From 1887f0d21984483a377d9c3adafd57594e107d76 Mon Sep 17 00:00:00 2001
From: Ultralytics Assistant
<135830346+UltralyticsAssistant@users.noreply.github.com>
Date: Thu, 12 Sep 2024 18:46:11 +0200
Subject: [PATCH] Delete greetings.yml
---
.github/workflows/greetings.yml | 65 ---------------------------------
1 file changed, 65 deletions(-)
delete mode 100644 .github/workflows/greetings.yml
diff --git a/.github/workflows/greetings.yml b/.github/workflows/greetings.yml
deleted file mode 100644
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-# Ultralytics YOLOv3 🚀, AGPL-3.0 license
-
-name: Greetings
-
-on:
- pull_request_target:
- types: [opened]
- issues:
- types: [opened]
-
-jobs:
- greeting:
- runs-on: ubuntu-latest
- steps:
- - uses: actions/first-interaction@v1
- with:
- repo-token: ${{ secrets.GITHUB_TOKEN }}
- pr-message: |
- 👋 Hello @${{ github.actor }}, thank you for submitting a YOLOv3 🚀 PR! To allow your work to be integrated as seamlessly as possible, we advise you to:
-
- - ✅ Verify your PR is **up-to-date** with `ultralytics/yolov3` `master` branch. If your PR is behind you can update your code by clicking the 'Update branch' button or by running `git pull` and `git merge master` locally.
- - ✅ Verify all YOLOv3 Continuous Integration (CI) **checks are passing**.
- - ✅ Reduce changes to the absolute **minimum** required for your bug fix or feature addition. _"It is not daily increase but daily decrease, hack away the unessential. The closer to the source, the less wastage there is."_ — Bruce Lee
-
- issue-message: |
- 👋 Hello @${{ github.actor }}, thank you for your interest in YOLOv3 🚀! Please visit our ⭐️ [Tutorials](https://docs.ultralytics.com/yolov5/) to get started, where you can find quickstart guides for simple tasks like [Custom Data Training](https://docs.ultralytics.com/yolov5/tutorials/train_custom_data/) all the way to advanced concepts like [Hyperparameter Evolution](https://docs.ultralytics.com/yolov5/tutorials/hyperparameter_evolution/).
-
- If this is a 🐛 Bug Report, please provide a **minimum reproducible example** to help us debug it.
-
- If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our [Tips for Best Training Results](https://docs.ultralytics.com/guides/model-training-tips//).
-
- ## Requirements
-
- [**Python>=3.7.0**](https://www.python.org/) with all [requirements.txt](https://github.com/ultralytics/yolov3/blob/master/requirements.txt) installed including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). To get started:
- ```bash
- git clone https://github.com/ultralytics/yolov3 # clone
- cd yolov3
- pip install -r requirements.txt # install
- ```
-
- ## Environments
-
- YOLOv3 may be run in any of the following up-to-date verified environments (with all dependencies including [CUDA](https://developer.nvidia.com/cuda)/[CUDNN](https://developer.nvidia.com/cudnn), [Python](https://www.python.org/) and [PyTorch](https://pytorch.org/) preinstalled):
-
- - **Notebooks** with free GPU: 
- - **Google Cloud** Deep Learning VM. See [GCP Quickstart Guide](https://docs.ultralytics.com/yolov5/environments/google_cloud_quickstart_tutorial/)
- - **Amazon** Deep Learning AMI. See [AWS Quickstart Guide](https://docs.ultralytics.com/yolov5/environments/aws_quickstart_tutorial/)
- - **Docker Image**. See [Docker Quickstart Guide](https://docs.ultralytics.com/yolov5/environments/docker_image_quickstart_tutorial/) 
-
- ## Status
-
- 
-
- If this badge is green, all [YOLOv3 GitHub Actions](https://github.com/ultralytics/yolov3/actions) Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv3 [training](https://github.com/ultralytics/yolov5/blob/master/train.py), [validation](https://github.com/ultralytics/yolov5/blob/master/val.py), [inference](https://github.com/ultralytics/yolov5/blob/master/detect.py), [export](https://github.com/ultralytics/yolov5/blob/master/export.py) and [benchmarks](https://github.com/ultralytics/yolov5/blob/master/benchmarks.py) on macOS, Windows, and Ubuntu every 24 hours and on every commit.
-
- ## Introducing YOLOv8 🚀
-
- We're excited to announce the launch of our latest state-of-the-art (SOTA) object detection model for 2023 - [YOLOv8](https://github.com/ultralytics/ultralytics) 🚀!
-
- Designed to be fast, accurate, and easy to use, YOLOv8 is an ideal choice for a wide range of object detection, image segmentation and image classification tasks. With YOLOv8, you'll be able to quickly and accurately detect objects in real-time, streamline your workflows, and achieve new levels of accuracy in your projects.
-
- Check out our [YOLOv8 Docs](https://docs.ultralytics.com/) for details and get started with:
- ```bash
- pip install ultralytics
- ```