def run(self):
try:
print "starting web server"
# initialise web server which will display final image
web = Webserver(balloon_config.config.parser,
(lambda: self.frame_filtered))
print "initialising camera"
# initialise video capture
balloon_video.init_camera()
print "Ready to go!"
while (True):
# get a frame
frame = balloon_video.capture_image()
# Convert BGR to HSV
hsv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# get latest colour filters
self.read_config_file(False)
# use trackbar positions to filter image
colour_low = np.array([self.h_low, self.s_low, self.v_low])
colour_high = np.array([self.h_high, self.s_high, self.v_high])
# Threshold the HSV image
mask = cv2.inRange(hsv_frame, colour_low, colour_high)
#PAPOU_MOD Blur & Erode
blurred = cv2.GaussianBlur(mask, (3, 3), 0)
# Erode
erode_kernel = np.ones((3, 3), np.uint8)
eroded_img = cv2.erode(blurred, erode_kernel, iterations=2)
# dilate
dilate_kernel = np.ones((10, 10), np.uint8)
dilated_img = cv2.dilate(eroded_img,
dilate_kernel,
iterations=1)
# Bitwise-AND mask and original image
self.frame_filtered = cv2.bitwise_and(frame,
frame,
mask=dilated_img)
# handle interrupts
except:
print "interrupted, exiting"
# exit and close web server
print "exiting..."
web.close()
def run(self):
try:
print "starting web server"
# initialise web server which will display final image
web = Webserver(balloon_config.config.parser, (lambda : self.frame_filtered))
print "initialising camera"
# initialise video capture
balloon_video.init_camera()
print "Ready to go!"
while(True):
# get a frame
frame = balloon_video.capture_image()
# Convert BGR to HSV
hsv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# get latest colour filters
self.read_config_file(False)
# use trackbar positions to filter image
colour_low = np.array([self.h_low,self.s_low,self.v_low])
colour_high = np.array([self.h_high,self.s_high,self.v_high])
# Threshold the HSV image
mask = cv2.inRange(hsv_frame, colour_low, colour_high)
# Erode
erode_kernel = np.ones((3,3),np.uint8);
eroded_img = cv2.erode(mask,erode_kernel,iterations = 1)
# dilate
dilate_kernel = np.ones((10,10),np.uint8);
dilated_img = cv2.dilate(eroded_img,dilate_kernel,iterations = 1)
# Bitwise-AND mask and original image
self.frame_filtered = cv2.bitwise_and(frame,frame, mask=dilated_img)
# handle interrupts
except:
print "interrupted, exiting"
# exit and close web server
print "exiting..."
web.close()
def main(self):
web = Webserver(balloon_config.config.parser, (lambda: self.frame))
# initialise camera
balloon_video.init_camera()
video_writer = balloon_video.open_video_writer()
# get start time
start_time = time.time()
# loop for 10 seconds looking for circles
while (time.time() - start_time < 20):
# Take each frame
frame = balloon_video.capture_image()
self.frame = frame
# is there the x & y position in frame of the largest balloon
found_in_image, xpos, ypos, size = self.analyse_frame(frame)
# display image
cv2.imshow('frame', frame)
# write the frame
video_writer.write(frame)
# exit if user presses ESC
k = cv2.waitKey(5) & 0xFF
if k == 27:
break
print "exiting..."
web.close()
# uncomment line below if window with real-time video was displayed
cv2.destroyAllWindows()
# release camera
balloon_video.close_camera()
def main(self):
web = Webserver(balloon_config.config.parser, (lambda : self.frame))
# initialise camera
balloon_video.init_camera()
video_writer = balloon_video.open_video_writer()
# get start time
start_time = time.time()
# loop for 10 seconds looking for circles
while(time.time() - start_time < 20):
# Take each frame
frame = balloon_video.capture_image()
self.frame = frame
# is there the x & y position in frame of the largest balloon
found_in_image, xpos, ypos, size = self.analyse_frame(frame)
# display image
cv2.imshow('frame',frame)
# write the frame
video_writer.write(frame)
# exit if user presses ESC
k = cv2.waitKey(5) & 0xFF
if k == 27:
break
print "exiting..."
web.close()
# uncomment line below if window with real-time video was displayed
cv2.destroyAllWindows()
# release camera
balloon_video.close_camera()
def run(self):
# initialise video capture
balloon_video.init_camera()
# create trackbars for color change
cv2.namedWindow('Colour Filters')
cv2.createTrackbar('Hue min', 'Colour Filters', self.h_low, 255,
self.empty_callback)
cv2.createTrackbar('Hue max', 'Colour Filters', self.h_high, 255,
self.empty_callback)
cv2.createTrackbar('Sat min', 'Colour Filters', self.s_low, 255,
self.empty_callback)
cv2.createTrackbar('Sat max', 'Colour Filters', self.s_high, 255,
self.empty_callback)
cv2.createTrackbar('Bgt min', 'Colour Filters', self.v_low, 255,
self.empty_callback)
cv2.createTrackbar('Bgt max', 'Colour Filters', self.v_high, 255,
self.empty_callback)
cv2.createTrackbar('Save', 'Colour Filters', 0, 10, self.save_callback)
while (True):
# get a frame
frame = balloon_video.capture_image()
output = frame.copy()
# Convert BGR to HSV
hsv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# get latest trackbar positions
self.h_low = cv2.getTrackbarPos('Hue min', 'Colour Filters')
self.h_high = cv2.getTrackbarPos('Hue max', 'Colour Filters')
self.s_low = cv2.getTrackbarPos('Sat min', 'Colour Filters')
self.s_high = cv2.getTrackbarPos('Sat max', 'Colour Filters')
self.v_low = cv2.getTrackbarPos('Bgt min', 'Colour Filters')
self.v_high = cv2.getTrackbarPos('Bgt max', 'Colour Filters')
# use trackbar positions to filter image
colour_low = np.array([self.h_low, self.s_low, self.v_low])
colour_high = np.array([self.h_high, self.s_high, self.v_high])
# Threshold the HSV image
mask = cv2.inRange(hsv_frame, colour_low, colour_high)
#PAPOU_MOD Hough Circle
#gray = cv2.cvtColor(mask, cv2.COLOR_HSV2GRAY)
blurred = cv2.GaussianBlur(mask, (3, 3), 0)
#circles = cv2.HoughCircles(blurred, cv2.cv.CV_HOUGH_GRADIENT, 1.9, 60)
# ensure at least some circles were found
#if circles is not None:
# convert the (x, y) coordinates and radius of the circles to integers
#circles = np.round(circles[0, :]).astype("int")
# loop over the (x, y) coordinates and radius of the circles
#for (x, y, r) in circles:
# draw the circle in the output image, then draw a rectangle
# corresponding to the center of the circle
#cv2.circle(output, (x, y), r, (0, 255, 0), 4)
#cv2.rectangle(output, (x - 5, y - 5), (x + 5, y + 5), (0, 128, 255), -1)
# Erode
erode_kernel = np.ones((3, 3), np.uint8)
eroded_img = cv2.erode(blurred, erode_kernel, iterations=2)
# dilate
dilate_kernel = np.ones((7, 7), np.uint8)
dilated_img = cv2.dilate(eroded_img, dilate_kernel, iterations=1)
# Bitwise-AND mask and original image
res = cv2.bitwise_and(frame, frame, mask=dilated_img)
#cv2.imshow('Original',frame)
cv2.imshow('Mask', mask)
cv2.imshow('Gaussian Blur', blurred)
cv2.imshow('Filtered Result', res)
#cv2.imshow('resultat', np.hstack([frame, output]))
#cv2.imshow('resultat', output)
k = cv2.waitKey(5) & 0xFF
if k == 27:
break
# close camera
frame = balloon_video.close_camera()
# close all windows
cv2.destroyAllWindows()
def run(self):
# initialise video capture
balloon_video.init_camera()
# create trackbars for color change
cv2.namedWindow('Colour Filters')
cv2.createTrackbar('Hue min', 'Colour Filters', self.h_low, 255,
self.empty_callback)
cv2.createTrackbar('Hue max', 'Colour Filters', self.h_high, 255,
self.empty_callback)
cv2.createTrackbar('Sat min', 'Colour Filters', self.s_low, 255,
self.empty_callback)
cv2.createTrackbar('Sat max', 'Colour Filters', self.s_high, 255,
self.empty_callback)
cv2.createTrackbar('Bgt min', 'Colour Filters', self.v_low, 255,
self.empty_callback)
cv2.createTrackbar('Bgt max', 'Colour Filters', self.v_high, 255,
self.empty_callback)
cv2.createTrackbar('Save', 'Colour Filters', 0, 10, self.save_callback)
while (True):
# get a frame
frame = balloon_video.capture_image()
# Convert BGR to HSV
hsv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# get latest trackbar positions
self.h_low = cv2.getTrackbarPos('Hue min', 'Colour Filters')
self.h_high = cv2.getTrackbarPos('Hue max', 'Colour Filters')
self.s_low = cv2.getTrackbarPos('Sat min', 'Colour Filters')
self.s_high = cv2.getTrackbarPos('Sat max', 'Colour Filters')
self.v_low = cv2.getTrackbarPos('Bgt min', 'Colour Filters')
self.v_high = cv2.getTrackbarPos('Bgt max', 'Colour Filters')
# use trackbar positions to filter image
colour_low = np.array([self.h_low, self.s_low, self.v_low])
colour_high = np.array([self.h_high, self.s_high, self.v_high])
# Threshold the HSV image
mask = cv2.inRange(hsv_frame, colour_low, colour_high)
#PAPOU_MOD Blur & Erode
blurred = cv2.GaussianBlur(mask, (3, 3), 0)
# Erode
erode_kernel = np.ones((3, 3), np.uint8)
#eroded_img = cv2.erode(mask,erode_kernel,iterations = 1)
eroded_img = cv2.erode(blurred, erode_kernel, iterations=2)
# dilate
#dilate_kernel = np.ones((10,10),np.uint8);
dilate_kernel = np.ones((7, 7), np.uint8)
dilated_img = cv2.dilate(eroded_img, dilate_kernel, iterations=1)
# Bitwise-AND mask and original image
res = cv2.bitwise_and(frame, frame, mask=dilated_img)
cv2.imshow('Original', frame)
cv2.imshow('Mask', mask)
cv2.imshow('Filtered Result', res)
#cv2.imshow('grey_res',grey_res)
k = cv2.waitKey(5) & 0xFF
if k == 27:
break
# close camera
frame = balloon_video.close_camera()
# close all windows
cv2.destroyAllWindows()
def run(self):
# initialise video capture
balloon_video.init_camera()
# create trackbars for color change
cv2.namedWindow('Colour Filters')
cv2.createTrackbar('Hue min','Colour Filters',self.h_low,255,self.empty_callback)
cv2.createTrackbar('Hue max','Colour Filters',self.h_high,255,self.empty_callback)
cv2.createTrackbar('Sat min','Colour Filters',self.s_low,255,self.empty_callback)
cv2.createTrackbar('Sat max','Colour Filters',self.s_high,255,self.empty_callback)
cv2.createTrackbar('Bgt min','Colour Filters',self.v_low,255,self.empty_callback)
cv2.createTrackbar('Bgt max','Colour Filters',self.v_high,255,self.empty_callback)
cv2.createTrackbar('Save','Colour Filters',0,10,self.save_callback)
while(True):
# get a frame
frame = balloon_video.capture_image()
# Convert BGR to HSV
hsv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# get latest trackbar positions
self.h_low = cv2.getTrackbarPos('Hue min','Colour Filters')
self.h_high = cv2.getTrackbarPos('Hue max','Colour Filters')
self.s_low = cv2.getTrackbarPos('Sat min','Colour Filters')
self.s_high = cv2.getTrackbarPos('Sat max','Colour Filters')
self.v_low = cv2.getTrackbarPos('Bgt min','Colour Filters')
self.v_high = cv2.getTrackbarPos('Bgt max','Colour Filters')
# use trackbar positions to filter image
colour_low = np.array([self.h_low,self.s_low,self.v_low])
colour_high = np.array([self.h_high,self.s_high,self.v_high])
# Threshold the HSV image
mask = cv2.inRange(hsv_frame, colour_low, colour_high)
# Erode
erode_kernel = np.ones((3,3),np.uint8);
eroded_img = cv2.erode(mask,erode_kernel,iterations = 1)
# dilate
dilate_kernel = np.ones((10,10),np.uint8);
dilated_img = cv2.dilate(eroded_img,dilate_kernel,iterations = 1)
# Bitwise-AND mask and original image
res = cv2.bitwise_and(frame,frame, mask=dilated_img)
cv2.imshow('Original',frame)
cv2.imshow('Mask',mask)
cv2.imshow('Filtered Result',res)
#cv2.imshow('grey_res',grey_res)
k = cv2.waitKey(5) & 0xFF
if k == 27:
break
# close camera
frame = balloon_video.close_camera()
# close all windows
cv2.destroyAllWindows()
