opencv/samples/dnn/resnet_ssd_face_python.py
catree 22dece8146 Fix DNN samples for compatibility with Python 3.
Add PyInt_Check in pyopencv_dnn.hpp.
2017-10-15 20:24:56 +02:00

56 lines
2.1 KiB
Python

import numpy as np
import argparse
import cv2 as cv
try:
import cv2 as cv
except ImportError:
raise ImportError('Can\'t find OpenCV Python module. If you\'ve built it from sources without installation, '
'configure environemnt variable PYTHONPATH to "opencv_build_dir/lib" directory (with "python3" subdirectory if required)')
from cv2 import dnn
inWidth = 300
inHeight = 300
confThreshold = 0.5
prototxt = 'face_detector/deploy.prototxt'
caffemodel = 'face_detector/res10_300x300_ssd_iter_140000.caffemodel'
if __name__ == '__main__':
net = dnn.readNetFromCaffe(prototxt, caffemodel)
cap = cv.VideoCapture(0)
while True:
ret, frame = cap.read()
cols = frame.shape[1]
rows = frame.shape[0]
net.setInput(dnn.blobFromImage(frame, 1.0, (inWidth, inHeight), (104.0, 177.0, 123.0), False))
detections = net.forward()
perf_stats = net.getPerfProfile()
print('Inference time, ms: %.2f' % (perf_stats[0] / cv.getTickFrequency() * 1000))
for i in range(detections.shape[2]):
confidence = detections[0, 0, i, 2]
if confidence > confThreshold:
xLeftBottom = int(detections[0, 0, i, 3] * cols)
yLeftBottom = int(detections[0, 0, i, 4] * rows)
xRightTop = int(detections[0, 0, i, 5] * cols)
yRightTop = int(detections[0, 0, i, 6] * rows)
cv.rectangle(frame, (xLeftBottom, yLeftBottom), (xRightTop, yRightTop),
(0, 255, 0))
label = "face: %.4f" % confidence
labelSize, baseLine = cv.getTextSize(label, cv.FONT_HERSHEY_SIMPLEX, 0.5, 1)
cv.rectangle(frame, (xLeftBottom, yLeftBottom - labelSize[1]),
(xLeftBottom + labelSize[0], yLeftBottom + baseLine),
(255, 255, 255), cv.FILLED)
cv.putText(frame, label, (xLeftBottom, yLeftBottom),
cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0))
cv.imshow("detections", frame)
if cv.waitKey(1) != -1:
break