def flandmark_init(model=MODEL): flandmark = PyFlandmark(model, False) # Initialize featurePool bw = flandmark.getBaseWindowSize() featurePool = PyFeaturePool(bw[0], bw[1], None) featurePool.addFeatuaddSparseLBPfeatures() flandmark.setFeaturePool(featurePool) return flandmark
""" import sys sys.path.append("D:/GitHub/clandmark/install/share/clandmark/python/") from py_flandmark import PyFlandmark from py_featurePool import PyFeaturePool #flandmark = PyFlandmark("D:/GitHub/clandmark/matlab_interface/models/FDPM.xml", False) flandmark = PyFlandmark("D:/GitHub/clandmark/matlab_interface/models/CDPM.xml", False) bw = flandmark.getBaseWindowSize() featurePool = PyFeaturePool(bw[0], bw[1], None) featurePool.addFeatuaddSparseLBPfeatures() flandmark.setFeaturePool(featurePool) import time import numpy as np import cv2 def rgb2gray(rgb): """ converts rgb array to grey scale variant accordingly to fomula taken from wiki (this function is missing in python) """ return np.dot(rgb[...,:3], [0.299, 0.587, 0.144]) cascPath = "D:/GitHub/clandmark/data/haarcascade_frontalface_alt.xml" faceCascade = cv2.CascadeClassifier(cascPath)
featurePool.addFeatuaddSparseLBPfeatures() flandmark.setFeaturePool(featurePool) return flandmark if __name__ == '__main__': # flandmark = flandmark_init() flandmark = PyFlandmark(MODEL, False) # Initialize featurePool bw = flandmark.getBaseWindowSize() featurePool = PyFeaturePool(bw[0], bw[1], None) featurePool.addFeatuaddSparseLBPfeatures() flandmark.setFeaturePool(featurePool) faceCascade = cv2.CascadeClassifier(CV_CASCADE_PATH) video_capture = cv2.VideoCapture(CAM_ID) while True: # Capture frame-by-frame ret, frame = video_capture.read() gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) arr = rgb2gray(frame) faces = faceCascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5,