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| # -*- coding:utf-8 -*- | |
| import cv2 | |
| from boss_train import Model | |
| from image_show import show_image | |
| if __name__ == '__main__': | |
| cap = cv2.VideoCapture(0) | |
| cascade_path = "/usr/local/opt/opencv/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml" | |
| model = Model() | |
| model.load() | |
| while True: | |
| _, frame = cap.read() | |
| # グレースケール変換 | |
| frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) | |
| # カスケード分類器の特徴量を取得する | |
| cascade = cv2.CascadeClassifier(cascade_path) | |
| # 物体認識（顔認識）の実行 | |
| facerect = cascade.detectMultiScale(frame_gray, scaleFactor=1.2, minNeighbors=3, minSize=(10, 10)) | |
| #facerect = cascade.detectMultiScale(frame_gray, scaleFactor=1.01, minNeighbors=3, minSize=(3, 3)) | |
| if len(facerect) > 0: | |
| print('face detected') | |
| color = (255, 255, 255) # 白 | |
| for rect in facerect: | |
| # 検出した顔を囲む矩形の作成 | |
| #cv2.rectangle(frame, tuple(rect[0:2]), tuple(rect[0:2] + rect[2:4]), color, thickness=2) | |
| x, y = rect[0:2] | |
| width, height = rect[2:4] | |
| image = frame[y - 10: y + height, x: x + width] | |
| result = model.predict(image) | |
| if result == 0: # boss | |
| print('Boss is approaching') | |
| show_image() | |
| else: | |
| print('Not boss') | |
| #10msecキー入力待ち | |
| k = cv2.waitKey(100) | |
| #Escキーを押されたら終了 | |
| if k == 27: | |
| break | |
| #キャプチャを終了 | |
| cap.release() | |
| cv2.destroyAllWindows() |