From a8fb235647e8b5923a718ccc5845fba5f2edb64d Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Tue, 16 Apr 2019 12:55:23 +0200 Subject: [PATCH] updates --- utils/utils.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/utils/utils.py b/utils/utils.py index 27b0d631..d4f5c300 100755 --- a/utils/utils.py +++ b/utils/utils.py @@ -263,14 +263,14 @@ def compute_loss(p, targets): # predictions, targets pi = pi0[b, a, gj, gi] # predictions closest to anchors tconf[b, a, gj, gi] = 1 # conf - lxy += (k * 0.07934) * MSE(torch.sigmoid(pi[..., 0:2]), txy[i]) # xy loss - lwh += (k * 0.01561) * MSE(pi[..., 2:4], twh[i]) # wh yolo loss - # lwh += (k * 0.01561) * MSE(torch.sigmoid(pi[..., 2:4]), twh[i]) # wh power loss - lcls += (k * 0.02094) * CE(pi[..., 5:], tcls[i]) # class_conf loss + lxy += (k * 0.07997) * MSE(torch.sigmoid(pi[..., 0:2]), txy[i]) # xy loss + lwh += (k * 0.007867) * MSE(pi[..., 2:4], twh[i]) # wh yolo loss + # lwh += (k * 0.007867) * MSE(torch.sigmoid(pi[..., 2:4]), twh[i]) # wh power loss + lcls += (k * 0.02111) * CE(pi[..., 5:], tcls[i]) # class_conf loss # pos_weight = ft([gp[i] / min(gp) * 4.]) # BCE = nn.BCEWithLogitsLoss(pos_weight=pos_weight) - lconf += (k * 0.8841) * BCE(pi0[..., 4], tconf) # obj_conf loss + lconf += (k * 0.8911) * BCE(pi0[..., 4], tconf) # obj_conf loss loss = lxy + lwh + lconf + lcls return loss, torch.cat((lxy, lwh, lconf, lcls, loss)).detach()