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#CV2 RESIZE IMAGE HOW TO#

Img_double = cv2.resize(img, (new_width, new_height)) It can be seen that the width and height of the new image are double of the original image. To double the image size, first, the pixel size of width and height for the new image are calculated and then they are passed to the cv2 resize() function. In : img_half = cv2.resize(img, None, fx = 0.5, fy = 0.5)Įxample – 3: Resize the Image to Double By Calculating Pixel Size In this case, there is no need to calculate the pixel size of the new image. This is another way of resizing the image to half by passing the value of x-axis and y-axis factor parameters as 0.5 to the cv2 resize function. Plt.imshow(cv2.cvtColor(img_half, cv2.COLOR_BGR2RGB))Įxample – 2: Scaling Down the Image to Factor 0.5 (Half) Img_half = cv2.resize(img, (new_width, new_height)) In : #Calculating the Pixel Size for Resizing It can be seen that the width and height of the new image are half of the original image. To resize the image to half, we first calculate the pixel size of width and height for the new image and then pass it to cv2 resize() function. Plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))Įxample – 1: Resize the Image to Half By Calculating Pixel Size We can see the original size of the image is 800×534 Next, we will read a sample image for our example and display it. Import matplotlib.pyplot as plt Read Sample Image and Display Let us start by importing the OpenCV library as shown below. Examples of cv2.resize() in Python OpenCV Neighborhood, it produces the highest quality but is slow.

cv2.INTER_LANCZOS4 – It uses Lanczos interpolation over an 8 x 8 pixel.

cv2.INTER_CUBIC – It uses bicubic interpolation over a 4 x 4 pixel.

cv2.INTER_AREA – It uses pixel area interpolation which is better used for downscaling the image.

cv2.INTER_NEAREST – It uses nearest-neighbor interpolation, which is fast but produces blocky images.

This is the default option in cv2.resize()

cv2.INTER_LINEAR – It uses bilinear interpolation, which is preferably used for scaling up the image to a larger size.

And when the image is scaled down it needs to This is because when the image is scaled up it needs more pixels to fill up the spaces between actual pixels. To resize the image, the cv2 resize() function uses interpolation for resizing. Interpolation Parameters for cv2.resize()

fx and fy are good options if you want to scale the image with a factor.

But for this, you will have to calculate the width and height of the resized image beforehand.

dsize parameter can be used to specify the exact image size.You may use either dsize or both fx and fy to resize the image.interpolation – Denotes the interpolation techniques, default is cv2.INTER_LINEAR Some Points to Consider about cv2.resize().fy – This denotes the scale factor along the y-axis.fx – This denotes the scale factor along the x-axis.dsize – The size of the output image, given as (width, height).src – This is the input image that needs to be resized.Resizing Image using OpenCV : cv2.resize() SyntaxĬv2.resize(src, dsize, fx, fy, interpolation) Then we will see various examples of resizing the images using this function. We shall first cover the syntax of cv2.resize() and understand its various parameters and options.

#CV2 RESIZE IMAGE HOW TO#

In this tutorial, we will explain how to scale and resize image in Python by using the OpenCV function cv2.resize(). 3.5 Example – 4: Scale Up the Image to Factor 2 (Double) Introduction.3.4 Example – 3: Resize the Image to Double By Calculating Pixel Size.3.3 Example – 2: Scaling Down the Image to Factor 0.5 (Half).3.2 Example – 1: Resize the Image to Half By Calculating Pixel Size.3 Examples of cv2.resize() in Python OpenCV.2.3 Interpolation Parameters for cv2.resize().2.2 Some Points to Consider about cv2.resize().2 Resizing Image using OpenCV : cv2.resize().