def Flat_Calibration():
blobs_threshold_flat = 240 #170 on laptop
blobs_min_size_flat = 1000
CROP_LENGTH = 20
flat_calibration_done = False
while (not flat_calibration_done
): # Repeat until flat flap calibration is performed correctly
image_and_coords = get_image_and_coords(CROP_LENGTH)
flat_image = image_and_coords["image"]
Calibration_coords = image_and_coords["coords"]
# flat_image = AcquireFlatImage()
# Calibration_coords = get_calibration_coordinates(flat_image)
print "Approximate coordinates of flap: ", Calibration_coords
Calibration_values = ColorAveraging(flat_image, Calibration_coords,
CROP_LENGTH)
filteredImage = Orange_Flap_V5_Demo.apply_filter(
Calibration_values, flat_image)
possible_flaps = filteredImage.findBlobs(
threshval=blobs_threshold_flat, minsize=blobs_min_size_flat)
if possible_flaps > 1:
possible_flaps = possible_flaps.sortDistance(
point=(Calibration_coords[0], Calibration_coords[1]))
# for i in range(0, len(possible_flaps)):
# filteredImage.dl().rectangle2pts(possible_flaps[i].topLeftCorner(),
# possible_flaps[i].bottomRightCorner(),Color.GREEN, width = 5)
# filteredImage.dl().text("%s" %i, (possible_flaps[i].topLeftCorner()), color=Color.RED)
elif possible_flaps < 1:
print "No possible flaps were found, starting calibration again"
demo_images.no_flaps_found(flat_image)
continue
flap = possible_flaps[0]
FlapWHRatio = round(float(flap.width()) / float(flap.height()), 4)
result = demo_images.show_detected_orange_flap(flat_image, flap,
FlapWHRatio, "Flat")
if result == True:
flat_calibration_done = True
continue
else:
continue
FlapWHRatio = round(float(flap.width()) / float(flap.height()), 4)
values = {
"AvHue": Calibration_values["AvHue"],
"AvSat": Calibration_values["AvSat"],
"StdSat": Calibration_values["StdSat"],
"FlatWHRatio": FlapWHRatio,
"mouseX": Calibration_coords[0],
"mouseY": Calibration_coords[1]
}
return values
def Slope_Calibration(AvHue, AvSat, StdSat, mouseX, mouseY):
blobs_threshold_slope = 240 #170 on laptop
blobs_min_size_slope = 1000
slope_calibration_done = False
while (not slope_calibration_done):
demo_images.ask_for_slope_position()
slope_image = GetImage()
# slope_image = AcquireSlopeImage()
filtered_image = Orange_Flap_V5_Demo.apply_filter(
{
"AvHue": AvHue,
"AvSat": AvSat,
"StdSat": StdSat
}, slope_image)
possible_flaps = filtered_image.findBlobs(
threshval=blobs_threshold_slope,
minsize=blobs_min_size_slope) #CAN ADD SIZES AND STUFF
if possible_flaps > 1:
possible_flaps = possible_flaps.sortDistance(point=(mouseX,
mouseY))
# for i in range(0, len(possible_flaps)):
# filtered_image.dl().rectangle2pts(possible_flaps[i].topLeftCorner(),
# possible_flaps[i].bottomRightCorner(),Color.GREEN, width = 5)
# filtered_image.dl().text("%s" %i, (possible_flaps[i].bottomRightCorner()), color=Color.RED)
elif possible_flaps < 1:
print "No flap was found, please take another picture"
demo_images.no_flaps_found(slope_image)
continue
flap = possible_flaps[0]
SlopeWHRatio = round(float(flap.width()) / float(flap.height()), 4)
result = demo_images.show_detected_orange_flap(slope_image, flap,
SlopeWHRatio, "Slope")
if result == True:
slope_calibration_done = True
continue
else:
continue
SlopeWHRatio = round(float(flap.width()) / float(flap.height()), 4)
return SlopeWHRatio
def Flat_Calibration():
blobs_threshold_flat = 240 #170 on laptop
blobs_min_size_flat = 1000
CROP_LENGTH = 20
flat_calibration_done = False
while (not flat_calibration_done): # Repeat until flat flap calibration is performed correctly
image_and_coords = get_image_and_coords(CROP_LENGTH)
flat_image = image_and_coords["image"]
Calibration_coords = image_and_coords["coords"]
# flat_image = AcquireFlatImage()
# Calibration_coords = get_calibration_coordinates(flat_image)
print "Approximate coordinates of flap: ", Calibration_coords
Calibration_values = ColorAveraging(flat_image, Calibration_coords, CROP_LENGTH)
filteredImage = Orange_Flap_V5_Demo.apply_filter(Calibration_values, flat_image)
possible_flaps = filteredImage.findBlobs(threshval = blobs_threshold_flat, minsize=blobs_min_size_flat)
if possible_flaps > 1:
possible_flaps = possible_flaps.sortDistance(point =(Calibration_coords[0], Calibration_coords[1]))
# for i in range(0, len(possible_flaps)):
# filteredImage.dl().rectangle2pts(possible_flaps[i].topLeftCorner(),
# possible_flaps[i].bottomRightCorner(),Color.GREEN, width = 5)
# filteredImage.dl().text("%s" %i, (possible_flaps[i].topLeftCorner()), color=Color.RED)
elif possible_flaps < 1:
print "No possible flaps were found, starting calibration again"
demo_images.no_flaps_found(flat_image)
continue
flap = possible_flaps[0]
FlapWHRatio = round(float(flap.width()) / float(flap.height()), 4)
result = demo_images.show_detected_orange_flap(flat_image,flap,FlapWHRatio, "Flat")
if result == True:
flat_calibration_done = True
continue
else:
continue
FlapWHRatio = round(float(flap.width()) / float(flap.height()), 4)
values = {"AvHue": Calibration_values["AvHue"], "AvSat": Calibration_values["AvSat"],
"StdSat": Calibration_values["StdSat"], "FlatWHRatio": FlapWHRatio,
"mouseX": Calibration_coords[0], "mouseY": Calibration_coords[1]}
return values
def Slope_Calibration(AvHue,AvSat,StdSat,mouseX,mouseY):
blobs_threshold_slope = 240 #170 on laptop
blobs_min_size_slope = 1000
slope_calibration_done = False
while (not slope_calibration_done):
demo_images.ask_for_slope_position()
slope_image = GetImage()
# slope_image = AcquireSlopeImage()
filtered_image = Orange_Flap_V5_Demo.apply_filter({"AvHue": AvHue, "AvSat": AvSat, "StdSat": StdSat}, slope_image)
possible_flaps = filtered_image.findBlobs(threshval = blobs_threshold_slope, minsize=blobs_min_size_slope) #CAN ADD SIZES AND STUFF
if possible_flaps > 1:
possible_flaps = possible_flaps.sortDistance(point =(mouseX, mouseY))
# for i in range(0, len(possible_flaps)):
# filtered_image.dl().rectangle2pts(possible_flaps[i].topLeftCorner(),
# possible_flaps[i].bottomRightCorner(),Color.GREEN, width = 5)
# filtered_image.dl().text("%s" %i, (possible_flaps[i].bottomRightCorner()), color=Color.RED)
elif possible_flaps < 1:
print "No flap was found, please take another picture"
demo_images.no_flaps_found(slope_image)
continue
flap = possible_flaps[0]
SlopeWHRatio = round(float(flap.width()) / float(flap.height()), 4)
result = demo_images.show_detected_orange_flap(slope_image,flap,SlopeWHRatio, "Slope")
if result == True:
slope_calibration_done = True
continue
else:
continue
SlopeWHRatio = round(float(flap.width()) / float(flap.height()), 4)
return SlopeWHRatio
