Train multi classes object detector (YOLOv4)
i finally found the solution.
The problem was that OID dataset downloads images with one specific class, like person, car etc.
AS Louis Lac mentioned i must train my model on dataset with all relevant classes
I want to train my YOLOv4 detector on 5 classes [Person,Car,Motorcycle,Bus,Truck]. I used around 2000 images for training and 500 for validation.
The dataset I used is from OID or from COCO.
The main problem is that, when the training is over, the detector finds only one class in the image every time. For example, if it's a human in a car, it returns only the Car or the Person bounding box detection.
I saw that the .txt annotation on every image is only for one class.
It's difficult to annotate by myself 10.000 images.
All the tutorials usually detect only one class in the image.
Any ideas on how to train my model on all 5 classes?