Check out the app live on Streamlit Share
This is my first project with neural networks. It classifies 130 different fruits on the basis of a dataset with more than 90,000 images.
I found the image dataset from kaggle by the name of Fruits 360. I split the dataset for training(80%) and validation(20%).then I added a preprocessing layer from TensorFlow.
I used the ResNet model ResNet50 as my base model. then I added a global average pooling layer and a prediction layer. I trained the model with 10 epochs and achieved an accuracy of 99.84% on the trainig dataset and 99.90% on the validation dataset.
