How to fine-tune on custom data?

[fcakyon]

Hello, how do I fine-tune one of your pretrained models with my custom data, is it similar to fine-tuning a detectron2 model?

[jhonygiraldo]

Since this repo is based on detectron2, I think you have to follow this tutorial: https://detectron2.readthedocs.io/tutorials/datasets.html

[jhonygiraldo]

I tried the tutorial of detectron2 with this repository and the model cfg.merge_from_file("configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml") and it works.

However when I try with cfg.merge_from_file("configs/COCO-InstanceSegmentation/mask_cascade_rcnn_ResNeSt_200_FPN_dcn_syncBN_all_tricks_3x.yaml") (that is the contribution of this work) it does not work and I get the following error message, and I am not sure what is the reason:

ERROR [07/16 08:35:35 d2.engine.train_loop]: Exception during training:
Traceback (most recent call last):
File "/content/detectron2_repo/detectron2/engine/train_loop.py", line 132, in train
self.run_step()
File "/content/detectron2_repo/detectron2/engine/train_loop.py", line 209, in run_step
data = next(self._data_loader_iter)
File "/content/detectron2_repo/detectron2/data/common.py", line 140, in iter
for d in self.dataset:
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 345, in next
data = self._next_data()
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 856, in _next_data
return self._process_data(data)
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 881, in _process_data
data.reraise()
File "/usr/local/lib/python3.6/dist-packages/torch/_utils.py", line 395, in reraise
raise self.exc_type(msg)
NotImplementedError: Caught NotImplementedError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop
data = fetcher.fetch(index)
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/content/detectron2_repo/detectron2/data/common.py", line 41, in getitem
data = self._map_func(self._dataset[cur_idx])
File "/content/detectron2_repo/detectron2/utils/serialize.py", line 23, in call
return self._obj(*args, **kwargs)
File "/content/detectron2_repo/detectron2/data/dataset_mapper.py", line 138, in call
instances.gt_boxes = instances.gt_masks.get_bounding_boxes()
File "/content/detectron2_repo/detectron2/structures/masks.py", line 203, in get_bounding_boxes
raise NotImplementedError
NotImplementedError

[07/16 08:35:35 d2.engine.hooks]: Total training time: 0:00:00 (0:00:00 on hooks)

NotImplementedError Traceback (most recent call last)
in ()
20 trainer = DefaultTrainer(cfg)
21 trainer.resume_or_load(resume=False)
---> 22 trainer.train()

7 frames
/usr/local/lib/python3.6/dist-packages/torch/_utils.py in reraise(self)
393 # (https://bugs.python.org/issue2651), so we work around it.
394 msg = KeyErrorMessage(msg)
--> 395 raise self.exc_type(msg)

NotImplementedError: Caught NotImplementedError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop
data = fetcher.fetch(index)
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/content/detectron2_repo/detectron2/data/common.py", line 41, in getitem
data = self._map_func(self._dataset[cur_idx])
File "/content/detectron2_repo/detectron2/utils/serialize.py", line 23, in call
return self._obj(*args, **kwargs)
File "/content/detectron2_repo/detectron2/data/dataset_mapper.py", line 138, in call
instances.gt_boxes = instances.gt_masks.get_bounding_boxes()
File "/content/detectron2_repo/detectron2/structures/masks.py", line 203, in get_bounding_boxes
raise NotImplementedError
NotImplementedError

[chongruo]

We didn't modify the dataloder

[jhonygiraldo]

It is a problem of memory, I tried with "mask_cascade_rcnn_ResNeSt_50_FPN_syncBN_1x" and it worked. I guess "mask_cascade_rcnn_ResNeSt_200_FPN_dcn_syncBN_all_tricks_3x" is a heavy model and it did not fit in my machine. As I said before, to train in custom data you just have to follow the detectron2 tutorial https://detectron2.readthedocs.io/tutorials/datasets.html. @chongruo I have a code in colab, let me know if you want I can share it with you. Regards.

[jaideep11061982]

@jhonygiraldo could you share one..

[jaideep11061982]

I no where find any raise statement throwing NotImplementedError ,in latest version they do have such