path)
    angle_deg,_ = predict_obb_best_angle(weight_path, image_path, save_path)
    annotated_img = None
    print(angle_deg)
    if annotated_img is not None:
        cv2.imshow("YOLO OBB Prediction", annotated_img)
        cv2.waitKey(0)
        cv2.destroyAllWindows()