forked from DeepLabCut/DeepLabCut-live
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathizzy_jump.py
143 lines (112 loc) · 3.53 KB
/
izzy_jump.py
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
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
"""
DeepLabCut Toolbox (deeplabcut.org)
© A. & M. Mathis Labs
Licensed under GNU Lesser General Public License v3.0
"""
import serial
import struct
import time
import numpy as np
from dlclive.processor import Processor, KalmanFilterPredictor
class IzzyJump(Processor):
def __init__(self, com="", lik_thresh=0.5, baudrate=int(9600), **kwargs):
super().__init__()
self.ser = serial.Serial(com, baudrate, timeout=0)
self.lik_thresh = lik_thresh
self.led_times = []
self.last_light = 0
def close_serial(self):
self.ser.close()
def switch_led(self, val, frame_time):
### check status of led ###
self.ser.write(b"R")
led_byte = b""
led_status = None
while (len(led_byte) != 0) or (led_status is None):
led_byte = self.ser.read()
if len(led_byte) > 0:
led_status = ord(led_byte)
if led_status != val:
ctime = time.time()
if ctime - self.last_light > 0.25:
self.ser.write(b"L")
self.last_light = ctime
self.led_times.append((val, frame_time, ctime))
def process(self, pose, **kwargs):
### bodyparts
# 0. nose
# 1. L-eye
# 2. R-eye
# 3. L-ear
# 4. R-ear
# 5. Throat
# 6. Withers
# 7. Tailset
# 8. L-front-paw
# 9. R-front-paw
# 10. L-front-wrist
# 11. R-front-wrist
# 12. L-front-elbow
# 13. R-front-elbow
# ...
l_elbow = pose[12, 1] if pose[12, 2] > self.lik_thresh else None
r_elbow = pose[13, 1] if pose[13, 2] > self.lik_thresh else None
elbows = [l_elbow, r_elbow]
this_elbow = (
min([e for e in elbows if e is not None])
if any([e is not None for e in elbows])
else None
)
withers = pose[6, 1] if pose[6, 2] > self.lik_thresh else None
if kwargs["record"]:
if withers is not None and this_elbow is not None:
if this_elbow < withers:
self.switch_led(True, kwargs["frame_time"])
else:
self.switch_led(False, kwargs["frame_time"])
return pose
def save(self, filename):
### save stim on and stim off times
if filename[-4:] != ".npy":
filename += ".npy"
arr = np.array(self.led_times, dtype=float)
try:
np.save(filename, arr)
save_code = True
except Exception:
save_code = False
return save_code
class IzzyJumpKF(KalmanFilterPredictor, IzzyJump):
def __init__(
self,
com="",
lik_thresh=0.5,
baudrate=int(9600),
adapt=True,
forward=0.003,
fps=30,
nderiv=2,
priors=[1, 1],
initial_var=1,
process_var=1,
dlc_var=4,
):
super().__init__(
adapt=adapt,
forward=forward,
fps=fps,
nderiv=nderiv,
priors=priors,
initial_var=initial_var,
process_var=process_var,
dlc_var=dlc_var,
com=com,
lik_thresh=lik_thresh,
baudrate=baudrate,
)
def process(self, pose, **kwargs):
future_pose = KalmanFilterPredictor.process(self, pose, **kwargs)
final_pose = IzzyJump.process(self, future_pose, **kwargs)
return final_pose
def save(self, filename):
return IzzyJump.save(self, filename)