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saveDSToFile.py
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import numpy as np
from numpy import array
from scipy.misc import imresize
from os import listdir
from os.path import isfile, join
from cutImages import cut_image
from orbFeatures import read_feature
from PIL import Image
from sklearn.utils import shuffle
from tqdm import tqdm
import cPickle
saved_folder = 'images/'
def saveFolderToFiles_UECFOOD100(path, type, img_size):
for c in tqdm(range(1, 7)):
folder_images = []
folder_images_path = saved_folder + str(c) + type + str(img_size)
mypath = path + str(c) + "/"
onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))]
# print (len(onlyfiles), c)
for x in tqdm(onlyfiles):
if x == 'bb_info.txt':
continue
# img = cut_image(mypath + x)
# arr = array(img)
try:
# arr = read_feature(img)
image_path = mypath + x
im = Image.open(image_path)
arr = array(im)
# print ((mypath + x), type(arr), arr.shape)
# arr = from features
arr = imresize(arr, [img_size, img_size, 3])
# r = arr[:, :, 0].flatten()
# g = arr[:, :, 1].flatten()
# b = arr[:, :, 2].flatten()
label = [c]
# out = np.array(list(label) + list(r) + list(g) + list(b), np.int)
out = np.array(list(label) + list(arr.flatten()), np.int)
new = out / 255.
new[0] = c
folder_images.append(new)
except:
continue
np.save(folder_images_path, folder_images)
def read_images_UECFOOD100(path, type, img_size):
fullList = []
for c in tqdm(range(1, 101)):
mypath = path + str(c) + "/"
onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))]
# print (len(onlyfiles), c)
for x in tqdm(onlyfiles):
if x == 'bb_info.txt':
continue
# img = cut_image(mypath + x)
# arr = array(img)
try:
# arr = read_feature(img)
image_path = mypath + x
im = Image.open(image_path)
arr = array(im)
# print ((mypath + x), type(arr), arr.shape)
# arr = from features
arr = imresize(arr, [img_size, img_size, 3])
# r = arr[:, :, 0].flatten()
# g = arr[:, :, 1].flatten()
# b = arr[:, :, 2].flatten()
label = [c]
# out = np.array(list(label) + list(r) + list(g) + list(b), np.int)
out = np.array(list(label) + list(arr.flatten()), np.int)
new = out / 255.
new[0] = c
fullList.append(new)
except:
continue
shuffle(fullList)
images_list = np.array(fullList, dtype=float)
print ("images shape: {}".format(images_list.shape))
np.save('UECFOOD100_' + type + str(img_size), images_list)
return images_list
def read_images_food101(path):
return None
saveFolderToFiles_UECFOOD100("/media/aymen/DATA/datasets/UECFOOD100-test/", 'test', 244)