def get_temp_max(runopts):
"""
Gets treatment temperature with the Lepton thermal camera
"""
if runopts.faket:
return 24
run = True
for rr in range(8):
try:
with Lepton("/dev/spidev0.1") as l:
data,_ = l.capture(retry_limit = 3)
if l is not None:
Ts = NP.amax(data[6:50,:,0]) / 100 - 273;
Tt = NP.amax(data[0:5,:,0]) / 100 - 273;
mm= NP.where( data == NP.amax(data[6:50,:,0]) )
print('max point at {},{}'.format(*mm))
for line in data:
l = len(line)
if (l != 80):
print("error: should be 80 columns, but we got {}".format(l))
elif Ts > 150:
print("Measured temperature is too high: {}".format(Ts))
time.sleep(0.070)
run = False
except Exception as e:
print(e)
print("\nHardware error on the thermal camera. Lepton restarting...")
gpio.output(35, gpio.HIGH)
time.sleep(0.5)
gpio.output(35, gpio.LOW)
print("Lepton restart completed!\n\n")
return [int(mm[0]), int(mm[1])]
def get_frame():
# camera = cv2.VideoCapture(0)
# while True:
# _, img = camera.read()
# img2 = face_recognition(img)
# imgencode = cv2.imencode('.jpg', img2)[1]
# stringData = imgencode.tostring()
# yield (b'--frame\r\n'b'Content-Type: text/plain\r\n\r\n'+stringData+b'\r\n')
# del(camera)
while True:
with Lepton() as l:
a, _ = l.capture()
cv2.normalize(a, a, 0, 65535, cv2.NORM_MINMAX) # extend contrast
np.right_shift(a, 8, a) # fit data into 8 bits
scale_percent = 400 # percent of original size
width = int(a.shape[1] * scale_percent / 100)
height = int(a.shape[0] * scale_percent / 100)
dim = (width, height)
resized = cv2.resize(a, dim, interpolation=cv2.INTER_AREA)
a = copy.copy(resized)
imgencode = cv2.imencode('.jpg', a)[1]
stringData = imgencode.tostring()
yield (b'--frame\r\n'
b'Content-Type: text/plain\r\n\r\n' + stringData + b'\r\n')
def captureFrame(self):
a,_ = Lepton().capture()
cv2.normalize(a, a, 0, 65535, cv2.NORM_MINMAX) # extend contrast
np.right_shift(a, 8, a) # fit data into 8 bits
cv2.imwrite("capture"+str(self.FrameId)+".jpg", np.uint8(a)) # write it!
self.FrameId = self.FrameId+1
self.newFrame = a
def runCode():
while True:
global pixdata, json_data, image, multiplicationFactor
FileName = "output.png"
with Lepton() as l:
a, _ = l.capture()
cv2.normalize(a, a, 0, 65535, cv2.NORM_MINMAX) # extend contrast
np.right_shift(a, 8, a) # fit data into 8 bits
cv2.imwrite(FileName, np.uint8(a))
image = Image.open(FileName)
imageOrigin = Image.open(FileName)
image = image.convert('RGB')
pixdata = image.load()
analyze()
imageOrigin = imageOrigin.resize((80 * multiplicationFactor, 60 * multiplicationFactor))
imageOrigin.save(FileName)
with open(FileName, 'rb') as f:
imdata = f.read()
f.close()
json_blobs = json.dumps(blobs, default=obj_dict)
outjson = {
"blobs": json.loads(json_blobs),
"img": imdata.encode('base64'),
"multiplicationFactor": multiplicationFactor
}
json_data = json.dumps(outjson)
def get_temp(runopts):
"""
Gets treatment temperature with the Lepton thermal camera
"""
if runopts.faket:
return 24
run = True
while run:
try:
with Lepton("/dev/spidev0.1") as l:
data, _ = l.capture(retry_limit=3)
if l is not None:
Ts = NP.amax(data) / 100 - 273
for line in data:
l = len(line)
if (l != 80):
print("error: should be 80 columns, but we got {}".
format(l))
elif Ts > 150:
print(
"Measured temperature is too high: {}".format(Ts))
#curtime = datetime.datetime.now().strftime("%Y-%m-%d_%H%M%S.%f")
#fname = "{}".format(curtime)
#Ts = NP.amax(data) / 100 - 273;
#Ts = NP.true_divide(NP.amax(data[7:50]),100)-273;
time.sleep(0.050)
run = False
except:
print(
"\nHardware error on the thermal camera. Lepton restarting...")
gpio.output(35, gpio.HIGH)
time.sleep(0.5)
gpio.output(35, gpio.LOW)
print("Lepton restart completed!\n\n")
return Ts
def capture(flip_v = False, device = "/dev/spidev0.0"):
with Lepton(device) as l:
a,_ = l.capture()
if flip_v:
cv2.flip(a,0,a)
cv2.normalize(a, a, 0, 255, cv2.NORM_MINMAX) #Normalization of data
#print(a)
return np.uint8(a)
def capture(flip_v=False, device="/dev/spidev0.0"):
with Lepton(device) as l:
a, _ = l.capture()
if flip_v:
cv2.flip(a, 0, a)
cv2.normalize(a, a, 0, 65535, cv2.NORM_MINMAX)
np.right_shift(a, 8, a)
return np.uint8(a)
def capture(device="/dev/spidev0.0"):
with Lepton(device) as l:
a, frame = l.capture()
#cv2.flip(a,0)
cv2.normalize(a, a, 0, 65535, cv2.NORM_MINMAX)
np.right_shift(a, 8, a)
return np.uint8(a)
def capture(flip_v=False, device="/dev/spidev0.0"):
with Lepton(device) as l:
a, _ = l.capture()
if flip_v:
cv2.flip(a, 0, a)
#cv2.normalize(a, a, 0, 65535, cv2.NORM_MINMAX)
#np.left_shift(a, 2, a)
return np.int16(a)
def capture(flip_v=False, device="/dev/spidev0.0"):
with Lepton(device) as l:
a, s = l.capture()
if flip_v:
cv2.flip(
a, -1, a
) #a flag to specify how to flip the array; 0 means flipping around the x-axis and positive value (for example, 1) means flipping around y-axis. Negative value (for example, -1) means flipping around both axes.
return a, s
def getIm():
with Lepton() as l:
a,_ = l.capture()
cv2.normalize(a,a,0,65535,cv2.NORM_MINMAX)
np.right_shift(a,8,a)
cv2.imshow("a",a)
return a/float(255)
def lepton_process(connection, lepton_device):
print('lepton process running')
with Lepton(lepton_device) as lepton:
while not connection.poll():
lepton_frame = lepton.capture()
connection.send(lepton_frame)
print('lepton process exiting')
connection.close()
print('lepton process exited')
def capture(flip_v=False, device="/dev/spidev0.0"):
with Lepton(device) as l:
a, _ = l.capture()
if flip_v:
cv2.flip(a, 0, a)
np.savetxt("Rpi.csv", a, delimiter=",")
cv2.normalize(a, a, 0, 65535, cv2.NORM_MINMAX)
np.savetxt("normalizedRpi.csv", a, delimiter=",")
np.right_shift(a, 8, a)
return np.uint8(a)
def capture_image(filename, size):
with Lepton() as l:
a, _ = l.capture()
#Create a PIL image from numpy array
image = Image.fromarray(a.astype('uint8'), 'RGB')
#resize PIL image to match picamera resolution
image = image.resize(size, Image.BICUBIC)
image.save(filename, 'JPEG')
def main():
with Lepton() as l:
# get image
img, _ = l.capture()
# extend contrast
cv2.normalize(img, img, 0, 65535, cv2.NORM_MINMAX)
# fit data into 8 bits
np.right_shift(img, 8, img)
# conver np array to uint8 type
img = np.uint8(img)
# create an output image
cv2.imwrite("out.jpg", img)
def _lept_snap(self):
"""
takes the image
"""
print('taking image')
with Lepton() as l:
raw, _ = l.capture()
cv2.normalize(raw, raw, 0, 65535, cv2.NORM_MINMAX)
np.right_shift(raw, 8, raw)
raw = np.uint8(raw)
adj = cv2.applyColorMap(raw, self.colormap)
return adj
def thermal_image(event, x, y, flags, param):
global i
if event == cv2.EVENT_LBUTTONUP:
with Lepton() as l:
a, _ = l.capture()
cv2.normalize(a, a, 0, 65535, cv2.NORM_MINMAX)
np.right_shift(a, 8, a)
thermal_image = np.uint8(a)
filename = './' + str(i) + '.jpg'
cv2.imshow('Thermal image', thermal_image)
cv2.imwrite(filename, thermal_image)
i += 1
def thermo(path, file_name, format):
with Lepton() as l:
a, _ = l.capture()
# print(a)
cv2.normalize(a, a, 0, 65535, cv2.NORM_MINMAX) # extend contrast
np.right_shift(a, 8, a) # fit data into 8 bits
cv2.imwrite(path + file_name + format, np.uint8(a))
thermo = Thermo()
thermo.name = file_name
thermo.image = file_name + format
thermo.save()
def main(flip_v=False, alpha=128, device="/dev/spidev0.0", numpics=1, freq=1):
# Create an array representing a 1280x720 image of
# a cross through the center of the display. The shape of
# the array must be of the form (height, width, color)
a = np.zeros((240, 320, 3), dtype=np.uint8)
lepton_buf = np.zeros((60, 80, 1), dtype=np.uint16)
with picamera.PiCamera() as camera:
camera.resolution = (320, 240)
camera.framerate = 24
camera.vflip = flip_v
camera.start_preview()
camera.fullscreen = True
# Add the overlay directly into layer 3 with transparency;
# we can omit the size parameter of add_overlay as the
# size is the same as the camera's resolution
o = camera.add_overlay(np.getbuffer(a),
size=(320, 240),
layer=3,
alpha=int(alpha),
crop=(0, 0, 80, 60),
vflip=flip_v)
try:
start = time.time()
time.sleep(0.2) # give the overlay buffers a chance to initialize
for i in range(1, numpics + 1):
with Lepton(device) as l:
frame_ushort, frame_id = l.capture(lepton_buf)
cv2.normalize(lepton_buf, lepton_buf, 0, 65535,
cv2.NORM_MINMAX)
np.right_shift(lepton_buf, 8, lepton_buf)
a[:lepton_buf.shape[0], :lepton_buf.shape[1], :] = lepton_buf
o.update(np.getbuffer(a))
filename = "output_" + str(i) + ".jpg"
cv2.imwrite(filename, lepton_buf)
time.sleep(1 / freq)
# print filename
except Exception:
traceback.print_exc()
finally:
time_spent = time.time() - start
print "\n\tSUMMARY"
print "================================"
print "Time spent:\t\t" + str(time_spent)
print "Photos taken:\t\t" + str(numpics)
print "Adjusted frequency:\t" + str(float(numpics / time_spent))
print "\n"
camera.remove_overlay(o)
async def get_temp_a(runopts):
"""
Gets treatment temperature with the Lepton thermal camera
"""
if runopts.faket:
return 24
run = True
while run:
try:
with Lepton("/dev/spidev0.1") as l:
data, _ = l.capture(retry_limit=3)
if l is not None:
##print(data[10:80]);
Ts = NP.amax(data[6:60, :, 0]) / 100 - 273
Tt = NP.amax(data[0:5, :, 0]) / 100 - 273
mm = NP.where(data == NP.amax(data))
Ts_lin = data[int(mm[0]), :, 0] / 100 - 273
Ts2 = (Ts_lin[int(mm[1]) + 2] + Ts_lin[int(mm[1]) - 2]) / 2
Ts3 = (Ts_lin[int(mm[1]) + 6] + Ts_lin[int(mm[1]) - 6]) / 2
for line in data:
l = len(line)
if (l != 80):
print("error: should be 80 columns, but we got {}".
format(l))
elif Ts > 150:
print(
"Measured temperature is too high: {}".format(Ts))
if runopts.save_therm:
curtime = datetime.datetime.now().strftime(
"%Y-%m-%d_%H%M%S.%f")
fname = "{}".format(curtime)
save_data(SAVEDIR_therm, data / 100.0 - 273, fname)
time.sleep(0.050)
run = False
except Exception as e:
print(e)
print(
"\nHardware error on the thermal camera. Lepton restarting...")
gpio.output(35, gpio.HIGH)
time.sleep(0.5)
gpio.output(35, gpio.LOW)
print("Lepton restart completed!\n\n")
#print(Ts)
return [Ts, Ts2, Ts3, Ts_lin, Tt, data]
def capture(flip_v=False, device="/dev/spidev0.1"):
with Lepton(device) as l:
data, _ = l.capture()
minVal, maxVal, _, _ = cv2.minMaxLoc(data)
resized_data = cv2.resize(data[:, :], (800, 480))
_, _, minLoc, maxLoc = cv2.minMaxLoc(resized_data)
# Detect leaf
# resized_data = detect_leaf(data)
image = raw_to_8bit(resized_data)
return (data, image, minVal, maxVal, minLoc, maxLoc)
def capture_ir(flip_v=False, device="/dev/spidev0.0"): # add the BB-SPIDEV0-00A0.dtbo for beaglebone green!
with Lepton(device) as l:
data, _ = l.capture()
minVal, maxVal, _, _ = cv2.minMaxLoc(data)
resized_data = cv2.resize(data[:,:], (800, 480))
_, _, minLoc, maxLoc = cv2.minMaxLoc(resized_data)
# Detect leaf
# resized_data = detect_leaf(data)
image = raw_to_8bit(resized_data)
return (data, image, minVal, maxVal, minLoc, maxLoc)
def frames():
# getImage = a.copy()
# if not camera.isOpened():
# raise RuntimeError('Could not start camera.')
while True:
# read current frame
with Lepton() as l:
a,_ = l.capture()
a = cv2.resize(a[:,:], (640, 480))
# encode as a jpeg image and return it
yield a#cv2.imencode('.jpg', img)[1].tobytes()
def main(flip_v=False, alpha=128, device="/dev/spidev0.0"):
# Create an array representing a 1280x720 image of
# a cross through the center of the display. The shape of
# the array must be of the form (height, width, color)
a = np.zeros((240, 320, 3), dtype=np.uint8)
lepton_buf = np.zeros((60, 80, 1), dtype=np.uint16)
with picamera.PiCamera() as camera:
camera.resolution = (320, 240)
camera.framerate = 24
camera.vflip = flip_v
camera.hflip = True
camera.start_preview()
camera.crop = (0.25, 0.25, 0.5, 0.5)
camera.fullscreen = True
# Add the overlay directly into layer 3 with transparency;
# we can omit the size parameter of add_overlay as the
# size is the same as the camera's resolution
o = camera.add_overlay(np.getbuffer(a),
size=(320, 240),
layer=3,
alpha=int(alpha),
crop=(0, 0, 80, 60),
vflip=flip_v,
hflip=True)
time.sleep(2)
try:
time.sleep(0.2) # give the overlay buffers a chance to initialize
with Lepton(device) as l:
last_nr = 0
while True:
_, nr = l.capture(lepton_buf)
if nr == last_nr:
# no need to redo this frame
continue
last_nr = nr
cv2.normalize(lepton_buf, lepton_buf, 0, 65535,
cv2.NORM_MINMAX)
np.right_shift(lepton_buf, 8, lepton_buf)
a[:lepton_buf.shape[0], :lepton_buf.
shape[1], :] = lepton_buf
o.update(np.getbuffer(a))
except KeyboardInterrupt:
print "hello"
traceback.print_exc()
finally:
camera.remove_overlay(o)
def capture(
flip_v=False,
device="/dev/spidev0.0"
): # update for the BBG and /boot/uEnv.txt should show BB-SPIDEV0-00A0.dtbo for overlays!
with Lepton(device) as l:
data, _ = l.capture()
minVal, maxVal, _, _ = cv2.minMaxLoc(data)
resized_data = cv2.resize(data[:, :], (800, 480))
_, _, minLoc, maxLoc = cv2.minMaxLoc(resized_data)
# Detect leaf
# resized_data = detect_leaf(data)
image = raw_to_8bit(resized_data)
return (data, image, minVal, maxVal, minLoc, maxLoc)
def capture(flip_v = False, device = "/dev/spidev0.1"):
with Lepton(device) as l:
a,_ = l.capture()
if flip_v:
cv2.flip(a,0,a)
'''
cv2.normalize(a, a, 0, 65535, cv2.NORM_MINMAX)
'''
'''
np.right_shift(a, 16, a)
'''
print np.max(a)
print np.min(a)
return np.uint16(a)
'''
def CaptureImage():
HPix = 80 # Image resolution in the the horizontal direction
VPix = 60 # Image resolution in the the vertical direction
# Code for capturing thermal image from FLIR Lepton sensor
with Lepton() as l:
a, _ = l.capture()
# extend contrast
cv2.normalize(a, a, 0, 65535, cv2.NORM_MINMAX)
# fit data into 8 bits
np.right_shift(a, 8, a)
# reshape data
b = np.reshape(a, (VPix, HPix))
return b
def capture(flip_v = False, device = "/dev/spidev0.0"):
threading.Timer(5,capture).start();
with Lepton(device) as l:
a,_ = l.capture()
if flip_v:
cv2.flip(a,0,a)
cv2.normalize(a, a, 0, 65535, cv2.NORM_MINMAX)
np.right_shift(a, 8, a)
image_captured = np.uint8(a)z
pub=rospy.Publisher("chatter", Image , queue_size=10)
rospy.init_node("talker", anonymous=True)
rate = rospy.Rate(2)
birdge=CvBridge();
cv_image = birdge.cv2_to_imgmsg(image_captured, 'passthrough' );
pub.publish(cv_image)
rate.sleep()
def capture(self):
with Lepton("/dev/spidev0.0") as l:
lepton_buf = np.zeros((60, 80, 1), dtype=np.uint16)
last_nr = 0
#print "Getting Image"
_, nr = l.capture(lepton_buf)
print "got image"
if nr != self.last_nr:
self.last_nr = nr
cv2.normalize(lepton_buf, lepton_buf, 0, 65535,
cv2.NORM_MINMAX)
np.right_shift(lepton_buf, 8, lepton_buf)
lepton_buf = np.uint8(lepton_buf)
finalImage = []
for x in lepton_buf:
for y in x:
for z in y:
finalImage.append(z)
self._receivedImage.publish(finalImage)
def capture_video():
with Lepton("/dev/spidev0.0") as l:
#a = np.zeros((240, 320, 3), dtype=np.uint8)
lepton_buf = np.zeros((60, 80, 1), dtype=np.uint16)
last_nr = 0
while True:
time.sleep(.1)
_, nr = l.capture(lepton_buf)
if nr == last_nr:
# no need to redo this frame
continue
last_nr = nr
cv2.normalize(lepton_buf, lepton_buf, 0, 65535, cv2.NORM_MINMAX)
np.right_shift(lepton_buf, 8, lepton_buf)
# a[:lepton_buf.shape[0], :lepton_buf.shape[1], :] = lepton_buf
resizedImage = cv2.resize(lepton_buf, (800, 600))
cv2.imshow('image', np.uint8(
resizedImage)) #just overwriting the saved file repeatedly
cv2.waitKey(1)
