In this project I built a simple image classification model to detect whether a fruit is fresh or rotten.
The goal of this project is to classify fruits to its category :
- Fresh
- Rotten
Note: The model is trained on specific fruits such as ( apple, banana, and orange ), so it works within this scope.
The steps for building the project were as follows:
- Collected dataset from Kaggle
- Performed image preprocessing (resizing & normalization)
- Built a CNN model using TensorFlow/Keras
- Trained and evaluated the model
- Created a simple Streamlit app for deployment
Dependencies:
- Python
- TensorFlow / Keras
- NumPy
- Streamlit
How to run the project:
- Install requirements:
- pip install -r requirements.txt
- Run the app: streamlit run streamlit/main.py
Link of Dataset on Kaggle :
Download model file in the folder of project :