def single_scan_for_max_temperature(self):
lepton_interface = Lepton_interface()
# time.sleep(0.2)
raw_values = lepton_interface.get_raw_values() # Get camera output (raw values)
max_temperature_old = self.get_max_temperature_data(raw_values) # Get the maximum temperature from raw values
return max_temperature_old # Return the max temperature
def iterate_for_max_temperature(self):
lepton_interface = Lepton_interface()
ITERATIONS = 5 # How many times to take image
max_temperature_old = {
"max_raw_pixel": 0,
"max_pixel_locations_x": 0,
"max_pixel_locations_y": 0,
"max_temperature": 0,
"raw_values": 0,
"min_temperature": 0
}
# Initialize variable
for i in range(0, ITERATIONS - 1): # Repeat as required by Iterations
time.sleep(0.2)
raw_values = lepton_interface.get_raw_values(
) # Get camera output (raw values)
max_temperature_new = self.get_max_temperature_data(
raw_values) # Get the maximum temperature from raw values
if max_temperature_new["max_temperature"] > max_temperature_old[
"max_temperature"]:
max_temperature_old = max_temperature_new # If new temp is max, record new max temperature
else:
continue # Else keep the old max temperature and continue
return max_temperature_old # Return the max temperature
def single_scan_for_max_temperature(self):
lepton_interface = Lepton_interface()
# time.sleep(0.2)
raw_values = lepton_interface.get_raw_values(
) # Get camera output (raw values)
max_temperature_old = self.get_max_temperature_data(
raw_values) # Get the maximum temperature from raw values
return max_temperature_old # Return the max temperature
def coloured_image_from_raw(self,raw_values, image_scalar):
STORED_IMAGE_NAME = "DetectionImage1.jpg"
lepton_object = Lepton_interface()
# Convert raw data to 8 bit image - takes 0.0008s
bit8_image = lepton_object.raw_to_8bit(raw_values)
bit8_image = bit8_image.astype(uint8)
# Remove non-needed dimension
bit8_image = bit8_image.squeeze()
# Colour image takes ~0.005
coloured_image = self.colour_thermal_image(bit8_image)
# Scale 8 bit coloured image # CV_INTER_CUBIC might be used - slow but looks better. INTER_NEAREST.
# INTER_LINEAR takes ~0.025s INTER_CUBIC - ~0.07s. Nearest - 0.01s
coloured_image = cv2.resize(coloured_image, (0,0), None, image_scalar, image_scalar, cv2.INTER_LINEAR)
# Takes ~0.2s, updated one takes ~0.0001s
# cv2.imwrite(STORED_IMAGE_NAME, np.uint8(coloured_image)) # Write the image to file
mat_array = cv.fromarray(coloured_image)
# Take the image from file as SIMPLECV image. Updated one ~0.005s
simplecv_img = Image(mat_array)
# simplecv_img = Image(STORED_IMAGE_NAME)
return simplecv_img
def iterate_for_max_temperature(self):
lepton_interface = Lepton_interface()
ITERATIONS = 5 # How many times to take image
max_temperature_old = {"max_raw_pixel": 0,
"max_pixel_locations_x": 0,
"max_pixel_locations_y": 0,
"max_temperature": 0,
"raw_values": 0,
"min_temperature": 0}
# Initialize variable
for i in range(0, ITERATIONS-1): # Repeat as required by Iterations
time.sleep(0.2)
raw_values = lepton_interface.get_raw_values() # Get camera output (raw values)
max_temperature_new = self.get_max_temperature_data(raw_values) # Get the maximum temperature from raw values
if max_temperature_new["max_temperature"] > max_temperature_old["max_temperature"]:
max_temperature_old = max_temperature_new # If new temp is max, record new max temperature
else:
continue # Else keep the old max temperature and continue
return max_temperature_old # Return the max temperature
def coloured_image_from_raw(self, raw_values, image_scalar):
STORED_IMAGE_NAME = "DetectionImage1.jpg"
lepton_object = Lepton_interface()
# Convert raw data to 8 bit image - takes 0.0008s
bit8_image = lepton_object.raw_to_8bit(raw_values)
bit8_image = bit8_image.astype(uint8)
# Remove non-needed dimension
bit8_image = bit8_image.squeeze()
# Colour image takes ~0.005
coloured_image = self.colour_thermal_image(bit8_image)
# Scale 8 bit coloured image # CV_INTER_CUBIC might be used - slow but looks better. INTER_NEAREST.
# INTER_LINEAR takes ~0.025s INTER_CUBIC - ~0.07s. Nearest - 0.01s
coloured_image = cv2.resize(coloured_image, (0, 0), None, image_scalar,
image_scalar, cv2.INTER_LINEAR)
# Takes ~0.2s, updated one takes ~0.0001s
# cv2.imwrite(STORED_IMAGE_NAME, np.uint8(coloured_image)) # Write the image to file
mat_array = cv.fromarray(coloured_image)
# Take the image from file as SIMPLECV image. Updated one ~0.005s
simplecv_img = Image(mat_array)
# simplecv_img = Image(STORED_IMAGE_NAME)
return simplecv_img