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