A Flask-based API using TensorFlow and Keras for face and signature image classification using a CNN model
Description: This project focuses on developing an image classification API using Flask. The API is capable of classifying images as either face or signature. It utilizes a Convolutional Neural Network (CNN) architecture implemented with TensorFlow and Keras. The training dataset is preprocessed, and the model is trained using techniques like random undersampling to address class imbalance. The trained model is evaluated using various metrics and saved for future use. The API is deployed on a server, allowing easy integration with other applications or services.
Key Features:
- Image classification API using Flask
- Convolutional Neural Network (CNN) architecture
- Data preprocessing and model training
- Evaluation metrics and model persistence
- Deployment on a server for integration
Achievements:
- Achieved high accuracy in classifying face and signature images
- Effectively addressed class imbalance through random undersampling
- Optimized model architecture for improved performance