"This notebook was written by Ultralytics LLC, and is freely available for redistribution under the [GPL-3.0 license](https://choosealicense.com/licenses/gpl-3.0/). \n",
"For more information please visit https://github.com/ultralytics/yolov5 and https://www.ultralytics.com."
"This is the **official YOLOv5 🚀 notebook** authored by **Ultralytics**, and is freely available for redistribution under the [GPL-3.0 license](https://choosealicense.com/licenses/gpl-3.0/). \n",
"For more information please visit https://github.com/ultralytics/yolov5 and https://www.ultralytics.com. Thank you!"
]
},
{
...
...
@@ -643,7 +643,7 @@
},
"source": [
"# 2. Test\n",
"Test a model on [COCO](https://cocodataset.org/#home) val or test-dev dataset to evaluate trained accuracy. Models are downloaded automatically from the [latest YOLOv5 release](https://github.com/ultralytics/yolov5/releases). To show results by class use the `--verbose` flag. Note that `pycocotools` metrics may be 1-2% better than the equivalent repo metrics, as is visible below, due to slight differences in mAP computation."
"Test a model's accuracy on [COCO](https://cocodataset.org/#home) val or test-dev datasets. Models are downloaded automatically from the [latest YOLOv5 release](https://github.com/ultralytics/yolov5/releases). To show results by class use the `--verbose` flag. Note that `pycocotools` metrics may be ~1% better than the equivalent repo metrics, as is visible below, due to slight differences in mAP computation."
