I have a dataset of hand drawings and i needed to create small square images from asymmetric drawings. If input_aspect_ratio = res_aspect_ratio: If input_aspect_ratio < res_aspect_ratio: If input_aspect_ratio > res_aspect_ratio: Then it resizes the input image to the destination width or height, and then cropping in the x or y (each depending on if ratio of aspect ratios). It works by first choosing whether to crop in the y or x by comparing the input image aspect ratio to the destination aspect ratio. I've just run into the same issue while preparing a dataset for a neural net, and in order to avoid having to distort the image, I've made a function which resizes and crops the image minimally to fit the destination size. Letter_box, col_start:col_start + image_resized.shape] = image_resized Row_start = int((letter_box.shape - image_resized.shape) / 2)Ĭol_start = int((letter_box.shape - image_resized.shape) / 2) Letter_box = np.zeros((int(rows), int(cols), 3)) Image_resized = cv2.resize(image, dsize=(0, 0), fx=ratio, fy=ratio) :return: numpy.ndarray((rows, cols, channels), dtype=numpy.uint8) :param cols: int cols of letter boxed image returned :param rows: int rows of letter boxed image returned :param image: numpy.ndarray((image_rows, image_cols, channels), dtype=numpy.uint8) On widescreen) if not same aspect ratio as specified rows and cols.
#Resize image cv2 movie
Letter box (black bars) a color image (think pan & scan movie shown import cv2ĭef resize_and_letter_box(image, rows, cols): and then it resizes this square image into desired size so the shape of original image content gets preserved.ĭoes not quite align with what the original question is asking, but I landed here searching for an answer to a similar question. It then places the original image at the center of the blank image. Squared_image=get_square(image, size=(28,28))įunction takes input of any size and it creates a squared shape blank image of size image's height or width whichever is bigger. Return cv2.resize(mask, size, interpolation)
Mask = np.zeros((dif, dif, c), dtype=img.dtype)
Mask = np.zeros((dif, dif), dtype=img.dtype) Interpolation = cv2.INTER_AREA if dif > (size+size)//2 else Return cv2.resize(img, size, cv2.INTER_AREA) def resize_image(img, size=(28,28)):Ĭ = img.shape if len(img.shape)>2 else 1 just pass the image and mention the size of square you want. Try this simple function in python that uses OpenCV.
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