def __init__(self):
self.processor = self.get_processor_name()
if "ARMv7" in self.processor:
print "running on Raspberry Pi 2"
#subprocess.call("~/rpi-fbcp/build/fbcp &", shell=True)
subprocess.call("gpio mode 4 out", shell=True)
self.camera = PiCamera()
self.camera.resolution = (1000, 1000)
temp_sensor.initialize()
self.temperature = temp_sensor.read_temp()
self.running_on_pi = True
else:
print "running on Desktop"
self.temperature = None
self.running_on_pi = False
def __init__(self):
self.processor = self.get_processor_name()
if "ARMv7" in self.processor:
print "running on Raspberry Pi 2"
#subprocess.call("~/rpi-fbcp/build/fbcp &", shell=True)
subprocess.call("gpio mode 4 out", shell=True)
self.camera = PiCamera()
self.camera.resolution = (1000, 1000)
temp_sensor.initialize()
self.temperature = temp_sensor.read_temp()
self.running_on_pi = True
else:
print "running on Desktop"
self.temperature = None
self.running_on_pi = False
def get_reading():
temperature = temp_sensor.read_temp()['1']
# Temperature is C by default. Change to F if indicated by FAHRENHEIT flag:
if FAHRENHEIT:
temperature = temperature * 9 / 5 + 32
return temperature
def read_temp(self):
self.temperature = temp_sensor.read_temp()
return self.temperature
def main():
#parameters
file = "./test.jpg"
draw = True
hough_circle = True
hough_line = True
hough_pline = True
do_canny = False
do_blur = True
do_threshold = True
window_name = 'gauge'
line_thickness = 2
#setup
#cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
im = cv2.imread(file)
gray_im = cv2.cvtColor(im, cv2.COLOR_RGB2GRAY)
canvas = np.zeros_like(im)
canvas = np.array(im)
prep = gray_im
m,n = gray_im.shape
mask = np.zeros_like(prep)
scale_factor = 1.15
#preprocessing image
if do_blur:
prep = cv2.GaussianBlur(prep, (3,3), 2,2)
if do_canny:
prep = cv2.Canny(prep, 20, 60)
if do_threshold:
#create structuring element that will be used to "dilate" and "erode" image.
#the element chosen here is a 3px by 3px rectangle
prep = cv2.threshold(prep, 50, 255, cv2.THRESH_BINARY_INV)[1]
erodeElement = cv2.getStructuringElement( cv2.MORPH_ELLIPSE,(3,3))
#dilate with larger element so make sure object is nicely visible
dilateElement = cv2.getStructuringElement( cv2.MORPH_ELLIPSE,(4,4))
prep = cv2.erode(prep,erodeElement,1)
prep = cv2.dilate(prep,dilateElement,1)
#Hough transforms (circles, lines, plines)
if hough_circle:
circles = cv2.HoughCircles(gray_im, cv.CV_HOUGH_GRADIENT, 2, 10, np.array([]), 20, 60, m/10)[0]
for c in circles[:1]:
cv2.circle(mask, (c[0],c[1]), int(c[2]*scale_factor), (255,255,255), -1)
#mask=cv2.threshold(mask, 128, 255,cv2.THRESH_BINARY)
prep = cv2.bitwise_and(prep,mask)
if hough_line:
lines = cv2.HoughLines(prep, 2, np.pi/90, 80)
if hough_pline:
plines = cv2.HoughLinesP(prep, 1, np.pi/180, 20,None, 10, 1)
first = True
for c in circles[:1]:
#green for circles (only draw the 3 strongest)
cv2.circle(canvas, (c[0],c[1]), c[2], (0,255,0), line_thickness)
#cv2.circle()
#res = cv2.bitwise_and(frame,frame, mask= mask)
if first:
first = False
circle_x = c[0]
circle_y = c[1]
radius = int(c[2])
first = True
lines = np.swapaxes(lines,0,1)
for line in lines[:3]:
for (rho, theta) in line:
# blue for infinite lines (only draw the 5 strongest)
x0 = np.cos(theta)*rho
y0 = np.sin(theta)*rho
pt1 = ( int(x0 + (m+n)*(-np.sin(theta))), int(y0 + (m+n)*np.cos(theta)) )
pt2 = ( int(x0 - (m+n)*(-np.sin(theta))), int(y0 - (m+n)*np.cos(theta)) )
cv2.line(canvas, pt1, pt2, (255,0,0), line_thickness)
if first:
first = False
line_x = x0
line_y = y0
angle = 90 - (theta *360 / (2 * np.pi))
line_mask = np.zeros_like(mask)
rect_height = int(radius / 4)
rect_width = int(radius * 2)
cv2.line(line_mask, pt1, pt2, (255,255,255), rect_height) #mask width is quarter of circle radius found above
mask = cv2.bitwise_and(mask, line_mask)
M = cv2.getRotationMatrix2D((x0,y0),(theta *360 / (2 * np.pi))-90,1)
prep = cv2.bitwise_and(prep, mask)
density = cv2.warpAffine(prep,M,(m,n))
density_rect_width = radius*2
if density_rect_width % 2 is not 0:
density_rect_width -= 1
density_rect_height = rect_height/3
if density_rect_height % 2 is not 0:
density_rect_height -= 1
density_rect_origin_x = int(line_x - density_rect_width/2)
density_rect_origin_y = int(line_y - density_rect_height/2)
density_rect = np.zeros(shape=(density_rect_height,density_rect_width)).astype(np.uint8)
for i, row in enumerate(density_rect):
for j, pixel in enumerate(row):
density_rect[i,j] = density[density_rect_origin_y+i, density_rect_origin_x+j]
left, right = np.hsplit(density_rect, 2)
left_density = 0
right_density = 0
for row in left:
for pixel in row:
if pixel:
left_density += 1
for row in right:
for pixel in row:
if pixel:
right_density += 1
if left_density > right_density:
angle += 180
cv2.putText(canvas,"angle:"+str(angle),(int(m*0.2),int(n*0.9)),cv2.FONT_HERSHEY_PLAIN,2,(200,50,0),3)
plines=np.swapaxes(plines,0,1)
for pline in plines[:10]:
for l in pline:
# red for line segments
cv2.line(canvas, (l[0],l[1]), (l[2],l[3]), (0,0,255), line_thickness)
if draw:
canvas = np.concatenate((im, canvas), axis = 1)
#cv2.imshow(window_name,canvas)
else:
pass
#cv2.imshow(window_name,prep)
#cv2.waitKey(0)
# save the resulting image
if draw:
cv2.imwrite("res.jpg",canvas)
time.sleep(1)
temperature = temp_sensor.read_temp()
f = open('gauge_angle.txt', 'w')
f.write("angle:"+str(angle)+"\n")
f.write("temperature:"+str(temperature))
f.close()
email.sendMail( ["*****@*****.**"],
"this is the subject",
"this is the body text of the email",
["res.jpg","gauge_angle.txt"] )
def read_temp(self):
self.temperature = temp_sensor.read_temp()
return self.temperature
def get_reading():
temperature = temp_sensor.read_temp()['1']
temperature = temperature * 1.8 + 32.0
return temperature
