In this video, we are going to implement custom object detection using yolov8 and Python. We will train custom object detection model using google colab.
We need to carry out object detection on custom dataset when have to fine tune an existing model on our own dataset for our own task. In this video, we will be using the pretrained yolov8m.pt model from ultralytics for our task. Yolo custom object detection is the state of the art approach for detecting objects in videos and images and fine tuning helps to better the accuracy of the model on custom tasks. In our case, we will be using the traffic sign dataset available on Kaggle.
Yolov8 Github: [ Ссылка ]
Yolov8 documentation: [ Ссылка ]
