You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
100 lines
3.2 KiB
100 lines
3.2 KiB
import cv2
|
|
import serial
|
|
import threading
|
|
import time
|
|
|
|
class Frame():
|
|
def __init__(self, time, data):
|
|
self.time = time
|
|
self.data = data
|
|
|
|
class GridEye():
|
|
def __init__(self, serialPort, baudrate):
|
|
self.port = serial.Serial(serialPort, baudrate)
|
|
self.frames = []
|
|
self.reading = True
|
|
self.thread = threading.Thread(target = self.reader)
|
|
self.thread.setDaemon(True)
|
|
|
|
def start(self):
|
|
self.thread.start()
|
|
|
|
def stop(self):
|
|
self.reading = False
|
|
self.thread.join()
|
|
|
|
def reader(self):
|
|
data = []
|
|
data_time = 0;
|
|
while (self.reading):
|
|
line = b''
|
|
while (self.reading):
|
|
c = self.port.read()
|
|
if c == b'\r':
|
|
c = self.port.read()
|
|
break
|
|
if c == b'\n':
|
|
break
|
|
line += c
|
|
#line = self.port.readline()#.decode('utf-8')
|
|
# if line:
|
|
# print (line)
|
|
# time.sleep(0.01)
|
|
# if self.port.in_waiting > 0:
|
|
# print (self.port.in_waiting)
|
|
if b'#' in line:
|
|
if len(data) == 8:
|
|
print (data_time)
|
|
#print (data)
|
|
self.frames.append(Frame(data_time, data))
|
|
if len(self.frames) > 100:
|
|
self.frames.pop(0)
|
|
else:
|
|
print ('something wrong', len(data))
|
|
data_time = time.time()
|
|
data = []
|
|
else:
|
|
try:
|
|
row = [float(x) for x in line.split()]
|
|
if len(row) == 8:
|
|
data.append(row)
|
|
except ValueError as e:
|
|
print ('error', e)
|
|
data_time = time.time()
|
|
data = []
|
|
if len(data) > 8:
|
|
data.pop(0)
|
|
|
|
|
|
|
|
if __name__ == '__main__':
|
|
import cv2
|
|
import numpy as np
|
|
SIZE = 128
|
|
overlap = 120
|
|
grideye = GridEye('COM12', 115200)
|
|
grideye.start()
|
|
cv2.imshow('sample', np.empty((SIZE*2,SIZE*2), np.uint8))
|
|
while True:
|
|
if len(grideye.frames) > 0:
|
|
frame = grideye.frames.pop(0)
|
|
img = (np.array(frame.data)-15)*10
|
|
img = cv2.resize(img.astype(np.uint8), (SIZE,SIZE), interpolation = cv2.INTER_LINEAR)
|
|
img2 = np.copy(img)
|
|
|
|
out = np.empty((SIZE*2, SIZE*2), dtype=np.uint16)
|
|
out[:SIZE, :SIZE] = img
|
|
out[:SIZE, SIZE:] = img2
|
|
|
|
out[SIZE:, :SIZE] = img
|
|
out[SIZE:, (SIZE-overlap):SIZE] += img2[:,:overlap]
|
|
out[SIZE:, (SIZE-overlap):SIZE] = out[SIZE:, (SIZE-overlap):SIZE]/2
|
|
|
|
out[SIZE:, SIZE:SIZE+(SIZE-overlap)] = img2[:,overlap:SIZE]
|
|
out = out.astype(np.uint8)
|
|
cv2.imshow('sample', out)
|
|
if cv2.waitKey(1) == ord('q'):
|
|
break
|
|
time.sleep(0.001)
|
|
grideye.stop()
|
|
|