The main purpose of this project is to train a image classifier to recognize different species of flowers.
This project contains two main parts: Jupyter Notebook and Python App.
- Image Classifier notebook
- Image Classifier.ipynb: This jupyter notebook shows the code and development of the image classifier.
- The project is broken down into multiple steps:
- Load and preprocess the image dataset
- Train the image classifier on the image dataset
- Use the trained classifier to predict image content
- Python App
- Predict.py: This Python script loads the data from a image folder. Then it uses the data to train and tune a Deep Learning model. Finally the model will be saved to checkpoint for further usage.
- Train.py: This Python script load and rebuild the model from checkpoint. Then it uses the model to predict the class of a image from a image file.