# 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 numpy as np
import torch
import torchvision.transforms as transforms
import argparse
from PIL import Image
from tqdm import tqdm

def preprocess(src_path, save_path):
    if not os.path.exists(save_path):
        os.makedirs(save_path)
    
    normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
    preprocess = transforms.Compose([
        transforms.Scale(256),
        transforms.CenterCrop(224),
        transforms.ToTensor(),
        normalize,
    ])

    i = 0
    in_files = os.listdir(src_path)
    for file in tqdm(in_files):
        i = i + 1
        input_image = Image.open(src_path + '/' + file).convert('RGB')
        input_tensor = preprocess(input_image)
        img = np.array(input_tensor).astype(np.float32)
        img.tofile(os.path.join(save_path, file.split('.')[0] + ".bin"))

if __name__ == '__main__':
    paser = argparse.ArgumentParser(description="Script to preprocess data.")
    paser.add_argument('-s', type=str, help='dirctory of raw data')
    paser.add_argument('-d', type=str, help='dirctory of preprocessed data')
    args = paser.parse_args()
    preprocess(args.s, args.d)