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

我想用openCv和numpy找出python中两个视频文件的PSNR和SSIM.
如何在python中找到PSNR

我尝试下面的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)

解决方法:

您可以按帧读取视频帧,并使用此功能计算帧之间的相似性并找到平均值.

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,并且您不希望使用灰色图像,请通过

multichannel=True

标签：python,numpy,matplotlib,opencv,ssim
来源： https://codeday.me/bug/20191003/1847645.html