experiments

Experiments Directory

This directory is for Jupyter notebooks that demonstrate various aspects of the Dynamic NeRF implementation.

Notebook Files

The following notebooks should be created in this directory:

1. dynamic_nerf_exploration.ipynb - Basic exploration of the Dynamic NeRF model
2. dataset_visualization.ipynb - Visualization of the dataset and preprocessing steps
3. hyperparameter_tuning.ipynb - Experiments with different hyperparameters
4. results_analysis.ipynb - Analysis of training results and model performance

Creating Notebooks

To create a new notebook, you can use Jupyter:

jupyter notebook

Navigate to this directory and click "New" -> "Python 3" to create a new notebook.

Using the Dynamic NeRF Package in Notebooks

To use the Dynamic NeRF package in your notebooks, add the following code at the beginning:

import os
import sys

# Add the project root to the path
module_path = os.path.abspath(os.path.join('..'))
if module_path not in sys.path:
    sys.path.append(module_path)

# Now you can import from the package
from src.models.nerf import NeRF
from src.models.dynamic_nerf import DynamicNeRF
# ... other imports

Example Notebook Structure

A typical notebook should include:

1. Introduction - Explain the purpose of the notebook
2. Setup - Import necessary modules and set up the environment
3. Data Loading - Load and preprocess data
4. Model Initialization - Initialize the Dynamic NeRF model
5. Experiments - Run experiments and visualize results
6. Conclusion - Summarize findings and next steps

Tips for Effective Notebooks

• Use markdown cells to document your code and explain your reasoning
• Include visualizations to help understand the data and results
• Keep code cells focused on a single task
• Use section headers to organize your notebook
• Save intermediate results to avoid rerunning long computations
• Include parameter explorations to understand model behavior