support ArrayLike data in to_xarray #825
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egpbos
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Jul 26, 2024
Either the image_arr is wrong (load_img runs a preprocess function that is meant for use with ResNet50, perhaps that's the issue) or the uint8 conversion kills something, but either way, the "fix" introduced there completely ruined the output for image vs captioning experiments! This commit fixes things again. Note that the np.array(input_image) could be replaced by a bare input_image if dianna PR dianna-ai/dianna#825 is accepted.
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This commit makes dianna swallow more kinds of data items without users having to mangle them manually themselves. As long as your data is numpy ArrayLike it will go. The only blocker for this was the direct use of the .ndim attribute on data, which assumes it is already a numpy array rather than something that can trivially be converted to a numpy array. A PIL.Image is an example of such an ArrayLike type. We use this in explainable_embedding to feed items into the OpenAI CLIP model.
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I rebased on main to get the linter fix in here. The changes themselves look good, nice generalization of to_xarray! Linter's happy as well, so let's merge. |
loostrum
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Jul 31, 2024
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@egpbos many checks are not passing. |
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Yep, those are mentioned above. They are unrelated to this PR. |
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closing and reopening for rerunning tests |
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This commit makes dianna swallow more kinds of data items without users having to mangle them manually themselves. As long as your data is numpy ArrayLike it will go. The only blocker for this was the direct use of the .ndim attribute on data, which assumes it is already a numpy array rather than something that can trivially be converted to a numpy array. A PIL.Image is an example of such an ArrayLike type. We use this in explainable_embedding to feed items into the OpenAI CLIP model.
I sprinkled in some nice type hinting, of course, but not for the other parameters, because they would become monstrosities.