diff --git a/ultralyticsplus/__init__.py b/ultralyticsplus/__init__.py
index 405edac..52065c2 100644
--- a/ultralyticsplus/__init__.py
+++ b/ultralyticsplus/__init__.py
@@ -1,4 +1,4 @@
 from .hf_utils import push_to_hfhub, download_from_hub
 from .ultralytics_utils import YOLO, render_model_output, postprocess_classify_output
 
-__version__ = "0.0.8"
+__version__ = "0.0.9"
diff --git a/ultralyticsplus/ultralytics_utils.py b/ultralyticsplus/ultralytics_utils.py
index b0ed905..ceedc26 100644
--- a/ultralyticsplus/ultralytics_utils.py
+++ b/ultralyticsplus/ultralytics_utils.py
@@ -1,14 +1,17 @@
 import logging
 import os
 from pathlib import Path
-from ultralytics import YOLO as YOLOBase
-from ultralytics.nn.tasks import attempt_load_one_weight
-from sahi.prediction import ObjectPrediction, PredictionScore
-from sahi.utils.cv import visualize_object_predictions
 
 import numpy as np
 from PIL import Image
-from sahi.utils.cv import read_image_as_pil
+from sahi.prediction import ObjectPrediction, PredictionScore
+from sahi.utils.cv import (
+    get_bool_mask_from_coco_segmentation,
+    read_image_as_pil,
+    visualize_object_predictions,
+)
+from ultralytics import YOLO as YOLOBase
+from ultralytics.nn.tasks import attempt_load_one_weight
 
 from ultralyticsplus.hf_utils import download_from_hub
 
@@ -69,9 +72,7 @@ def _load_from_hf_hub(self, weights: str, hf_token=None):
         ) = self._guess_ops_from_task(self.task)
 
 
-def render_model_output(
-    image, model: YOLO, model_output: dict
-) -> Image.Image:
+def render_model_output(image, model: YOLO, model_output: dict) -> Image.Image:
     """
     Renders predictions on the image
 
@@ -84,7 +85,7 @@ def render_model_output(
     Returns:
         Image.Image: Image with predictions
     """
-    if model.overrides["task"] not in ['detect', 'segment']:
+    if model.overrides["task"] not in ["detect", "segment"]:
         raise ValueError(
             f"Model task must be either 'detect' or 'segment'. Got {model.overrides['task']}"
         )
@@ -103,11 +104,16 @@ def render_model_output(
         for *xyxy, conf, cls in det:
             if segment:
                 segmentation = [segment[det_ind].ravel().tolist()]
+                bool_mask = get_bool_mask_from_coco_segmentation(
+                    segmentation, width=np_image.shape[1], height=np_image.shape[0]
+                )
+                if sum(sum(bool_mask == 1)) == 0:
+                    continue
                 object_prediction = ObjectPrediction.from_coco_segmentation(
                     segmentation=segmentation,
                     category_name=names[int(cls)],
                     category_id=int(cls),
-                    full_shape=[np_image.shape[1], np_image.shape[0]]
+                    full_shape=[np_image.shape[0], np_image.shape[1]],
                 )
                 object_prediction.score = PredictionScore(value=conf)
             else:
@@ -115,7 +121,7 @@ def render_model_output(
                     bbox=xyxy,
                     category_name=names[int(cls)],
                     category_id=int(cls),
-                    score=conf
+                    score=conf,
                 )
             object_predictions.append(object_prediction)
             det_ind += 1
@@ -125,7 +131,7 @@ def render_model_output(
         object_prediction_list=object_predictions,
     )
 
-    return Image.fromarray(result['image'])
+    return Image.fromarray(result["image"])
 
 
 def postprocess_classify_output(model: YOLO, prob: np.ndarray) -> dict: