上代码:
import cv2 filepath = "imagePath/2.jpg" img = cv2.imread(filepath) # 读取图片 gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 转换灰色 # OpenCV人脸识别分类器 classifier = cv2.CascadeClassifier( "opencv-master\data\haarcascades\haarcascade_frontalface_default.xml" ) color = (0, 255, 0) # 定义绘制颜色 # 调用识别人脸 faceRects = classifier.detectMultiScale( gray, scaleFactor=1.2, minNeighbors=3, minSize=(32, 32)) if len(faceRects): # 大于0则检测到人脸 g = 0 for faceRect in faceRects: # 单独框出每一张人脸 x, y, w, h = faceRect # 框出人脸 cv2.rectangle(img, (x, y), (x + h, y + w), color, 1) cropped = img[y:y+w, x:x+h] # 裁剪坐标为[y0:y1, x0:x1] g = g + 1 cv2.imwrite("imagePath/2-%d.png" % g, cropped) ''' # 左眼 cv2.circle(img, (x + w // 4, y + h // 4 + 30), min(w // 8, h // 8), color) #右眼 cv2.circle(img, (x + 3 * w // 4, y + h // 4 + 30), min(w // 8, h // 8), color) #嘴巴 cv2.rectangle(img, (x + 3 * w // 8, y + 3 * h // 4), (x + 5 * w // 8, y + 7 * h // 8), color) ''' ''' cv2.imshow("image", cropped) # 显示图像 k = cv2.waitKey(0) if k == ord("s"): cv2.imwrite("imagePath/9-3.png", cropped) ''' cv2.destroyAllWindows()
效果:
原图:
一样替换代码:
cropped = img[y+1:y+w, x+1:x+h] # 裁剪坐标为[y0:y1, x0:x1]
就可以提取人脸不要边框: 效果: