Plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))Ä®xample â 1: Resize the Image to Half By Calculating Pixel Size We can see the original size of the image is 800Ã534 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 â It uses Lanczos interpolation over an 8 x 8 pixel.cv2.INTER_CUBIC â It uses bicubic interpolation over a 4 x 4 pixel.cv2.INTER_AREA â It uses pixel area interpolation which is better used for downscaling the image.cv2.INTER_NEAREST â It uses nearest-neighbor interpolation, which is fast but produces blocky images.This is the default option in cv2.resize() cv2.INTER_LINEAR â 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 â Denotes the interpolation techniques, default is cv2.INTER_LINEAR Some Points to Consider about cv2.resize().fy â This denotes the scale factor along the y-axis.fx â This denotes the scale factor along the x-axis.dsize â The size of the output image, given as (width, height).src â 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. In this tutorial, we will explain how to scale and resize image in Python by using the OpenCV function cv2.resize(). 3.5 Example â 4: Scale Up the Image to Factor 2 (Double) Introduction.3.4 Example â 3: Resize the Image to Double By Calculating Pixel Size.3.3 Example â 2: Scaling Down the Image to Factor 0.5 (Half).3.2 Example â 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().Finally returns the center cropped image. Thrid line slices from the original image array that becomes cropped image array. RGB image read in OpenCV will be in shape: (height, width, channel). The first two lines will get coordinates required for slicing numpy array i.e. mid_x, mid_y = int(width/2), int(height/2) cw2, ch2 = int(crop_width/2), int(crop_height/2) crop_img = img return crop_img The last two lines choose the maximum dimension without exceeding the original image dimension. Crop dimensions passed in arguments may exceed the original dimension, this results in improper image cropping. The first line gets the width and height of the original image. width, height = img.shape, img.shape #process crop width and height for max available dimension crop_width = dim if dimcenter_crop(img, dim): """Returns center cropped image Args: img: image to be center cropped dim: dimensions (width, height) to be cropped from center """ So I created a function to crop from center to maximum dimension without exceeding the available dimension of the original image. I was working on a webcam and pi camera that had different resolutions. It is useful when dealing with many images with different resolutions, say for the computer vision or machine learning applications. Center crop is cropping an image from center which gives an equal padding on both sides vertically and horizontally.
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