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,