model = torch.hub.load('ultralytics/yolov5', 'yolov5s-seg')

[mohamed-29]

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• I have searched the YOLOv5 issues and discussions and found no similar questions.

Question

is there yolov5 segmentation model ?

Additional

No response

[github-actions]

👋 Hello @mohamed-29, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.

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[glenn-jocher]

@mohamed-29 yes, segmentation models were recently introduced. You can load one with the code below, but they are not yet fully supported for PyTorch Hub inference, so I'd recommend using the usage examples in segment/predict.py:
https://github.com/ultralytics/yolov5/blob/master/segment/predict.py

import torch

model = torch.hub.load('ultralytics/yolov5', 'custom', 'yolov5s-seg.pt')

[mohamed-29]

KeyError Traceback (most recent call last)
Input In [11], in <cell line: 6>()
1 results = model(img)
3 #results.show()
4
5 # Results
----> 6 results.show()

File ~/.cache\torch\hub\ultralytics_yolov5_master\models\common.py:776, in Detections.show(self, labels)
775 def show(self, labels=True):
--> 776 self._run(show=True, labels=labels)

File ~/.cache\torch\hub\ultralytics_yolov5_master\models\common.py:737, in Detections._run(self, pprint, show, save, crop, render, labels, save_dir)
735 for c in pred[:, -1].unique():
736 n = (pred[:, -1] == c).sum() # detections per class
--> 737 s += f"{n} {self.names[int(c)]}{'s' * (n > 1)}, " # add to string
738 s = s.rstrip(', ')
739 if show or save or render or crop:

KeyError: 94

[glenn-jocher]

@mohamed-29 SegmentationModel and ClassificationModel types are not yet supported by YOLOv5 PyTorch Hub AutoShape models. I will add a warning to notify users.

[glenn-jocher]

@mohamed-29 good news 😃! Your original issue may now be improved ✅ in PR #9632. This PR adds a warning to users to notify them that SegmentationModels are not yet fully supported.

To receive this update:

• Git – git pull from within your yolov5/ directory or git clone https://github.com/ultralytics/yolov5 again
• PyTorch Hub – Force-reload model = torch.hub.load('ultralytics/yolov5', 'yolov5s', force_reload=True)
• Notebooks – View updated notebooks
• Docker – sudo docker pull ultralytics/yolov5:latest to update your image

Thank you for spotting this issue and informing us of the problem. Please let us know if this update resolves the issue for you, and feel free to inform us of any other issues you discover or feature requests that come to mind. Happy trainings with YOLOv5 🚀!

[rusvagzur]

Hi @glenn-jocher , do you have an estimation on when segmentation inference will be supported for pytorch hub? Thanks!

[glenn-jocher]

@rusvagzur no, I'm sorry. If you'd like to contribute a PR for this that would be great!

The fastest and easiest way to incorporate your ideas into the official codebase is to submit a Pull Request (PR) implementing your idea, and if applicable providing before and after profiling/inference/training results to help us understand the improvement your feature provides. This allows us to directly see the changes in the code and to understand how they affect workflows and performance.

Please see our ✅ Contributing Guide to get started.