senas/train.py at master · cazdlt/senas · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
import numpy as np
from matplotlib import pyplot as plt
import argparse

parser = argparse.ArgumentParser()
parser.add_argument("seña", help="número de la seña en ./señas",
                    type=int)
parser.add_argument("--ignore","-i", action='store_true',help="ignora los videos en los que no el programa funciona correctamente")
args = parser.parse_args()

#número de seña a analizar
fileNumber=int(args.seña)

#Ignora seña si está en la lista de los que no funcionan
fileIgnore=(4,8,9,10,11,14,16,20,21,22,23,24,25,26,30,31,32,33,34,35,36,37,39,42,44,45,47)
if args.ignore and (fileNumber in fileIgnore):
    sys.exit("File ignored")

#distancia de un punto a la cara
def distFace(A):
 return np.sqrt(np.power(A[0],2) + np.power(A[1],2))

#Extrae las trayectorias del archivo
with open('./out2/traj%d.txt'%fileNumber) as file:
    line=file.readline()
    face=tuple([int(n) for n in (line.split()[0][1:-1],line.split()[1][0:-1])])
    line=file.readline()
    trajLeft=np.array([[int(n) for n in ((line.split('[')[1].split(']')[0]).split())]])
    trajRight=np.array([[int(n) for n in ((line.split('[')[2].split(']')[0]).split())]])
    for line in file:
        trajLeft = np.append(trajLeft, [[int(n) for n in ((line.split('[')[1].split(']')[0]).split())]], 0)
        trajRight = np.append(trajRight, [[int(n) for n in ((line.split('[')[2].split(']')[0]).split())]], 0)

#cambia referencia de coordenadas en video a  posicion de la cara
trajLeft[:,0]=trajLeft[:,0]-face[0]
trajLeft[:,1]=-(trajLeft[:,1]-face[1])
trajRight[:,0]=trajRight[:,0]-face[0]
trajRight[:,1]=-(trajRight[:,1]-face[1])

#Centros de las trayectorias
xCenterLeft=(max(trajLeft[:,0])-min(trajLeft[:,0]))/2+min(trajLeft[:,0])
yCenterLeft=(max(trajLeft[:,1])-min(trajLeft[:,1]))/2+min(trajLeft[:,1])
centerLeft=np.array([xCenterLeft,yCenterLeft])
xCenterRight=(max(trajRight[:,0])+min(trajRight[:,0]))/2
yCenterRight=(max(trajRight[:,1])+min(trajRight[:,1]))/2
centerRight=np.array([xCenterRight,yCenterRight])

#máxima altura de la trayectoria
hLeft=trajLeft[np.where(trajLeft[:,0] == min(trajLeft[:,0]))]
hRight=trajRight[np.where(trajRight[:,0] == min(trajRight[:,0]))]
hLeft=np.array(hLeft[0])
hRight=np.array(hRight[0])

#distancia mínima a la cara
minLeft=0
dmin=100000
for p in trajLeft:
    if abs(distFace(p))<dmin:
        minLeft=p
        dmin=abs(distFace(p))
minRight=0
dmin=100000
for p in trajRight:
    if abs(distFace(p))<dmin:
        minRight=p
        dmin=abs(distFace(p))


#promedio de las trayectorias
avxLeft=sum(trajLeft[:,0])/len(trajLeft[:,0])
avyLeft=sum(trajLeft[:,1])/len(trajLeft[:,1])
avxRight=sum(trajRight[:,0])/len(trajRight[:,0])
avyRight=sum(trajRight[:,1])/len(trajRight[:,1])
avLeft=np.array([avxLeft,avyRight])
avRight=np.array([avxRight,avyRight])

#velocidad de las manos
spxLeft=[(a-b) for a, b in zip(trajLeft[::1,0], trajLeft[1::1,0])]
spyLeft=[(a-b) for a, b in zip(trajLeft[::1,1], trajLeft[1::1,1])]
spxRight=[(a-b) for a, b in zip(trajRight[::1,0], trajRight[1::1,0])]
spyRight=[(a-b) for a, b in zip(trajRight[::1,1], trajRight[1::1,1])]

#distancia recorrida por las manos
distLeft=np.array([sum(abs(x) for x in spxLeft),sum(abs(x) for x in spyLeft)])
distRight=np.array([sum(abs(x) for x in spxRight),sum(abs(x) for x in spyRight)])

#grafica y muestra resultados
plt.figure(1)
plt.plot(trajLeft[:,0],trajLeft[:,1],label="left hand")
plt.plot(trajRight[:,0],trajRight[:,1],label="right hand")
plt.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3,
           ncol=1,  borderaxespad=0.)
plt.plot(xCenterLeft,yCenterLeft,'rs')
plt.plot(xCenterRight,yCenterRight,'rs')
plt.plot(minLeft[0],minLeft[1],'b^')
plt.plot(minRight[0],minRight[1],'b^')
plt.plot(avxLeft,avyLeft,'gx')
plt.plot(avxRight,avyRight,'gx')
plt.plot(hLeft[0],hLeft[1],'g*')
plt.plot(hRight[0],hRight[1],'g*')
plt.title('position')
plt.savefig('./out2/interest%d.png'%(fileNumber))

#exporta nombre y (altura, centro, distancia mínima, promedio, distancia recorrida)  de seña a archivo para entrenamiento
dict = {'Name': 'Zara', 'Age': 7, 'Class': 'First'}

with open('./out2/class%d.txt'%(fileNumber),"w") as fp:
    if fileNumber in (1,7,15):
        fp.write("alcohol\n")
    elif fileNumber in (18,38,40):
        fp.write("dormir\n")
    elif fileNumber in (3,6,13):
        fp.write("mama\n")
    elif fileNumber in (43,49,51):
        fp.write("gelatina\n")
    fp.write(('{} {}'.format(hLeft,hRight))+'\n')
    fp.write('{} {}'.format(centerLeft,centerRight)+'\n')
    fp.write('{} {}'.format(minLeft,minRight)+'\n')
    fp.write('{} {}'.format(avLeft,avRight)+'\n')
    fp.write('{} {}'.format(distLeft,distRight)+'\n')