🧠 Enhanced NeRF in PyTorch

This repository contains a minimal yet enhanced implementation of Neural Radiance Fields (NeRF) using PyTorch. It is designed for learning and experimenting with neural rendering techniques on synthetic datasets, specifically the Tiny NeRF dataset.

🚀 Features

• 🔍 Data Loader
  Efficiently loads and splits the dataset for training and validation.

• 🧱 Enhanced NeRF Model
  Supports positional encoding with configurable frequency bands, deeper MLP architecture, and Xavier weight initialization.

• 🧮 Fixed Volume Rendering
  Implements a numerically stable version of NeRF’s volume rendering algorithm.

• 🎯 Training Loop
  Includes random pixel sampling, ray generation, rendering, loss computation, and validation visualization.

• 📉 Live Visualization
  Displays rendered validation images and loss curve during training.

• 💾 Progress Logging
  Intermediate results are saved in a progress/ directory for inspection or debugging.

📦 Dependencies

Make sure to install the following Python packages:

• torch
• numpy
• matplotlib
• IPython
• wget (for downloading the dataset)

You can install them using pip:

pip install torch numpy matplotlib ipython


# Clone the repo
git clone https://github.com/yourusername/enhanced-nerf-pytorch.git
cd enhanced-nerf-pytorch

# Run the script
python3 your_script_name.py