Comments (8)
Thanks for describing your pain points in great detail! We know that setting up the data for the object detector is tricky and appreciate all the feedback we can get to help make the process easier.
It looks like you are all set, except for one thing. Each cell in the annotations
column must contain a list of dictionaries. This is to allow more than one object per image. Of course, if you are only planning to have one object per image, that is perfectly fine too and I have trained successful detectors on such data. However, we still need it to be a list in that case. You can correct this for your data by calling:
data['annotations'] = data['annotations'].apply(lambda x: [x])
This will put what you have now into lists of length 1 and the detector functions should be happy.
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Thank you for explaining it. I was also running into the same problem.
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@johnyquest7 Thanks for the feedback! We'll try to make this clearer in the documentation and perhaps also in the error message.
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The annotation column in my SFrame ends up having 3 rows after I read annotation list for 3 objects in an image, but the image column has only 1 row representing the corresponding image, thus resulting in row mismatch. Shall I be loading 3 copies of the image if I intend to detect 3 objects in an image such that number of rows match ?
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@atthaje If you have an image with three objects, then it should be 1 row in an SFrame and the annotations column should be a list of three dictionaries. I hope that clarifies things! Feel free to open up a new issue if you are still having problems.
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Thank you for the clarification.
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Reopening to track a product change to eliminate this pain point: let's allow for the annotations being either a single dictionary or a list of dictionaries.
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This was fixed by #293
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