face recognizing for static image

facerecog.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 23 00:05:14 2017

@author: ossyaritoori
"""

#coding: utf-8

import cv2
import numpy as np

# find haar classifier
faceCascade = cv2.CascadeClassifier('/home/yoshi/anaconda3/pkgs/opencv3-3.2.0-np111py35_0/share/OpenCV/haarcascades/haarcascade_frontalface_alt.xml')

img = cv2.imread('lena.png', cv2.IMREAD_COLOR)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
face = faceCascade.detectMultiScale(gray, 1.1, 3)

# write rectangle in detected face
if len(face) > 0:
	for rect in face:
		cv2.rectangle(img, tuple(rect[0:2]), tuple(rect[0:2]+rect[2:4]), (0, 0,255), thickness=2)
else:
	print("no face")

cv2.imshow('detected',img)
cv2.waitKey(0)
cv2.imwrite('detected.png', img)

facerecog_video.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 23 00:39:48 2017

@author: ossyaritoori
"""

import cv2

# cascade 
cascade = cv2.CascadeClassifier('/home/yoshi/anaconda3/pkgs/opencv3-3.2.0-np111py35_0/share/OpenCV/haarcascades/haarcascade_frontalface_alt.xml')


# Capture from camera
cap = cv2.VideoCapture(0)

color = (255, 255, 255) # white

while(True):

    # get frame from video stream
    ret, frame = cap.read()

    #face recognition
    facerect = cascade.detectMultiScale(frame, scaleFactor=1.2, minNeighbors=2, minSize=(10, 10))

    for rect in facerect:
        # put rectangle
        cv2.rectangle(frame, tuple(rect[0:2]),tuple(rect[0:2] + rect[2:4]), color, thickness=2)

     # show
    cv2.imshow("Show FLAME Image", frame) 

    # end after 'q' pressed
    k = cv2.waitKey(1)
    if k == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

facerecog_videoM.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 23 01:18:52 2017

@author: yoshi
"""

#webカメラの映像から顔を探し白の枠線をつけて保存するプログラム

import cv2
import threading
from datetime import datetime

class FaceThread(threading.Thread):
	def __init__(self, frame):
		super(FaceThread, self).__init__()
		self._cascade_path = '/home/yoshi/anaconda3/pkgs/opencv3-3.2.0-np111py35_0/share/OpenCV/haarcascades/haarcascade_frontalface_alt.xml'
		self._frame = frame

	def run(self):
		#グレースケール変換
		self._frame_gray = cv2.cvtColor(self._frame, cv2.COLOR_BGR2GRAY)

		#カスケード分類器の特徴量を取得する
		self._cascade = cv2.CascadeClassifier(self._cascade_path)

		#物体認識(顔認識)の実行 -> each rectangle coordinate of face is in _facerect
		self._facerect = self._cascade.detectMultiScale(self._frame_gray, scaleFactor=1.2, minNeighbors=3, minSize=(10, 10))

		if len(self._facerect) > 0:
			print('Detected Face!')
			self._color = (255, 255, 255) #白
			for self._rect in self._facerect:
				##検出した顔を囲む矩形の作成
				#cv2.rectangle(self._frame, tuple(self._rect[0:2]),tuple(self._rect[0:2] + self._rect[2:4]), self._color, thickness=2)	
				
				#現在の時間を取得
				self._now = datetime.now().strftime('%Y%m%d%H%M%S')
				self._image_path = 'faces/' + self._now + '.jpg'
				#切り出し
				self.x = self._rect[0]
				self.y = self._rect[1]
				self.width = self._rect[2]
				self.height = self._rect[3]
				self.dst = self._frame[self.y:self.y+self.height, self.x:self.x+self.width]	
				#認識結果の保存				
				cv2.imwrite(self._image_path, self.dst)



# main


# カメラをキャプチャ開始
cap = cv2.VideoCapture(0)

ret, frame = cap.read()

while(cap.isOpened()):
	ret, frame = cap.read()

	#frameを表示
	cv2.imshow('camera capture', frame)

	if(threading.activeCount() == 1):
		th = FaceThread(frame)
		th.start()

	#10msecキー入力待ち
	k = cv2.waitKey(10)
	#Escキー or'q' を押されたら終了
	if k == 27:
		break
	if k == ord('q'):
		break

#キャプチャを終了
cap.release()
cv2.destroyAllWindows()