Update README.md

README.md

@@ -14,11 +14,35 @@ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-
 
 # Butterfly Classification using CNN
 
+- **Author:** Kamelia Zaman Moon
+- **Project link:** https://huggingface.co/spaces/KameliaZaman/Butterfly-Classification-using-CNN
+- **Language(s):** Python
+- **License:** MIT
+- **Contact:** [email protected]
+
+## Table of Contents
+-  [Introduction](#introduction)
+-  [Model Architecture](#model-architecture)
+-  [How-to Guide](#how-to-guide)
+-  [License](#license)
+-  [Contributors](#contributors)
+
 ## 1. Introduction
 This project focuses on classifying butterfly images using a Convolutional Neural Network (CNN). The dataset includes images of butterflies and moths, with the goal of training a model to accurately predict the species of a given butterfly image.
 
 ## 2. Model Architecture
 The CNN model used for this project is based on the ResNet50V2 architecture. The model is trained on a dataset consisting of training, validation, and test sets. The key components of the model architecture include convolutional layers, dropout for regularization, global average pooling, and fully connected layers. The model is compiled using the Adam optimizer and sparse categorical crossentropy loss.
+```
+──  model_checkpoint_manual_effnet.h5 - generated model.
+
+──  Butterfly classification with CNN.ipynb - preprocesses input, trains, saves and evaluates the model.
+
+──  app.py - this module starts the app interface.
+
+──  README.md - readme file of this project.
+
+──  requirements.txt - list of required packages.
+```
 
 ## 3. How-to Guide
 ### 3.1. Data Preparation
@@ -45,8 +69,22 @@ The CNN model used for this project is based on the ResNet50V2 architecture. The
 - Gradio is utilized for deploying the trained model.
 - Users can input an image, and the model will predict the butterfly species.
 
+```bash
+# clone project   
+git clone https://huggingface.co/spaces/KameliaZaman/Butterfly-Classification-using-CNN/tree/main
+
+# go inside the project directory 
+cd Butterfly-Classification-using-CNN
+
+# install the required packages
+pip install -r requirements.txt
+
+# run the gradio app
+python app.py 
+```
+
 ## 4. License
 This project is licensed under the [MIT License](LICENSE).
 
 ## 5. Contributors
-- Kamelia Zaman Moon
+- Kamelia Zaman Moon - [email protected]