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  1. tutorial.ipynb +16 -6
tutorial.ipynb CHANGED
@@ -896,13 +896,26 @@
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  "id": "bOy5KI2ncnWd"
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  },
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  "source": [
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- "# Start tensorboard (optional)\n",
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  "%load_ext tensorboard\n",
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  "%tensorboard --logdir runs"
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  ],
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  "execution_count": null,
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  "outputs": []
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  },
 
 
 
 
 
 
 
 
 
 
 
 
 
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  {
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  "cell_type": "code",
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  "metadata": {
@@ -1013,12 +1026,9 @@
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  "source": [
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  "## Weights & Biases Logging 🌟 NEW\n",
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  "\n",
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- "[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",
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- "```bash\n",
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- "$ pip install wandb\n",
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- "```\n",
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  "\n",
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- "During training you will see live updates at [https://www.wandb.com/](https://www.wandb.com/), and you can create and share detailed [Reports](https://wandb.ai/glenn-jocher/yolov5_tutorial/reports/YOLOv5-COCO128-Tutorial-Results--VmlldzozMDI5OTY) of your results. For more information see the [YOLOv5 Weights & Biases Tutorial](https://github.com/ultralytics/yolov5/issues/1289). \n",
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  "\n",
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  "<img src=\"https://user-images.githubusercontent.com/26833433/98184457-bd3da580-1f0a-11eb-8461-95d908a71893.jpg\" width=\"800\">"
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  ]
 
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  "id": "bOy5KI2ncnWd"
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  },
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  "source": [
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+ "# Tensorboard (optional)\n",
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  "%load_ext tensorboard\n",
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  "%tensorboard --logdir runs"
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  ],
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  "execution_count": null,
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  "outputs": []
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  },
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+ {
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+ "cell_type": "code",
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+ "metadata": {
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+ "id": "2fLAV42oNb7M"
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+ },
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+ "source": [
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+ "# Weights & Biases (optional)\n",
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+ "%pip install -q wandb \n",
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+ "!wandb login # use 'wandb disabled' or 'wandb enabled' to disable or enable"
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+ ],
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+ "execution_count": null,
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+ "outputs": []
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+ },
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  {
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  "cell_type": "code",
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  "metadata": {
 
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  "source": [
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  "## Weights & Biases Logging 🌟 NEW\n",
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  "\n",
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+ "[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 `pip install wandb`, and then train normally (you will be guided through setup on first use). \n",
 
 
 
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  "\n",
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+ "During training you will see live updates at [https://wandb.ai/home](https://wandb.ai/home), and you can create and share detailed [Reports](https://wandb.ai/glenn-jocher/yolov5_tutorial/reports/YOLOv5-COCO128-Tutorial-Results--VmlldzozMDI5OTY) of your results. For more information see the [YOLOv5 Weights & Biases Tutorial](https://github.com/ultralytics/yolov5/issues/1289). \n",
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  "\n",
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  "<img src=\"https://user-images.githubusercontent.com/26833433/98184457-bd3da580-1f0a-11eb-8461-95d908a71893.jpg\" width=\"800\">"
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  ]