import cv2
import os
import shutil
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,
    large_angle_output_dir="./large_angle_images",  # 新增：大角度图像保存目录
    conf_thresh=0.15,
    imgsz=640,
    angle_threshold_deg=10.0  # 夹角阈值：超过即视为“大角度”
):
    """
    批量处理 OBB 图像，若任意两个目标的主方向夹角 > angle_threshold_deg，
    则将原图移动到 large_angle_output_dir。
    """
    os.makedirs(large_angle_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]

        # 提取旋转角
        boxes = result.obb
        angles_deg = []
        has_large_angle = False  # 标记是否有大角度的目标
        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}°")

            # 计算两两夹角
            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)
                        angle_diff_deg = np.degrees(min_diff_rad)
                        pairwise_angles_deg.append(angle_diff_deg)
                        print(f"  Box {i + 1} 与 Box {j + 1} 夹角: {angle_diff_deg:.2f}°")
                        if angle_diff_deg > angle_threshold_deg:
                            has_large_angle = True
            elif len(angles_deg) == 1:
                print("  仅检测到一个目标，无法计算夹角")

        # 保存结果
        results_dict[img_filename] = {
            "angles_deg": angles_deg,
            "pairwise_angles_deg": pairwise_angles_deg,
            "has_large_angle": has_large_angle
        }

        # 如果存在大角度，移动原图到新文件夹
        if has_large_angle:
            print(f"发现夹角 > {angle_threshold_deg}°，移动原图到大角度文件夹")
            shutil.move(img_path, os.path.join(large_angle_output_dir, img_filename))

    print(f"\n所有图像处理完成！大角度图像已移动至: {large_angle_output_dir}")
    return results_dict


# ------------------- 测试调用 -------------------
if __name__ == "__main__":
    MODEL_PATH = r'/home/hx/yolo/ultralytics_yolo11-main/runs/train/exp_obb_new3/weights/best.pt'
    IMAGE_SOURCE_DIR = r"/media/hx/04e879fa-d697-4b02-ac7e-a4148876ebb0/dataset/1/ready"
    LARGE_ANGLE_DIR = "/media/hx/04e879fa-d697-4b02-ac7e-a4148876ebb0/dataset/1/large_angle_images"  # 新增输出目录

    results = process_obb_images(
        model_path=MODEL_PATH,
        image_dir=IMAGE_SOURCE_DIR,
        large_angle_output_dir=LARGE_ANGLE_DIR,
        conf_thresh=0.15,
        imgsz=640,
        angle_threshold_deg=10.0
    )

    # 可选：打印大角度图像
    large_angle_imgs = [name for name, info in results.items() if info["has_large_angle"]]
    print(f"\n共 {len(large_angle_imgs)} 张图像包含 >10° 的夹角：")
    for name in large_angle_imgs:
        print(f"  - {name}")