Closed RainbowSun11Q2H closed 1 year ago
See #23 for fine-tune details. You can ignore pretrained checkpoints if you want to train DINO on your custom datasets from scratch.
See #23 for fine-tune details. You can ignore pretrained checkpoints if you want to train DINO on your custom datasets from scratch.
I have gone through #23 and it was all I needed, everything worked fine.
Finally had the training own dataset working. The link of #23 seems not correct. I am not sure how it was working as setting dn_labelbook_size = number_class.
In my case, I have 3 classes. When I set dn_labelbook_size = 3
and num_classes = 3' in
DINO_4scale.py' , it didn't work. It threw out the following error message.
"""
C:\cb\pytorch_1000000000000\work\aten\src\ATen\native\cuda\IndexKernel.cu:91: block: [33,0,0], thread: [95,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds"
failed.
Traceback (most recent call last):
File "main.py", line 397, in 0
might be assigned to the background by default in DETR. Now it is working.
@SlongLiu, @SuperHenry2333 Maybe you guys can think about adding more details about how to train custom datasets. This will help more people try the DINO. By the way, I have reviewed three of your papers and all of them are very beautiful. This is why I finally came to DINO and tried it on my own dataset to see if it can beat others. However, it took me quite a while to make the training work.
Thanks for pointing out the problem. We will correct them and update a manual for custom training later.
Thanks for your excellent work.
How can I try the model on my own dataset? I just change the num_classes in coco.py and the code can't go on. If you have a tutorial on how to train the custom dataset, it should be great.
Thanks for your time.