Training Perception Models

Object Detection (YOLOv8)

The notebook notebook/kitti_yolo_training.ipynb provides a comprehensive guide for training a YOLOv8 object detection model on the KITTI dataset.

• Key Steps in the Notebook: 1. KITTI to YOLO Format Conversion. 2. Dataset Splitting. 3. YAML Configuration (kitti.yaml). 4. Hyperparameter Tuning (Optuna). 5. Training. 6. Evaluation. 7. Inference & Visualization. 8. ONNX Export.

NLP Chatbot Model

Training for the NLP chatbot’s intent classification model is integrated within NLP/adas_chatbot.py.

• When the Chatbot class is initialized, it checks for NLP/models/processed_data_pytorch.pkl and NLP/models/qa_nn_model.pth.

• If missing, DataPreprocessor and ModelTrainer are invoked to: 1. Process moroccan_traffic_code.json. 2. Train the NeuralNet. 3. Save processed data and the model.