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