text: '''Krishna Somandepalli - 01/23/2016'''
  from matplotlib import pyplot
  import numpy as np
  import os,commands
  import cv2
  import time
  from skimage import io, transform
  import sys, json
  # Make sure that you set this to the location your caffe2 library lies.
  
  
  
  movie_path = sys.argv[1]
  object_json_path = sys.argv[2]
  movie_width = int(commands.getoutput("mediainfo '--Inform=Video;%Width%' "+movie_path))
  
  movie_height = int(commands.getoutput("mediainfo '--Inform=Video;%Height%' "+movie_path))
  #for load into json first, object detection on every 10 frames
  dict_list = json.load(open(object_json_path,'rU'))
  # What is the subsampling ration
  DOWNSAMPLE = 10
  
  # what is the threshold for confidence in NN object detection
  DNN_BOX_CONF = 0.1
  
  RUN_VIDEO=True
  DISPLAY=False
  SAVE=True
  
  ##  - version for the chosen boxes     
  key_frames=[i['init_frame'] for i in dict_list if (i['final_frame']-i['init_frame'])>1] #getting the frame numbers from the object detection list 
  
  if RUN_VIDEO:
      if os.path.isfile(movie_path):
        movie_name = os.path.basename(movie_path).split('.')[0]
        frame_count = 0
        im_out_dir = './Objects_SAL_tracked/'+movie_name
        if not os.path.isdir(im_out_dir): os.makedirs(im_out_dir) 
        mov = cv2.VideoCapture(movie_path)
  
        while(mov.isOpened()):
            frame_count+=1
            ret, img_bgr = mov.read()
  
            if img_bgr is not None:
  	  	
            # same as  -- if ret:
                if frame_count==key_frames[0]:
  	      	  print 'now showing --- ', frame_count
  		  key_dict = [i for i in dict_list if i['init_frame']==frame_count]
  		  x1,y1,w,h = key_dict[0]['init_bbox']
  		  frames_tracked = key_dict[0]['final_frame']-key_dict[0]['init_frame']
  		  print 'tracked for # frames = ', frames_tracked
  		  x2 = x1+w
  		  y2 = y1+h
  		  print x1,y1,w,h
  		  if x1<0: x1=0
  		  if y1<0: y1=0
  		  if DISPLAY:
  		  	cv2.imshow( 'object', img_bgr[y1:y2,x1:x2,:] )
  		 	cv2.waitKey(0)
  		  if SAVE:
  		  	cv2.imwrite(im_out_dir+'/'+str(frame_count)+'_'+str(frames_tracked)+'.ppm', img_bgr[y1:y2,x1:x2,:])
  		  key_frames.pop(0)
  
  
            else:
                mov.release()
                cv2.destroyAllWindows()
                                        
  
        
        print 'DONEEEEEEEEEEEEEEEEEEEEEEEE'
  
  
      else:
          print 'CHECK MOVIE PATH - DOESNOT EXIST', movie_path, '--nothing to do--'
          #break
  
  print 'TOTAL TIME (seconds) = ', time.time()-start_time
  