diff --git a/README.md b/README.md
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+# Jingwen Wang s5820023 ML Project
+
+## Introduction
+
+This project aims to develop a machine learning tool that generates PBR material maps from single photographs, addressing the lighting contamination issue in existing scanned material libraries. The focus will be on a single material category, with the first stage targeting either extracting base color by removing lighting effects, or implementing photo super-resolution.
+
+## Main Approach
+
+**Option 1:** Pixel classification - classify pixels into diffuse, specular highlight, and shadow regions to extract base color
+
+**Option 2:** Super-resolution - upscale low-resolution photos to 2K/4K quality
+
+Feedback needed on which approach is more suitable for the first stage.
+
+## Key Datasets
+
+- Segmentation: UCI Image Segmentation Dataset
+- Super-resolution: DIV2K, Urban100
+
+## Reading Material
+
+- Minaee, Shervin, et al. Image Segmentation Using Deep Learning: A Survey. arXiv, 2020.
+- Wang, Zhihao, et al. Deep Learning for Image Super-Resolution: A Survey. arXiv, 2020.
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diff --git a/notebooks/01_Project_Design.ipynb b/notebooks/01_Project_Design.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "bb2fe1ff",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "import torchvision\n",
+    "import matplotlib.pyplot as plt\n",
+    "from PIL import Image"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9574da48",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.21"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/requirements.txt b/requirements.txt
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+torch
+torchvision
+matplotlib
+jupyter
+numpy
+Pillow
+scikit-learn