Mas*_*vLx 18 python opencv numpy python-2.7
我正在尝试检测一张脸并在一个单独的文件中记下脸部区域.我该怎么做?我认为我必须使用"faces"(你可以在代码中看到这个var).但是怎么样?
from ffnet import mlgraph, ffnet, tmlgraph, imlgraph
import pylab
import sys
import cv,cv2
import numpy
cascade = cv.Load('C:\opencv\data\haarcascades\haarcascade_frontalface_alt.xml')
def detect(image):
bitmap = cv.fromarray(image)
faces = cv.HaarDetectObjects(bitmap, cascade, cv.CreateMemStorage(0))
if faces:
for (x,y,w,h),n in faces:
cv2.rectangle(image,(x,y),(x+w,y+h),(255,255,255),3)
return image
if __name__ == "__main__":
cam = cv2.VideoCapture(0)
while 1:
_,frame =cam.read()
frame = numpy.asarray(detect(frame))
cv2.imshow("features", frame)
if cv2.waitKey(1) == 0x1b: # ESC
print 'ESC pressed. Exiting ...'
break
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小智 33
以下代码应提取图像中的面部并将面部保存在磁盘上
def detect(image):
image_faces = []
bitmap = cv.fromarray(image)
faces = cv.HaarDetectObjects(bitmap, cascade, cv.CreateMemStorage(0))
if faces:
for (x,y,w,h),n in faces:
image_faces.append(image[y:(y+h), x:(x+w)])
#cv2.rectangle(image,(x,y),(x+w,y+h),(255,255,255),3)
return image_faces
if __name__ == "__main__":
cam = cv2.VideoCapture(0)
while 1:
_,frame =cam.read()
image_faces = []
image_faces = detect(frame)
for i, face in enumerate(image_faces):
cv2.imwrite("face-" + str(i) + ".jpg", face)
#cv2.imshow("features", frame)
if cv2.waitKey(1) == 0x1b: # ESC
print 'ESC pressed. Exiting ...'
break
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或者,使用MTCNN和 OpenCV(还需要其他依赖项,包括 TensorFlow),您可以:
1执行人脸检测(输入一张图片,输出所有检测到的人脸框):
from mtcnn.mtcnn import MTCNN
import cv2
face_detector = MTCNN()
img = cv2.imread("Anthony_Hopkins_0001.jpg")
detect_boxes = face_detector.detect_faces(img)
print(detect_boxes)
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[{'box': [73, 69, 98, 123], 'confidence': 0.9996458292007446, 'keypoints': {'left_eye': (102, 116), 'right_eye': (150, 114), 'nose' : (129, 142), 'mouth_left': (112, 168), 'mouth_right': (146, 167)}}]
2将所有检测到的人脸保存到单独的文件中:
for i in range(len(detect_boxes)):
box = detect_boxes[i]["box"]
face_img = img[box[1]:(box[1] + box[3]), box[0]:(box[0] + box[2])]
cv2.imwrite("face-{:03d}.jpg".format(i+1), face_img)
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3 或绘制所有检测到的人脸的矩形:
for box in detect_boxes:
box = box["box"]
pt1 = (box[0], box[1]) # top left
pt2 = (box[0] + box[2], box[1] + box[3]) # bottom right
cv2.rectangle(img, pt1, pt2, (0,255,0), 2)
cv2.imwrite("detected-boxes.jpg", img)
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