Using Out Of Distribution scores during classification

This code snippet shows how to compute and use Out Of Distribution scores during classification.

C++

#include <eVision/EasyDeepLearning/EasyClassify/EClassifier.h>

using namespace eVision;
using namespace eVision::EasyDeepLearning;

// Classifier
EClassifier classifier;

// Load a pretrained classifier whose OOD parameters have been learned
classifier.Load("classifierPath");

// Test image
EImageBW8 image;

// Get result
EClassificationResult result = classifier.Classify(image);

// Get OOD score
float score = result.GetOODScore();
// Get OOD threshold
float threshold = result.GetOODThreshold();
// Get binary OOD result
bool isOOD = result.IsOOD();

// Set custom OOD threshold
classifier.SetOODThreshold(0.5);

// Disable OOD computation
classifier.SetComputeOODWithResult(false);

C#

using eVision;
using eVision.EasyDeepLearning;

// Classifier
EClassifier classifier = new EClassifier();

// Train the classifier
classifier.Load("classifierPath");

// Test image
EImageBW8 image = new EImageBW8();

// Get result
EClassificationResult result = classifier.Classify(image);

// Get OOD score
float score = result.OODScore;
// Get OOD threshold
float threshold = result.OODThreshold;
// Get binary OOD result
bool isOOD = result.IsOOD();

// Set custom OOD threshold
classifier.OODThreshold = 0.5f;

// Disable OOD computation
classifier.ComputeOODWithResult = false;

Python

import eVision
from eVision import EasyDeepLearning as edl

# Classifier
classifier = edl.EClassifier()

# Load a pretrained classifier whose OOD parameters have been learned
classifier.Load("classifierPath")

# Test image
image = eVision.EImageBW8()

# Get result
result = classifier.Classify(image)

# Get OOD score
score = result.OODScore
# Get OOD threshold
threshold = result.OODThreshold
# Get binary OOD result
isOOD = result.IsOOD()

# Set custom OOD threshold
classifier.OODThreshold = 0.5

# Disable OOD computation
classifier.ComputeOODWithResult = False