/flower_classifier

[Deep Learning] Building an image classifier application using Pytorch - a project from Data Scientist NanoDegree

Primary LanguageJupyter Notebook

Image-Classifier-Application-with-Pytorch

Built a neural network model on the training set of ~6.5k images of 102 flower species using 3 Torchvision pre-trained models: VGG16, VGG19 and DenseNet121, achieved accuracy of 89% on the test set of ~800 records

The project is broken down into multiple steps:

  • Load and preprocess the image dataset
  • Train the image classifier on your dataset
  • Use the trained classifier to predict image content

The files in this repo:

  1. Image Classifier Application Project using Pytorch.ipynb : The project file in Jupyter Notebook where most steps are conducted and validated
  2. train.py and predict.py: 2 main python functions to run the command line application.
  3. Helper functions:
    • helper.py : Host functions to process images, view images, save and load checkpoint of the model
    • TrainTestPredictFunc.py : Host functions to train, validate and predict images