diff --git a/.github/workflows/greetings.yml b/.github/workflows/greetings.yml index 42a2463585a8..a4eca919a5b3 100644 --- a/.github/workflows/greetings.yml +++ b/.github/workflows/greetings.yml @@ -23,7 +23,7 @@ jobs: - โœ… 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."_ โ€” Bruce Lee issue-message: | - ๐Ÿ‘‹ Hello @${{ github.actor }}, thank you for your interest in YOLOv5 ๐Ÿš€! Please visit our โญ๏ธ [Tutorials](https://github.com/ultralytics/yolov5/wiki#tutorials) to get started, where you can find quickstart guides for simple tasks like [Custom Data Training](https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data) all the way to advanced concepts like [Hyperparameter Evolution](https://github.com/ultralytics/yolov5/issues/607). + ๐Ÿ‘‹ Hello @${{ github.actor }}, thank you for your interest in YOLOv5 ๐Ÿš€! Please visit our โญ๏ธ [Tutorials](https://docs.ultralytics.com/yolov5/#tutorials) to get started, where you can find quickstart guides for simple tasks like [Custom Data Training](https://docs.ultralytics.com/yolov5/train_custom_data/) all the way to advanced concepts like [Hyperparameter Evolution](https://docs.ultralytics.com/yolov5/hyp_evolution/). If this is a ๐Ÿ› Bug Report, please provide a **minimum reproducible example** to help us debug it. diff --git a/README.md b/README.md index cb1540737a14..9c991abf0179 100644 --- a/README.md +++ b/README.md @@ -165,7 +165,7 @@ python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml - - [Hyperparameter Evolution](https://docs.ultralytics.com/yolov5/hyp_evolution) - [Transfer Learning with Frozen Layers](https://docs.ultralytics.com/yolov5/transfer_learn_frozen) - [Architecture Summary](https://docs.ultralytics.com/yolov5/architecture) ๐ŸŒŸ NEW -- [Roboflow for Datasets, Labeling, and Active Learning](https://docs.ultralytics.com/yolov5/roboflow) +- [Roboflow for Datasets](https://docs.ultralytics.com/yolov5/roboflow) - [ClearML Logging](https://docs.ultralytics.com/yolov5/clearml) ๐ŸŒŸ NEW - [YOLOv5 with Neural Magic's Deepsparse](https://docs.ultralytics.com/yolov5/neural_magic) ๐ŸŒŸ NEW - [Comet Logging](https://docs.ultralytics.com/yolov5/comet) ๐ŸŒŸ NEW diff --git a/README.zh-CN.md b/README.zh-CN.md index 9a819598be7e..761e61634dfb 100644 --- a/README.zh-CN.md +++ b/README.zh-CN.md @@ -159,7 +159,7 @@ python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml - - [่ถ…ๅ‚ๆ•ฐ่ฟ›ๅŒ–](https://docs.ultralytics.com/yolov5/hyp_evolution) - [ๅ†ป็ป“ๅฑ‚็š„่ฟ็งปๅญฆไน ](https://docs.ultralytics.com/yolov5/transfer_learn_frozen) - [ๆžถๆž„ๆฆ‚่ฟฐ](https://docs.ultralytics.com/yolov5/architecture) ๐ŸŒŸ ๆ–ฐ -- [Roboflow ็”จไบŽๆ•ฐๆฎ้›†ใ€ๆ ‡็ญพๅ’ŒไธปๅŠจๅญฆไน ](https://docs.ultralytics.com/yolov5/roboflow) +- [Roboflow](https://docs.ultralytics.com/yolov5/roboflow) - [ClearML ๆ—ฅๅฟ—่ฎฐๅฝ•](https://docs.ultralytics.com/yolov5/clearml) ๐ŸŒŸ ๆ–ฐ - [YOLOv5 ไธŽ Neural Magic ็š„ Deepsparse](https://docs.ultralytics.com/yolov5/neural_magic) ๐ŸŒŸ ๆ–ฐ - [Comet ๆ—ฅๅฟ—่ฎฐๅฝ•](https://docs.ultralytics.com/yolov5/comet) ๐ŸŒŸ ๆ–ฐ diff --git a/requirements.txt b/requirements.txt index 11cb9aaaf99e..fc7193604607 100644 --- a/requirements.txt +++ b/requirements.txt @@ -46,5 +46,4 @@ setuptools>=65.5.1 # Snyk vulnerability fix # mss # screenshots # albumentations>=1.0.3 # pycocotools>=2.0.6 # COCO mAP -# roboflow # ultralytics # HUB https://hub.ultralytics.com diff --git a/tutorial.ipynb b/tutorial.ipynb index 32af68b57945..0d1f387cf040 100644 --- a/tutorial.ipynb +++ b/tutorial.ipynb @@ -632,19 +632,13 @@ "automatically from the [latest YOLOv5 release](https://github.com/ultralytics/yolov5/releases)\n", "- **[Datasets](https://github.com/ultralytics/yolov5/tree/master/data)** available for autodownload include: [COCO](https://github.com/ultralytics/yolov5/blob/master/data/coco.yaml), [COCO128](https://github.com/ultralytics/yolov5/blob/master/data/coco128.yaml), [VOC](https://github.com/ultralytics/yolov5/blob/master/data/VOC.yaml), [Argoverse](https://github.com/ultralytics/yolov5/blob/master/data/Argoverse.yaml), [VisDrone](https://github.com/ultralytics/yolov5/blob/master/data/VisDrone.yaml), [GlobalWheat](https://github.com/ultralytics/yolov5/blob/master/data/GlobalWheat2020.yaml), [xView](https://github.com/ultralytics/yolov5/blob/master/data/xView.yaml), [Objects365](https://github.com/ultralytics/yolov5/blob/master/data/Objects365.yaml), [SKU-110K](https://github.com/ultralytics/yolov5/blob/master/data/SKU-110K.yaml).\n", "- **Training Results** are saved to `runs/train/` with incrementing run directories, i.e. `runs/train/exp2`, `runs/train/exp3` etc.\n", - "

\n", + "
\n", "\n", "A **Mosaic Dataloader** is used for training which combines 4 images into 1 mosaic.\n", "\n", - "## Train on Custom Data with Roboflow ๐ŸŒŸ NEW\n", - "\n", - "[Roboflow](https://roboflow.com/?ref=ultralytics) enables you to easily **organize, label, and prepare** a high quality dataset with your own custom data. Roboflow also makes it easy to establish an active learning pipeline, collaborate with your team on dataset improvement, and integrate directly into your model building workflow with the `roboflow` pip package.\n", - "\n", - "- Custom Training Example: [https://blog.roboflow.com/how-to-train-yolov5-on-a-custom-dataset/](https://blog.roboflow.com/how-to-train-yolov5-on-a-custom-dataset/?ref=ultralytics)\n", - "- Custom Training Notebook: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/roboflow-ai/yolov5-custom-training-tutorial/blob/main/yolov5-custom-training.ipynb)\n", - "
\n", + "## Label a dataset on Roboflow (optional)\n", "\n", - "

Label images lightning fast (including with model-assisted labeling)" + "[Roboflow](https://roboflow.com/?ref=ultralytics) enables you to easily **organize, label, and prepare** a high quality dataset with your own custom data. Roboflow also makes it easy to establish an active learning pipeline, collaborate with your team on dataset improvement, and integrate directly into your model building workflow with the `roboflow` pip package." ] }, {