Update README.md

README.md

@@ -56,13 +56,29 @@ The ENA is detailed in the paper *Earthwork Network Architecture (ENA): Research
 - **Libraries**: Install the required libraries using `pip install`. Detailed dependencies will be provided in the code files.
 
 ### Data Preparation
-1. **Input Data**:
-   - Prepare CAD cross-sectional drawings as input files.
+1. **Prepare Train Dataset**:
+   - Prepare CAD cross-sectional drawings as input files and load it on Autocad. Run the below program to extract the entities per each cross-section in the drawing. In addition, you can define the earthwork item's layer name in config.json. 
+   ```bash
+   python create_earthwork_dataset.py --config config.json --output output/ --view output/chain_chunk_6.json
+   ```
+   - In reference, we assume that each earthwork item's layer including entities were segmented(Please refer to the below paper). 
    - Use the provided scripts to preprocess and tokenize geometrical features.
-   
+   ```bash
+   python prepare_dataset.py --input output/ --output dataset/
+   ```
+
 2. **Training Data**:
-   - Features are tokenized into sequences for MLP, LSTM, Transformers, and LLM models.
+   - Features are tokenized into sequences for MLP, LSTM, Transformers, and LLM models. We'll upload the train source file after arrangement.
+   ```bash
+   python train_ena_model.py --model_type [MLP|LSTM|Transformer|LLM]
+   ```
 
+3. **Run and Test ENA model**:
+   - Run the below program to run and test the each ENA model. It will generate log and graph image files to check the performance.
+   ```bash
+   python ena_run_model.py --model_type [MLP|LSTM|Transformer|LLM]
+   ```     
+   
 ### Training and Evaluation
 1. Select the model architecture (`MLP`, `LSTM`, `Transformer`, or `LLM`).
 2. Configure hyperparameters (batch size, learning rate, etc.) as required.
@@ -89,6 +105,6 @@ This project is licensed under the MIT License.
 ## Citation
 If you use this repository, please cite:
 ```
-Kang, T.; Kang, K. Earthwork Network Architecture (ENA): Research for Earthwork Quantity Estimation Method Improvement with Large Language Models. Appl. Sci. 2024, 14, 10517.
+Kang, T.; Kang, K. [Earthwork Network Architecture (ENA): Research for Earthwork Quantity Estimation Method Improvement with Large Language Models](https://www.mdpi.com/2076-3417/14/22/10517). Appl. Sci. 2024, 14, 10517.
 https://doi.org/10.3390/app142210517
 ```