This project implements an image classifier using the ResNet architecture. The model was trained on the CIFAR-10 dataset and achieved over 90% accuracy.
- ResNet Architecture: Custom Residual Network (ResNet) implemented in Keras.
- Experiment Tracking: Integrated MLflow for tracking experiments, logging metrics, and saving the final model.
- User Interface: User-friendly interface using Gradio for easy interaction with the model.
- Python 3.x
- Keras
- TensorFlow
- MLflow
- Gradio