Exemplo n.º 1
0
    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()
Exemplo n.º 3
0
    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()
Exemplo n.º 4
0
    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()