import xml.etree.ElementTree as ET 
import numpy as np
import os 

tree = ET.parse('ibug_300W_large_face_landmark_dataset/labels_ibug_300W_train.xml')
root = tree.getroot()
root_dir = 'ibug_300W_large_face_landmark_dataset'

bboxes = [] # face bounding box used to crop the image
landmarks = [] # the facial keypoints/landmarks for the whole training dataset
img_filenames = [] # the image names for the whole dataset

for filename in root[2]:
	img_filenames.append(os.path.join(root_dir, filename.attrib['file']))
	box = filename[0].attrib
	# x, y for the top left corner of the box, w, h for box width and height
	bboxes.append([box['left'], box['top'], box['width'], box['height']]) 

	landmark = []
	for num in range(68):
		x_coordinate = int(filename[0][num].attrib['x'])
		y_coordinate = int(filename[0][num].attrib['y'])
		landmark.append([x_coordinate, y_coordinate])
	landmarks.append(landmark)

landmarks = np.array(landmarks).astype('float32')     
bboxes = np.array(bboxes).astype('float32')