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

IMG_EXTENSIONS = {'.jpg', '.jpeg', '.png', '.bmp', '.tif', '.tiff', '.webp'}


def process_obb_images(model_path, image_dir, output_dir="./inference_results", conf_thresh=0.15, imgsz=640):
    """
    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。

    输入：
        model_path: YOLO 权重路径
        image_dir: 图像文件夹路径
        output_dir: 输出结果保存路径
        conf_thresh: 置信度阈值
        imgsz: 输入图像大小
    输出：
        results_dict: {image_filename: {'angles_deg': [...], 'pairwise_angles_deg': [...]}}
    """
    os.makedirs(output_dir, exist_ok=True)
    results_dict = {}

    print("加载 YOLO 模型...")
    model = YOLO(model_path)
    print("✅ 模型加载完成")

    # 获取图像文件
    image_files = [f for f in os.listdir(image_dir) if os.path.splitext(f.lower())[1] in IMG_EXTENSIONS]
    if not image_files:
        print(f"❌ 未找到图像文件：{image_dir}")
        return results_dict

    print(f"发现 {len(image_files)} 张图像待处理")

    for img_filename in image_files:
        img_path = os.path.join(image_dir, img_filename)
        print(f"\n正在处理：{img_filename}")

        img = cv2.imread(img_path)
        if img is None:
            print(f"❌ 跳过：无法读取图像 {img_path}")
            continue

        # 推理 OBB
        results = model(img, save=False, imgsz=imgsz, conf=conf_thresh, mode='obb')
        result = results[0]
        annotated_img = result.plot()

        # 保存可视化
        save_path = os.path.join(output_dir, "detected_" + img_filename)
        cv2.imwrite(save_path, annotated_img)
        print(f"✅ 推理结果已保存至: {save_path}")

        # 提取旋转角
        boxes = result.obb
        angles_deg = []
        if boxes is None or len(boxes) == 0:
            print("❌ 该图像中未检测到任何目标")
        else:
            for i, box in enumerate(boxes):
                cls = int(box.cls.cpu().numpy()[0])
                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
                angle_deg = np.degrees(direction)
                angles_deg.append(angle_deg)
                print(f"  Box {i + 1}: Class={cls}, Conf={conf:.3f}, 主方向={angle_deg:.2f}°")

        # 两两夹角
        pairwise_angles_deg = []
        if len(angles_deg) >= 2:
            for i in range(len(angles_deg)):
                for j in range(i + 1, len(angles_deg)):
                    diff_rad = abs(np.radians(angles_deg[i]) - np.radians(angles_deg[j]))
                    min_diff_rad = min(diff_rad, np.pi - diff_rad)
                    pairwise_angles_deg.append(np.degrees(min_diff_rad))
                    print(f"  Box {i + 1} 与 Box {j + 1} 夹角: {np.degrees(min_diff_rad):.2f}°")

        # 保存每张图像结果
        results_dict[img_filename] = {
            "angles_deg": angles_deg,
            "pairwise_angles_deg": pairwise_angles_deg
        }

    print("\n所有图像处理完成！")
    return results_dict


# ------------------- 测试调用 -------------------
if __name__ == "__main__":
    MODEL_PATH = r'best.pt'
    IMAGE_SOURCE_DIR = r"./test_image"
    OUTPUT_DIR = "./inference_results"

    results = process_obb_images(MODEL_PATH, IMAGE_SOURCE_DIR, OUTPUT_DIR)
    for img_name, info in results.items():
        print(f"\n {img_name}:")
        print(f"主方向角度列表: {info['angles_deg']}")
        print(f"两两夹角列表: {info['pairwise_angles_deg']}")