I'm trying to use OpenCV 2.1 to combine two images into one, with the two images placed adjacent to each other. In Python, I'm doing:
import numpy as np, cv
img1 = cv.LoadImage(fn1, 0)
img2 = cv.LoadImage(fn2, 0)
h1, w1 = img1.height,img1.width
h2, w2 = img2.height,img2.width
# Create an array big enough to hold both images next to each other.
vis = np.zeros((max(h1, h2), w1+w2), np.float32)
mat1 = cv.CreateMat(img1.height,img1.width, cv.CV_32FC1)
cv.Convert( img1, mat1 )
mat2 = cv.CreateMat(img2.height, img2.width, cv.CV_32FC1)
cv.Convert( img2, mat2 )
# Copy both images into the composite image.
vis[:h1, :w1] = mat1
vis[:h2, w1:w1+w2] = mat2
h,w = vis.shape
vis2 = cv.CreateMat(h, w, cv.CV_32FC3)
vis0 = cv.fromarray(vis)
cv.CvtColor(vis0, vis2, cv.CV_GRAY2BGR)
cv.ShowImage('test', vis2)
cv.WaitKey()
The two input images are:
https://code.ros.org/trac/opencv/browser/trunk/opencv/samples/c/box.png?rev=2270
https://code.ros.org/trac/opencv/browser/trunk/opencv/samples/c/box_in_scene.png?rev=2270
The resulting image is:
It may be hard to distinguish from the rest of the site, but most of the image is white, corresponding to where the individual images should be. The black area is where no image data was written.
Why is all my image data being converted to white?
This question is related to
python
image-processing
opencv
computer-vision
You can also use OpenCV's inbuilt functions cv2.hconcat
and cv2.vconcat
which like their names suggest are used to join images horizontally and vertically respectively.
import cv2
img1 = cv2.imread('opencv/lena.jpg')
img2 = cv2.imread('opencv/baboon.jpg')
v_img = cv2.vconcat([img1, img2])
h_img = cv2.hconcat([img1, img2])
cv2.imshow('Horizontal', h_img)
cv2.imshow('Vertical', v_img)
cv2.waitKey(0)
cv2.destroyAllWindows()
Horizontal Concatenation
Vertical Concatenation
The three best way to do it using a single line of code
import cv2
import numpy as np
img = cv2.imread('Imgs/Saint_Roch_new/data/Point_4_Face.jpg')
dim = (256, 256)
resizedLena = cv2.resize(img, dim, interpolation = cv2.INTER_LINEAR)
X, Y = resizedLena, resizedLena
# Methode 1: Using Numpy (hstack, vstack)
Fusion_Horizontal = np.hstack((resizedLena, Y, X))
Fusion_Vertical = np.vstack((newIMG, X))
cv2.imshow('Fusion_Vertical using vstack', Fusion_Vertical)
cv2.waitKey(0)
# Methode 2: Using Numpy (contanate)
Fusion_Vertical = np.concatenate((resizedLena, X, Y), axis=0)
Fusion_Horizontal = np.concatenate((resizedLena, X, Y), axis=1)
cv2.imshow("Fusion_Horizontal usung concatenate", Fusion_Horizontal)
cv2.waitKey(0)
# Methode 3: Using OpenCV (vconcat, hconcat)
Fusion_Vertical = cv2.vconcat([resizedLena, X, Y])
Fusion_Horizontal = cv2.hconcat([resizedLena, X, Y])
cv2.imshow("Fusion_Horizontal Using hconcat", Fusion_Horizontal)
cv2.waitKey(0)
import numpy as np, cv2
img1 = cv2.imread(fn1, 0)
img2 = cv2.imread(fn2, 0)
h1, w1 = img1.shape[:2]
h2, w2 = img2.shape[:2]
vis = np.zeros((max(h1, h2), w1+w2), np.uint8)
vis[:h1, :w1] = img1
vis[:h2, w1:w1+w2] = img2
vis = cv2.cvtColor(vis, cv2.COLOR_GRAY2BGR)
cv2.imshow("test", vis)
cv2.waitKey()
or if you prefer legacy way:
import numpy as np, cv
img1 = cv.LoadImage(fn1, 0)
img2 = cv.LoadImage(fn2, 0)
h1, w1 = img1.height,img1.width
h2, w2 = img2.height,img2.width
vis = np.zeros((max(h1, h2), w1+w2), np.uint8)
vis[:h1, :w1] = cv.GetMat(img1)
vis[:h2, w1:w1+w2] = cv.GetMat(img2)
vis2 = cv.CreateMat(vis.shape[0], vis.shape[1], cv.CV_8UC3)
cv.CvtColor(cv.fromarray(vis), vis2, cv.CV_GRAY2BGR)
cv.ShowImage("test", vis2)
cv.WaitKey()
in OpenCV 3.0 you can use it easily as follow:
#combine 2 images same as to concatenate images with two different sizes
h1, w1 = img1.shape[:2]
h2, w2 = img2.shape[:2]
#create empty martrix (Mat)
res = np.zeros(shape=(max(h1, h2), w1 + w2, 3), dtype=np.uint8)
# assign BGR values to concatenate images
for i in range(res.shape[2]):
# assign img1 colors
res[:h1, :w1, i] = np.ones([img1.shape[0], img1.shape[1]]) * img1[:, :, i]
# assign img2 colors
res[:h2, w1:w1 + w2, i] = np.ones([img2.shape[0], img2.shape[1]]) * img2[:, :, i]
output_img = res.astype('uint8')
For those who are looking to combine 2 color images into one, this is a slight mod on Andrey's answer which worked for me :
img1 = cv2.imread(imageFile1)
img2 = cv2.imread(imageFile2)
h1, w1 = img1.shape[:2]
h2, w2 = img2.shape[:2]
#create empty matrix
vis = np.zeros((max(h1, h2), w1+w2,3), np.uint8)
#combine 2 images
vis[:h1, :w1,:3] = img1
vis[:h2, w1:w1+w2,:3] = img2
Source: Stackoverflow.com