# How to run object detection inference with a YOLOE segmentation model? **URL:** \ **Category:** Discussion\ **Tags:** code\ **Created:** [September 2, 2025, 6:02pm UTC](https://community.ultralytics.com/t/how-to-run-object-detection-inference-with-a-yoloe-segmentation-model/1436 "2025-09-02T18:02:22Z")\ **Posts on this page:** 8\ **Page:** 1
**Author:** ![Kallinteris-Andreas](https://sea1.discourse-cdn.com/flex001/user_avatar/community.ultralytics.com/kallinteris-andreas/32/838_2.png) [@Kallinteris-Andreas](https://community.ultralytics.com/u/Kallinteris-Andreas)\ **Post date:** [September 2, 2025, 6:02pm UTC](https://community.ultralytics.com/t/how-to-run-object-detection-inference-with-a-yoloe-segmentation-model/1436/1 "2025-09-02T18:02:22Z")
How to load YOLOE model without the segmentation head YOLOE support training for object detection, and I am trying to verify inference of an YOLOE object detection models works and benchmark it ```py model = YOLO("yoloe-11l.yaml").load('panopticon_models/yoloe-11l-seg.pt') model.set_classes(["person"]) # this fails model.predict() ``` Note: I am not up-to-date with how the latest YOLO architectures do segmentation, the latest paper I have read is `YOLOACT`, and I assume that YOLO{NUMEBER}-seg models work in a similar way (by extending detection head to detect mask) Thanks! ---
**Author:** ![Toxite](https://sea1.discourse-cdn.com/flex001/user_avatar/community.ultralytics.com/toxite/32/123_2.png) [@Toxite](https://community.ultralytics.com/u/Toxite)\ **Post date:** [September 2, 2025, 11:14pm UTC](https://community.ultralytics.com/t/how-to-run-object-detection-inference-with-a-yoloe-segmentation-model/1436/2 "2025-09-02T23:14:06Z")
The code you provided works fine for me. What exactly “fails”? ---
**Author:** ![Kallinteris-Andreas](https://sea1.discourse-cdn.com/flex001/user_avatar/community.ultralytics.com/kallinteris-andreas/32/838_2.png) [@Kallinteris-Andreas](https://community.ultralytics.com/u/Kallinteris-Andreas)\ **Post date:** [September 3, 2025, 7:11am UTC](https://community.ultralytics.com/t/how-to-run-object-detection-inference-with-a-yoloe-segmentation-model/1436/3 "2025-09-03T07:11:06Z")
```sh $ py Python 3.12.11 (main, Jul 23 2025, 11:34:34) [GCC 15.1.1 20250425] on linux Type "help", "copyright", "credits" or "license" for more information. >>> from ultralytics import YOLO >>> model = YOLO("yoloe-11l.yaml").load('panopticon_models/yoloe-11l-seg.pt') Transferred 1108/1108 items from pretrained weights >>> model.set_classes(["person"]) Traceback (most recent call last): File "", line 1, in File "/home/master-andreas/panopticon/test_env/lib/python3.12/site-packages/ultralytics/models/yolo/model.py", line 330, in set_classes embeddings = self.get_text_pe(classes) # generate text embeddings if not provided ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/master-andreas/panopticon/test_env/lib/python3.12/site-packages/ultralytics/models/yolo/model.py", line 269, in get_text_pe return self.model.get_text_pe(texts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/master-andreas/panopticon/test_env/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 120, in decorate_context return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "/home/master-andreas/panopticon/test_env/lib/python3.12/site-packages/ultralytics/nn/tasks.py", line 1038, in get_text_pe assert not self.training ^^^^^^^^^^^^^^^^^ AssertionError ``` ---
**Author:** ![Toxite](https://sea1.discourse-cdn.com/flex001/user_avatar/community.ultralytics.com/toxite/32/123_2.png) [@Toxite](https://community.ultralytics.com/u/Toxite)\ **Post date:** [September 3, 2025, 8:51am UTC](https://community.ultralytics.com/t/how-to-run-object-detection-inference-with-a-yoloe-segmentation-model/1436/4 "2025-09-03T08:51:19Z")
You’re using `set_classes()` incorrectly. > **[YOLOE (Real-Time Seeing Anything)](https://docs.ultralytics.com/models/yoloe/#predict-usage)** > > YOLOE is a real-time open-vocabulary detection and segmentation model that extends YOLO with text, image, or internal vocabulary prompts, enabling detection of any object class with state-of-the-art zero-shot performance. ---
**Author:** ![Kallinteris-Andreas](https://sea1.discourse-cdn.com/flex001/user_avatar/community.ultralytics.com/kallinteris-andreas/32/838_2.png) [@Kallinteris-Andreas](https://community.ultralytics.com/u/Kallinteris-Andreas)\ **Post date:** [September 14, 2025, 1:37pm UTC](https://community.ultralytics.com/t/how-to-run-object-detection-inference-with-a-yoloe-segmentation-model/1436/5 "2025-09-14T13:37:15Z")
that is a perfectly valid way of using `YOLOE.set_classes`, but even if the more verbose way of using the function is used (as shown in the documentation), it fails in the same way ```py from ultralytics import YOLO model = YOLO("yoloe-11l.yaml").load('panopticon_models/yoloe-11l-seg.pt') names = ['person'] model.set_classes(names, model.get_text_pe(names)) # this also fails model.set_classes(names) # this fails ``` ```sh $ py test.py Transferred 1108/1108 items from pretrained weights Traceback (most recent call last): File "/home/master-andreas/panopticon/test.py", line 5, in model.set_classes(names, model.get_text_pe(names)) # this also fails ^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/master-andreas/panopticon/test_env/lib/python3.12/site-packages/ultralytics/models/yolo/model.py", line 269, in get_text_pe return self.model.get_text_pe(texts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/master-andreas/panopticon/test_env/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 120, in decorate_context return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "/home/master-andreas/panopticon/test_env/lib/python3.12/site-packages/ultralytics/nn/tasks.py", line 1038, in get_text_pe assert not self.training ^^^^^^^^^^^^^^^^^ AssertionError ``` ---
**Author:** ![Toxite](https://sea1.discourse-cdn.com/flex001/user_avatar/community.ultralytics.com/toxite/32/123_2.png) [@Toxite](https://community.ultralytics.com/u/Toxite)\ **Post date:** [September 14, 2025, 2:10pm UTC](https://community.ultralytics.com/t/how-to-run-object-detection-inference-with-a-yoloe-segmentation-model/1436/6 "2025-09-14T14:10:55Z")
Seems like your transferring of the weights is causing the issue. You can do `model.eval()` before `set_classes()` ---
**Author:** ![Kallinteris-Andreas](https://sea1.discourse-cdn.com/flex001/user_avatar/community.ultralytics.com/kallinteris-andreas/32/838_2.png) [@Kallinteris-Andreas](https://community.ultralytics.com/u/Kallinteris-Andreas)\ **Post date:** [September 14, 2025, 2:32pm UTC](https://community.ultralytics.com/t/how-to-run-object-detection-inference-with-a-yoloe-segmentation-model/1436/7 "2025-09-14T14:32:28Z")
It works thanks ```py from ultralytics import YOLO model = YOLO("yoloe-11s.yaml").load('panopticon_models/yoloe-11s-seg.pt') model.eval() names = ['person'] model.set_classes(names, model.get_text_pe(names)) # this works model.set_classes(names) # this also works ``` What does `YOLOE.eval()` do, I can not seem to find any details on the documentation, (I can only find the `val()` method, which does something different) ---
**Author:** ![BurhanQ](https://sea1.discourse-cdn.com/flex001/user_avatar/community.ultralytics.com/burhanq/32/7_2.png) [@BurhanQ](https://community.ultralytics.com/u/BurhanQ)\ **Post date:** [September 14, 2025, 2:36pm UTC](https://community.ultralytics.com/t/how-to-run-object-detection-inference-with-a-yoloe-segmentation-model/1436/8 "2025-09-14T14:36:16Z")
That is because it’s not an Ultralytics specific method, it’s inherited from the PyTorch `Module` class and you can check those docs here > **[Module — PyTorch 2.8 documentation](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module.eval)**