import torch
import torch.utils.data as data
import os
import pickle
import numpy as np
#import nltk
from PIL import Image
import os.path
import random


def load_dataset(N = 30000, NP = 1800):

	obstacles = np.zeros((N, 2800), dtype=np.float32)
	for i in range(0, N):
		temp = np.fromfile('/mnt/hgfs/Databases/dataset2/obs_cloud/obc'+str(i)+'.dat')
		temp = temp.reshape(len(temp)//2, 2)
		obstacles[i] = temp.flatten()

	
	return 	obstacles	
