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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.frame = None
self.reading = True
self.thread = threading.Thread(target = self.reader)
self.thread.setDaemon(True)
self.lock = threading.Lock()
def start(self):
self.port.reset_input_buffer()
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)
self.lock.acquire()
self.frame = Frame(data_time, data)
self.lock.release()
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)
class Distance():
def __init__(self, serialPort, baudrate):
self.port = serial.Serial(serialPort, baudrate)
self.distance = 200
self.reading = True
self.thread = threading.Thread(target = self.reader)
self.thread.setDaemon(True)
self.lock = threading.Lock()
def start(self):
self.port.reset_input_buffer()
self.thread.start()
def stop(self):
self.reading = False
self.thread.join()
def reader(self):
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
if b'Distance' in line:
try:
dist = float(line.decode('utf-8').split(':')[1])
print (dist)
if dist > 200.0:
dist = 200.0
self.lock.acquire()
self.distance = dist
self.lock.release()
except ValueError as e:
print ('error', e)
if __name__ == '__main__':
import cv2
import numpy as np
import math
def exponential(img, value):
tmp = cv2.pow(img.astype(np.double), value)*(255.0/(255.0**value))
return tmp.astype(np.uint8)
SIZE = 128
overlap = 120
AVERAGE_FRAME = 10
distanceBetweenSensors = 7.7 #cm
distance2Object = 60.0 #cm
ADJUST_BACK = 5
EXPONENTAL_VALUE = 0.4
offset = (distanceBetweenSensors / (2*distance2Object*math.tan(30.0/180.0*math.pi))) * SIZE
overlap = int(SIZE - offset)
print (overlap)
grideye = GridEye('COM15', 115200)
grideye.start()
grideye2 = GridEye('COM17', 115200)
grideye2.start()
distanceSensor = Distance('COM18', 9600)
distanceSensor.start()
fourcc = cv2.VideoWriter_fourcc(*'XVID')
videoWriter = cv2.VideoWriter('output.avi', fourcc, 10.0, (SIZE*2,SIZE*3))
cv2.imshow('sample', np.zeros((SIZE*3,SIZE*2), np.uint8))
aver1 = np.zeros((SIZE,SIZE), np.uint16)
aver2 = np.zeros((SIZE,SIZE), np.uint16)
cnt = 0
while True:
if grideye.frame and grideye2.frame:
grideye.lock.acquire()
grideye2.lock.acquire()
distanceSensor.lock.acquire()
frame = grideye.frame
grideye.frame = None
frame2 = grideye2.frame
grideye2.frame = None
# frame2 = frame
distance2Object = distanceSensor.distance
distanceSensor.lock.release()
grideye2.lock.release()
grideye.lock.release()
img = (np.array(frame.data)-15)*10
img = cv2.resize(img.astype(np.uint8), (SIZE,SIZE), interpolation = cv2.INTER_CUBIC) # INTER_LINEAR, INTER_CUBIC
img2 = (np.array(frame2.data)-15)*10
img2 = cv2.resize(img2.astype(np.uint8), (SIZE,SIZE), interpolation = cv2.INTER_CUBIC)
if cnt < AVERAGE_FRAME:
cnt += 1
aver1 += img
aver2 += img2
if cnt == AVERAGE_FRAME:
aver1 = aver1/AVERAGE_FRAME
aver1 = aver1.astype(np.uint8)
aver1 += ADJUST_BACK
aver2 = aver2/AVERAGE_FRAME
aver2 = aver2.astype(np.uint8)
aver2 += ADJUST_BACK
continue
img = cv2.subtract(img, aver1)
img2 = cv2.subtract(img2, aver2)
out = np.full((SIZE*3, SIZE*2), 255, dtype=np.uint16)
out[:SIZE, :SIZE] = img
out[:SIZE, SIZE:] = img2
overlap = int(SIZE - (distanceBetweenSensors / (2*distance2Object*math.tan(30.0/180.0*math.pi))) * SIZE)
offset = int(overlap/2)
# tmp = cv2.resize(img.astype(np.uint8), (SIZE*2-overlap, SIZE))
# tmp.astype(np.uint16)
tmp = np.zeros((SIZE, SIZE*2-overlap), dtype=np.uint16)
tmp[:, :SIZE] = img
tmp[:, -SIZE:] += img2
tmp[:, (SIZE-overlap): SIZE] = tmp[:, (SIZE-overlap): SIZE]/2
tmp = exponential(tmp, EXPONENTAL_VALUE)
out[SIZE:SIZE*2, offset: SIZE*2-overlap+offset] = tmp
# out[SIZE:SIZE*2, offset:SIZE+offset] = img
# out[SIZE:SIZE*2, (SIZE-overlap)+offset:SIZE+offset] += img2[:,:overlap]
# out[SIZE:SIZE*2, (SIZE-overlap)+offset:SIZE+offset] = out[SIZE:SIZE*2, (SIZE-overlap)+offset:SIZE+offset]/2
# out[SIZE:SIZE*2, SIZE+offset:SIZE+(SIZE-overlap)+offset] = img2[:,overlap:SIZE]
maxProduct = 0
overlap2 = 0
for i in range(80, 128):
product = sum(img[:,SIZE-i:].astype(np.uint32)*img2[:,:i].astype(np.uint32))
product = sum(product) / len(product)
if product > maxProduct:
maxProduct = product
overlap2 = i
offset = int(overlap2/2)
tmp = np.zeros((SIZE, SIZE*2-overlap2), dtype=np.uint16)
tmp[:, :SIZE] = img
tmp[:, -SIZE:] += img2
tmp[:, (SIZE-overlap2): SIZE] = tmp[:, (SIZE-overlap2): SIZE]/2
tmp = exponential(tmp, EXPONENTAL_VALUE)
out[SIZE*2:, offset: SIZE*2-overlap2+offset] = tmp
# out[SIZE*2:, offset:SIZE+offset] = img
# out[SIZE*2:, (SIZE-overlap2)+offset:SIZE+offset] += img2[:,:overlap2]
# out[SIZE*2:, (SIZE-overlap2)+offset:SIZE+offset] = out[SIZE*2:, (SIZE-overlap2)+offset:SIZE+offset]/2
# out[SIZE*2:, SIZE+offset:SIZE+(SIZE-overlap2)+offset] = img2[:,overlap2:SIZE]
out = out.astype(np.uint8)
cv2.imshow('sample', out)
videoWriter.write(cv2.cvtColor(out,cv2.COLOR_GRAY2BGR))
key = cv2.waitKey(1)
if key == ord('q'):
break
elif key == ord('a'):
overlap += 1
elif key == ord('d'):
overlap -= 1
elif key == ord('c'):
cv2.imwrite('out.jpg', out)
time.sleep(0.001)
grideye.stop()
grideye2.stop()
videoWriter.release()
cv2.destroyAllWindows()