如何使用openCV和其他库在python中找到两个视频文件的PSNR和SSIM？

Question

我想使用 openCv 和 numpy 在 python 中找出两个视频文件的 PSNR 和 SSIM。 如何在python中找到PSNR

我尝试了下面的 SSIM 代码

# compute the Structural Similarity Index (SSIM) between the two
# images, ensuring that the difference image is returned
(score, diff) = compare_ssim(grayA, grayB, full=True)
diff = (diff * 255).astype("uint8")
print("SSIM: {}".format(score))

# 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]
cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
        cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if imutils.is_cv2() else cnts[1]

# loop over the contours

for c in cnts:
        # compute the bounding box of the contour and then draw the
        # bounding box on both input images to represent where the two
        # images differ
        (x, y, w, h) = cv2.boundingRect(c)
        cv2.rectangle(imageA, (x, y), (x + w, y + h), (0, 0, 255), 2)
        cv2.rectangle(imageB, (x, y), (x + w, y + h), (0, 0, 255), 2)

Answer 1

您可以逐帧读取视频并使用此函数计算帧之间的相似度并找到平均值。

确保提供图像的完整路径。

def compare(ImageAPath, ImageBPath):
    img1 = cv2.imread(ImageAPath)          # queryImage
    img2 = cv2.imread(ImageBPath)
    image1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
    image2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)          # trainImage


    score, diff = compare_ssim(image1, image2, full=True,  multichannel=False)
    print("SSIM: {}".format(score))

如果您的图像是彩色的并且您不想使用灰色图像，请通过

multichannel=True