图片的横向全景拼接Python代码

以下是基于OpenCV库的Python代码实现图片的横向全景拼接：

import cv2
import numpy as np

# 读取图片列表
img_names = ['img1.jpg', 'img2.jpg', 'img3.jpg']

# 定义SIFT特征提取器
sift = cv2.xfeatures2d.SIFT_create()

# 定义FLANN匹配器
FLANN_INDEX_KDTREE = 0
flann_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5)
flann = cv2.FlannBasedMatcher(flann_params, {})

# 提取特征点和描述符
descriptors = []
keypoints = []
for name in img_names:
    img = cv2.imread(name)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    kp, des = sift.detectAndCompute(gray, None)
    descriptors.append(des)
    keypoints.append(kp)

# 匹配相邻两张图片
matches = []
for i in range(len(descriptors) - 1):
    matches.append(flann.knnMatch(descriptors[i], descriptors[i+1], k=2))

# 根据匹配结果计算变换矩阵
M = np.eye(3, 3, dtype=np.float32)
for match in matches:
    src_pts = np.float32([keypoints[i][m.queryIdx].pt for m in match]).reshape(-1, 1, 2)
    dst_pts = np.float32([keypoints[i+1][m.trainIdx].pt for m in match]).reshape(-1, 1, 2)
    M_, _ = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0)
    M = np.dot(M_, M)

# 计算全景图尺寸
h, w = cv2.imread(img_names[0]).shape[:2]
corners = np.array([[0, 0], [0, h-1], [w-1, h-1], [w-1, 0]], dtype=np.float32).reshape(-1, 1, 2)
corners = cv2.perspectiveTransform(corners, M)
x, y, w, h = cv2.boundingRect(corners)
pano_size = (w, h)

# 计算全景图
pano = cv2.warpPerspective(cv2.imread(img_names[0]), M, pano_size)
for name in img_names[1:]:
    img = cv2.imread(name)
    pano = cv2.warpPerspective(img, M, pano_size)
    mask = pano[:, :, 0] > 0
    pano[mask] = img[mask]

# 显示全景图
cv2.imshow('panorama', pano)
cv2.waitKey()
cv2.destroyAllWindows()

其中，`img_names`为待拼接的图片列表，`sift`为SIFT特征提取器，`flann`为FLANN匹配器，`descriptors`和`keypoints`分别为每张图片的特征描述符和特征点，`matches`为相邻两张图片之间的匹配结果，`M`为相邻两张图片之间的变换矩阵，`pano_size`为全景图的尺寸，`pano`为拼接后的全景图。