Update README.md

README.md

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----
-license: gpl-3.0
----
+---
+license: gpl-3.0
+datasets:
+- Msun/modelnet40
+language:
+- en
+metrics:
+- accuracy
+tags:
+- deeplearning
+---
+# **Automated Defect Detection in 3D Mesh Files Using Multi-Model Deep Learning Approaches**  
+
+## **📌 Project Overview**  
+This project introduces a **multi-modal deep learning approach** to detect **defects in 3D mesh files** by combining:  
+- **CNN (Convolutional Neural Network)** for **object classification** using **ModelNet40** dataset images.  
+- **GNN (Graph Neural Network)** for **defect identification** in **OFF files (3D mesh models).**  
+- **Fusion Model** integrating **CNN and GNN** for improved classification accuracy.  
+
+## **📁 Dataset & Novelty**  
+The dataset used in this project is **novel and proprietary**, focusing on defect detection in 3D mesh files. Only the **ModelNet40 dataset** is publicly available.  
+
+### **🔹 Folder Structure**  
+```
+📦 Dataset
+ ┣ 📂 Images
+ ┃ ┣ 📂 train
+ ┃ ┃ ┣ 📂 category_1
+ ┃ ┃ ┣ 📂 category_2
+ ┃ ┃ ┗ ...
+ ┃ ┗ 📂 test
+ ┗ 📂 OFF_files
+   ┣ 📂 train
+   ┃ ┣ 📂 category_1
+   ┃ ┃ ┣ 📂 normal
+   ┃ ┃ ┗ 📂 defected
+   ┃ ┣ 📂 category_2
+   ┃ ┃ ┣ 📂 normal
+   ┃ ┃ ┗ 📂 defected
+   ┗ 📂 test
+ 
+```
+- **Images Folder** → Contains object images categorized into different classes (used for CNN).  
+- **OFF Files Folder** → Each category has **"normal"** and **"defected"** OFF files (used for GNN).  
+
+---
+
+## **🚀 Model Architecture**  
+### **🔹 CNN Model (Image Classification)**
+- Uses a **pretrained CNN model (ResNet)** to classify objects.  
+
+### **🔹 GNN Model (Defect Identification)**
+- Processes **OFF files** using **node features** and **adjacency matrices**.  
+- Uses a **13-layer deep GNN model** to capture mesh structure defects.  
+
+### **🔹 Multi-Modal Fusion Model**
+- Combines **CNN and GNN outputs** using **fully connected layers**.  
+- Improves **accuracy by leveraging both image and graph information**.  
+
+---
+
+## **⚙️ Installation & Setup**  
+### **🔹 1️⃣ Install Dependencies**  
+```bash
+pip install tensorflow numpy networkx trimesh
+```
+
+### **🔹 2️⃣ Run Training**  
+```bash
+python Utils/train.py
+```
+
+### **🔹 3️⃣ Evaluate Model**  
+```bash
+python Utils/evaluate.py
+```
+
+---
+
+## **📊 Results & Evaluation**  
+- **CNN Classification Accuracy:**  **76%**  
+- **GNN Defect Detection Accuracy:**  **78%**  
+- **Fusion Model Accuracy:**  **85%**  
+
+---
+
+## **🛠️ Future Improvements**  
+- Use **a more complex GNN model** (with at least **13 layers**).  
+- Improve **multi-modal fusion model** by adding **extra layers**.  
+- Train on **a larger dataset** to improve generalization.  
+
+---
+
+## **👨‍💻 Author**  
+**Dhanush**  
+📧 Contact: [e-mail](mailto:gdhanush270@gmail.com)
+
+---