import cv2
import numpy as np
from matplotlib import pyplot as plt

if __name__ == "__main__":
    left_img = cv2.imread("left.jpg")
    right_img = cv2.imread("right.jpg")

    # 配准
    left_gray = cv2.cvtColor(left_img, cv2.COLOR_BGR2GRAY)
    right_gray = cv2.cvtColor(right_img, cv2.COLOR_BGR2GRAY)

    h, w = left_gray.shape
    print(f"图像尺寸: 宽度={w}像素, 高度={h}像素")

    template = left_gray[100:h - 100, w - 100:w]
    print(f"模板区域: 上边界=100, 下边界={h - 100}, 左边界={w - 100}, 右边界={w}")

    search_area = right_gray[:, :200]
    print(f"搜索区域: 宽度={200}, 高度={h}")

    res = cv2.matchTemplate(search_area, template, cv2.TM_CCOEFF_NORMED)
    min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
    print(f"匹配质量: {max_val:.4f} (1.0=完美匹配)")

    match_x, match_y = max_loc
    print(f"匹配位置: x={match_x}, y={match_y} (在搜索区域内)")

    dx = w - 100 - match_x
    dy = 100 - match_y
    print(f"计算平移量: dx={dx}, dy={dy}")

    # 拼接
    new_h, new_w = h + abs(dy), w + dx
    canvas = np.zeros((new_h, new_w, 3), dtype=np.uint8)
    left_mask = np.zeros((new_h, new_w), dtype=np.uint8)
    right_mask = np.zeros((new_h, new_w), dtype=np.uint8)
    iou = np.zeros((new_h, new_w), dtype=np.uint8)

    if dy >= 0:
        canvas[0:h, 0:w] = left_img
        canvas[dy:new_h, dx:new_w] = right_img

        left_mask[0:h, 0:w] = 255
        right_mask[dy:new_h, dx:new_w] = 255
        iou = cv2.bitwise_and(left_mask, right_mask)
    else:
        dy = -dy
        canvas[dy:new_h, 0:w] = left_img
        canvas[0:h, dx:new_w] = right_img

        left_mask[dy:new_h, 0:w] = 255
        right_mask[0:h, dx:new_w] = 255
        iou = cv2.bitwise_and(left_mask, right_mask)

    plt.subplot(221)
    plt.imshow(cv2.cvtColor(canvas, cv2.COLOR_BGR2RGB))

    plt.subplot(222)
    plt.imshow(iou, cmap='hot')

    plt.subplot(223)
    plt.imshow(left_mask, cmap='hot')

    plt.subplot(224)
    plt.imshow(right_mask, cmap='hot')

    plt.show()