# for tsi object
tsi_object[view] = TSIUtil.TSI(M[view])
# for 3 frame difference
prev_epi = [None, None]
prev_tsi = [None, None]
for i in range(2):
img_color = img = next(fi[view])
prev_imgs_color[view] = img
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
dst = cv2.warpPerspective(img, M[view], (1000, 300))
prev_epi[i] = epi_object[view].apply(dst)
prev_tsi[i] = tsi_object[view].apply(dst)
fdiff_epi[view] = FrameDifference(*prev_epi)
fdiff_tsi[view] = FrameDifference(*prev_tsi)
mask_path = '../../data/gt/2016-ITS-BrnoCompSpeed/dataset/session{}_{}/video_mask.png'.format(
ses_id, view)
masks[view] = cv2.imread(mask_path, 0)
"""
-------------------------------------------------------------------------------
Main Program
-------------------------------------------------------------------------------
"""
ctr = 0
while True:
ctr += 1
intersection = None
# for 3 frame difference
prev_dst = [None, None]
prev_view = [None, None]
for i in range(2):
img = next(fi[view])
prev_imgs_color[view] = img
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
dst = cv2.warpPerspective(img, M[view], (1000, 300))
prev_dst[i] = dst
prev_view[i] = img
# bm_dst[view] = BackgroundModel (iter (prev_dst), detectShadows=False)
# bm_dst[view].learn (tot_frame_init=2)
fdiff_dst[view] = FrameDifference(*prev_dst)
fdiff_view[view] = FrameDifference(*prev_view)
mask_path = '../../data/gt/2016-ITS-BrnoCompSpeed/dataset/session{}_{}/video_mask.png'.format(
ses_id, view)
masks[view] = cv2.imread(mask_path, 0)
"""
-------------------------------------------------------------------------------
Main Program
-------------------------------------------------------------------------------
"""
ctr = 0
while True:
ctr += 1
intersection = None
# get rectangular homography mapping
corner_gt = np.float32(corner)
corner_wrap = np.float32([[0, 300], [0, 0], [1000, 0], [1000, 300]])
M[view] = cv2.getPerspectiveTransform(corner_gt, corner_wrap)
# for 3 frame difference
prev_img = [None, None]
for i in range(2):
img = next(fi[view])
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# save background
prev_img[i] = img
fdiff_view[view] = FrameDifference(*prev_img)
mask_path = '../../data/gt/2016-ITS-BrnoCompSpeed/dataset/session{}_{}/video_mask.png'.format(
ses_id, view)
masks[view] = cv2.imread(mask_path, 0)
ss = list(prev_img[0].shape)
ss.append(int(3))
ss = tuple(ss)
print(ss)
print(type(prev_img[0].shape))
fourcc = cv2.VideoWriter_fourcc(*'XVID')
video = cv2.VideoWriter('video.avi', fourcc, 25.0, prev_img[0].shape)
"""
-------------------------------------------------------------------------------
logger.info("-- Generate prev_epi and tsi")
for i in range(2):
img_color = img = next(fi[view])
prev_imgs_color[view] = img
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
dst = cv2.warpPerspective(img, M[view], (1000, 300))
for j in range(tot_epi):
prev_epi[j][i] = epi_object[view][j].apply(dst)
prev_tsi[i] = tsi_object[view].apply(dst)
logger.info("-- Initialize EPI FrameDifference")
fdiff_epi[view] = []
for i in range(tot_epi):
fdiff_epi[view].append(FrameDifference(*prev_epi[i]))
logger.info("-- Initialize TSI FrameDifference")
fdiff_tsi[view] = FrameDifference(*prev_tsi)
mask_path = '../../data/gt/2016-ITS-BrnoCompSpeed/dataset/session{}_{}/video_mask.png'.format(
ses_id, view)
masks[view] = cv2.imread(mask_path, 0)
flag_prev_object = False
list_height = []
logger.info("Done initializing")
logger.info("Start counting")
"""
-------------------------------------------------------------------------------
else:
tsi_multi = np.hstack((tsi_multi, strip))
cv2.line(new_dst, (j * tsi_const['xrange'], 0),
(j * tsi_const['xrange'], 300),
color=(255, 255, 0),
thickness=3)
# prev_tsi[i] = tsi_object[view].apply (dst)
prev_view[i] = dst
prev_tsi_multi[i] = tsi_multi
logger.info("-- Initialize TSI FrameDifference")
# fdiff_tsi[view] = FrameDifference (*prev_tsi)
# fdiff_view[view] = BackgroundModel (iter (prev_view), detectShadows=False)
# fdiff_view[view].learn (tot_frame_init=2)
fdiff_view[view] = FrameDifference(*prev_view)
# fdiff_tsi_multi[view] = BackgroundModel (iter (prev_tsi_multi), detectShadows=False)
# fdiff_tsi_multi[view].learn (tot_frame_init=2)
fdiff_tsi_multi[view] = FrameDifference(*prev_tsi_multi)
mask_path = '../../data/gt/2016-ITS-BrnoCompSpeed/dataset/session{}_{}/video_mask.png'.format(
ses_id, view)
masks[view] = cv2.imread(mask_path, 0)
# flag_prev_object = False
# list_height = []
# logger.info ("Creating tsi_multi")
logger.info("Done initializing")
logger.info("Start counting")