Update README.md

README.md

@@ -61,6 +61,7 @@ You can find our dataset on huggingface: 🤗[InfoChartQA Dataset](https://huggi
 Each question entry is arranged as:
 
 ```
+{
         "question_id": id of the question,
         "qtype": type of the question, for example: "rank" questions 
         "figure_path": local path of the image if you download the image,
@@ -72,15 +73,18 @@ Each question entry is arranged as:
         "parent": the original image of the cropped image, 
         "difficulty": difficulty level,
         "chart_type": chart_type,
+}
 ```
 
-Each question is built as:
+Each question is built on:
 
 ```
-image_input: url (may need to download for models that don't support url input)
-text_iunput: question + instructions (if any)
+image_input: item["url"] (may need to download for models that don't support url input)
+text_iunput: item["question"] + item["instructions"] (if any)
 ```
 
+where ``item`` is an entry of the dataset.
+
 # Evaluate
 
 You should store and evaluate model's response as:
@@ -107,7 +111,9 @@ for query in tqdm(queries):
     question_text = build_question(query)
     chart_figure = query["url"]  # This should be a list of url
     """
-    Note that for models that do not support url input, you may need to download images first.
+        Note that for models that do not support url input, you may need to download images first.
+        For example, for model like Qwen2.5-VL, you may need to down load the image first and pass the local image path to the model,
+        like: figure_path = YOUR_LOCAL_IMAGE_PATH OF query['figure_path']
     """
     # Replace with your model
     response = model.generate(question_text, chart_figure)