lightly-ai / NvidiaTLTActiveLearning
In this tutorial, we will show you how you can do active learning for object detection with the Nvidia Transfer Learning Toolkit. The task will be object detection of apples in a plantation setting. Accurately detecting and counting fruits is a critical step towards automating harvesting processes. Furthermore, fruit counting can be used to project expected yield and hence to detect low yield years early on.
To set up lightly for active learning, head to the Lightly Platform and create a free account by logging in. Make sure to get your token by clicking on your e-mail address and selecting "Preferences". You will need the token for the rest of this tutorial.
To install the Nvidia Transfer Learning Toolkit, follow these instructions. If you want to use custom scripts for training and inference, you can skip this part.
To make all relevant directories accessible to the Nvidia TLT, you need to mount the current working directory and the yolo_v4/specs directory to the Nvidia TLT docker. You can do so with the provided mount.py script.
