I would like to fine-tune a YOLOv4 pre-trained model on a new dataset that has only 1 class I would like YOLOv4 to be able to detect, which is ambulance vehicle.
The first step is to find a pre-trained model with weights based on the darknet framework:
https://github.com/AlexeyAB/darknet#pre-trained-models
Second, fine-tune the pre-trained model in the link above on the new dataset that has only one class. But I am not sure if I can do that on the darknet, please. In PyTorch, it's not difficult, but I would like to see if I can fine-tune a pre-trained model in the darknet framework.
Third, the pre-trained model in the darknet detect ambulance vehicle as a vehicle, but I would like to have a special class only for ambulance vehicle. I have a dataset of ambulance vehicles, so I have in the text file (classes.txt) only 1 class, which is emergency along with the txt file for bounding boxes of the ambulance vehicles. So do you think I should fine-tune the pre-trained YOLOv4 model on 1 class or I should still have another label for vehicles although I don't want to do that as the pre-trained YOLOv4 already recognizes a vehicle?
