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setting NUM_CLASSES

See original GitHub issue

in the beginning i would like to give others some notice: even though you’ve install pytorch via anaconda with cudatoolkit. But still. it is just for the pytorch. not for detectron2. pls consider using cuda package locally or use a docker.

question 1: train_log_init.txt

I’ve found out you’ve noticed, that we should change MODEL.ROI_HEADS.NUM_CLASSES and MODEL.RETINANET.NUM_CLASSES. I’ve changed them in detectron2/config/defaults.py Or tried to add the params in all.sh via adding MODEL.ROI_HEADS.NUM_CLASSES 2, MODEL.FCOS.NUM_CLASSES 2, MODEL.RETINANET.NUM_CLASSES 2 for my 2 classes (background not included). but none of them helps… The error: AssertionError: A prediction has category_id=62, which is not available in the dataset. question 2: the training seems stop immediately. i’ve changed the MAX_ITER in yaml file, but it was not helped…

I think the both problems could be relevant, because the model is not trained for 2 classes. the log file is attached. many thanks for your help!

Issue Analytics

State:
Created 2 years ago
Comments:13 (6 by maintainers)

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1reaction

heiziecommented, Jun 6, 2021

Thanks for the beginning tips.

That’s strange. I have seen your log error. Could you remove the ‘,’ after 2 (which makes it a tuple but we need int) and directly try to modify this line?

hmm. it came something new. new errors… train_log_init.txt

[06/06 18:32:03 d2.data.common]: Serializing 561 elements to byte tensors and concatenating them all ...
[06/06 18:32:03 d2.data.common]: Serialized dataset takes 11.80 MiB
[06/06 18:32:03 d2.data.detection_utils]: TransformGens used in training: [ResizeShortestEdge(short_edge_length=(640, 672, 704, 736, 768, 800), max_size=1333, sample_style='choice'), RandomFlip()]
[06/06 18:32:03 d2.data.build]: Using training sampler TrainingSampler
[06/06 18:32:04 fvcore.common.checkpoint]: [Checkpointer] Loading from ./pretrained_models/BCNet_models/fcos_Res101.pth ...
[06/06 18:32:04 d2.engine.train_loop]: Starting training from iteration 0
[06/06 18:32:04 d2.engine.hooks]: Total training time: 0:00:00 (0:00:00 on hooks)
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WARNING [06/06 18:32:04 d2.data.datasets.coco]: 
Category ids in annotations are not in [1, #categories]! We'll apply a mapping for you.

[06/06 18:32:04 d2.data.datasets.coco]: Loaded 70 images in COCO format from ./datasets/coco/annotations/instances_val.json
[06/06 18:32:04 d2.data.build]: Distribution of instances among all 3 categories:
|   category   | #instances   |  category  | #instances   |  category  | #instances   |
|:------------:|:-------------|:----------:|:-------------|:----------:|:-------------|
| _background_ | 0            |   Cable    | 308          |  CableEnd  | 616          |
|              |              |            |              |            |              |
|    total     | 924          |            |              |            |              |
[06/06 18:32:04 d2.data.common]: Serializing 70 elements to byte tensors and concatenating them all ...
[06/06 18:32:04 d2.data.common]: Serialized dataset takes 0.31 MiB
[06/06 18:32:04 d2.evaluation.evaluator]: Start inference on 70 images
Traceback (most recent call last):
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/engine/train_loop.py", line 131, in train
    self.run_step()
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/engine/train_loop.py", line 211, in run_step
    loss_dict = self.model(data, self.iter, self.max_iter)
  File "/home/iwb/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 532, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/modeling/meta_arch/fcos.py", line 176, in forward
    centerness, gt_instances, batched_inputs, images, c_iter, max_iter
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/modeling/meta_arch/fcos.py", line 188, in _forward_train
    locations, box_cls, box_regression, centerness, gt_instances
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/modeling/meta_arch/loss_fcos.py", line 260, in __call__
    reduction="sum",
RuntimeError: CUDA error: device-side assert triggered
The above operation failed in interpreter.
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/fvcore-0.1.5.post20210604-py3.6.egg/fvcore/nn/focal_loss.py", line 34
    """
    p = torch.sigmoid(inputs)
    ce_loss = F.binary_cross_entropy_with_logits(inputs, targets, reduction="none")
              ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
    p_t = p * targets + (1 - p) * (1 - targets)
    loss = ce_loss * ((1 - p_t) ** gamma)
  File "/home/iwb/.local/lib/python3.6/site-packages/torch/nn/functional.py", line 2126, in binary_cross_entropy_with_logits
        raise ValueError("Target size ({}) must be the same as input size ({})".format(target.size(), input.size()))

    return torch.binary_cross_entropy_with_logits(input, target, weight, pos_weight, reduction_enum)
           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE


During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "./tools/train_net.py", line 184, in <module>
    args=(args,),
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/engine/launch.py", line 51, in launch
    main_func(*args)
  File "./tools/train_net.py", line 149, in main
    return trainer.train()
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/engine/defaults.py", line 373, in train
    super().train(self.start_iter, self.max_iter)
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/engine/train_loop.py", line 134, in train
    self.after_train()
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/engine/train_loop.py", line 142, in after_train
    h.after_train()
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/engine/hooks.py", line 353, in after_train
    self._do_eval()
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/engine/hooks.py", line 321, in _do_eval
    results = self._func()
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/engine/defaults.py", line 324, in test_and_save_results
    self._last_eval_results = self.test(self.cfg, self.model)
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/engine/defaults.py", line 484, in test
    results_i = inference_on_dataset(model, data_loader, evaluator)
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/evaluation/evaluator.py", line 122, in inference_on_dataset
    outputs = model(inputs, idx, len(data_loader))
  File "/home/iwb/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 532, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/modeling/meta_arch/fcos.py", line 155, in forward
    images = self.preprocess_image(batched_inputs)
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/modeling/meta_arch/fcos.py", line 425, in preprocess_image
    images = [x["image"].to(self.device) for x in batched_inputs]
  File "/home/iwb/project/dlo_bcnet/BCNet/detectron2/modeling/meta_arch/fcos.py", line 425, in <listcomp>
    images = [x["image"].to(self.device) for x in batched_inputs]
RuntimeError: CUDA error: device-side assert triggered

0reactions

TechyRiocommented, Nov 20, 2021

The message: “Category ids in annotations are not in [1, #categories]! We’ll apply a mapping for you.” What is your category ids in annotations?

I didn’t define it yet. That should be fine right? i’ve used same setting for CenterMask 2, also in detection 2 framework.

=========update =============== i’ve opened the json file. it shows at the end:

====== update again ======== the id in converted json file is shifted…from 1 to N original id is from 0 to N-1 pytorch/pytorch#21136 (left:converted, right:original instances_val.zip)

I also encountered the same problem as you. How did you convert the json file to remove the background? Do you have a conversion script file?

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