integrations/mnn/

[giscus[bot]]

integrations/mnn/

Optimize YOLO11 models for mobile and embedded devices by exporting to MNN format.

https://docs.ultralytics.com/integrations/mnn/

[robert-hardman]

Hello
Error: NameError: name 'mnn_model' is not defined
ultralytics==8.3.34

[glenn-jocher]

It seems like there's a minor typo in your code. Ensure you are using model instead of mnn_model when calling the inference function. Here's a quick fix:

from ultralytics import YOLO

# Load the YOLO11 MNN model
model = YOLO("yolo11n.mnn")

# Run inference
results = model("https://ultralytics.com/images/bus.jpg")

This should resolve the NameError. If you need more help, please check the MNN documentation.

[UltralyticsAssistant]

👋 Hello, thank you for reaching out to Ultralytics 🚀! It looks like you're interested in optimizing YOLO11 models for mobile and embedded devices using the MNN format. For comprehensive guidance, please check out the MNN Integration Docs.

If this is a 🐛 Bug Report, we kindly request you to provide a minimum reproducible example to assist us in addressing the issue effectively.

If you're facing challenges related to custom training ❓, sharing dataset examples and training logs will be highly beneficial. Additionally, ensure that you are adhering to our Model Training Tips for optimal results.

Feel free to join our community for more discussions and support. For dynamic interactions, join us on Discord 🎧. If you prefer more detailed conversations, visit our Discourse. You can also explore our Subreddit for community knowledge sharing.

Upgrade

Please upgrade to the latest ultralytics package and include all requirements in a Python>=3.8 environment with PyTorch>=1.8 to ensure you are using the most up-to-date features:

pip install -U ultralytics

Environments

You can run YOLO in these verified environments, each pre-equipped with necessary dependencies including CUDA, Python, and PyTorch:

• Notebooks with free GPU:
• Google Cloud Deep Learning VM. Check the GCP Quickstart Guide
• Amazon Deep Learning AMI. See the AWS Quickstart Guide
• Docker Image. Our Docker Quickstart Guide offers a quick setup.

Status

A green badge indicates all Ultralytics CI tests are passing, confirming successful operation of all YOLO Modes and Tasks across various platforms.

Please note: This is an automated response and an Ultralytics engineer will get back to you soon to offer further assistance! 🛠️