import numpy as np
import os
from matplotlib.pyplot import imshow
from PIL import Image
%matplotlib inline
Information on the NTIRE dehazing competition can be found:
Registration is required to access the images. This script save the images in numpy array. Another script contains the dataloader, to load the numpy arrays and prepare them to train learning algorithms.
folder = "./data/dehazing/NN-HAZE_train/GT"
onlyfiles = [f for f in os.listdir(folder) if os.path.isfile(os.path.join(folder, f))]
print("Working with {0} images".format(len(onlyfiles)))
print("Image examples: ")
train_gt = []
for i in range(len(onlyfiles)):
#for i in range(40, 42):
print(onlyfiles[i])
pil_im = Image.open(folder + "/" + onlyfiles[i], 'r')
#imshow(np.asarray(pil_im))
#display(Image(filename=folder + "/" + onlyfiles[i], width=240, height=320))
#pil_im.show() # open image outside of the notebook
#print(pil_im.size)
#width, height = pil_im.size
np_im = np.array(pil_im)
#np_im = np_im.reshape((3, width, height))
train_gt.append(np_im)
#print(np.size(np_im))
train_gt = np.array(train_gt)
print(train_gt.size)
print('Saving train ground-truth data')
np.save('./data/dehazing/train_gt.npy', train_gt)
folder = "./data/dehazing/NN-HAZE_train/HAZY"
onlyfiles = [f for f in os.listdir(folder) if os.path.isfile(os.path.join(folder, f))]
print("Working with {0} images".format(len(onlyfiles)))
print("Image examples: ")
train_hazy = []
for i in range(len(onlyfiles)):
#for i in range(40, 42):
print(onlyfiles[i])
pil_im = Image.open(folder + "/" + onlyfiles[i], 'r')
#pil_im.show() # open image outside of the notebook
#print(pil_im.size)
np_im = np.array(pil_im)
train_hazy.append(np_im)
train_hazy = np.array(train_hazy)
print(train_hazy.size)
print('Saving train hazy data')
np.save('./data/dehazing/train_data.npy', train_hazy)
folder = "./data/dehazing/NN-HAZE_val/HAZY"
onlyfiles = [f for f in os.listdir(folder) if os.path.isfile(os.path.join(folder, f))]
print("Working with {0} images".format(len(onlyfiles)))
print("Image examples: ")
val_hazy = []
for i in range(len(onlyfiles)):
#for i in range(40, 42):
print(onlyfiles[i])
pil_im = Image.open(folder + "/" + onlyfiles[i], 'r')
#pil_im.show() # open image outside of the notebook
print(pil_im.size)
np_im = np.array(pil_im)
val_hazy.append(np_im)
val_hazy = np.array(val_hazy)
print(val_hazy.size)
print('Saving validation hazy data')
np.save('./data/dehazing/val_data.npy', val_hazy)