Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

could you provide method to call yolov5 model in C/C++??? #2804

Closed
158545614 opened this issue Apr 16, 2021 · 2 comments
Closed

could you provide method to call yolov5 model in C/C++??? #2804

158545614 opened this issue Apr 16, 2021 · 2 comments
Labels
enhancement New feature or request

Comments

@158545614
Copy link

🚀 Feature

Motivation

Pitch

Alternatives

Additional context

@158545614 158545614 added the enhancement New feature or request label Apr 16, 2021
@github-actions
Copy link
Contributor

github-actions bot commented Apr 16, 2021

👋 Hello @158545614, 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.

If this is a custom training ❓ Question, please provide as much information as possible, including dataset images, training logs, screenshots, and a public link to online W&B logging if available.

For business inquiries or professional support requests please visit https://www.ultralytics.com or email Glenn Jocher at glenn.jocher@ultralytics.com.

Requirements

Python 3.8 or later with all requirements.txt dependencies installed, including torch>=1.7. To install run:

$ pip install -r requirements.txt

Environments

YOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):

Status

CI CPU testing

If this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training (train.py), testing (test.py), inference (detect.py) and export (export.py) on MacOS, Windows, and Ubuntu every 24 hours and on every commit.

@glenn-jocher
Copy link
Member

glenn-jocher commented Apr 16, 2021

@158545614 torchscript models are intended for use in C/C++ environments. See https://pytorch.org/tutorials/beginner/Intro_to_TorchScript_tutorial.html

To export models into torchscript format see ONNX and TorchScript Export tutorial below:

YOLOv5 Tutorials

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement New feature or request
Projects
None yet
Development

No branches or pull requests

2 participants