def load_and_prepare_image()

in eval_retrieval.py [0:0]

• 18 lines of code
• 7 McCabe index (conditional complexity)

    def load_and_prepare_image(self, fname, roi=None):
        # Read image, get aspect ratio, and resize such as the largest side equals S
        im = Image.open(fname)
        im_size_hw = np.array((im.size[1], im.size[0]))
        if self.S == -1:
            ratio = 1.0
        elif self.S == -2:
            if np.max(im_size_hw) > 124:
                ratio = 1024.0/np.max(im_size_hw)
            else:
                ratio = -1
        else:
            ratio = float(self.S)/np.max(im_size_hw)
        new_size = tuple(np.round(im_size_hw * ratio).astype(np.int32))
        im_resized = self.transforms(im.resize((new_size[1], new_size[0]), Image.BILINEAR))
        # If there is a roi, adapt the roi to the new size and crop. Do not rescale
        # the image once again
        if roi is not None:
            # ROI format is (xmin,ymin,xmax,ymax)
            roi = np.round(roi * ratio).astype(np.int32)
            im_resized = im_resized[:, roi[1]:roi[3], roi[0]:roi[2]]
        return im_resized