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Update Train Custom Data wiki page #2187

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OvidijusParsiunas opened this issue Feb 12, 2021 · 2 comments
Closed

Update Train Custom Data wiki page #2187

OvidijusParsiunas opened this issue Feb 12, 2021 · 2 comments
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enhancement New feature or request Stale

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@OvidijusParsiunas
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OvidijusParsiunas commented Feb 12, 2021

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Hey, I'm a big fan of the yolov5 model and congratulations on reaching such a breakthrough!
I was reading the Train Custom Data wiki to familiarise myself with how to get the setup working and noticed you have included some labelling tool suggestions in the 2. Create Labels section. I have recently released a free computer vision based data labelling tool called MyVision which is starting to pick up popularity and was wondering if you could potentially include it in the list as it supports the YOLO format and more.
Website: https://myvision.ai/
Opensource repository location: https://github.com/OvidijusParsiunas/myvision

Thankyou very much and keep up the good work!

@OvidijusParsiunas OvidijusParsiunas added the enhancement New feature or request label Feb 12, 2021
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github-actions bot commented Feb 12, 2021

👋 Hello @OvidijusParsiunas, 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 [email protected].

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.

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This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

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