def label(self, task_id, img_file_list, boundingbox):
LOG.debug('label function called! labeling following files:')
LOG.debug(img_file_list)
cache_manager = cachemanagement.cacheManager()
cur_dir =os.path.dirname(os.path.realpath(__file__))
# task_id is needed for separating labeling multiple objects
cache_dir = os.path.dirname(os.path.realpath(__file__)) + '/tmp/s3/'
cache_dir, img_file_list = cache_manager.cacheImageFromFileList(img_file_list, cache_dir)
img_file_list = map(lambda x: cache_dir+'/'+x, img_file_list)
input_img_file = cache_dir+'/'+ str(task_id) +'labeler_input_img_list.txt'
MyUtils.writeListToFile(img_file_list, input_img_file)
output_bx_file = cache_dir +'/'+ str(task_id) + 'labeler_output_bx_list.txt'
cmd = cur_dir+'/TrackingApp '
cmd += str(input_img_file) + ' '
cmd += str(output_bx_file) + ' '
for bx_vec in boundingbox:
cmd += str(bx_vec) + ' '
cmd += 'BOOSTING'
# call tracker
os.system(cmd)
# get input
output_bxes = []
with open(output_bx_file, 'r') as bx_file:
bxes = bx_file.read().splitlines()
for bx in bxes:
LOG.debug(bx)
output_bx = ast.literal_eval(bx)
output_bxes.append(output_bx)
return output_bxes
def label_old(self, task_id, img_file_list, boundingbox):
LOG.debug('camshift labeler label function called! labeling following files:')
LOG.debug(img_file_list)
cache_manager = cachemanagement.cacheManager()
cache_dir = os.path.dirname(os.path.realpath(__file__)) + '/tmp/s3'
cache_dir, img_file_list = cache_manager.cacheImageFromFileList(img_file_list, cache_dir)
img_file_list = map(lambda x: cache_dir+'/'+x, img_file_list)
MyUtils.writeListToFile(img_file_list, cache_dir+'/'+'labeler_input_img_list.txt')
initialized = False
result_bounding_boxes=[boundingbox]
for each_img_file in img_file_list:
LOG.debug('read in image file' + each_img_file)
self.frame = cv2.imread(each_img_file)
vis = self.frame.copy()
hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv, np.array((0., 60., 32.)), np.array((180., 255., 255.)))
if not initialized:
# set up initial labeled img
x0, y0, width, height = boundingbox
x1 = x0 + width
y1 = y0 + height
self.track_window = (x0, y0, width, height)
hsv_roi = hsv[y0:y1, x0:x1]
mask_roi = mask[y0:y1, x0:x1]
hist = cv2.calcHist( [hsv_roi], [0], mask_roi, [16], [0, 180] )
cv2.normalize(hist, hist, 0, 255, cv2.NORM_MINMAX);
self.hist = hist.reshape(-1)
initialized = True
continue
# self.show_hist()
prob = cv2.calcBackProject([hsv], [0], self.hist, [0, 180], 1)
prob &= mask
term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 )
track_box, self.track_window = cv2.CamShift(prob, self.track_window, term_crit)
# pdb.set_trace()
# get rectangle
track_rect = cv2.boundingRect(cv2.boxPoints(track_box))
# try:
# pt1 = (track_rect[0],track_rect[1])
# pt2 = (track_rect[0] + track_rect[2], track_rect[1] + track_rect[3])
# cv2.rectangle(vis, pt1, pt2, (0, 255, 0), 2)
# cv2.ellipse(vis, track_box, (0, 0, 255), 2)
# except:
print track_rect
result_bounding_boxes.append(list(track_rect))
return result_bounding_boxes
