print 'NEW RATIO = ', l_ratio l_x_size = l_ratio * l_size[0] l_y_size = l_ratio * l_size[1] l_image = l_im.resize( (l_x_size, l_y_size))else: l_done = Truel_image.show() print l_image.sizeTags: None nikie #2 Mar 27 '06, 12:45 AM Re: PIL & imag...
[Python][转载]比例缩放图片不变形 cv2importnumpy as np def resizeAndPad(img, size,padColor=0): h, w=img.shape[:2]sh, sw=size# interpolation methodifh>shor w>sw:# shrinking imageinterp=cv2.INTER_AREA else:# stretching imageinterp=cv2.INTER_CUBIC# aspect ratio of imageaspect=w / h# ...
open(filename) im_width, im_height = image.size if im_width > im_height: image = image.rotate(90, expand=1) im_width, im_height = image.size ratio = (PRINTER_HEIGHT/float(im_width)) height = int((float(im_height)*float(ratio))) image = image.resize((PRINTER_HEIGHT, height),...
0.4: Image resize command-line tool 0.5: Facial recognition cropping 0.6: Fill resizing mode 0.7: Resize using crop position 0.7.1: Resize using a single dimension, maintaining aspect ratio 0.7.2: Added filter and quality options 0.7.3: Support python 3 ...
Python Imaging Library (Fork). Contribute to python-pillow/Pillow development by creating an account on GitHub.
:param image: The image to resize and crop. :param size: The requested output size in pixels, given as a (width, height) tuple. :param method: Resampling method to use. Default is :py:attr:`PIL.Image.BICUBIC`. See :ref:`concept-filters`. :return: An image. """ im_ratio = image...
0.4: Image resize command-line tool 0.5: Facial recognition cropping 0.6: Fill resizing mode 0.7: Resize using crop position 0.7.1: Resize using a single dimension, maintaining aspect ratio 0.7.2: Added filter and quality options 0.7.3: Support python 3 0.7.4: Fixed cli for image generation...
resize((w,h),Image.ANTIALIAS) # normalize contrast im = ImageOps.autocontrast(im) # down to 3-bit im = ImageOps.posterize(im,3) # colorhack each 6-cell for i in range(w/2): for j in range(h/3): colorhack(im,i*2,j*3) # define gencode def gencode(self,image,x,y): "...
image.size[1])) < ratioDev: diff = int(self.image.size[1] * ratioDev) - self.image.size[0] self.image = ImageOps.expand(self.image, border=(int(diff / 2), 0), fill=self.fill) elif (float(self.image.size[0]) / float(self.image.size[1])) > ratioDev: diff = int(self....
size[1] ) calc_width = ( width / height ) * height_ratio calc_height = ( height / width ) * width_ratio if calc_width < min_width: new_height = ( height / width ) * min_width dim = min_width, int(new_height) out = ImageOps.fit(img, dim, Image.NEAREST, 0, (0.0,0.0))...