A deep learning project focused on classifying fish species using Convolutional Neural Networks (CNNs) and transfer learning, wrapped in a user-friendly Streamlit web application.
- Deep Learning
- Python
- TensorFlow / Keras
- Streamlit
- Data Preprocessing
- Transfer Learning
- Model Evaluation
- Visualization
- Model Deployment
Image Classification
The goal is to classify fish images into multiple species using CNN-based deep learning models. The project involves training models from scratch, applying transfer learning, and deploying the best-performing model through a web application using Streamlit.
- 🔍 Enhanced Accuracy: Identify the best model for high-accuracy classification of fish species.
- 🌐 Deployment Ready: Create an easy-to-use web interface for image uploads and real-time predictions.
- 📊 Model Comparison: Analyze and compare various models to determine the most efficient approach.
- Rescale images to range
[0, 1] - Apply techniques like rotation, zoom, flipping to improve generalization