def __getitem__(self, index):
    left_img = self.load_image(os.path.join(self.datapath, self.left_filenames[index]))
    right_img = self.load_image(os.path.join(self.datapath, self.right_filenames[index]))
    disparity = self.load_disp(os.path.join(self.datapath, self.disp_filenames[index]))
    if self.training:
        (w, h) = left_img.size
        (crop_w, crop_h) = (512, 256)
        x1 = random.randint(0, (w - crop_w))
        y1 = random.randint(0, (h - crop_h))
        left_img = left_img.crop((x1, y1, (x1 + crop_w), (y1 + crop_h)))
        right_img = right_img.crop((x1, y1, (x1 + crop_w), (y1 + crop_h)))
        disparity = disparity[y1:(y1 + crop_h), x1:(x1 + crop_w)]
        processed = get_transform()
        left_img = processed(left_img)
        right_img = processed(right_img)
        return {'left': left_img, 'right': right_img, 'disparity': disparity}
    else:
        (w, h) = left_img.size
        (crop_w, crop_h) = (960, 512)
        left_img = left_img.crop(((w - crop_w), (h - crop_h), w, h))
        right_img = right_img.crop(((w - crop_w), (h - crop_h), w, h))
        disparity = disparity[(h - crop_h):h, (w - crop_w):w]
        processed = get_transform()
        left_img = processed(left_img)
        right_img = processed(right_img)
        return {'left': left_img, 'right': right_img, 'disparity': disparity, 'top_pad': 0, 'right_pad': 0, 'left_filename': self.left_filenames[index]}
def __getitem__(self, index):
    left_img = self.load_image(os.path.join(self.datapath, self.left_filenames[index]))
    right_img = self.load_image(os.path.join(self.datapath, self.right_filenames[index]))
    disparity = self.load_disp(os.path.join(self.datapath, self.disp_filenames[index]))
    if self.training:
        (w, h) = left_img.size
        (crop_w, crop_h) = (512, 256)
        x1 = random.randint(0, (w - crop_w))
        y1 = random.randint(0, (h - crop_h))
        left_img = left_img.crop((x1, y1, (x1 + crop_w), (y1 + crop_h)))
        right_img = right_img.crop((x1, y1, (x1 + crop_w), (y1 + crop_h)))
        disparity = disparity[y1:(y1 + crop_h), x1:(x1 + crop_w)]
        processed = get_transform()
        left_img = processed(left_img)
        right_img = processed(right_img)
        return {'left': left_img, 'right': right_img, 'disparity': disparity}
    else:
        (w, h) = left_img.size
        (crop_w, crop_h) = (960, 512)
        left_img = left_img.crop(((w - crop_w), (h - crop_h), w, h))
        right_img = right_img.crop(((w - crop_w), (h - crop_h), w, h))
        disparity = disparity[(h - crop_h):h, (w - crop_w):w]
        processed = get_transform()
        left_img = processed(left_img)
        right_img = processed(right_img)
        return {'left': left_img, 'right': right_img, 'disparity': disparity, 'top_pad': 0, 'right_pad': 0, 'left_filename': self.left_filenames[index]}