RuntimeError: invalid argument 2: size '[16 x 3 x 15 x 13 x 13]' is invalid for input with 689520 elements at /pytorch/aten/src/TH/THStorage.cpp:84 about yolov3

[glenn-jocher]

Please adjust the model accordingly for your dataset. The repository works for any object detection dataset, but you need to modify certain areas which are COCO-specific currently. The full list of directions is on this comment #6 (comment)

[sporterman]

@glenn-jocher Thanks! I've trained 68 epoches , finally the precision was 1, but recall was 0, did you met this trouble? need some advice.

[Electronicshelf]

I had a similar problem, the best thing to do is to adjust the last constitutional layer before the [yolo] of the yolov3.cfg or the .cfg file that contains your model.
please Note that there are 3 [yolo] sections. so you have to change the filter size to macth your model. for one class, start from 18 then adjust accordingly...

[glenn-jocher]

This tutorial explains how to train custom datasets, including updating the yolov3.cfg file for your class count.
https://github.com/ultralytics/yolov3/wiki/Example:-Train-Single-Class

[brlivsky]

@glenn-jocher @Electronicshelf @sporterman

Hey guys!
I had the same error while running train.py.

This tutorial explains how to train custom datasets, including updating the yolov3.cfg file for your class count.
https://github.com/ultralytics/yolov3/wiki/Example:-Train-Single-Class

I'm training the model on my custom dataset. I did follow the below steps.

1. Converted the dataset into darknet format
2. Created train and test *.txt files
3. Create a new *.names file
4. Updated cfg/coco.data
5. Updated *.cfg file

I have got a doubt whether I should modify the classes=80 in the 3 [yolo] sections in yolov3.cfg file. I've also read this comment, but I don't know how to implement steps 4, 5, 6 in the above comment.

UPDATE
I have modified classes=80 with 3(as I've 3 classes) and it has worked out for me!

[glenn-jocher]

@Vysakhr great to hear its working for you now. We have updated the tutorials now to clearly state that the class counts need to updated in each YOLO layer in the *.cfg file, i.e. in your case from classes=80 to classes=3.