convert_image_data.py

import os
import os.path
from os import listdir
from os.path import join, isdir

import cv2
import numpy as np

from images_utils import get_images_recursively


def imread(path):
  img_bgr = cv2.imread(path)
  img_rgb = img_bgr[..., ::-1]
  # img_hsl = convert_to_hsl(img_rgb)
  return img_rgb.astype(np.float)


def normalize_rgb(image):
  return np.array(image) / 127.5 - 1.


def is_normalized(image):
  for x, row in enumerate(image):
    for y, p in enumerate(row):
      if -1 > p[0] > 1 and -1 > p[1] > 1 and -1 > p[2] > 1:
        return False

  return True


def create_folder_is_not_exists(folder):
  if not os.path.exists(folder):
    os.mkdir(folder)


def convert_to_files(data_set):
  images_paths = get_images_recursively('data/' + data_set)

  data_set_rgb = data_set + '-rgb'
  # data_set_hsl = data_set + '-hsl'

  if not os.path.exists('data/' + data_set_rgb):
    os.mkdir('data/' + data_set_rgb)
    count = 0
    for image_path in images_paths:
      print('converting {} to RGB'.format(image_path))
      rgb_normalized = normalize_rgb(imread(image_path))
      np.save('data/' + data_set_rgb + '/' + str(count) + '.npy', rgb_normalized)
      count += 1

  # if not os.path.exists('data/' + data_set_hsl):
  #   os.mkdir('data/' + data_set_hsl)
  #   count = 0
  #   for image_path in images_paths:
  #     print('converting {} to HSL'.format(image_path))
  #     hsl = convert_to_hsl(imread(image_path))
  #     np.save('data/' + data_set_hsl + '/' + str(count) + '.npy', hsl)
  #     count += 1


folders = [f for f in listdir('data') if isdir(join('data', f))]

for data_set in folders:
  if not data_set.endswith('-rgb') and not data_set.endswith('-hsl'):
    convert_to_files(data_set)