Update README.md

README.md

@@ -41,17 +41,70 @@ We investigate domain adaptation of MLLMs through post-training, focusing on dat
     <img src="https://cdn-uploads.huggingface.co/production/uploads/650801ced5578ef7e20b33d4/-Jp7pAsCR2Tj4WwfwsbCo.png" width="600">
 </p>
 
-## How to use
+## How to Use  
 
+### Loading Data  
+You can load datasets using the `datasets` library:  
 ```python
 from datasets import load_dataset
 
 # Choose the task name from the list of available tasks
-task_name = 'FoodSeg103' # Options: 'Food101', 'FoodSeg103', 'Nutrition5K', 'Recipe1M'
+task_name = 'FoodSeg103'  # Options: 'Food101', 'FoodSeg103', 'Nutrition5K', 'Recipe1M'
 
 # Load the dataset for the chosen task
 data = load_dataset('AdaptLLM/food-VQA-benchmark', task_name, split='test')
-```
+```  
+
+### Mapping Categories to Indices  
+The mapping between category names and indices for `Food101`, `FoodSeg103`, and `Nutrition5K` datasets is provided in the following files:  
+- **Food101**: `food101_name_to_label_map.json`  
+- **FoodSeg103**: `foodSeg103_id2label.json`  
+- **Nutrition5K**: `nutrition5k_ingredients.py`  
+
+### Examples of Usage  
+
+#### Food101  
+```python
+import json
+
+# Load the mapping file
+map_path = 'food101_name_to_label_map.json'
+name_to_label_map = json.load(open(map_path))
+
+# Reverse mapping: label to name
+label_to_name_map = {value: key.replace('_', ' ') for key, value in name_to_label_map.items()}
+```  
+
+#### FoodSeg103  
+```python
+import json
+
+# Load the mapping file
+map_path = 'foodSeg103_id2label.json'
+id2name_map = json.load(open(map_path))
+
+# Remove background and irrelevant labels
+id2name_map.pop("0")  # Background
+id2name_map.pop("103")  # Other ingredients
+
+# Convert keys to integers
+id2name_map = {int(key): value for key, value in id2name_map.items()}
+
+# Create reverse mapping: name to ID
+name2id_map = {value: key for key, value in id2name_map.items()}
+```  
+
+#### Nutrition5K  
+```python
+from nutrition5k_ingredients import all_ingredients
+
+# Create mappings
+id2name_map = dict(zip(range(0, len(all_ingredients)), all_ingredients))
+name2id_map = {value: key for key, value in id2name_map.items()}
+```  
+
+
+
 
 ## Citation
 If you find our work helpful, please cite us.