faceUtil.py

#!/user/bin/ env python
# -*- coding:utf-8 -*-
# Author: Chen X
import cv2
import matplotlib as plt
#預設值
#把安裝opencv的目錄下的預設資料xml的位置放進去
model_face ='D:\Maindocument\opencvfile\opencv\sources\data\haarcascades/haarcascade_frontalface_default.xml'
min_height_dec = 20
min_width_dec = 20
min_height_thresh = 50
 
min_width_thresh = 50
FACE_PAD  =  50
#人臉模型
def get_model_type(model_name):
    if not (model_face):
        return cv2.CascadeClassifier(model_face)
    return cv2.CascadeClassifier(model_face)

#人臉識別
#回臉和IMG
def detect_faces(face_model,image_name):
    face_cascade = get_model_type(face_model)#載入模型
 
print(image_name)
    img = cv2.imread(image_name)#讀取圖片
print(img)
    min_h = int(max(img.shape[0]/min_height_dec,min_height_thresh))
    min_w = int(max(img.shape[1]/min_width_dec,min_width_thresh))
    if img.ndim == 3 :
        gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    else:
        gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)#轉灰度
 
faces = face_cascade.detectMultiScale(gray,1.3,minNeighbors=5,minSize=(min_h,min_w))

    result = []
    for (x,y,width,height) in faces:
        result.append((x,y,x+width,y+height))
        draw_rect(img,x,y,width,height) #劃線標記
return (result,img)

#畫圖
def draw_rect(img,x,y,w,h):
    upper_cut = [min(img.shape[0],y+h+FACE_PAD),min(img.shape[1],x+w+FACE_PAD)]
    lower_cut = [max(y-FACE_PAD,0),max(x-FACE_PAD,0)]
    img = cv2.rectangle(img,(lower_cut[1],lower_cut[0]),(upper_cut[1],upper_cut[0]),
            (255,0,0),2)



#擷取圖字圖片
def sub_image(name,img,x,y,w,h):
    upper_cut = [min(img.shape[0],y+h+FACE_PAD),min(img.shape[1],x+w+FACE_PAD)]
    lower_cut = [max(y - FACE_PAD, 0), max(x - FACE_PAD, 0)]
    roi_color = img[lower_cut[0]:upper_cut[0],lower_cut[1]]
    cv2.imwrite(name,roi_color)
    return sub_image()
#儲存影象
def save_image(filename,img):
    cv2.imwrite(filename,img)

test.py

#!/user/bin/ env python
# -*- coding:utf-8 -*-
# Author: Chen X
import cv2
import matplotlib as plt
import sys
import time
import numpy as np
from openCV第五章人臉檢測和識別.faceUtil import *
filename = './liu.jpg'
face_model = " "
#output_name = "./out/%s.jpg"%(time.strftime('%Y-%m-%d-%H:%M:%S',time.localtime(time.time())))
output_name = "./%s.jpg"%(time.strftime('%Y-%m-%d-%H:%M:%S',time.localtime(time.time())))

#image_file = sys.argy[1]
#if not IMAGE_FILE）:
image_name = filename
img_name = filename

#影象檢測
image,img = detect_faces(model_face,img_name)
#顯示圖片
#plt.imshow(img)#顯示圖片
#plt.axis('off')#並不顯示座標軸
#plt.show()
#儲存圖片
save_image(output_name,img)
cv2.imshow("camer",img)
cv2.waitKey(0)
cv2.destroyAllWindows()

結果截圖