# Copyright 2021 Huawei Technologies Co., Ltd

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

#     http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

import os

import torch

import sys

import numpy as np

from PIL import Image

from tqdm import tqdm

from torchvision import transforms

from torchvision.transforms.functional import InterpolationMode





def get_img_path(img_folder):

    img_paths = []

    for root, dirs, files in os.walk(img_folder):

        for f in files:

            if f.endswith('.png'):

                print(os.path.join(root, f))

                img_paths.append(os.path.join(root, f))

    return img_paths



def flip(x, dim):

    xsize = x.size()

    dim = x.dim() + dim if dim < 0 else dim

    x = x.view(-1, *xsize[dim:])

    x = x.view(x.size(0), x.size(1), -1)[:, getattr(torch.arange(x.size(1)-1, 

                            -1, -1), ('cpu','cuda')[x.is_cuda])().long(), :]

    return x.view(xsize)



def _img_transform(image):

    image_transform = transforms.Compose([

        transforms.Resize((512,1024),InterpolationMode.BICUBIC),

        transforms.ToTensor()])

    image = image_transform(image)

    image *= 255.

    image = flip(image, 0)

    image -= np.array((104.00698793, 116.66876762, 122.67891434), dtype=np.float32).reshape(-1,1,1)

    return image



if __name__ == '__main__':

    cityscapes_path = sys.argv[1]

    bin_path = sys.argv[2]

    if os.path.exists(bin_path) is False:

        os.mkdir(bin_path)

        

    split = "val"

    img_folder = os.path.join(cityscapes_path, 'leftImg8bit/' + split)  

    img_paths = get_img_path(img_folder)

    

    for i in tqdm(range(len(img_paths))):

        filename = os.path.basename(img_paths[i])

        image = Image.open(img_paths[i]).convert('RGB')  # image shape: (W,H,3)

        image = _img_transform(image)  # image shape: (3,H,W) [0,1]

        image = torch.unsqueeze(image, 0)  # image shape: (1,3,H,W) [0,1]        

        image = np.array(image).astype(np.float32)

        image.tofile(os.path.join(bin_path, filename.split('.')[0] + '.bin')) # save bin