for file_name,measur_circle in correct_circles:
#Keep track of the number of balls measured
num_balls+= len(measur_circle)
image = InputOutput.get_image(file_name)
InputOutput.display_image(image,"Starting Image")
image_hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) # convert to HSV for thresholding
image_hsv = cv2.blur(image_hsv, (9,9)) # blur to reduce noise
thresh = ImageProcessing.thresholdRed(image_hsv)
InputOutput.display_image(thresh,"Thresholded")
thresh = ImageProcessing.removeNoise(thresh)
#calc_circles = ImageProcessing.houghTransform(thresh)
calc_circles = ImageProcessing.blob_circle_detection(thresh)
if calc_circles == None:
calc_circles = []
#calc_circles = ImageProcessing.get_blob_centroid(image, thresh, 5)
InputOutput.display_image_with_circles(image,"Result!",calc_circles)
#evalueateSuccess by comparing the circle position with the most similar
#red ball's measured circle.
#Print basic file facts
print ("")
print ("file: " + file_name)
print ("# of Balls in image: " + str(len(measur_circle)))
print ("# of Balls detected: " + str(len(calc_circles)))
