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
returns 2x2 matrix coordinates of
left upper and right lower corners
of rectangle that contains face stored
in columns of matrix
"""
f = open(file_name)
str = f.read().replace(',', ' ')
f.close()
ret = np.array(list(map(int,str.split())) ,dtype=np.int32)
ret = ret.reshape((2,2), order='F')
return ret
DIR = '../../../data/Images/'
JPGS = [f for f in os.listdir(DIR) if fnmatch(f, '*.jpg')]
flmrk = PyFlandmark("../../../data/flandmark_model.xml", False)
for jpg_name in JPGS:
file_name = jpg_name[:-4]
img = Image.open(DIR + jpg_name)
arr = rgb2gray(np.asarray(img))
bbox = read_bbox_from_txt(DIR + jpg_name[:-4] + '.det')
d_landmarks = flmrk.detect(arr, bbox)
n = d_landmarks.shape[1]
print("test detect method")
im = Image.fromarray(arr)
returns 2x2 matrix coordinates of
left upper and right lower corners
of rectangle that contains face stored
in columns of matrix
"""
f = open(file_name)
str = f.read().replace(',', ' ')
f.close()
ret = np.array(map(int, str.split()), dtype=np.int32)
ret = ret.reshape((2, 2), order='F')
return ret
DIR = '../../../data/Images/'
JPGS = [f for f in os.listdir(DIR) if fnmatch(f, '*.jpg')]
flmrk = PyFlandmark("../../../data/flandmark_model.xml", False)
for jpg_name in JPGS:
file_name = jpg_name[:-4]
img = Image.open(DIR + jpg_name)
arr = rgb2gray(np.asarray(img))
bbox = read_bbox_from_txt(DIR + jpg_name[:-4] + '.det')
d_landmarks = flmrk.detect(arr, bbox)
n = d_landmarks.shape[1]
print "test detect method"
im = Image.fromarray(arr)
img_dr = ImageDraw.Draw(im)
returns 2x2 matrix coordinates of
left upper and right lower corners
of rectangle that contains face stored
in columns of matrix
"""
f = open(file_name)
str = f.read().replace(",", " ")
f.close()
ret = np.array(map(int, str.split()), dtype=np.int32)
ret = ret.reshape((2, 2), order="F")
return ret
DIR = "../../../data/Images/"
JPGS = [f for f in os.listdir(DIR) if fnmatch(f, "*.jpg")]
flmrk = PyFlandmark("../../../data/flandmark_model.xml", False)
for jpg_name in JPGS:
file_name = jpg_name[:-4]
img = Image.open(DIR + jpg_name)
arr = rgb2gray(np.asarray(img))
bbox = read_bbox_from_txt(DIR + jpg_name[:-4] + ".det")
d_landmarks = flmrk.detect(arr, bbox)
n = d_landmarks.shape[1]
print "test detect method"
im = Image.fromarray(arr)
# -*- coding: utf-8 -*-
"""
Created on Sun Feb 05 16:26:55 2017
@author: uricar.michal
"""
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)
flandmark = PyFlandmark(model, False)
# Initialize featurePool
bw = flandmark.getBaseWindowSize()
featurePool = PyFeaturePool(bw[0], bw[1], None)
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)
# -*- coding: utf-8 -*-
"""
Created on Sun Feb 05 16:26:55 2017
@author: uricar.michal
"""
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
from py_flandmark import PyFlandmark
from py_featurePool import PyFeaturePool
# flandmark = PyFlandmark("../../../data/flandmark_model.xml", False)
# flandmark = PyFlandmark("../../../data/FRONTAL_21L.xml", False)
flandmark = PyFlandmark("../../../data/300W/FDPM.xml", False)
bw = flandmark.getBaseWindowSize()
featurePool = PyFeaturePool(bw[0], bw[1], None)
featurePool.addFeatuaddSparseLBPfeatures()
flandmark.setFeaturePool(featurePool)
import time
import numpy as np
import os
from fnmatch import fnmatch
from PIL import Image
import matplotlib.pyplot as plt
#%matplotlib inline
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])