How do I get the SSIM between two directories that contained corresponding images?-CodePudding

I am trying to calculate the SSIM between corresponding images. For example, an image called 106.tif in the ground truth directory corresponds to a 'fake' generated image 106.jpg in the fake directory.

The ground truth directory absolute pathway is /home/pr/pm/zh_pix2pix/datasets/mousebrain/test/B The fake directory absolute pathway is /home/pr/pm/zh_pix2pix/output/fake_B

The images inside correspond to each other, like this:

Results

Highlighted differences

Similarity score

Image similarity 0.9639027981846681

Difference masks

Code

from skimage.metrics import structural_similarity
import cv2
import numpy as np

before = cv2.imread('5.jpg')
after = cv2.imread('6.jpg')

# Convert images to grayscale
before_gray = cv2.cvtColor(before, cv2.COLOR_BGR2GRAY)
after_gray = cv2.cvtColor(after, cv2.COLOR_BGR2GRAY)

# Compute SSIM between two images
(score, diff) = structural_similarity(before_gray, after_gray, full=True)
print("Image similarity", score)

# The diff image contains the actual image differences between the two images
# and is represented as a floating point data type in the range [0,1] 
# so we must convert the array to 8-bit unsigned integers in the range
# [0,255] before we can use it with OpenCV
diff = (diff * 255).astype("uint8")

# Threshold the difference image, followed by finding contours to
# obtain the regions of the two input images that differ
thresh = cv2.threshold(diff, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
contours = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contours = contours[0] if len(contours) == 2 else contours[1]

mask = np.zeros(before.shape, dtype='uint8')
filled_after = after.copy()

for c in contours:
    area = cv2.contourArea(c)
    if area > 40:
        x,y,w,h = cv2.boundingRect(c)
        cv2.rectangle(before, (x, y), (x   w, y   h), (36,255,12), 2)
        cv2.rectangle(after, (x, y), (x   w, y   h), (36,255,12), 2)
        cv2.drawContours(mask, [c], 0, (0,255,0), -1)
        cv2.drawContours(filled_after, [c], 0, (0,255,0), -1)

cv2.imshow('before', before)
cv2.imshow('after', after)
cv2.imshow('diff',diff)
cv2.imshow('mask',mask)
cv2.imshow('filled after',filled_after)
cv2.waitKey(0)