import cv2
from skimage.metrics import structural_similarity as ssim
import os

def calculate_ssim(image_path1, image_path2):
    """
    计算两张图片的 SSIM 相似度
    """
    # 读取图像
    img1 = cv2.imread(image_path1)
    img2 = cv2.imread(image_path2)

    if img1 is None:
        print(f"❌ 无法读取图片1: {image_path1}")
        return None
    if img2 is None:
        print(f"❌ 无法读取图片2: {image_path2}")
        return None

    # 转为灰度图
    gray1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
    gray2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)

    # 确保尺寸一致
    if gray1.shape != gray2.shape:
        print("⚠️ 图像尺寸不一致，正在调整...")
        h, w = min(gray1.shape[0], gray2.shape[0]), min(gray1.shape[1], gray2.shape[1])
        gray1 = cv2.resize(gray1, (w, h))
        gray2 = cv2.resize(gray2, (w, h))

    # 计算 SSIM
    try:
        similarity = ssim(gray1, gray2)
        return similarity
    except Exception as e:
        print(f"❌ SSIM 计算失败: {e}")
        return None


# ==================== 使用示例 ====================
if __name__ == "__main__":
    # 替换成你本地的两张图片路径
    path1 = "/home/hx/桌面/image/image/frame_20250805_120334_585.jpg"
    path2 = "/home/hx/桌面/image/image/frame_20250805_120334_570.jpg"

    # 检查文件是否存在
    if not os.path.exists(path1):
        print(f"文件不存在: {path1}")
        print("请修改 path1 为实际存在的图片路径")
    elif not os.path.exists(path2):
        print(f"文件不存在: {path2}")
        print("请修改 path2 为实际存在的图片路径")
    else:
        print("正在计算 SSIM...")
        sim = calculate_ssim(path1, path2)
        if sim is not None:
            print(f"✅ SSIM 相似度: {sim:.4f}")
            if sim > 0.9:
                print("🔴 太相似（>0.9），应跳过重复帧")
            elif sim > 0.7:
                print("🟡 较相似，内容变化不大")
            else:
                print("🟢 差异明显，建议保存")