This project demonstrates how to perform image classification using the pre-trained VGG19 model from Keras. It's a simple, clean example of transfer learning for identifying image content with high accuracy.
- ✅ Uses VGG19 pretrained on ImageNet
- ✅ Loads and preprocesses custom images
- ✅ Outputs top predictions with class names and confidence scores
- ✅ Easy to customize for other datasets or models
Install the required libraries:
pip install tensorflow numpy pillowpip install -r requirements.txt!download this:
vgg19_weights_tf_dim_ordering_tf_kernels_notop.h5
!this will be create in VGG.ipynb:
image_classification_model.keras
