Open W-hary opened 1 year ago
This is indirectly because loss_by_feat()
isn't implemented for the instance segmentation head. That is, instance segmentation is only supported currently for inference. I don't think it is that difficult to implement this function (you can look at the YOLOv5 detection vs. instance seg versions, and then the RTMDet detection version) but I haven't tried to get it working yet.
If I get it working I'll submit a PR, but I'm not sure when that will be.
Related to #649, #853
Hi, I would like to ask if this problem has been solved
Same question. Look forward to seeing the fast training for Rtmdet-ins
No update on this?
Am I correct in assuming rtmdet-ins on mmdetection is the same as on mmyolo anyways but just slower training?
One difference I found is mmdeploy only offers deployment to Core ML with segmentation through mmseg.
Does mmdetection support instance segmentation training with rtmdet? Or just inference like mmyolo? -CollinOn Feb 6, 2024, at 6:19 PM, jlok @.***> wrote: No update on this? Am I correct in assuming rtmdet-ins on mmdetection is the same as on mmyolo anyways but just slower training?
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Mmdet supports training and inference on rtmdet-ins
Mmdet supports training and inference on rtmdet-ins
can you provide more information about configuration of mmdet, mmcv, and related mmyolo version ? Thank you
Prerequisite
🐞 Describe the bug
Install and successfully run the demo test according to ‘15_minutes_instance_segmentation.md‘. An error occurred when training the balloon data set using ‘rtmdet-ins_s_syncbn_fast_8xb32-300e_coco.py’
python tools/train.py configs/rtmdet/rtmdet-ins_s_syncbn_fast_8xb32-300e_coco.py
Traceback (most recent call last): File "tools/train.py", line 123, in
main()
File "tools/train.py", line 119, in main
runner.train()
File "/root/miniconda3/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1745, in train
model = self.train_loop.run() # type: ignore
File "/root/miniconda3/lib/python3.8/site-packages/mmengine/runner/loops.py", line 96, in run
self.run_epoch()
File "/root/miniconda3/lib/python3.8/site-packages/mmengine/runner/loops.py", line 112, in run_epoch
self.run_iter(idx, data_batch)
File "/root/miniconda3/lib/python3.8/site-packages/mmengine/runner/loops.py", line 128, in run_iter
outputs = self.runner.model.train_step(
File "/root/miniconda3/lib/python3.8/site-packages/mmengine/model/base_model/base_model.py", line 114, in train_step
losses = self._run_forward(data, mode='loss') # type: ignore
File "/root/miniconda3/lib/python3.8/site-packages/mmengine/model/base_model/base_model.py", line 340, in _run_forward
results = self(*data, mode=mode)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(input, *kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/mmdet/models/detectors/base.py", line 92, in forward
return self.loss(inputs, data_samples)
File "/root/miniconda3/lib/python3.8/site-packages/mmdet/models/detectors/single_stage.py", line 78, in loss
losses = self.bbox_head.loss(x, batch_data_samples)
File "/root/autodl-tmp/mmyolo/mmyolo/models/dense_heads/yolov5_head.py", line 470, in loss
losses = self.loss_by_feat(loss_inputs)
TypeError: loss_by_feat() takes from 5 to 6 positional arguments but 7 were given
Environment
PyTorch 1.11.0 Python 3.8(ubuntu20.04) Cuda 11.3
Additional information
No response