Fruit Classification is a machine learning project designed for classifying images of fruits into different categories. This project leverages Inceptionv3 as the base model for high-performance image classification.
The goal of the Fruit Classification project is to build a model capable of accurately classifying images of fruits into predefined categories. This model uses Inceptionv3 as its backbone to achieve state-of-the-art performance.
To get started with Fruit Classification, follow these instructions to set up your environment and run the project.
Prerequisites
- Python 3.x
- TensorFlow or PyTorch
- NumPy
- Pandas
- Matplotlib (for visualization)
Installation
1.Clone the repo
git clone https://github.com/steve601/fruit-classification-Inceptionv3.git
2.Create venv 3.Install dependancies
pip install -r requirements.txt
4.Run .py file
python app.py