prepare frontal face images to be passed to fisherBased.py
- find eyes using HAAR wavelet based detection (Viola-Jones method)
- image registration
- rotate the image so that line joining the centers of the eyes
is horizontal
- translate and scale so that all images are in same coordinate system
'''
import cv2
import imgUtils
import registerImage
import os
# Assume supplied images have single, frontal face
sourcePath = '/Users/pradeep/Desktop/Hackathon/Face Recognition/trainFaces/teen/'
filePaths, fileNames = imgUtils.fetchFiles(sourcePath, 'ENDS_WITH', '.jpg')
#print filePaths[:5]
#print fileNames[:5]
# faceCasc = imgUtils.chooseCascade(choice='frontalFace')
eyeCasc = imgUtils.chooseCascade(
choice='eyeGlasses') # left one ins't always first in returned list
sz = 94
offSetH = 0.25
offSetV = 0.25
for path, name in zip(filePaths, fileNames):
# Load image in single channle grayscale
img = cv2.imread(path, 0)
featureExtractor = feature.Fisherfaces()
# Type of distance should match classifier
distance = distance.EuclideanDistance()
# Type of classifier and criterion for selection
classifier = classifier.NearestNeighbor(dist_metric=distance, k=3)
# The overall architecture
predictor = model.PredictableModel(featureExtractor,classifier)
# The training patterns
# these patterns were preprocessed via createSample.py
# with sz=210, offSetH = 0.25 and offSetV = 0.25
filePaths, fileNames = imgUtils.fetchFiles('/Users/pradeep/Desktop/Hackathon/Face Recognition/trainFaces/ageTraining/',
'ENDS_WITH',
'proto.jpg')
# Labels of the raw patterns
X = []
y = []
for path, name in zip(filePaths,fileNames):
img = cv2.imread(path,0)
X.append(img)
if name.endswith('tNES_proto.jpg'):
y.append(0) # feminie
else:
y.append(1) # masculine
# Train on the samples and corresponding labels
prepare frontal face images to be passed to fisherBased.py
- find eyes using HAAR wavelet based detection (Viola-Jones method)
- image registration
- rotate the image so that line joining the centers of the eyes
is horizontal
- translate and scale so that all images are in same coordinate system
'''
import cv2
import imgUtils
import registerImage
import os
# Assume supplied images have single, frontal face
sourcePath = '/Users/pradeep/Desktop/Hackathon/Face Recognition/May2014Training/'
filePaths, fileNames = imgUtils.fetchFiles(sourcePath, 'ENDS_WITH', '.jpg')
# faceCasc = imgUtils.chooseCascade(choice='frontalFace')
eyeCasc = imgUtils.chooseCascade(choice='eyeGlasses') # left one ins't always first in returned list
sz = 110
offSetH = 0.25
offSetV = 0.25
for path, name in zip(filePaths,fileNames):
# Load image in single channle grayscale
img = cv2.imread(path,0)
# Register the image with alignment at eyes
#img = registerImage.alignAtEyes(eyeCasc, img, name, sz, offSetH,offSetV)
