import os, sys, inspect
from src.utils.io import showimage_pil, show_dot, filename2arr, add_boxes
from PIL import Image
tests_dir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe()))) # script directory src/
src_dir = os.path.dirname(tests_dir)
xray_dir = os.path.dirname(src_dir) #xray directory
os.chdir(xray_dir)
sys.path.append(src_dir)
import pickle
boxes = pickle.load(open('/Users/ruhansa/Desktop/train/result/clf_1_20_np/21_boxes.pkl', "rb"))
from src.utils.util import non_max_suppression_merge
boxes = non_max_suppression_merge(boxes, 0.9)
fn = xray_dir + '/data/LL/21.jpg'
img = Image.open(fn)
img = add_boxes(boxes, img)
img.show()
#
# img = Image.open(fn)
# img = add_boxes(boxes, img)
# img.show()
# img.save('/Users/ruhansa/Desktop/train/result/1_clf_1_2/boxes.jpg')
# import pickle
# pickle.dump(aftermath, open('/Users/ruhansa/Desktop/train/result/1_clf_1_2/boxes.pkl', 'wb'))
half_clf = pickle.load(open(fn, "rb"))
for i in range(starti, endi+1):
testn = str(i)
report.write("==================== sample #: " + testn + "==========================\n")
t0 = time.time()
fn = data_folder + testn + '.jpg'
arr = filename2arr(fn)
### step1: get bounding boxes
# halves = detect_halves(arr, half_clf, step_size_W=80, step_size_H=80, winH=200, winW=300, report=report)
fn = result_dir + '/' + testn + '_half_boxes.pkl'
halves = pickle.load(open(fn, "rb"))
halves = non_max_suppression_merge(halves, overlapThresh=0)
if halves is not None:
# 1. detect ROI
bbox = get_huge_bounding_box(halves)
img1 = Image.fromarray(arr)
# fn = result_dir + '/' + testn + '_half_boxes.pkl'
# pickle.dump(halves, open(fn, "wb"))
img1=add_boxes(halves, img1)
img1.show()
img1.save(result_dir +'/' + testn +'_half_boxes.jpg')
# 2. detect edges
ROI = arr[bbox[1]: bbox[3], bbox[0]: bbox[2]]
edges, sigma, cur_ROI= best_edges(ROI, threshold=0.02)
showimage_pil(edges)
