From 1415a798fe214432adc68c90ae323accf2071359 Mon Sep 17 00:00:00 2001
From: Glenn Jocher <glenn.jocher@ultralytics.com>
Date: Sat, 17 Nov 2018 12:54:44 +0100
Subject: [PATCH] updates

---
 models.py      | 20 ++++++++++----------
 utils/utils.py |  8 ++++----
 2 files changed, 14 insertions(+), 14 deletions(-)

diff --git a/models.py b/models.py
index 61c66dc1..b9e3f88d 100755
--- a/models.py
+++ b/models.py
@@ -123,16 +123,16 @@ class YOLOLayer(nn.Module):
         y = torch.sigmoid(p[..., 1])  # Center y
 
         # Width and height (yolo method)
-        # w = p[..., 2]  # Width
-        # h = p[..., 3]  # Height
-        # width = torch.exp(w.data) * self.anchor_w
-        # height = torch.exp(h.data) * self.anchor_h
+        w = p[..., 2]  # Width
+        h = p[..., 3]  # Height
+        width = torch.exp(w.data) * self.anchor_w
+        height = torch.exp(h.data) * self.anchor_h
 
         # Width and height (power method)
-        w = torch.sigmoid(p[..., 2])  # Width
-        h = torch.sigmoid(p[..., 3])  # Height
-        width = ((w.data * 2) ** 2) * self.anchor_w
-        height = ((h.data * 2) ** 2) * self.anchor_h
+        # w = torch.sigmoid(p[..., 2])  # Width
+        # h = torch.sigmoid(p[..., 3])  # Height
+        # width = ((w.data * 2) ** 2) * self.anchor_w
+        # height = ((h.data * 2) ** 2) * self.anchor_h
 
         # Add offset and scale with anchors (in grid space, i.e. 0-13)
         pred_boxes = FT(bs, self.nA, nG, nG, 4)
@@ -174,8 +174,8 @@ class YOLOLayer(nn.Module):
                 # lconf = k * BCEWithLogitsLoss(pred_conf[mask], mask[mask].float())
                 lconf = (k * 10) * BCEWithLogitsLoss(pred_conf, mask.float())
 
-                lcls = (k / 10) * CrossEntropyLoss(pred_cls[mask], torch.argmax(tcls, 1))
-                # lcls = k * BCEWithLogitsLoss(pred_cls[mask], tcls.float())
+                # lcls = (k / 10) * CrossEntropyLoss(pred_cls[mask], torch.argmax(tcls, 1))
+                lcls = (k * 10) * BCEWithLogitsLoss(pred_cls[mask], tcls.float())
             else:
                 lx, ly, lw, lh, lcls, lconf = FT([0]), FT([0]), FT([0]), FT([0]), FT([0]), FT([0])
 
diff --git a/utils/utils.py b/utils/utils.py
index 55e7e64a..f62eca34 100755
--- a/utils/utils.py
+++ b/utils/utils.py
@@ -259,12 +259,12 @@ def build_targets(pred_boxes, pred_conf, pred_cls, target, anchor_wh, nA, nC, nG
         ty[b, a, gj, gi] = gy - gj.float()
 
         # Width and height (yolo method)
-        # tw[b, a, gj, gi] = torch.log(gw / anchor_wh[a, 0])
-        # th[b, a, gj, gi] = torch.log(gh / anchor_wh[a, 1])
+        tw[b, a, gj, gi] = torch.log(gw / anchor_wh[a, 0])
+        th[b, a, gj, gi] = torch.log(gh / anchor_wh[a, 1])
 
         # Width and height (power method)
-        tw[b, a, gj, gi] = torch.sqrt(gw / anchor_wh[a, 0]) / 2
-        th[b, a, gj, gi] = torch.sqrt(gh / anchor_wh[a, 1]) / 2
+        # tw[b, a, gj, gi] = torch.sqrt(gw / anchor_wh[a, 0]) / 2
+        # th[b, a, gj, gi] = torch.sqrt(gh / anchor_wh[a, 1]) / 2
 
         # One-hot encoding of label
         tcls[b, a, gj, gi, tc] = 1