import cv2
import numpy as np
cap = cv2.VideoCapture('/home/sm/Desktop/VIRB0022.MP4')
frame_num = 0
num_frames = 30000 #the total number of frames in the video
cif = [] #the data for detected juggling balls
while frame_num < num_frames: #look through each frame of video
    ret, img = cap.read()
    img = img[0:400, 420:800] #only look at the relevant part of image (faster processing)
    gimg = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    #find the juggling balls!
    circles = cv2.HoughCircles(gimg, cv2.HOUGH_GRADIENT, 2, 15, np.array([]), 100, 30, 1, 30)
    c = 0 #the number of circles in the frame
    try:
        a, b, c = circles.shape
        for i in range(b):
            if circles[0][i][2] > 6 and circles[0][i][2] <12:
                c+=1
                cv2.circle(img, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv2.LINE_AA)
    except: pass
    cv2.imshow("detected circles", img)
    cv2.waitKey(1)
    frame_num += 1
    cif.append(c)
#determine if the frame contains juggling
for i in range(len(cif)-20):
    if sum(cif[i:i+15])<17:
        cif[i] = 'e'
run_num = 1
cut_tally = 0
while len(cif)>20:
    while cif[0]=='e':
        cif.remove('e')
        cut_tally+= 1
    try:
        #find the run length
        run_length = sum(cif[:cif.index('e')])/88.1
        if run_length > 13:
            #find when the runs starts, and make a video link
            video_link = 'https://youtu.be/sm-GxpeuMsA?t=' + str(int(cut_tally/60.01)) + 's'
            print 'Run number', run_num, 'was ', int(run_length) , 'catches:', video_link
            run_num += 1
        cut_tally += cif.index('e')
        cif = cif[cif.index('e'):]
    except: break