Wu Yuxiong - born natural python learning Notes: python crawling face graphics with Open CV and save

After the face recognition out of the range, it can be identified on the part of the grab. Grab a picture 
portion of the graph is the method by crop pillow package implemented

We first learn to read package with pillow picture file, the syntax is:

For example, open test.jpg picture file, then save to img variables:

Then specify the scope of our crawl pictures with crop method, the syntax is:

For example, to crawl (50, 50) to (200, 200) and stored in the picture img2 variables:

Different image crawled down the face size may be inconsistent, in order to facilitate comparison graphics, images may be 
adjusted to a fixed size. pillow package resize method may be implemented to reset the size of the image:

 

 

 

 

 

 

Grab the face area in the picture and save

First obtain a face area with OpenCV, then crop the method pillow package gripper face region and stored.

 

 

import cv2 
from PIL import Image

casc_path = "E:\\haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(casc_path)
imagename = "F:\\pythonBase\\pythonex\\ch10\\media\\person1.jpg"
image = cv2.imread(imagename)
faces = faceCascade.detectMultiScale(image, scaleFactor=1.1, minNeighbors=5, minSize=(30,30), flags = cv2.CASCADE_SCALE_IMAGE)
count = 1
for (x,y,w,h) in faces:
    cv2.rectangle(image, (x,y), (x+w,y+h), (128,255,0), 2)
    filename = "E:\\" + str(count)+ ".jpg"
    image1 = Image.open(imagename)
    image2 = image1.crop((x, y, x+w, y+h))
    image3 = image2.resize((200, 200), Image.ANTIALIAS)
    image3.save(filename)
    count += 1
cv2.namedWindow("facedetect")
cv2.imshow("facedetect", image)
cv2.waitKey(0)  
cv2.destroyWindow("facedetect")

 

 

 

 

 

 

import cv2 
from PIL import Image

casc_path = "E:\\haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(casc_path)
imagename = "F:\\pythonBase\\pythonex\\ch10\\media\\person3.jpg"
image = cv2.imread(imagename)
faces = faceCascade.detectMultiScale(image, scaleFactor=1.1, minNeighbors=5, minSize=(30,30), flags = cv2.CASCADE_SCALE_IMAGE)
count = 1
for (x,y,w,h) in faces:
    cv2.rectangle(image, (x,y), (x+w,y+h), (128,255,0), 2)
    filename = "E:\\aa\\" + str(count)+ ".jpg"
    image1 = Image.open(imagename)
    image2 = image1.crop((x, y, x+w, y+h))
    image3 = image2.resize((200, 200), Image.ANTIALIAS)
    image3.save(filename)
    count += 1
cv2.namedWindow("facedetect")
cv2.imshow("facedetect", image)
cv2.waitKey(0)  
cv2.destroyWindow("facedetect")

 

 

 

 

import cv2 
from PIL import Image

casc_path = "E:\\haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(casc_path)
imagename = "F:\\pythonBase\\pythonex\\ch10\\media\\person8.jpg"
image = cv2.imread(imagename)
faces = faceCascade.detectMultiScale(image, scaleFactor=1.1, minNeighbors=5, minSize=(30,30), flags = cv2.CASCADE_SCALE_IMAGE)
count = 1
for (x,y,w,h) in faces:
    cv2.rectangle(image, (x,y), (x+w,y+h), (128,255,0), 2)
    filename = "E:\\aa\\bb\\" + str(count)+ ".jpg"
    image1 = Image.open(imagename)
    image2 = image1.crop((x, y, x+w, y+h))
    image3 = image2.resize((200, 200), Image.ANTIALIAS)
    image3.save(filename)
    count += 1
cv2.namedWindow("facedetect")
cv2.imshow("facedetect", image)
cv2.waitKey(0)  
cv2.destroyWindow("facedetect")