Open mck0517 opened 4 years ago
I want to train only 6 classes (person, bicycle, car, motorbike, bus, truck) in the coco dataset.
The coco.names file has been modified as follows. person bicycle car motorbike bus truck
The coco.data file was modified as follows. classes= 6 train = /home/ckmoon/work_object_detection/darknet/scripts/coco/trainvalno5k.txt valid = /home/ckmoon/work_object_detection/darknet/scripts/testdev2017.txt names = /home/ckmoon/work_object_detection/darknet/cfg/coco.names backup = backup eval=coco
After downloading csdarknet53-omega_final.weights, the file csdarknet53-omega.conv.105 was obtained.
The classes and filters of yolov4.cfg file were modified as follows for all three parts. [convolutional] filters=33 #(6+5)*3
[yolo] classes=6
You shoule change lables first to fit your custom dataset. For example, class "bus" has id = 5 in coco dataset, but you should change it to id = 4 in all labels of coco, because id of bus is 4 in your case.
I want to train only 6 classes (person, bicycle, car, motorbike, bus, truck) in the coco dataset.
The coco.names file has been modified as follows. person bicycle car motorbike bus truck
The coco.data file was modified as follows. classes= 6 train = /home/ckmoon/work_object_detection/darknet/scripts/coco/trainvalno5k.txt valid = /home/ckmoon/work_object_detection/darknet/scripts/testdev2017.txt names = /home/ckmoon/work_object_detection/darknet/cfg/coco.names backup = backup eval=coco
After downloading csdarknet53-omega_final.weights, the file csdarknet53-omega.conv.105 was obtained.
The classes and filters of yolov4.cfg file were modified as follows for all three parts. [convolutional] filters=33 #(6+5)*3
[yolo] classes=6