最近iPhone X博人眼球,其中最絕妙的設計就是人臉辨識解鎖,本文主要為大家詳細介紹了Python人臉辨識初探的相關資料,具有一定的參考價值,有興趣的小夥伴們可以參考一下,希望能幫助大家。
1.利用opencv函式庫
sudo apt-get install libopencv-* sudo apt-get install python-opencv sudo apt-get install python-numpy
2 .Python實作
import os import os from PIL import Image,ImageDraw import cv def detect_object(image): grayscale = cv.CreateImage((image.width,image.height),8,1)#创建空的灰度值图片 cv.CvtColor(image,grayscale,cv.CV_BGR2GRAY) cascade=cv.Load("/usr/share/opencv/haarcascades/haarcascade_frontalface_alt_tree.xml")#记载特征值库,此目录下还有好多库可以选用 rect=cv.HaarDetectObjects(grayscale,cascade,cv.CreateMemStorage(),1.1,2,cv.CV_HAAR_DO_CANNY_PRUNING,(20,20)) result=[]#标记位置 for r in rect: result.append((r[0][0],r[0][1],r[0][0]+r[0][2],r[0][1]+r[0][3])) return result def process(infile): image = cv.LoadImage(infile) if image: faces = detect_object(image) im = Image.open(infile) path = os.path.abspath(infile) save_path = os.path.splitext(path)[0]+"_face" try: os.mkdir(save_path) except: pass if faces: draw = ImageDraw.Draw(im) count=0 for f in faces: count+=1 draw.rectangle(f,outline=(255,0,0)) a=im.crop(f) file_name=os.path.join(save_path,str(count)+".jpg") a.save(file_name) drow_save_path = os.path.join(save_path,"out.jpg") im.save(drow_save_path,"JPEG",quality=80) else: print "Error: cannot detect faces on %s" % infile if __name__ == "__main__": process("test3.jpg")
##3.效果比較
以上是實例詳解Python人臉辨識的詳細內容。更多資訊請關注PHP中文網其他相關文章!