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data_utils.py
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Thu, Sep 26, 23:54

data_utils.py
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import numpy as np
import torch
import random
def computeVelocity(coords, timestep=4):
'''
Compute speed of pedestrian at each timestep given its coordinates during the sequence
timestep = 4 seconds by default (observations each 10 frames with a 2.5 framerate)
Returns velocity vector (vx, vy)
'''
npos = coords.size()[0] #number of observed positions
velocity = np.zeros((npos,2))
x = coords[:,0]
y = coords[:,1]
for i in range(1, npos):
velocity[i,0] = (x[i]-x[i-1])/timestep
velocity[i,1] = (y[i]-y[i-1])/timestep
velocity = torch.from_numpy(velocity)
return velocity
def getTargets(coords):
'''
returns a target array for given coordinates for supervised training
'''
targets = coords[1:]
return targets
def flipPosition(traindata,method):
'''
Flips given coordinates of all pedestrian in traindata
method:
1: change signs of x position (vertical symmetry)
2: change signs of y position (horizontal symmetry)
3: change signs of x and y positions
'''
#method = random.randint(1,3)
for p in range(0, len(traindata)): #loop of over each pedestrian
if method == 1:
#change signs of x position
print(traindata[p].coords,'before')
traindata[p].coords[:,0] = - traindata[p].coords[:,0]
print(traindata[p].coords,'after')
traindata[p].neighbors[:,0] = - traindata[p].neighbors[:,0]
elif method == 2:
#change signs og y position
traindata[p].neighbors[:,1] = - traindata[p].neighbors[:,1]
#coords[:,1] = -coords[:,1]
else:
#change both signs
traindata[p].coords = - traindata[p].coords
traindata[p].neighbors = - traindata[p].neighbors
return traindata
def getCoords(velocity, timestep = 4):
'''
Compute x and y coordinates given a velocity array
'''
x_pos = velocity[:,0]*timestep
y_pos = velocity[:,1]*timestep
return x_pos, y_pos

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