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View Code? Open in Web Editor NEWEvaluation Docker for the ATLAS2.0 Grand Challenge
License: Apache License 2.0
Evaluation Docker for the ATLAS2.0 Grand Challenge
License: Apache License 2.0
like for the leasion count the code:
if(not batchwise):
prediction = np.reshape(prediction, (1, *prediction.shape))
truth = np.reshape(truth, (1, *truth.shape))
pred_shape = prediction.shape
truth_shape = truth.shape
is missing..
Currently it does slicewise labelling and f1_score.
Line 45 of the scoring code implicitly assumes that either the prediction or the truth will have non-zero values.
The metrics iterate over predictions, but they should be iterating over the (more-reliable) truth arrays.
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