在 openCV 中的特定坐标处将图像显示在另一图像上

Question

我正在尝试在特定坐标处将一个图像显示在另一个图像上。我已使用网络摄像头检测到 aruco 标记，并且我想在 aruco 标记上显示另一个图像。 aruco 标记可以移动，并且覆盖的图像应与标记一起移动。

有各种绘图功能以及将文本输入到图像中。我尝试过图像叠加和图像单应性。

我可以获得角点的坐标。 有没有什么函数可以在这些坐标处插入图像？

import cv2
import cv2.aruco as aruco
import glob

markerLength = 0.25

cap = cv2.VideoCapture(0)

criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)

objp = np.zeros((6*7,3), np.float32)
objp[:,:2] = np.mgrid[0:7,0:6].T.reshape(-1,2)

objpoints = [] 
imgpoints = []

images = glob.glob('calib_images/*.jpg')

for fname in images:
    img = cv2.imread(fname)
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

    ret, corners = cv2.findChessboardCorners(gray, (7,6),None)

    if ret == True:
        objpoints.append(objp)

        corners2 = cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)
        imgpoints.append(corners2)
        img = cv2.drawChessboardCorners(img, (7,6), corners2,ret)


ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1],None,None)

calibrationFile = "calibrationFileName.xml"
calibrationParams = cv2.FileStorage(calibrationFile, cv2.FILE_STORAGE_READ) 
camera_matrix = calibrationParams.getNode("cameraMatrix").mat() 
dist_coeffs = calibrationParams.getNode("distCoeffs").mat() 

while(True):
    ret, frame = cap.read()

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    aruco_dict = aruco.Dictionary_get(aruco.DICT_6X6_250)
    arucoParameters =  aruco.DetectorParameters_create()

    corners, ids, rejectedImgPoints = aruco.detectMarkers(gray, aruco_dict, parameters=arucoParameters)
    if np.all(ids != None):
        rvec, tvec, _ = aruco.estimatePoseSingleMarkers(corners, markerLength, mtx, dist) 
        axis = aruco.drawAxis(frame, mtx, dist, rvec, tvec, 0.3) 
        print(ids)
        display = aruco.drawDetectedMarkers(axis, corners)
        display = np.array(display)
    else:
        display = frame

    cv2.imshow('Display',display)
    if cv2.waitKey(1) & 0xFF == ord('q'):
            break

cap.release()
cv2.destroyAllWindows()```

Answer 1

替换图像的一部分

import cv2
import numpy as np

img1 = cv2.imread('Desert.jpg')
img2 = cv2.imread('Penguins.jpg')

img3 = img1.copy()
# replace values at coordinates (100, 100) to (399, 399) of img3 with region of img2
img3[100:400,100:400,:] = img2[100:400,100:400,:]
cv2.imshow('Result1', img3)

对两个图像进行 Alpha 混合

alpha = 0.5
img3 = np.uint8(img1*alpha + img2*(1-alpha))
cv2.imshow('Result2', img3)

Answer 2

@user8190410 的答案效果很好。只是为了给出一个完整的答案，为了在特定位置对两个不同大小的图像进行 alpha 混合，您可以执行以下操作：

alpha= 0.7
img1_mod = img1.copy()
img1_mod[:pos_x,:pos_y,:] = img1[:pos_x,:pos_y,:]*alpha + img2*(1-alpha)
cv2.imshow('Image1Mod', img1_mod)

Answer 3

实际上，我发现可以使用图像单应性来做到这一点。 这是更新后的代码。

import numpy as np
import cv2
import cv2.aruco as aruco

cap = cv2.VideoCapture(0)

while(True):
    ret, frame = cap.read()

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    aruco_dict = aruco.Dictionary_get(aruco.DICT_6X6_250)
    arucoParameters =  aruco.DetectorParameters_create()

    corners, ids, rejectedImgPoints = aruco.detectMarkers(gray, aruco_dict, parameters=arucoParameters)
    if np.all(ids != None):
        display = aruco.drawDetectedMarkers(frame, corners)
        x1 = (corners[0][0][0][0], corners[0][0][0][1]) 
        x2 = (corners[0][0][1][0], corners[0][0][1][1]) 
        x3 = (corners[0][0][2][0], corners[0][0][2][1]) 
        x4 = (corners[0][0][3][0], corners[0][0][3][1])  

        im_dst = frame 
        im_src = cv2.imread("mask.jpg")
        size = im_src.shape
        pts_dst = np.array([x1,x2,x3,x4])
        pts_src = np.array(
                       [
                        [0,0],
                        [size[1] - 1, 0],
                        [size[1] - 1, size[0] -1],
                        [0, size[0] - 1 ]
                        ],dtype=float
                       );


        h, status = cv2.findHomography(pts_src, pts_dst)
        temp = cv2.warpPerspective(im_src, h, (im_dst.shape[1],im_dst.shape[0])) 
        cv2.fillConvexPoly(im_dst, pts_dst.astype(int), 0, 16);
        im_dst = im_dst + temp  
        cv2.imshow('Display',im_dst) 
    else:
        display = frame
        cv2.imshow('Display',display)
    if cv2.waitKey(1) & 0xFF == ord('q'):
            break

cap.release()
cv2.destroyAllWindows()

Answer 4

画中画

[![import cv2
import numpy as np

def picture_in_picture(main_image_path, overlay_image_path, img_ratio=4, border_size=5, x_margin=25, y_offset_adjust=-150):
    """
    Overlay an image onto a main image with a white border.
    
    Args:
        main_image_path (str): Path to the main image.
        overlay_image_path (str): Path to the overlay image.
        img_ratio (int): The ratio to resize the overlay image height relative to the main image.
        border_size (int): Thickness of the white border around the overlay image.
        x_margin (int): Margin from the right edge of the main image.
        y_offset_adjust (int): Adjustment for vertical offset.

    Returns:
        np.ndarray: The resulting image with the overlay applied.
    """
    # Load images
    main_image = cv2.imread(main_image_path)
    overlay_image = cv2.imread(overlay_image_path)

    if main_image is None or overlay_image is None:
        raise FileNotFoundError("One or both images not found.")

    # Resize the overlay image to 1/img_ratio of the main image height
    new_height = main_image.shape\[0\] // img_ratio
    new_width = int(new_height * (overlay_image.shape\[1\] / overlay_image.shape\[0\]))
    overlay_resized = cv2.resize(overlay_image, (new_width, new_height))

    # Add a white border to the overlay image
    overlay_with_border = cv2.copyMakeBorder(
        overlay_resized,
        border_size, border_size, border_size, border_size,
        cv2.BORDER_CONSTANT, value=\[255, 255, 255\]
    )

    # Determine overlay position
    x_offset = main_image.shape\[1\] - overlay_with_border.shape\[1\] - x_margin
    y_offset = (main_image.shape\[0\] // 2) - overlay_with_border.shape\[0\] + y_offset_adjust

    # Overlay the image
    main_image\[y_offset:y_offset + overlay_with_border.shape\[0\], x_offset:x_offset + overlay_with_border.shape\[1\]\] = overlay_with_border

    return main_image

# Usage example
result_image = picture_in_picture("points_img.jpg", "points_img.jpg")
cv2.imshow("Image with Picture-in-Picture", result_image)
cv2.imwrite("output_image_with_border.jpg", result_image)
cv2.waitKey(0)
cv2.destroyAllWindows()][1]][1]