This projce include three parts: Classification, Difference Measure for Images and Evaluation.
1 Classification
1.1 Re-train VGG16 model to get the optimal weights
1.2 Classification for Images
2 Difference Measure
2.1 Raw Images and Feature Vectors
2.2 Classifier Vectors
2.3 Average Hash
2.4 Difference Hash
3 Evaluation
3.1 Intra-class and Inter-class average distance
3.1.1 Raw Images
3.1.2 Feature Vectors
3.1.3 Classifier Vectors
3.1.4 Average Hash
3.1.5 Difference Hash
3.2 Clustering
3.2.1 Raw Images and Feature Vectors
3.2.2 Classifier Vectors
3.2.3 Average Hash + Difference Hash