Update links and add disclaimer in YOLOv8 notebook.

roboflow · Oct 10, 2023 · 28abdd7 · 28abdd7
1 parent 190a817
commit 28abdd7
Showing 1 changed file with 6 additions and 3 deletions.
diff --git a/notebooks/how-to-track-and-count-vehicles-with-yolov8.ipynb b/notebooks/how-to-track-and-count-vehicles-with-yolov8.ipynb
@@ -18,10 +18,13 @@
         "\n",
         "Ultralytics YOLOv8 is the latest version of the YOLO (You Only Look Once) object detection and image segmentation model developed by Ultralytics. The YOLOv8 model is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and image segmentation tasks. It can be trained on large datasets and is capable of running on a variety of hardware platforms, from CPUs to GPUs.\n",
         "\n",
-        "This notebook uses legacy versions of ByteTrack and Supervision. To be up to date, use our revamped notebook.\n",
+        "## ⚠️ Disclaimer\n",
+        "\n",
+        "This notebook uses legacy versions of ByteTrack and Supervision. To be up to date, use our updated [notebook](https://colab.research.google.com/github/roboflow-ai/notebooks/blob/main/notebooks/how-to-track-and-count-vehicles-with-yolov8-and-supervison.ipynb).\n",
+        "\n",
         "## Accompanying Blog Post\n",
         "\n",
-        "We recommend that you follow along in this notebook while reading the blog post on how to train YOLOv8 Tracking and Counting, concurrently.\n",
+        "We recommend that you follow along in this notebook while reading the [blog post](https://blog.roboflow.com/yolov8-tracking-and-counting/) on how to train YOLOv8 Tracking and Counting, concurrently.\n",
         "\n",
         "## Pro Tip: Use GPU Acceleration\n",
         "\n",
@@ -688,4 +691,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}