and then it resizes this square image into desired size so the shape of original image content gets preserved. Resizes the container so that it contains n elements. it then places the original image at the center of the blank image. Usage: squared_image=get_square(image, size=(28,28))Įxplanation: function takes input of any size and it creates a squared shape blank image of size image's height or width whichever is bigger. def resize_image(img, size=(28,28)): h, w = img.shape c = img.shape if len(img.shape)>2 else 1 if h = w: return cv2.resize(img, size, cv2.INTER_AREA) dif = h if h > w else w interpolation = cv2.INTER_AREA if dif > (size+size)//2 else cv2.INTER_CUBIC x_pos = (dif - w)//2 y_pos = (dif - h)//2 if len(img.shape) = 2: mask = np.zeros((dif, dif), dtype=img.dtype) mask = img else: mask = np.zeros((dif, dif, c), dtype=img.dtype) mask = img return cv2.resize(mask, size, interpolation)
just pass the image and mention the size of square you want. If you have any other queries then you can contact us for getting more help.Try this simple function in python that uses OpenCV.
Hope you have liked this “how-to” tutorial. But I will prefer you to use cv2.resize() method for it. Basic image processing techniques do not give good results as they do not. When increasing the dimensions of an image, the extra pixels need to be interpolated somehow. Follow this blog to learn the options for Super Resolution in OpenCV. There are also other python modules that allow you to resize an image. Super-resolution refers to the process of upscaling or improving the details of the image. It is consist of the interpolation parameter, which also plays an important role in resizing. You can verify the size of the image using the resized_img_with_scaling.shape. We can rescale the image using OpenCV using cv2.resize(). Resized_img_with_scaling = cv2.resize(img,(width,height)) Scaling allows you to adjust the image proportionally so that it looks good. If you look at the above-resized image, then you will see the image is not look good after the resizing. Variable alteredsize resizes the image using cv2.resize() function, the interpolation method used here is cv2.INTERAREA, which is basically used to shrink. If you print the shape of the image then you will get the output as below. The implementation of cv::cuda::resize with linear interpolation does not use NPP and is aligned with GPU texture unit implementation to reuse it for some cases. 1import cv2 2 3src cv2.imread(D:/cv2-resize-image-original.png, cv2.IMREADUNCHANGED) 4 5percent by which the image is resized 6scalepercent 50 7. Output Resized Image of 600×500 dimension Hackathon findings on the problem: The issue is reproducible with OpenCV 3.4.10 and 4.3.0 (contrib master) too. Then I will pass these dimensions inside the resize() method. Suppose I want to resize the image to 500×600 pixels. If you print the shape of the original image then you will get a width of 1280 and a height of 960. Output Sample image for implementing cv2 resize Step 3: Resize the image using cv2.resize() methodĪfter reading the image in step 2, in this section, I will resize the image using the resize() method. def readimage (imgpath): print (imgpath) img cv2.imread (imgpath) img cv2.resize (img, (128, 128)) return img for file in tqdm (glob. I used the following function in a loop to resize in Python using OpenCV. I want to resize these images to 128x128. There is a method in OpenCV for it and that is the cv2.imread() method. I have a lot of image files in a folder (5M+). Now before resizing the image you have to read the image. The statement %matplotlib inline allows you to display all the images in inline. Make sure that you also do all the work on it for a better understanding. Please note that I am executing all examples in the Jupyter notebook. The matplotlib module will be used for displaying the image. In our example, I am using the OpenCV module and the matplotlib python module. The first and basic step is to import all the necessary libraries. dsize is the desired size of the output image. The syntax of the cv2.resize () function is: cv2.resize(src, dsize, fx, fy, interpolation) Where: src is the source of the image. It takes the original image, modifies it, and returns a new image. Steps to Implement cv2 reize() method in python Step 1: Import all the necessary libraries To resize images with OpenCV, use the cv2.resize () function.
#Opencv resize how to#
In this entire tutorial, you will know how to scale and resize an image using the OpenCV cv2 resize() method with step by step. Do you want to resize an image in python using cv2.