/
neural_f_basic.py
34 lines (31 loc) · 1.34 KB
/
neural_f_basic.py
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import samples
import numpy as np
from neuralNetwork import NeuralNetworkClassifier
def testing(num):
trainData = np.load("trainfacebasic.npy")
trainLabels = samples.loadLabelsFile("data/facedata/facedatatrainlabels", num)
testData = np.load("testfacebasic.npy")
testLabels = samples.loadLabelsFile("data/facedata/facedatatestlabels", 151)
validData = np.load("validationfacebasic.npy")
validLabels = samples.loadLabelsFile("data/facedata/facedatavalidationlabels", 301)
loop=True
while loop:
neural = NeuralNetworkClassifier(60 * 70, 500, 1, num, 0.03)
neural.train(trainData[:,0:num], trainLabels, 100)
print "Test Data"
guess = neural.classify(testData)
loop=samples.verify(neural, guess, testLabels)
if loop:
continue
print "==================================="
print "Validation Data"
guess = neural.classify(validData)
samples.verify(neural, guess, validLabels)
if __name__ == "__main__":
sampleDigit=[500,1000,1500,2000,2500,3000,3500,4000,4500,5000]
sampleFace=[45,90,135,180,225,270,315,300,405,451]
sample=sampleFace
for i in range(len(sample)):
print str(10*(i+1))+"%% training data, %d" % sample[i]
testing(sample[i])
print "==================================="