ImportError: cannot import name 'DetectMultiBackend' .

[manish33scss]

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• I have searched the YOLOv5 issues and found no similar bug report.

YOLOv5 Component

No response

Bug

Sounds very trivial, but yolov5 fails to import DetectMultiBackend, and yes I cross checked, its present in the common.py file. exactly here, "from models.common import DetectMultiBackend".

Environment

No response

Minimal Reproducible Example

No response

Additional

No response

Are you willing to submit a PR?

• Yes I'd like to help by submitting a PR!

[github-actions]

👋 Hello @manish33scss, 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.

If this is a 🐛 Bug Report, please provide screenshots and minimum viable code to reproduce your issue, otherwise we can not help you.

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Requirements

Python>=3.6.0 with all requirements.txt installed including PyTorch>=1.7. To get started:

$ git clone https://github.com/ultralytics/yolov5
$ cd yolov5
$ pip install -r requirements.txt

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• Google Colab and Kaggle notebooks with free GPU:
• Google Cloud Deep Learning VM. See GCP Quickstart Guide
• Amazon Deep Learning AMI. See AWS Quickstart Guide
• Docker Image. See Docker Quickstart Guide

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[glenn-jocher]

@manish33scss your code or models may be out of date. To update your code (new models download automatically on first use):

• 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

[manish33scss]

@manish33scss your code or models may be out of date. To update your code (new models download automatically on first use):

• 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

No, I've just downloaded this, it's working fine with colab, but not in my pc, it says, can't import detectmultibackend. Thing is previous version was working fine, where we used attempt_load().

[GriffinBoris]

@manish33scss @glenn-jocher I ran into a similar issue. If your project directory contains your main script and a models directory/package in the same directory level it tends to clash with torch when loading models and code from torch hub.

---

Failing Project Setup Example:

Project Structure:

project/
    main.py
    models/something.py

main.py

import torch
from PIL import Image
from models.something import Anything

if __name__ == '__main__':
	image = Image.open('car.jpg')
	model = torch.hub.load('ultralytics/yolov5', 'yolov5s')
	results = model(i)
	print(results.pandas().xyxy[0].to_dict('records'))

Result:

Produces ModuleNotFoundError: No module named 'models.common'

---

Fixed Project Setup Example:

To fix this either rename the models directory/package or nest it in a directory.

Working Project Setup Example #1:

Nesting the models package under some_package_name.

Project Structure:

project/
    main.py
    some_package_name/models/something.py

main.py

import torch
from PIL import Image
from some_package_name.models.something import Anything

if __name__ == '__main__':
	image = Image.open('car.jpg')
	model = torch.hub.load('ultralytics/yolov5', 'yolov5s')
	results = model(i)
	print(results.pandas().xyxy[0].to_dict('records'))

Working Project Setup Example #2:

Renaming the models package to things.

Project Structure:

project/
    main.py
    things/something.py

main.py

import torch
from PIL import Image
from things.something import Anything

if __name__ == '__main__':
	image = Image.open('car.jpg')
	model = torch.hub.load('ultralytics/yolov5', 'yolov5s')
	results = model(i)
	print(results.pandas().xyxy[0].to_dict('records'))

---

Hope this helps!

[glenn-jocher]

@GriffinBoris yes these are good tips! The import order also matters, so it might (should?) be possible to create YOLOv5 models first from PyTorch Hub and then import local packages afterward.

[GriffinBoris]

Roger that! I will give that a try as well!

[Rijulsin]

@GriffinBoris yes these are good tips! The import order also matters, so it might (should?) be possible to create YOLOv5 models first from PyTorch Hub and then import local packages afterward.

Hi Glenn, did this work for you?

[glenn-jocher]

@Rijulsin a PyTorch maintainer suggested this in a separate issue.

[github-actions]

👋 Hello, this issue has been automatically marked as stale because it has not had recent activity. Please note it will be closed if no further activity occurs.

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