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- #BEST IMAGE RESIZER PYTHON HOW TO#
- #BEST IMAGE RESIZER PYTHON FREE#
- #BEST IMAGE RESIZER PYTHON WINDOWS#
The command will output (680, 850, 2) where 680 is the width, and 850 is the height in pixel size, while 2 is the image channel (RGB), or it means that the image has 680 rows and 850 columns. Shape ) to display the dimensions of our source image. Henceforth, we will use the image above in this paper. Let’s first try reading our image source and displaying it with the functions previously described.
#BEST IMAGE RESIZER PYTHON HOW TO#
As explained earlier in this article, we will learn how to apply resizing, cropping, and rotating techniques to images. Now we can go back to the original topic of basic image manipulation in OpenCV and Python. import cv2įor details on OpenCV Core Image Operations, please read the OpenCV documentation. To write / save images in OpenCV using a function cv2.imwrite()where the first parameter is the name of the new file that we will save and the second parameter is the source of the image itself. import cv2Ĭv2.imshow('Displaying Images', img) Writing / Saving Images Displaying an Imageĭisplaying an image in OpenCV using a function cv2.imshow()where the first parameter is the window name to display the image and the second parameter is the image itself.
#BEST IMAGE RESIZER PYTHON WINDOWS#
destroyAllWindows ( ) is to close other windows that are currently open. Whiskey ( 0 ) is to keep the window displaying the image. Also, don't forget to subscribe to the mailing list so that you don't miss any of the next articles.To read images in OpenCV, use a function cv2.imread()where the first parameter is the image file name complete with its extension.
#BEST IMAGE RESIZER PYTHON FREE#
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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. 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. 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.
![best image resizer python best image resizer python](https://miro.medium.com/max/1400/1*rG8gu1SSUcU_zQgEU78C4g.png)
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. Resizing with a Scaling Factor (Preserve Aspect Ratio)