" KeyError: 'annotations' " on evaluating the model using evaluator.update(predictions)- DETR

[eloisacorti]

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Notebook name

train-huggingface-detr-on-custom-dataset.ipynb

Bug

When training on custom dataset, it seems like I'm not getting any predictions. During trainning I get loss resultos, so it seems like the trainning is doing fine, but then I can't get inferences. If I try to run the CocoEvaluator I get this bug:

`KeyError Traceback (most recent call last)

in () 21 predictions = {target['image_id'].item(): output for target, output in zip(labels, results)} 22 predictions = prepare_for_coco_detection(predictions) ---> 23 evaluator.update(predictions) 24 25 evaluator.synchronize_between_processes() 3 frames /usr/local/lib/python3.10/dist-packages/pycocotools/coco.py in getAnnIds(self, imgIds, catIds, areaRng, iscrowd) 144 anns = list(itertools.chain.from_iterable(lists)) 145 else: --> 146 anns = self.dataset['annotations'] 147 anns = anns if len(catIds) == 0 else [ann for ann in anns if ann['category_id'] in catIds] 148 anns = anns if len(areaRng) == 0 else [ann for ann in anns if ann['area'] > areaRng[0] and ann['area'] < areaRng[1]] KeyError: 'annotations'` ### Environment -Google colab ### Minimal Reproducible Example _No response_ ### Additional _No response_ ### Are you willing to submit a PR? - [ ] Yes I'd like to help by submitting a PR!

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[SkalskiP]

Hi @eloisacorti 👋🏻! Does that happen with football-players-detection-3zvbc dataset? Or your custom one?

[eloisacorti]

Hi @SkalskiP It happen with custom dataset.

[SkalskiP]

@eloisacorti, is that dataset coming from Roboflow? If so, could you share a link?

[eloisacorti]

No, I have it my drive.

The directory structure is:

maize10----|valid #images + .json |train #images + .json |__test #images + .json

https://drive.google.com/drive/folders/1d0LUp_SPpcbPdRVYvO3lHZjTTlJJaPWj?usp=sharing

[SkalskiP]

Could you share you colab where you try and fail to load that dataset?

[eloisacorti]

Yes. I only changed the location of the dataset https://colab.research.google.com/drive/1qIxmCAueQxkYd2b5Y6DAA-pWWVGuhskF?usp=sharing

[SkalskiP]

Okey. I'll take a look at it as soon as possible. But I'm afraid I won't be able to do it this week.

[eloisacorti]

Thanks!! @SkalskiP

[Heni-Loukil]

@eloisacorti have you find a solution ? I got the same problem, for some datasets it throws the exact error as you encountered but for other datasets it works fine !

[poyingHAHA]

@eloisacorti @eloisacorti change this line in your colab in the section causing the error: results = image_processor.post_process_object_detection(outputs, target_sizes=orig_target_sizes) to: results = image_processor.post_process_object_detection(outputs, target_sizes=orig_target_sizes, threshold=0)

I think this is because the default threshold is too high that causes the results to be empty in most values.

[SkalskiP]

@poyingHAHA so that happens because during evaluation, there are no detections produced by the model?

[poyingHAHA]

Yes, training step is fine, but the you get nothing during evaluation because of the default threshold and model not training well.

[Kalyugsasur]

how do i ensure that the model is training well? like i am using this notebook as a reference to train for the object detection on soccernet dataset, and i am facing the same issue.

[NielsRogge]

Hi folks,

Thanks for reporting, I was fine-tuning DETR and the new DETA model on a custom dataset and faced the same issue. Glad I found this 😅 will update my demo notebooks.

Regarding making sure the model is training well, fine-tuning is working well for me on the balloon dataset: https://github.com/NielsRogge/Transformers-Tutorials/blob/master/DETA/Fine_tuning_DETA_on_a_custom_dataset_(balloon).ipynb.

Also pushed an update for my DETR notebook.