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Roof-Type-Classification

Roof Type Classification with Innovative Machine Learning Approaches

Abstract

In this study, roof type classification was made with a small number of examples for training, in accordance with the one-shot learning approach and using the "Siamese Neural Network" method. The images used for training were artificially produced due to the difficulty of finding roof data. A dataset consisting of real roof pictures was used for the test. The test and training dataset consists of 3 different types: Flat, Gable and Hip. Finally, a CNN-based model and a Siamese Neural Network model were trained with the same datasets and the test results were compared with each other.

Data

  • Hip, Flat and Gable roof type of examples are given.
  • Cati images are of three types of examples, Flat, Gable, and Hip, and were produced by the authors using Autodesk Maya software

Codes

  • one_shot_model.py is the code for create Siamese model.
  • one_shot_mydataset.py is the code for read and label the dataset.
  • one_shot_train.py is the code for train your dataset and for get results.