diff --git a/nodes.py b/nodes.py
index 21f77cf..7930f96 100644
--- a/nodes.py
+++ b/nodes.py
@@ -3,7 +3,7 @@ import torchvision.transforms.functional as F
 import io
 import os
 import matplotlib
-matplotlib.use('Agg')
+matplotlib.use('Agg')   
 import matplotlib.pyplot as plt
 import matplotlib.patches as patches
 from PIL import Image, ImageDraw, ImageColor, ImageFont
@@ -11,7 +11,6 @@ import random
 import numpy as np
 import re
 
-
 #workaround for unnecessary flash_attn requirement
 from unittest.mock import patch
 from transformers.dynamic_module_utils import get_imports
@@ -127,8 +126,8 @@ class Florence2Run:
             }
         }
     
-    RETURN_TYPES = ("IMAGE", "MASK", "STRING",)
-    RETURN_NAMES =("image", "mask", "caption",)
+    RETURN_TYPES = ("IMAGE", "MASK", "STRING", "JSON")
+    RETURN_NAMES =("image", "mask", "caption", "data") 
     FUNCTION = "encode"
     CATEGORY = "Florence2"
 
@@ -174,6 +173,7 @@ class Florence2Run:
         out = []
         out_masks = []
         out_results = []
+        out_datas = []
         pbar = ProgressBar(len(image))
         for img in image:
             image_pil = F.to_pil_image(img)
@@ -206,6 +206,7 @@ class Florence2Run:
                 out_results.append(clean_results)
 
             W, H = image_pil.size
+            data = []
             parsed_answer = processor.post_process_generation(results, task=task_prompt, image_size=(W, H))
 
             if task == 'region_caption' or task == 'dense_region_caption' or task == 'caption_to_phrase_grounding' or task == 'region_proposal':           
@@ -364,7 +365,9 @@ class Florence2Run:
                 scale = 1
                 draw = ImageDraw.Draw(image_pil)
                 bboxes, labels = predictions['quad_boxes'], predictions['labels']
+                
                 for box, label in zip(bboxes, labels):
+                    data.append({"label": label, "box": box})
                     color = random.choice(colormap)
                     new_box = (np.array(box) * scale).tolist()
                     draw.polygon(new_box, width=3, outline=color)
@@ -373,6 +376,7 @@ class Florence2Run:
                                 align="right",
                                 font=font,
                                 fill=color)
+                    
                 image_tensor = F.to_tensor(image_pil)
                 image_tensor = image_tensor[:3, :, :].unsqueeze(0).permute(0, 2, 3, 1).cpu().float()
                 out.append(image_tensor)
@@ -402,6 +406,8 @@ class Florence2Run:
                 out.append(F.to_tensor(image_pil).unsqueeze(0).permute(0, 2, 3, 1).cpu().float())
 
                 pbar.update(1)
+            # data for task to out_datas
+            out_datas.append(data)
 
         if len(out) > 0:
             out_tensor = torch.cat(out, dim=0)
@@ -417,13 +423,5 @@ class Florence2Run:
             model.to(offload_device)
             mm.soft_empty_cache()
         
-        return (out_tensor, out_mask_tensor, out_results,)
+        return (out_tensor, out_mask_tensor, out_results, out_datas)
      
-NODE_CLASS_MAPPINGS = {
-    "DownloadAndLoadFlorence2Model": DownloadAndLoadFlorence2Model,
-    "Florence2Run": Florence2Run,
-}
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "DownloadAndLoadFlorence2Model": "DownloadAndLoadFlorence2Model",
-    "Florence2Run": "Florence2Run",
-}