Implement face detection on live video stream (test on Raspberry pi required)
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1 changed files with 16 additions and 2 deletions
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@ -38,7 +38,7 @@ def face_detector_ssd(image):
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pwd = sys.path[0]
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pwd = sys.path[0]
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net = cv2.dnn.readNetFromCaffe(pwd+"/Facial_models/deploy.prototxt", pwd+"/Facial_models/res10_300x300_ssd_iter_140000_fp16.caffemodel")
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net = cv2.dnn.readNetFromCaffe(pwd+"/Facial_models/deploy.prototxt", pwd+"/Facial_models/res10_300x300_ssd_iter_140000_fp16.caffemodel")
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resize = (800, 800)
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resize = (300, 300)
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confidence_thres = 0.65
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confidence_thres = 0.65
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blob = cv2.dnn.blobFromImage(cv2.resize(image, dsize=resize), 1.0, resize, (104.0, 177.0, 123.0))
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blob = cv2.dnn.blobFromImage(cv2.resize(image, dsize=resize), 1.0, resize, (104.0, 177.0, 123.0))
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@ -66,6 +66,19 @@ def face_detector_ssd(image):
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if __name__=="__main__":
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if __name__=="__main__":
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cameraCapture = cv2.VideoCapture(1)
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success, frame = cameraCapture.read()
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while success and cv2.waitKey(1) == -1:
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success, frame = cameraCapture.read()
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face_detector_ssd(frame)
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cv2.imshow("video", frame)
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cameraCapture.release()
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cv2.destroyAllWindows()
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# image process (keep it in case if needed)
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'''
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image_name = "8.jpg"
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image_name = "8.jpg"
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split_name = image_name.split(".")
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split_name = image_name.split(".")
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@ -75,7 +88,7 @@ if __name__=="__main__":
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image = cv2.imread(image_read_path)
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image = cv2.imread(image_read_path)
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image = face_detector_ssd(image)
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image = face_detector_ssd(image)
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#image = face_detector_haarcascade(image)
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image = face_detector_haarcascade(image)
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print(image_save_path)
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print(image_save_path)
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@ -83,6 +96,7 @@ if __name__=="__main__":
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cv2.imshow("result", image)
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cv2.imshow("result", image)
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cv2.waitKey()
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cv2.waitKey()
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cv2.destroyAllWindows()
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cv2.destroyAllWindows()
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'''
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