人臉檢測+標注
利用Dlib官方訓練好的模型“shape_predictor_68_face_landmarks.dat”進行68點標定,利用 opencv 進行圖像化處理,在人臉上畫出68個點,並標明序號;
68點標注模型下載: https://github.com/davisking/dlib-models 或者http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2
1. 調用dlib庫來進行人臉識別,調用預測器“shape_predictor_68_face_landmarks.dat”進行68點標定
2. 存入68個點坐標
3. 利用 cv2.circle 來畫68個點
4. 利用 cv2.putText() 函數來畫數字1-68
# _*_ coding:utf-8 _*_ import numpy as np import cv2 import dlib detector = dlib.get_frontal_face_detector() predictor = dlib.shape_predictor('shape_predictor_68_face_landmarks.dat') # cv2讀取圖像 img = cv2.imread("1.jpg") # 取灰度 img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) # 人臉數rects rects = detector(img_gray, 0) for i in range(len(rects)): landmarks = np.matrix([[p.x, p.y] for p in predictor(img,rects[i]).parts()]) for idx, point in enumerate(landmarks): # 68點的坐標 pos = (point[0, 0], point[0, 1]) print(idx,pos) # 利用cv2.circle給每個特征點畫一個圈,共68個 cv2.circle(img, pos, 5, color=(0, 255, 0)) # 利用cv2.putText輸出1-68 font = cv2.FONT_HERSHEY_SIMPLEX cv2.putText(img, str(idx+1), pos, font, 0.8, (0, 0, 255), 1,cv2.LINE_AA) cv2.namedWindow("img", 2) cv2.imshow("img", img) cv2.waitKey(0)
攝像頭實時
import dlib import numpy as np detector=dlib.get_frontal_face_detector() predictor=dlib.shape_predictor("./shape_predictor_68_face_landmarks.dat") def Detect_face(camera_idx): # camera_idx: 電腦自帶攝像頭或者usb攝像頭 cv2.namedWindow("detect") cap=cv2.VideoCapture(camera_idx) cap.set(3, 1280) cap.set(4, 1280) while cap.isOpened(): cv2.namedWindow('detect', cv2.WINDOW_AUTOSIZE) ## frame = cv.flip(frame, 1, dst=None) ok,frame=cap.read() if not ok: break gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY) rects=detector(gray,0) for i in range(len(rects)): landmarks = np.matrix([[p.x, p.y] for p in predictor(frame, rects[i]).parts()]) for idx, point in enumerate(landmarks): pos = (point[0, 0], point[0, 1]) # print(idx, pos) cv2.circle(frame, pos, 1, color=(0, 255, 0)) font = cv2.FONT_HERSHEY_SIMPLEX cv2.putText(frame, str(idx + 1), pos, font, 0.4, (0, 255, 255), 1, cv2.LINE_AA) cv2.imshow('detect', frame) c = cv2.waitKey(10) if c & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows() if __name__=='__main__': Detect_face(0)