本章节的主要内容是：基于Python和OpenCV的DNN深度学习模块进行实时人脸检测。
以下代码均在python3.6，opencv4.2.0环境下试了跑一遍，可直接运行。
完整代码如下：
代码语言：javascript复制# encoding:utf-8
from __future__ import division
import cv2
import time
import sys
def detectFaceOpenCVDnn(net, frame):
frameOpencvDnn = frame.copy()
frameHeight = frameOpencvDnn.shape[0]
frameWidth = frameOpencvDnn.shape[1]
blob = cv2.dnn.blobFromImage(frameOpencvDnn, 1.0, (300, 300), [104, 117, 123], False, False)
net.setInput(blob)
detections = net.forward()
bboxes = []
for i in range(detections.shape[2]):
confidence = detections[0, 0, i, 2]
if confidence > conf_threshold:
x1 = int(detections[0, 0, i, 3] * frameWidth)
y1 = int(detections[0, 0, i, 4] * frameHeight)
x2 = int(detections[0, 0, i, 5] * frameWidth)
y2 = int(detections[0, 0, i, 6] * frameHeight)
bboxes.append([x1, y1, x2, y2])
cv2.rectangle(frameOpencvDnn, (x1, y1), (x2, y2), (0, 255, 0), int(round(frameHeight/150)), 8)
return frameOpencvDnn, bboxes
if __name__ == "__main__" :
# OpenCV DNN supports 2 networks.
# 1. FP16 version of the original caffe implementation ( 5.4 MB )
# 2. 8 bit Quantized version using Tensorflow ( 2.7 MB )
DNN = "TF"
if DNN == "CAFFE":
modelFile = "res10_300x300_ssd_iter_140000_fp16.caffemodel"
configFile = "deploy.prototxt"
net = cv2.dnn.readNetFromCaffe(configFile, modelFile)
else:
modelFile = "opencv_face_detector_uint8.pb"
configFile = "opencv_face_detector.pbtxt"
net = cv2.dnn.readNetFromTensorflow(modelFile, configFile)
conf_threshold = 0.7
source = 0
if len(sys.argv) > 1:
source = sys.argv[1]
cap = cv2.VideoCapture(source)
hasFrame, frame = cap.read()
vid_writer = cv2.VideoWriter('output-dnn-{}.avi'.format(str(source).split(".")[0]),cv2.VideoWriter_fourcc('M','J','P','G'), 15, (frame.shape[1],frame.shape[0]))
frame_count = 0
tt_opencvDnn = 0
while(1):
hasFrame, frame = cap.read()
if not hasFrame:
break
frame_count = 1
t = time.time()
outOpencvDnn, bboxes = detectFaceOpenCVDnn(net,frame)
tt_opencvDnn = time.time() - t
fpsOpencvDnn = frame_count / tt_opencvDnn
label = "OpenCV DNN ; FPS : {:.2f}".format(fpsOpencvDnn)
cv2.putText(outOpencvDnn, label, (10,50), cv2.FONT_HERSHEY_SIMPLEX, 1.4, (0, 0, 255), 3, cv2.LINE_AA)
cv2.imshow("Face Detection Comparison", outOpencvDnn)
vid_writer.write(outOpencvDnn)
if frame_count == 1:
tt_opencvDnn = 0
k = cv2.waitKey(10)
if k == 27:
break
cv2.destroyAllWindows()
vid_writer.release()测试结果：
不戴口罩
戴口罩
以上内容如有错误或者需要补充的，请留言！
