Comments (2)
Can you post your entire code? I suspect that when you try to teach new labels to your model, the shape of the new data doesn't match the previously available training data, but I can't be sure without the source code.
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I think the problem is that you didn't reshape your images to a numpy array with shape (n_images, n_dim), where n_dim is the heightwidthchannels of the image. Try calling .reshape(-1,1) on your images in the read_img
function after you have resized them.
As this is not the issue of modAL
, I'll close this. If you have any problems, let me know!
from modal.
Related Issues (20)
- Multivariate Active regression
- How to extract the image names and labels in the training set after completing the active learning loop and write them to a CSV file
- decision_function instead of predict_proba HOT 5
- AttributeError: bootstrap_init HOT 3
- TypeError: cannot concatenate object of type '<class 'numpy.ndarray'>'; only Series and DataFrame objs are valid
- Can I use modAL with estimators from other libraries than scikit-learn like xgboost? HOT 1
- Which sampling method is best for very unbalanced data? HOT 1
- Encountering error with number of batches per epoch
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- modAL not installable via pypi anymore HOT 3
- the modAL package has been changed into modal in the pip repository HOT 7
- Data augmentation with `skorch`
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- Spacy NER HOT 1
- raise ImportError( ImportError: C extension: None not built. If you want to import pandas from the source directory, you may need to run 'python setup.py build_ext' to build the C extensions first.
- uncertainty query for 2d classifier output
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