From 9514e7443891ab2eaa106292a041cb0b8770f7c3 Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Mon, 10 Sep 2018 17:02:38 +0200 Subject: [PATCH] updates --- models.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/models.py b/models.py index 136c314d..0df5930e 100755 --- a/models.py +++ b/models.py @@ -159,14 +159,16 @@ class YOLOLayer(nn.Module): lh = 5 * MSELoss(h[mask], th[mask]) lconf = 1.5 * BCEWithLogitsLoss1(pred_conf[mask], mask[mask].float()) - lcls = nM * CrossEntropyLoss(pred_cls[mask], torch.argmax(tcls, 1)) - # lcls = nM * BCEWithLogitsLoss2(pred_cls[mask], tcls.float()) + # lcls = nM * CrossEntropyLoss(pred_cls[mask], torch.argmax(tcls, 1)) + lcls = nM * BCEWithLogitsLoss2(pred_cls[mask], tcls.float()) else: lx, ly, lw, lh, lcls, lconf = FT([0]), FT([0]), FT([0]), FT([0]), FT([0]), FT([0]) lconf += nM * BCEWithLogitsLoss2(pred_conf[~mask], mask[~mask].float()) loss = lx + ly + lw + lh + lconf + lcls + + # Sum False Positives from unnasigned anchors i = torch.sigmoid(pred_conf[~mask]) > 0.99 FPe = torch.zeros(self.nC) if i.sum() > 0: