[issue-799] coco split into train/test; updated coco dataset module api #805
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update: @ItayGabbay @nirhutnik In general |
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Seems good to me, but would prefer Gabbay take a look as its his code. If I understand correctly, this means that sometimes we get average precision = None (why?), and in those cases you want it to count as 0. Not sure what is done later with that information - if its summed up, then ok, but I guess it is averaged again and in that case maybe should be just ignored and not counted in the denominator as well. But didn't dive into the code yet. |
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also, are those two lines within 80: if train and test:
81: train.validate_shared_label(test)if I got it right, in object-detection task label is a 2d array each row of which we probably should only verify that number of columns is the same? |
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@yromanyshyn I think that Gabbay's PR solves that anyway as he transfers label validation to the LabelEncoder classes |
| pin_memory: bool = True, | ||
| object_type: Literal['Dataset', 'DataLoader'] = 'DataLoader' | ||
| ) -> t.Union[DataLoader, vision.VisionDataset]: | ||
| """Get the COCO dataset and return a dataloader. |
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I would call it the COCO 128 dataset, as the COCO dataset is much larger than that.
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Also, did we validate the license of this dataset? and model?
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changed,
it is GNU Version 3
makefile
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| xargs -P4 -I'{}' $(JUPYTER) nbconvert --execute '{}' \ | ||
| --to notebook --stdout > /dev/null | ||
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| $(JUPYTER) nbconvert --execute $$(find ./docs/source/examples -name "*.ipynb") --to notebook --stdout > /dev/null |
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weird but I initially thought that this was causing 'notebook check' failure. I have undone it
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Maybe you are correct. I'm now checking this
| @@ -79,7 +79,10 @@ def compute(self): | |||
| **self._compute_ap_recall(ev["scores"], ev["matched"], ev["NP"]) | |||
| } | |||
| if self.return_ap_only: | |||
| res = torch.tensor([res[k]["AP"] for k in sorted(res.keys())]) | |||
| res = torch.tensor([ | |||
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I think that's OK. This may happen in the case the model detected a class that doesn't exist in the test set.
Anyway, we are planning to replace this module in the near future.
resolves #799