cv2 resize
resized_image = cv2.resize(image, (100, 50))cv2 resize
resized_image = cv2.resize(image, (100, 50))cv2.resize()
import cv2
img = cv2.imread('/home/img/python.png', cv2.IMREAD_UNCHANGED)
print('Original Dimensions : ', img.shape)
scale_percent = 60 # percent of original size
width = int(img.shape[1] * scale_percent / 100)
height = int(img.shape[0] * scale_percent / 100)
dim = (width, height)
# resize image
resized = cv2.resize(img, dim, interpolation = cv2.INTER_AREA)
print('Resized Dimensions : ',resized.shape)
cv2.imshow("Resized image", resized)
cv2.waitKey(0)
cv2.destroyAllWindows()cv2 .resie
import cv2
cv2.resize(src, dsize[, dst[, fx[, fy[, interpolation]]]])
src [required] source/input image
dsize [required] desired size for the output image
fx [optional] scale factor along the horizontal axis
fy [optional] scale factor along the vertical axis
interpolation [optional] flag that takes one of the following methods. INTER_NEAREST – a nearest-neighbor
interpolation INTER_LINEAR – a bilinear interpolation (used by default) INTER_AREA – resampling using pixel area
relation. It may be a preferred method for image decimation, as it gives moire’-free results.
But when the image is zoomed,it is similar to the INTER_NEAREST method. INTER_CUBIC – a bicubic interpolation
over 4×4 pixel neighborhood INTER_LANCZOS4 – a Lanczos interpolation over 8×8 pixel neighborhoodCopyright © 2021 Codeinu
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