#  Flower Recognition Model

## Table of Contents

- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)

---

## Features

- This model can recognize various types of flowers using CNN(Convolution Neural Network).
- It is built using TensorFlow and Keras.
- The model can be trained on your own dataset or fine-tuned on an existing flower recognition dataset.
- Provides a user-friendly interface for making predictions on new flower images.

---
## Installation

1. **Clone the Repository**:
   ```
   git clone https://github.com/yourusername/nameofrepo.git
   ```

2. **Navigate to the Meddy Directory**:
   ```
   cd "Flower Recognition"
   ```

3. **Install Dependencies**:
   Use pip to install the required Python packages:
   ```
   pip install -r requirements.txt
   ```

4. **Launch the Application**:
   Open the VS Code Editor and open the prediction.ipynb file and run all cells.

5. **Launch website for user**:
   Run the below code in ternimal:
   ```
   python -m streamlit run app.py
   ```

---

## Usage

Using prediction is straightforward:

1. **Launch the Application**: Open the url provided in the terminal.

2. **Upload Image**: Upload image of the flower.

3. **Get Predictions**: You will get prediction.