Otherwise, feel free to use your own image. If you want to use the same image, simply right click on the image and save it. We are going to use the image of the fox above for this post. Load an Image Huli (狐狸) means fox in Mandarin. There are numerous guides here that cover topics, such as image processing, object detection, machine learning, etc. dsize: The output dimension of the image. The cv2.resize () function takes the following parameters. Another way is by mentioning a scaling factor. One way is by mentioning the output dimension directly. If you have any questions regarding OpenCV and its numerous applications, please check out this link. We can easily resize the image in two ways using the cv2.resize () function.
#Opencv resize how to
In today’s post, we are going to learn how to load images, perform color conversion, manipulate images by cropping and resizing, and how to save our new images.įor this tutorial, I used OpenCV 3.4.1 and Python 3.6. We will go over some of the basic ways you can alter/manipulate images, and in the next post we look at how to use bounding boxes to select areas of image and then fill in our picture frames. My walls in my own apartment are a little empty and I figured I could use OpenCV and Python to think about ways to decorate my walls with new pictures. If you are wondering what the wall is for, it is my blank canvas, my foundation if you will. Build an easy foundation for image manipulation using Python and OpenCV. So, with that simplicity in mind (and the sunshine beaming in) I figured today we would just keep things simple and focused. How, if we have a dream, it always seems like life has a way of trying to slow us down, stop us, or just muddle with our plans. 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. And it’s got me thinking about all the simple things in life. Also, don't forget to subscribe to the mailing list so that you don't miss any of the next articles.It’s 5 here in the morning in China and I am watching the sun rise. Please feel free to leave a comment in the section below. If you want to learn more about computer vision and image processing then check out my course Computer Vision with OpenCV and Python. This is useful when you want to resize your image by providing a specific width or height. Syntax: cv2.
#Opencv resize windows
This only works for created windows having flags other than CVWINDOWAUTOSIZE. The specified window size is for images excluding toolbars. You also learned how to use a scaling factor to preserve the aspect ratio while resizing the resulting image didn't look distorted.įinally, I showed you how to resize an image by preserving the aspect ratio without using a scaling factor. resizeWindow () method in Python OpenCV is used to resize window displaying images/videos to a specific size. In this tutorial, you learned how to resize an image using a custom width and height but the resulting image looked distorted. If we want to resize using a new width, we calculate the ratio using new_width/width and if we want to resize using a new height, we calculate the ratio using new_height/height. The ratio is equal to: ratio = new_width/width = new_height/height. We use this new width to calculate the ratio and we calculate the new height by multiplying the original height by the ratio. Let's say we want our new image to have a width of 400px. Ratio = new_width / width # (or new_height / height) # and compute the new height based on the aspect ratio # let's say we want the new width to be 400px So in order to do that, we need to calculate the aspect ratio of the original image and use it to resize the image. Usually, you don't want to set a scale factor, instead, you want to resize the image to a specific width or height, and you want the aspect ratio to be automatically maintained. Resizing with a Specific Width or Height (Preserve Aspect Ratio)
Here, we wanted our new image to be 60% of the original one, so we multiplied the width and height by 0.6. New_image = cv2.resize(image, dimensions, interpolation=cv2.INTER_LINEAR)Ĭv2.destroyAllWindows() Original shape: (400, 600, 3) # We want the new image to be 60% of the original image This way, you are sure that the aspect ratio of the original image will be the same as that of the new image. For example, if you want your new image to be half of the original image, then the scaling factor should be 0.5.
Basically, a scaling factor is a number by which you multiply the dimension of the image. We can resize an image by using a scaling factor. Sponsored Resizing with a Scaling Factor (Preserve Aspect Ratio)