CODEWITHSUNDEEP
pythonimageopencvimage-processingcomputer-vision
Neil Vicker
Neil Vicker

Reputation: 99

Stitching images together Opencv -Python

My program takes in an image and crops the image into seperate images according to the scale parameter, e.g. scale = 3 produces 9 images of equal size. I then work out mean rgb of each cropped image and set all pixel values in the image equal to the mean rgb value.

I am wondering how I can stich the cropped images back together to output one image? Which in this case would be a grid of nine different colours.

Here is my code:

# import packages
import numpy as np
import cv2
import dateutil
import llist
from matplotlib import pyplot as plt
import argparse

#Read in image
img = cv2.imread('images/0021.jpg')

scale = 3
#Get x and y components of image
y_len,x_len,_ = img.shape

mean_values = []
for y in range(scale):
    for x in range(scale):
        #Crop image 3*3 windows
        cropped_img=img[(y*y_len)/scale:((y+1)*y_len)/scale,
                          (x*x_len)/scale:((x+1)*x_len)/scale]

        mean_val=cv2.mean(cropped_img)
        mean_val=mean_val[:3]
        #Set cropped img pixels equal to mean RGB
        cropped_img[:,:,:] = mean_val

        cv2.imshow('cropped',cropped_img)
        cv2.waitKey(0)

        #Print mean_values array
        #mean_values.append([mean_val])
#mean_values=np.asarray(mean_values)
#print mean_values.reshape(3,3,3)

As it stands the nested for loop iterates over the image and outputs the images (which are just blocks of one colour) in the order that I want to stitch them together, but im not sure how to achieve this.

Upvotes: 3

Views: 1236

Answers (1)

Mark Setchell
Mark Setchell

Reputation: 207345

I don't know if such things exist in OpenCV, but in ImageMagick you can simply resize the image down to the tile-size (which will implicitly average the pixels) and the re-scale the image back up to the original size without interpolation - also called Nearest Neighbour Resampling. Like this:

enter image description here

# Get original width and height
identify -format "%wx%h" face1.jpg
500x529

# Resize down to, say 10x10 and then back up to the original size
convert face1.jpg -resize 10x10! -scale "${geom}"! out.jpg

enter image description here

Per your original, 3x3 becomes:

convert face1.jpg -resize 3x3! -scale "${geom}"! out.jpg

enter image description here

and 3x5 becomes:

convert face1.jpg -resize 3x5! -scale "${geom}"! out.jpg

enter image description here

Upvotes: 2

Related Questions