"""
###############################
draw spline using average position
of the center of the vertebrae
###############################
"""
data_folder = xray_dir + '/data/LL/'
result_folder = '/Users/ruhansa/Desktop/train/result/clf_blur_canny_1_20_0413/whole_boxes/'
if ~os._exists(result_folder):
os.mkdir(result_folder)
starti = 2
endi = 10
for i in range(starti, endi+1):
testn = str(i)
fn = data_folder + testn + '.jpg'
arr=filename2arr(fn)
img = Image.open(open(fn, "rb"))
fn = '/Users/ruhansa/Desktop/train/result/clf_blur_canny_1_20_0413/' + testn + '_boxes.pkl'
boxes = pickle.load(open(fn, 'rb'))
boxes, _, _ = non_max_suppression_center(boxes, overlapThresh=0.3)
img = add_boxes(boxes, img)
img.save(result_folder + testn + '.jpg')
# report.write("==================== sample #: " + testn + "==========================\n")
t0 = time.time()
fn = data_folder + testn + '.jpg'
arr = filename2arr(fn)
img3 = Image.fromarray(arr)
### step1: get bounding boxes
fn = prev_halves_folder + testn + '_half_boxes.pkl'
halves = pickle.load(open(fn, "rb"))
img3 = add_boxes(halves, img3)
img3.show()
if debug is True:
raw_input("rough detection")
img3 = Image.fromarray(arr)
halves_b, halves_c, halves_wh= non_max_suppression_center(halves)
pts=get_spline(halves_b, 0.2*arr.shape[0], 0.75*arr.shape[0])
if pts is not None:
img3 = add_boxes(halves_b, img3)
img3.show()
if debug is True:
raw_input("clear out the clutter")
img3 = add_points(pts, img3)
img3.show()
if debug is True:
raw_input("rough curvature line")
fn = prev_whole_folder + testn + '_boxes.pkl'
wholes = pickle.load(open(fn, "rb"))
wholes_b, wholes_c, wholes_wh= non_max_suppression_center(wholes, overlapThresh=0.3)
img3 = Image.fromarray(arr)
