This project builds a deep learning model to classify pet images as either cats or dogs using Convolutional Neural Networks (CNNs).
The model learns features from image data and predicts the pet type.
- Data Collection & Preprocessing
- Load and resize images.
- Normalize pixel values.
- Apply data augmentation for better generalization.
- Model Training
- Implement a CNN using PyTorch.
- Train the model on labeled cat and dog images.
- Evaluation & Visualization
- Assess model performance using accuracy, loss curves, and confusion matrix.
- Display the classification report.
The Cat or Dog Classifier effectively differentiates between cats and dogs using a CNN model trained on labeled images. Through data preprocessing and augmentation, the model achieves improved accuracy. Future enhancements could include transfer learning with pretrained models and deployment for real-time classification.