def evaluate(classifierPath, testPath):
# Evaluate whole
actualLabels = classifier.loadLabels(testPath)
predictedLabels = test(classifierPath, testPath)
resultByName = evaluation_process.evaluateClassifier(actualLabels, predictedLabels, 'Boosted convolutional neural network')
# Evaluate parts
for weakClassifierPath in glob.glob(os.path.join(classifierPath, 'weak*.info')):
weakName = store.extractFileBaseName(weakClassifierPath)
weakClassifierInformation = store.loadInformation(weakClassifierPath)
resultByName[weakName] = weakClassifierInformation['performance']
# Return
return resultByName
def evaluate(classifierPath, testPath):
actualLabels = loadLabels(testPath)
predictedLabels = test(classifierPath, testPath)
resultByName = evaluation_process.evaluateClassifier(actualLabels, predictedLabels, 'Convolutional neural network')
return resultByName
