Python + OpenCV:cv2.imwrite

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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xtl*_*luo 5

在此处输入图片说明 在此处输入图片说明 在此处输入图片说明

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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