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Merge a974079bd5b867303b7c77442be14c11ca312482 into 6fbaf42b23f6709f4e34a51430587673e70e151d
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@ -581,6 +581,7 @@ def ap_per_class(
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n_l = nt[ci] # number of labels
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n_p = i.sum() # number of predictions
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if n_p == 0 or n_l == 0:
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prec_values.append(np.zeros(1000))
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continue
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# Accumulate FPs and TPs
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