import cv2
import numpy as np

# 全局变量
points = []  # 存储选择的四个点
img = None  # 存储原始图像
img_copy = None  # 用于绘制的图像副本


def mouse_callback(event, x, y, flags, param):
    """鼠标回调函数，用于选择四个点"""
    global img_copy, points

    if event == cv2.EVENT_LBUTTONDOWN:
        if len(points) < 4:
            points.append((x, y))
            print(f"已选择点 {len(points)}: ({x}, {y})")

            # 在图像上绘制点
            cv2.circle(img_copy, (x, y), 5, (0, 255, 0), -1)

            # 如果已经选择了4个点，绘制连线
            if len(points) == 4:
                # 按照上、右、下、左的顺序连接点
                for i in range(4):
                    cv2.line(img_copy, points[i], points[(i + 1) % 4], (0, 255, 0), 2)

                # 标记每个点的位置
                cv2.putText(img_copy, "Top", points[0], cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2)
                cv2.putText(img_copy, "Right", points[1], cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2)
                cv2.putText(img_copy, "Bottom", points[2], cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2)
                cv2.putText(img_copy, "Left", points[3], cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2)

        cv2.imshow("Select Points", img_copy)


def perspective_transform(image, src_points):
    """执行透视变换"""
    # 将点排序为上、右、下、左
    top, right, bottom, left = src_points

    # 计算新图像的宽度（取左右边的最大值）
    width_a = np.linalg.norm(np.array(right) - np.array(left))
    width_b = np.linalg.norm(np.array(top) - np.array(bottom))
    max_width = max(int(width_a), int(width_b))

    # 计算新图像的高度（取上下边的最大值）
    height_a = np.linalg.norm(np.array(bottom) - np.array(top))
    height_b = np.linalg.norm(np.array(right) - np.array(left))
    max_height = max(int(height_a), int(height_b))

    # 定义目标点
    dst = np.array([
        [0, 0],  # 左上角
        [max_width - 1, 0],  # 右上角
        [max_width - 1, max_height - 1],  # 右下角
        [0, max_height - 1]  # 左下角
    ], dtype="float32")

    # 转换源点数组为numpy数组
    src = np.array([top, right, bottom, left], dtype="float32")

    # 计算透视变换矩阵
    M = cv2.getPerspectiveTransform(src, dst)

    # 执行透视变换
    warped = cv2.warpPerspective(image, M, (max_width, max_height))

    return warped

def k_perspective_transform(image, src_points):
    """执行透视变换"""
    # 将点排序为上、右、下、左
    top, right, bottom, left = src_points

    # 计算新图像的宽度（取左右边的最大值）
    sub_zy = np.array(right) - np.array(left)
    sub_sx = np.array(top) - np.array(bottom)

    sub_x=sub_sx[0]/2
    print("x差值",sub_sx[0])

    sub_y = sub_zy[1] / 2
    print("y差值", sub_sx[0])

    # 定义目标点
    dst = np.array([
        [top[0]-sub_x, top[1]],  # 左上角
        [right[0], right[1]- sub_y],  # 左上角
        [bottom[0]+sub_x, bottom[1]],  # 左上角
        [left[0] , left[1]+ sub_y],  # 左上角
    ], dtype="float32")

    # 转换源点数组为numpy数组
    src = np.array([top, right, bottom, left], dtype="float32")

    # 计算透视变换矩阵
    M = cv2.getPerspectiveTransform(src, dst)

    print(f"矩阵M={M}")

    # 执行透视变换
    warped = cv2.warpPerspective(image, M, (1050, 900))

    return warped

def main():
    global img, img_copy, points

    # 读取图像
    img = cv2.imread("images/trans/subRawImg.jpg")
    if img is None:
        print("无法加载图像，请检查路径是否正确")
        return

    img_copy = img.copy()

    # 创建窗口并设置鼠标回调
    cv2.namedWindow("Select Points")
    cv2.setMouseCallback("Select Points", mouse_callback)

    print("请按顺序点击选择四个点：上、右、下、左")
    print("选择完成后按任意键继续...")

    while True:
        cv2.imshow("Select Points", img_copy)
        key = cv2.waitKey(1) & 0xFF

        # 如果已经选择了4个点，按任意键继续
        if len(points) == 4:
            break

    # 执行透视变换
    warped = k_perspective_transform(img, points)

    # 显示结果
    cv2.imshow("Original Image", img)
    cv2.imshow("Transformed", warped)

    output_path="images/trans/_4point.jpg"
    cv2.imwrite(output_path, warped)
    print(f"图像已保存到 {output_path}")

    cv2.waitKey(0)
    cv2.destroyAllWindows()


if __name__ == "__main__":
    main()