Wsrtjtyk

I'm trying to overlay random images (natural scene images should be overlayed with sign images) using OpenCV and Python. They can vary in size, file extension and no. of channels (and many more, I guess). So I'm resizing the sign images according to the size of the natural scene image and put them onto the latter.

I have implemented fireant's code found here: overlay a smaller image on a larger image python OpenCv

But it only works for images with 4 channels.

Using cv2.addWeighted() always crops the larger image (scene image) to the size of the smaller image (sign image). Has anybody an idea how to do that? Help is highly appreciated.

EDIT: See the expected output below. At first the, escape route sign and the background are separate images.

And this is my code, it is working, but since a lot of my images seem to have only 3 channels, I would like to get it working for those also.

import cv2

import time

import math

import os



pathSigns = "/home/moritz/Schreibtisch/Signs"

pathScenes = "/home/moritz/Schreibtisch/Scenes"

i = 0



for fSigns in os.listdir(pathSigns):

    fSigns = os.path.join(pathSigns, fSigns)

    s_img = cv2.imread(fSigns, -1)



    for fScenes in os.listdir(pathScenes):

        try:

            l_img = cv2.imread(os.path.join(pathScenes, fScenes))

            l_height, l_width, l_channels = l_img.shape



            TARGET_PIXEL_AREA = (l_height * l_width) * 0.05



            ratio = float(s_img.shape[1]) / float(s_img.shape[0])

            s_new_h = int(math.sqrt(TARGET_PIXEL_AREA / ratio) + 0.5)

            s_new_w = int((s_new_h * ratio) + 0.5)



            s_img = cv2.resize(s_img,(s_new_w, s_new_h))



            x_offset=y_offset=50

            # l_img[y_offset:y_offset+s_img.shape[0], 

               x_offset:x_offset+s_img.shape[1]] = s_img



            y1, y2 = y_offset, y_offset + s_img.shape[0]

            x1, x2 = x_offset, x_offset + s_img.shape[1]



            height, width, channels = s_img.shape



            if channels <= 3:

                alpha_s = s_img[:, :, 2] / 255.0

                alpha_l = 1.0 - alpha_s

            else:

                alpha_s = s_img[:, :, 3] / 255.0

                alpha_l = 1.0 - alpha_s



            for c in range(0, 3):

                l_img[y1:y2, x1:x2, c] = (alpha_s * s_img[:, :, c] +

                  alpha_l * l_img[y1:y2, x1:x2, c])



            fResult = "/home/moritz/Schreibtisch/results/data_" + str(i) + 

                   ".png"

            i += 1

            cv2.imwrite(fResult, l_img)

        except IndexError:

            pass

thanks to @DanMašek hint and How to crop or remove white background from an image, I have worked out a solution. The following code will first remove white background from the smaller image, then set all images to 4 channels and then overlay the larger image with a smaller image. Works for me.

import cv2

import time

import math

import os

import numpy as np



pathSigns = "/home/moritz/Schreibtisch/Signs"

pathScenes = "/home/moritz/Schreibtisch/Scenes"

i = 0



for fSigns in os.listdir(pathSigns):

    fSigns = os.path.join(pathSigns, fSigns)

    s_img = cv2.imread(fSigns, -1)

    s_height, s_width, s_channels = s_img.shape



    # crop image

    gray = cv2.cvtColor(s_img, cv2.COLOR_BGR2GRAY)

    th, threshed = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY_INV)



    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (11,11))

    morphed = cv2.morphologyEx(threshed, cv2.MORPH_CLOSE, kernel)



    _, cnts, _ = cv2.findContours(morphed, cv2.RETR_EXTERNAL, 

    cv2.CHAIN_APPROX_SIMPLE)

    cnt = sorted(cnts, key=cv2.contourArea)[-1]

    x,y,w,h = cv2.boundingRect(cnt)

    s_img = s_img[y:y+h, x:x+w]



    # set channels to 4

    if s_channels < 4:

        s_img = cv2.cvtColor(s_img, cv2.COLOR_BGR2BGRA)



    for fScenes in os.listdir(pathScenes):

        try:

            l_img = cv2.imread(os.path.join(pathScenes, fScenes))

            l_height, l_width, l_channels = l_img.shape



            if l_channels < 4:

                l_img = cv2.cvtColor(l_img, cv2.COLOR_BGR2BGRA)



            TARGET_PIXEL_AREA = (l_height * l_width) * 0.05



            ratio = float(s_img.shape[1]) / float(s_img.shape[0])

            s_new_h = int(math.sqrt(TARGET_PIXEL_AREA / ratio) + 0.5)

            s_new_w = int((s_new_h * ratio) + 0.5)



            s_img = cv2.resize(s_img,(s_new_w, s_new_h))



            x_offset=y_offset=50



            y1, y2 = y_offset, y_offset + s_img.shape[0]

            x1, x2 = x_offset, x_offset + s_img.shape[1]



            alpha_s = s_img[:, :, 3] / 255.0

            alpha_l = 1.0 - alpha_s



            for c in range(0, 3):

                l_img[y1:y2, x1:x2, c] = (alpha_s * s_img[:, :, c] + alpha_l * 

                 l_img[y1:y2, x1:x2, c])



            fResult = "/home/moritz/Schreibtisch/results/data_" + str(i) + ".png"

            i += 1

            cv2.imwrite(fResult, l_img)

        except IndexError:

            pass