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comparison python/ml.py @ 961:ec1682ed999f

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added computation of confusion matrix and improved default parameter for block normalization for SVM classification
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Sun, 05 Nov 2017 23:45:47 -0500
parents 989917b1ed85
children 184f1dd307f9
comparison
equal deleted inserted replaced
960:0c1d1eeef544 961:ec1682ed999f
16 import utils 16 import utils
17 17
18 ##################### 18 #####################
19 # OpenCV ML models 19 # OpenCV ML models
20 ##################### 20 #####################
21
22 def computeConfusionMatrix(model, samples, responses):
23 'computes the confusion matrix of the classifier (model)'
24 classifications = {}
25 for x,y in zip(samples, responses):
26 predicted = model.predict(x)
27 classifications[(y, predicted)] = classifications.get((y, predicted), 0)+1
28 return classifications
21 29
22 class StatModel(object): 30 class StatModel(object):
23 '''Abstract class for loading/saving model''' 31 '''Abstract class for loading/saving model'''
24 def load(self, filename): 32 def load(self, filename):
25 if path.exists(filename): 33 if path.exists(filename):
44 # self.model.setCoef0(coef0) 52 # self.model.setCoef0(coef0)
45 # self.model.setC(Cvalue) 53 # self.model.setC(Cvalue)
46 # self.model.setNu(nu) 54 # self.model.setNu(nu)
47 # self.model.setP(p) 55 # self.model.setP(p)
48 56
49 def train(self, samples, responses): 57 def train(self, samples, responses, computePerformance = False):
50 self.model.train(samples, responses, params = self.params) 58 self.model.train(samples, responses, params = self.params)
59 if computePerformance:
60 return computeConfusionMatrix(self, samples, responses)
51 61
52 def predict(self, hog): 62 def predict(self, hog):
53 return self.model.predict(hog) 63 return self.model.predict(hog)
54 64
55 65