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Update tutorial.ipynb

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Glenn Jocher 2020-11-11 16:15:20 +01:00 committed by GitHub
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tutorial.ipynb vendored
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@ -1012,7 +1012,7 @@
"source": [ "source": [
"## Weights & Biases Logging (🚀 NEW)\n", "## Weights & Biases Logging (🚀 NEW)\n",
"\n", "\n",
"[Weights & Biases](https://www.wandb.com/) (W&B) is now integrated with YOLOv5 for real-time visualization and cloud logging of training runs. This allows for better run comparison and introspection, as well improved visibility and collaboration for teams. To enable W&B logging install `wandb`, and then train normally (you will be guided setup on first use).\n", "[Weights & Biases](https://www.wandb.com/) (W&B) is now integrated with YOLOv5 for real-time visualization and cloud logging of training runs. This allows for better run comparison and introspection, as well improved visibility and collaboration for teams. To enable W&B logging install `wandb`, and then train normally (you will be guided through setup on first use).\n",
"```bash\n", "```bash\n",
"$ pip install wandb\n", "$ pip install wandb\n",
"```\n", "```\n",
@ -1030,7 +1030,7 @@
"source": [ "source": [
"## Local Logging\n", "## Local Logging\n",
"\n", "\n",
"All results are logged by default to `runs/train`, with a new experiment directory created for each new training as `runs/train/exp1`, `runs/train/exp2`, etc. View train and test jpgs to see mosaics, labels, predictions and augmentation effects. Note a **Mosaic Dataloader** is used for training (shown below), a new concept developed by Ultralytics and first featured in [YOLOv4](https://arxiv.org/abs/2004.10934)." "All results are logged by default to `runs/train`, with a new experiment directory created for each new training as `runs/train/exp0`, `runs/train/exp1`, etc. View train and test jpgs to see mosaics, labels, predictions and augmentation effects. Note a **Mosaic Dataloader** is used for training (shown below), a new concept developed by Ultralytics and first featured in [YOLOv4](https://arxiv.org/abs/2004.10934)."
] ]
}, },
{ {