The goal of this project is to build an image classifier by using Pytorch python library. The classifier takes flowers images and uses a pre-trained deep learning model in order to classify the 102 species of flowers in the dataset.
The code is provided in the Image Classifier Project.html file.
The project also includes four files train.py, predict.py, dl_classifier.py and image_preprocessing.py. The first file, train.py, will train a new network on a dataset and save the model as a checkpoint. The second file, predict.py, uses a trained network to predict the class for an input image. The third file, image_preprocessing.py, contains code that is related to preprocessing images. The fourth file, dl_classifier.py, contains functions for creating the deep learning model. These four files also can be used to run the model.
The data is provided in flowers folder. The dataset contains 102 categories and it is divided into three sets: training, validation and testing.
PyTorch
- Image Classifier Project.html
- cat_to_name.json
- predict.py
- train.py
- dl_classifier.py
- image_preprocessing.py
- flowers