Project Title

This project involves predicting stable heights using a machine learning model. The submission includes the model code, test predictions (in Kaggle format), and instructions to reproduce the results.

Table of Contents

• Requirements
• Image Files
• Running the File
• CSV Predictions

Requirements

Install the required Python packages using pip:

pip install -r requirements.txt

Ensure the following libraries are installed:

• pandas
• timm
• matplotlib
• torch
• fastai
• OpenCV (cv2)
• numpy

If the required packages are missing in the requirements.txt, you can manually install them:

 pip install pandas timm matplotlib torch fastai opencv-python numpy

Image Files

• Training Data: Found in the relative file path \COMP90086_2024_Project_train
• Test Data: Found in the relative file path \COMP90086_2024_Project_test

Running the File

The jupyter notebook can be run after the requirements have been installed. To test different configurations of models, item transformation, and batch transformations, uncomment the desired parts of the code found under the Training Loop section. Specific implementation details are can be found within the comments of the Jupyter notebook.

CSV Predictions

CSV predictions are found in results_vit_final.csv. It is in the Kaggle format of

id,stable_height
17809,6
45934,1
22537,3