如何在python中调整输出图像的大小？

Question

嗨，我在 python 中运行这个模糊检测代码（来源：https://www.pyimagesearch.com/2015/09/07/blur-detection-with-opencv/）

# import the necessary packages
from imutils import paths
import argparse
import cv2

def variance_of_laplacian(image):
    # compute the Laplacian of the image and then return the focus
    # measure, which is simply the variance of the Laplacian
    return cv2.Laplacian(image, cv2.CV_64F).var()

# loop over the input images
for imagePath in paths.list_images("images/"):
    # load the image, convert it to grayscale, and compute the
    # focus measure of the image using the Variance of Laplacian
    # method
    image = cv2.imread(imagePath)
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    fm = variance_of_laplacian(gray)
    text = "Not Blurry"

    # if the focus measure is less than the supplied threshold,
    # then the image should be considered "blurry"
    if fm < 100:
        text = "Blurry"

        # show the image
    cv2.putText(image, "{}: {:.2f}".format(text, fm), (10, 30),
    cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 3)
    cv2.imshow("Image", image)
    print("{}: {:.2f}".format(text, fm))
    key = cv2.waitKey(0)

使用这个 2173 x 3161 的输入文件 input image

这是输出显示 the output image 图片已放大，未完整显示。

在源代码中，他们使用 450 x 600 px 的输入图像： input in source code 这是输出： output in source code

我认为图像的像素会影响输出。那么，我怎样才能得到像源代码中的输出一样的输出到所有图像？ 我必须调整输入图像的大小吗？如何？但如果我这样做我怕会影响他的模糊效果

Answer 1

摘自DOCUMENTATION。

有一种特殊情况，您已经可以创建一个窗口并稍后将图像加载到其中。在这种情况下，您可以指定窗口是否可调整大小。它是通过函数 cv2.namedWindow() 完成的。默认情况下，标志是 cv2.WINDOW_AUTOSIZE。但是如果你指定 flag 为 cv2.WINDOW_NORMAL，你可以调整窗口大小。当图像尺寸过大和在窗口中添加轨迹栏时会很有帮助。

我只是使用了问题中的代码，但添加了行 cv2.namedWindow("Image", cv2.WINDOW_NORMAL)，如 cmets 中所述。

# import the necessary packages
from imutils import paths
import argparse
import cv2

def variance_of_laplacian(image):
    # compute the Laplacian of the image and then return the focus
    # measure, which is simply the variance of the Laplacian
    return cv2.Laplacian(image, cv2.CV_64F).var()

# loop over the input images
for imagePath in paths.list_images("images/"):
    # load the image, convert it to grayscale, and compute the
    # focus measure of the image using the Variance of Laplacian
    # method
    image = cv2.imread(imagePath)
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    fm = variance_of_laplacian(gray)
    text = "Not Blurry"

    # if the focus measure is less than the supplied threshold,
    # then the image should be considered "blurry"
    if fm < 100:
        text = "Blurry"

        # show the image
    cv2.putText(image, "{}: {:.2f}".format(text, fm), (10, 30),
    cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 3)
    cv2.namedWindow("Image", cv2.WINDOW_NORMAL)       #---- Added THIS line
    cv2.imshow("Image", image)
    print("{}: {:.2f}".format(text, fm))
    key = cv2.waitKey(0)

Answer 2

如果您想使用与您给出的示例完全相同的分辨率，您可以使用 cv2.resize() https://docs.opencv.org/2.4/modules/imgproc/doc/geometric_transformations.html#resize 方法或（如果您想保持 x/y 坐标的比例）使用https://www.pyimagesearch.com/2015/02/02/just-open-sourced-personal-imutils-package-series-opencv-convenience-functions/中提供的imutils类

您仍然必须决定是否要先调整大小。灰度或调整大小的顺序无关紧要。

您可以添加的命令： resized_image = cv2.resize(image, (450, 600))