Dry Fruit Type Classification Model

The Dry Fruit Classification Model is an advanced machine learning project that utilizes transfer learning to classify images of dry fruits into different categories. By leveraging the powerful VGG16 pre-trained model, this project applies deep learning techniques to harness the features learned from large datasets and adapt them to classify dry fruits with high accuracy.

Key Features:

• Classifies different types of dry fruits.
• Uses deep learning techniques for image classification.
• Achieves an accuracy of 90% on the test set.

Technologies Used:

• Python
• TensorFlow/Keras
• OpenCV
• NumPy, Pandas

How to Run the Model (Locally)

1. Clone the repository:

   git clone https://github.com/yourusername/dry-fruit-classification.git

2. Clone the repository:

   Open notebook notebook/dryfruitdetection in colab