Alat Pendeteksi Lalu Lintas Berbasis Deep Learning

This project leverages deep learning techniques for license plate detection and DeepOCR using HALCON 23.11-Progress Software.

Requirements

• HALCON 23.11
• A labeled dataset of license plates

Step-by-Step Guide

1. Prepare Your Dataset

Modify the dataset path in prepare_data_detection.hdev:

• Set the path to your dataset directory

ExampleDataDir := '/home/dika/Documents/PKM_program/Dataset/Plate'

Run prepare_data_detection.hdev to prepare the dataset for training.

2. Train Your Model

Modify the data directory path in train_data_detection.hdev to point to the prepared dataset:

• Update with your dataset path

dataDir := 'path_from_ur_prepare_dataset'

Run train_data_detection.hdev to start training your model.

3. Running Plate Detection and OCR

After training, update the model paths in PlateDetectionDeepOCR.hdev with the appropriate file locations:

• Set the paths for the preprocess parameters and trained model

PreprocessParamFileName := '/home/dika/Documents/PKM_program/Deteksink/detect_plat_data/dldataset_plat512x320dl_preprocess_param.hdict'
TrainedModelFileName := '/home/dika/Documents/PKM_program/Deteksink/detect_plat_data/best_dl_model_detection.hdl'

Once the paths are updated, you can run the plate detection and OCR using this script.

Results Detection