From 4d8d84b0ea7147aca64e7c38ce1bdb5fbb9c5a53 Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Wed, 3 Aug 2022 12:49:02 +0200 Subject: [PATCH] Created using Colaboratory --- tutorial.ipynb | 17 +++++------------ 1 file changed, 5 insertions(+), 12 deletions(-) diff --git a/tutorial.ipynb b/tutorial.ipynb index 83be103..2aaa93b 100644 --- a/tutorial.ipynb +++ b/tutorial.ipynb @@ -686,6 +686,8 @@ "- **Training Results** are saved to `runs/train/` with incrementing run directories, i.e. `runs/train/exp2`, `runs/train/exp3` etc.\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 🌟 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", @@ -935,20 +937,11 @@ "source": [ "## Local Logging\n", "\n", - "All results are logged by default to `runs/train`, with a new experiment directory created for each new training as `runs/train/exp2`, `runs/train/exp3`, etc. View train and val statistics, mosaics, labels, predictions and augmentations, as well as metrics and charts including Precision-Recall curves and Confusion Matrices. \n", + "Training results are automatically logged with [Tensorboard](https://www.tensorflow.org/tensorboard) and [CSV](https://github.com/ultralytics/yolov5/pull/4148) loggers to `runs/train`, with a new experiment directory created for each new training as `runs/train/exp2`, `runs/train/exp3`, etc.\n", "\n", - "A **Mosaic Dataloader** is used for training (shown in train*.jpg images), which combines 4 images into 1 mosaic during training.\n", + "This directory contains train and val statistics, mosaics, labels, predictions and augmentated mosaics, as well as metrics and charts including precision-recall (PR) curves and confusion matrices. \n", "\n", - "\"Local\n", - "\n", - "Training results are automatically logged to [Tensorboard](https://www.tensorflow.org/tensorboard) and [CSV](https://github.com/ultralytics/yolov5/pull/4148) as `results.csv`, which is plotted as `results.png` (below) after training completes. You can also plot any `results.csv` file manually:\n", - "\n", - "```python\n", - "from utils.plots import plot_results \n", - "plot_results('path/to/results.csv') # plot 'results.csv' as 'results.png'\n", - "```\n", - "\n", - "\"COCO128" + "\"Local\n" ] }, {