mirror of https://github.com/JDAI-CV/fast-reid.git
add eps in attr_evaluation.py
parent
254a489eb1
commit
c9537c97d1
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@ -36,6 +36,8 @@ class AttrEvaluator(DatasetEvaluator):
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@staticmethod
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def get_attr_metrics(gt_labels, pred_logits, thres):
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eps = 1e-20
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pred_labels = copy.deepcopy(pred_logits)
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pred_labels[pred_logits < thres] = 0
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pred_labels[pred_logits >= thres] = 1
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@ -53,13 +55,13 @@ class AttrEvaluator(DatasetEvaluator):
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gt_labels = gt_labels.astype(bool)
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intersect = (pred_labels & gt_labels).astype(float)
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union = (pred_labels | gt_labels).astype(float)
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ins_acc = (intersect.sum(axis=1) / union.sum(axis=1)).mean()
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ins_prec = (intersect.sum(axis=1) / pred_labels.astype(float).sum(axis=1)).mean()
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ins_rec = (intersect.sum(axis=1) / gt_labels.astype(float).sum(axis=1)).mean()
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ins_f1 = (2 * ins_prec * ins_rec) / (ins_prec + ins_rec)
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ins_acc = (intersect.sum(axis=1) / (union.sum(axis=1) + eps)).mean()
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ins_prec = (intersect.sum(axis=1) / (pred_labels.astype(float).sum(axis=1) + eps)).mean()
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ins_rec = (intersect.sum(axis=1) / (gt_labels.astype(float).sum(axis=1) + eps)).mean()
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ins_f1 = (2 * ins_prec * ins_rec) / (ins_prec + ins_rec + eps)
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term1 = correct_pos / real_pos
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term2 = correct_neg / real_neg
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term1 = correct_pos / (real_pos + eps)
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term2 = correct_neg / (real_neg + eps)
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label_mA_verbose = (term1 + term2) * 0.5
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label_mA = label_mA_verbose.mean()
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