diff --git a/util/utils.py b/util/utils.py
index 62278cb..eb7c8b2 100644
--- a/util/utils.py
+++ b/util/utils.py
@@ -76,8 +76,8 @@ def get_yolo_model(model_path):
 
 
 @torch.inference_mode()
-def get_parsed_content_icon(filtered_boxes, starting_idx, image_source, caption_model_processor, prompt=None, batch_size=None):
-    # Number of samples per batch, --> 256 roughly takes 23 GB of GPU memory for florence model
+def get_parsed_content_icon(filtered_boxes, starting_idx, image_source, caption_model_processor, prompt=None, batch_size=128):
+    # Number of samples per batch, --> 128 roughly takes 4 GB of GPU memory for florence v2 model
     to_pil = ToPILImage()
     if starting_idx:
         non_ocr_boxes = filtered_boxes[starting_idx:]
@@ -103,7 +103,6 @@ def get_parsed_content_icon(filtered_boxes, starting_idx, image_source, caption_
     
     generated_texts = []
     device = model.device
-    # batch_size = 64
     for i in range(0, len(croped_pil_image), batch_size):
         start = time.time()
         batch = croped_pil_image[i:i+batch_size]
@@ -405,7 +404,7 @@ def int_box_area(box, w, h):
     area = (int_box[2] - int_box[0]) * (int_box[3] - int_box[1])
     return area
 
-def get_som_labeled_img(image_source: Union[str, Image.Image], model=None, BOX_TRESHOLD=0.01, output_coord_in_ratio=False, ocr_bbox=None, text_scale=0.4, text_padding=5, draw_bbox_config=None, caption_model_processor=None, ocr_text=[], use_local_semantics=True, iou_threshold=0.9,prompt=None, scale_img=False, imgsz=None, batch_size=64):
+def get_som_labeled_img(image_source: Union[str, Image.Image], model=None, BOX_TRESHOLD=0.01, output_coord_in_ratio=False, ocr_bbox=None, text_scale=0.4, text_padding=5, draw_bbox_config=None, caption_model_processor=None, ocr_text=[], use_local_semantics=True, iou_threshold=0.9,prompt=None, scale_img=False, imgsz=None, batch_size=128):
     """Process either an image path or Image object
     
     Args:
@@ -413,8 +412,8 @@ def get_som_labeled_img(image_source: Union[str, Image.Image], model=None, BOX_T
         ...
     """
     if isinstance(image_source, str):
-        image_source = Image.open(image_source).convert("RGB")
-    
+        image_source = Image.open(image_source)
+    image_source = image_source.convert("RGB") # for CLIP
     w, h = image_source.size
     if not imgsz:
         imgsz = (h, w)
@@ -538,6 +537,4 @@ def check_ocr_box(image_source: Union[str, Image.Image], display_img = True, out
             bb = [get_xywh(item) for item in coord]
         elif output_bb_format == 'xyxy':
             bb = [get_xyxy(item) for item in coord]
-    return (text, bb), goal_filtering
-
-
+    return (text, bb), goal_filtering
\ No newline at end of file