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test_rpca_tracker.py
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'''
Created on Oct 27, 2015
@author: krsna
'''
from tracker_utils import *
import sys, commands
# Use these to loop later?
movie_dir = '/home/krsna/workspace/animation/tanaya_shotdetect/HTD_scenes_mkv/'#'Antz_scenes'#'../tanaya_shotdetect/scenes/' str(sys.argv[1])#
#0022.avi
# very good example for HTD -0488
num_to_try = 10
shot_ids_rand = list(np.random.randint(5,100,num_to_try))#[int(sys.argv[2])] #
# shot_num = '0030'
# movie_name = '%s.avi' % (shot_num)#'0022.avi'#'0671.avi' #'Antz.avi'
# movie_path = os.path.join(movie_dir, movie_name)
# print movie_name
# lrmf_path = os.path.join(movie_dir, 'IALM_fgbg_%s.mat' % (shot_num))#"./IALM_background_subtraction2.mat"
BOX_TO_TRACK=[]
color = np.random.randint(0,255,(100,3))
color = np.vstack(([0,255,0],color))
#### - - incorporating low rank factored matrix back into video
#for shot_id in shot_ids_rand:
for movie_name in [i for i in os.listdir(movie_dir) if (i.endswith('.avi') and i.startswith('1510'))]:
cv2.destroyAllWindows()
shot_num = movie_name.split('.')[0]
#shot_num = str('%04d' % (shot_id,))
#movie_name = '%s.avi' % (shot_num)#'0022.avi'#'0671.avi' #'Antz.avi'
movie_path = os.path.join(movie_dir, movie_name)
print movie_name
lrmf_path = os.path.join(movie_dir, 'IALM_fgbg_%s.mat' % (shot_num))#"./IALM_background_subtraction2.mat"
if True:
AE = loadmat(lrmf_path)
# AE = loadmat("HTD_outputs/IALM_fgbg_671.mat")
E = AE['FG']
A = AE['BG']
print E.shape
mid_frame = np.round(E.shape[-1]/2.0)
print mid_frame
mov = cv2.VideoCapture(movie_path)
frame_count = 0
ret, frame1_ = mov.read()
frame1 = cv2.resize(frame1_, (frame1_.shape[1]/2, frame1_.shape[0]/2))
hsv = np.zeros_like(frame1)
frame1_gs = cv2.cvtColor(frame1,cv2.COLOR_BGR2GRAY)
r,c = frame1_gs.shape
flow_ref_img = frame1_gs.copy()
E_frame1 = np.asarray(E[:,:,frame_count],'uint8')
A_frame1 = np.asarray(A[:,:,frame_count],'uint8')
gs_img_fg1 = frame1_gs *E_frame1
dst1 = cv2.medianBlur(gs_img_fg1, 5)
_, fg_img_thr = cv2.threshold(dst1, 30, 255, cv2.THRESH_BINARY)
fg_img_rgb1 = cv2.cvtColor(fg_img_thr, cv2.COLOR_GRAY2BGR)
frame1_equ = rgb_equalize(frame1)
cam_frame1 = (fg_img_rgb1) & frame1_equ
#cv2.filter2D(E_frame,-1,kernel)
# _,dst1_ = cv2.threshold(dst1, 0, 255, cv2.THRESH_BINARY)
contours1, hierarchy1 = cv2.findContours(dst1, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
bounding_box_list1 = get_bounding_boxes(contours1)
trimmed_box_list1 = trim_boxes_by_area(bounding_box_list1, 0.8)
bounding_box_list1 = merge_collided_bboxes( trimmed_box_list1, 20 )
_,areas = get_biggest_box(bounding_box_list1,r,c)
print areas, '....areas', bounding_box_list1
# prepare CAMSHIFT - setup ROIs for tracking
# frame_camshift = frame1.copy()
frame_camshift = (fg_img_rgb1) & frame1
bounding_box_list_to_start, _ = get_biggest_box(bounding_box_list1, r, c) #bounding_box_list1
# bounding_box_list_to_start = bounding_box_list1
track_windows, roi_hists = get_camshift_params(bounding_box_list_to_start,frame_camshift)
print 'windows for camshift', track_windows
fg_accumulator = fg_img_rgb1
fg_adder = fg_img_thr
term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 )
FRAME_CUTOFF=33+24
INITIALIZE_counter=[0]
while (frame_count<=FRAME_CUTOFF):
print frame_count
frame_count += 1
#print 'retrieving frames'
ret, frame_orig = mov.read()
if frame_orig is not None:
print frame_count,
#0. Resize image
frame = cv2.resize(frame_orig, (frame_orig.shape[1]/2, frame_orig.shape[0]/2))
my_frame = frame.copy()
rgb_frame = frame.copy()
# cam_frame = frame.copy()
frame_equ = rgb_equalize(frame)
gs_img = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gs_img_3ch = cv2.cvtColor(gs_img, cv2.COLOR_GRAY2BGR)
# hsv_img = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
A_frame = np.asarray(A[:,:,frame_count],'uint8')
bg_img = cv2.cvtColor(A_frame, cv2.COLOR_GRAY2RGB)
# _, A_frame_thr = cv2.threshold(A_frame, 240, 255, cv2.THRESH_BINARY)
# if frame_count==1: A_frame_blur = cv2.medianBlur(A_frame_thr,3)
# A_frame_blur+=cv2.medianBlur(A_frame_thr,3)
E_frame = np.asarray(E[:,:,frame_count]*255,'uint8')
gs_img_fg = gs_img *E_frame
kernel = np.ones((5,5),np.float32)/25
E_blur = cv2.medianBlur(E_frame, 5)#cv2.filter2D(E_frame,-1,kernel)
fg_img = E_blur.copy()
_, fg_img_thr = cv2.threshold(fg_img, 30, 255, cv2.THRESH_BINARY)
fg_rgb_img = cv2.cvtColor(fg_img_thr, cv2.COLOR_GRAY2RGB)
#---- OPTICAL FLOW
flow_input_img = gs_img.copy()
flow_output_img = get_flow_img(hsv, flow_ref_img, flow_input_img)
flow_ref_img = flow_input_img
#--- EO - OPTICAL FLOW
# use flow image & fg image masked rgb image for CAM shift?
cam_frame = (flow_output_img.copy() | fg_rgb_img) & frame_equ
#accumulate all the fg_pixel info and
fg_accumulator = (fg_accumulator | (fg_rgb_img))
fg_adder+=fg_img_thr
# mask the frame with accumulated fg image and then use this for CAMshift to track on
blanket_frame = frame_equ & fg_accumulator
contours, hierarchy = cv2.findContours(E_blur, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
bounding_box_list = get_bounding_boxes(contours)
trimmed_box_list = trim_boxes_by_area(bounding_box_list, 0.9)
bounding_box_list = merge_collided_bboxes( trimmed_box_list, 20 )
print len(bounding_box_list)
SHOW_INIT_BOXES=False
if frame_count >= mid_frame:
SHOW_INIT_BOXES=True
if SHOW_INIT_BOXES:
for box in bounding_box_list:
# if box !=
cv2.rectangle( frame, box[0], box[1], (0,255,0), 1 )
#print 'boxes tracked by me', bounding_box_list
#### ------ DO CAMSHIFT NOW
box_after_shift=[]
for i, track_window in enumerate(track_windows):
roi_hist = roi_hists[i]
# tracking on cam_frame space - not on the whole frame - call it a blanket frame
# other options are cam_frame or just frame
hsv = cv2.cvtColor(cam_frame, cv2.COLOR_BGR2HSV)
dst = cv2.calcBackProject([hsv],[0],roi_hist,[0,180],1)
ret, win_after_shift = cv2.CamShift(dst, track_window, term_crit)
x,y,w,h = win_after_shift
if frame_count==FRAME_CUTOFF:
BOX_TO_TRACK=[x*2, y*2, w*2, h*2]
#print x*2, y*2, w*2, h*2, '------box after camshift----'
box_after_shift.append(((x,y), (x+w,y+h)))
if frame_count<=FRAME_CUTOFF:
for box in box_after_shift:
cv2.rectangle( my_frame, box[0], box[1], (0,255,0), 1)
# box_after_shift = merge_collided_bboxes(box_after_shift, 0)
for box in box_after_shift:
img2 = cv2.rectangle(frame, box[0], box[1], color[len(INITIALIZE_counter)],2)
# cv2.imshow('img2',cam_frame)
#print 'box_after shift',box_after_shift,
bounding_box_for_shift = box_after_shift
# if not bounding_box_for_shift: track_windows, roi_hists = get_camshift_params(bounding_box_for_shift, cam_frame)
_,test = cv2.threshold(fg_adder, 240, 255, cv2.THRESH_BINARY)
cv2.imshow('y_%s' % (shot_num),np.hstack(((fg_accumulator & rgb_frame), cam_frame, frame, my_frame)))
k = cv2.cv.WaitKey(30) & 0xff
# if frame_count==mid_frame: time.sleep(2.0)
print BOX_TO_TRACK
if BOX_TO_TRACK:
if frame_count==FRAME_CUTOFF:
print 'box tracked = ', BOX_TO_TRACK
bbox_init_str = ','.join([str(l) for l in BOX_TO_TRACK])
print '------GET READY TO TRACK-------'
track_status=commands.getoutput('python run.py --skip %s --bbox=%s %s ' % (str(FRAME_CUTOFF) ,bbox_init_str, movie_path))
print track_status
else:
mov.release()
cv2.destroyAllWindows()