import numpy as np
import cv2
import os, os.path
#from skimage.transform import resize

face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_eye.xml')
images_path = os.path.join(os.path.dirname(__file__), 'complete_images')

def filtering():
	try:
		if not os.path.exists('data'):
			os.makedirs('data')
	except OSError:
		print ('Error: Creating directory of data')
	image_size=160
	margin=10

	currentframe = 0
	for folder in os.listdir(images_path):
		folder_path = os.path.join(os.path.dirname(__file__), 'complete_images/'+folder)

		i=0
		for images in os.listdir(folder_path):
			img = cv2.imread(folder_path+'/'+images)
			print(folder_path)
			faces = face_cascade.detectMultiScale(img, 1.3, 5)
			try:
				(x, y, w, h) = faces[0]
				cropped=img[y:y+h, x:x+w]
				aligned = cv2.resize(cropped, (image_size, image_size))
				name = './data/speaker/frame'+str(currentframe)+'.jpg'
			except:
				try:
					eyes = eye_cascade.detectMultiScale(img, 1.3, 5)

					if eyes.shape[0]==2:
							x= max(eyes[1][0],eyes[0][0])
							y= max(eyes[1][1],eyes[0][1])
							w= max(eyes[1][2],eyes[0][2])
							h= max(eyes[1][3],eyes[0][3])
							cropped=img[y-h:y+5*h, x-3*w:x+2*w]
							aligned = cv2.resize(cropped, (image_size, image_size))
							name = './data/speaker/frame'+str(currentframe)+'.jpg'

					else:
						name = './data/nospeaker/frame'+str(currentframe)+'.jpg'
						aligned=img
				except:
						name = './data/nospeaker/frame'+str(currentframe)+'.jpg'
						aligned=img

			cv2.imwrite(name,aligned)
			currentframe += 1
			#if i==100:
				#break
			i+=1
	cv2.destroyAllWindows()

if __name__ == '__main__':
	filtering()