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datareader_preprocessed.py
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Sat, Oct 19, 23:48

datareader_preprocessed.py
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import pickle
import os
import pickle
import argparse
import time
import torch
from torch.autograd import Variable
import numpy as np
import project.data_utils as du
# all_files = os.listdir("test/") # imagine you're one directory above test dir
# print(all_files) #
'''
Reads preprocessed data. For each pedestrian, the coordinates are normalized and the coordinates of pedestrians in same frames are expressed
relatively to them
'''
#import utils
def DataPaths():
'''
returns the path of all videos for each scene
DataPaths[0] = biwi
DataPaths[1] = crowds
DataPaths[2] = mot
DataPaths[3] = stanford
'''
#biwi datasets Project/preprocessed_data/biwi/biwi_hotel.txt_5.txt
biwi_list = os.listdir('preprocessed_data/biwi')
#print(os.listdir('Project/preprocessed_data/biwi'))
#print(biwi_list, 'biwi list')
if 'Icon\r' in biwi_list: #remove the icon file
biwi_list.remove('Icon\r')
biwi_files = np.array(biwi_list) #
biwi_paths = np.array(['preprocessed_data/biwi/' + x for x in biwi_files])
#print(biwi_files,'biwi')
#crowds
crowds_list = os.listdir('preprocessed_data/crowds')
if 'Icon\r' in crowds_list: #remove the icon file
crowds_list.remove('Icon\r')
crowds_files = np.array(crowds_list) #
crowds_paths = np.array(['preprocessed_data/crowds/' + x for x in crowds_files])
#mot
mot_list = os.listdir('preprocessed_data/mot')
if 'Icon\r' in mot_list: #remove the icon file
mot_list.remove('Icon\r')
mot_files = np.array(mot_list) #
mot_paths = np.array(['preprocessed_data/mot/' + x for x in mot_files])
#stanford
stanford_list = os.listdir('preprocessed_data/stanford')
if 'Icon\r' in stanford_list: #remove the icon file
stanford_list.remove('Icon\r')
stanford_files = np.array(stanford_list) #
stanford_paths = np.array(['preprocessed_data/stanford/' + x for x in stanford_files])
path_dataset=[biwi_paths, crowds_paths, mot_paths, stanford_paths]
return path_dataset
class Pedestrian():
'''
Class of pedestrians, instanciated from data text files
Attributes:
frames: frames where the pedestrian appears
neighbors : other pedestrians in the frames
coords : coordinates of the pedestrian in each frame
neigh_coords: coordinates of the neighbors in each frame
'''
def __init__(self, pedID, frames, coords, neighbors, velocity):
self.pedID = pedID
self.frames = frames
self.coords = coords
self.neighbors = neighbors
self.velocity = velocity
def getPedID(self):
return self.pedID
def getFrames(self):
return self.frames
def getCoords(self):
return self.coords
def getNeighbors(self):
return self.neighbors
def getVelocity(self):
return self.velocity
def DataLoader(path_dataset):
'''
Returns a list of "Pedestrian" objects for each dataset passed as arg
'''
datalist = []
numpeds = len(path_dataset)
for directory in range(0,len(path_dataset)):
data = np.genfromtxt(path_dataset[directory], dtype = 'float')
pedID = data[0,1]
ped_data= data[np.where(data[:,1]==pedID)]
frames = np.asarray(ped_data[:,0])
coords = np.asarray(ped_data[:,2:4])
print(dtype(coords))
neighbors = data[np.where(data[:,1]!=pedID)]
velocity = du.computeVelocity(coords)
current_ped = Pedestrian(pedID, frames, coords, neighbors)
datalist.append(current_ped)
#print('Number of frames: %f' %len(frameList))
print('Number of pedestrians: %f' %numpeds)
return datalist

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