From 0e54731bb8313dd37f9bae2c397e32ec8f8050b1 Mon Sep 17 00:00:00 2001
From: Glenn Jocher <glenn.jocher@ultralytics.com>
Date: Sun, 22 Dec 2019 14:19:46 -0800
Subject: [PATCH] updates

---
 utils/utils.py | 26 ++++++++++++--------------
 1 file changed, 12 insertions(+), 14 deletions(-)

diff --git a/utils/utils.py b/utils/utils.py
index 18ccb514..8d37e62b 100755
--- a/utils/utils.py
+++ b/utils/utils.py
@@ -253,21 +253,21 @@ def bbox_iou(box1, box2, x1y1x2y2=True, GIoU=False, DIoU=False, CIoU=False):
         b2_y1, b2_y2 = box2[1] - box2[3] / 2, box2[1] + box2[3] / 2
 
     # Intersection area
-    inter_area = (torch.min(b1_x2, b2_x2) - torch.max(b1_x1, b2_x1)).clamp(0) * \
-                 (torch.min(b1_y2, b2_y2) - torch.max(b1_y1, b2_y1)).clamp(0)
+    inter = (torch.min(b1_x2, b2_x2) - torch.max(b1_x1, b2_x1)).clamp(0) * \
+            (torch.min(b1_y2, b2_y2) - torch.max(b1_y1, b2_y1)).clamp(0)
 
     # Union Area
     w1, h1 = b1_x2 - b1_x1, b1_y2 - b1_y1
     w2, h2 = b2_x2 - b2_x1, b2_y2 - b2_y1
-    union_area = (w1 * h1 + 1e-16) + w2 * h2 - inter_area
+    union = (w1 * h1 + 1e-16) + w2 * h2 - inter
 
-    iou = inter_area / union_area  # iou
+    iou = inter / union  # iou
     if GIoU or DIoU or CIoU:
         cw = torch.max(b1_x2, b2_x2) - torch.min(b1_x1, b2_x1)  # convex (smallest enclosing box) width
         ch = torch.max(b1_y2, b2_y2) - torch.min(b1_y1, b2_y1)  # convex height
         if GIoU:  # Generalized IoU https://arxiv.org/pdf/1902.09630.pdf
             c_area = cw * ch + 1e-16  # convex area
-            return iou - (c_area - union_area) / c_area  # GIoU
+            return iou - (c_area - union) / c_area  # GIoU
         if DIoU or CIoU:  # Distance or Complete IoU https://arxiv.org/abs/1911.08287v1
             # convex diagonal squared
             c2 = cw ** 2 + ch ** 2 + 1e-16
@@ -297,20 +297,18 @@ def box_iou(boxes1, boxes2):
             IoU values for every element in boxes1 and boxes2
     """
 
-    def box_area(boxes):
-        return (boxes[:, 2] - boxes[:, 0]) * (boxes[:, 3] - boxes[:, 1])
+    def box_area(box):
+        # box = 4xn
+        return (box[2] - box[0]) * (box[3] - box[1])
 
-    area1 = box_area(boxes1)
-    area2 = box_area(boxes2)
+    area1 = box_area(boxes1.t())
+    area2 = box_area(boxes2.t())
 
     lt = torch.max(boxes1[:, None, :2], boxes2[:, :2])  # [N,M,2]
     rb = torch.min(boxes1[:, None, 2:], boxes2[:, 2:])  # [N,M,2]
 
-    wh = (rb - lt).clamp(min=0)  # [N,M,2]
-    inter = wh[:, :, 0] * wh[:, :, 1]  # [N,M]
-
-    iou = inter / (area1[:, None] + area2 - inter)
-    return iou
+    inter = (rb - lt).clamp(min=0).prod(2)  # [N,M]
+    return inter / (area1[:, None] + area2 - inter)  # iou = inter / (area1 + area2 - inter)
 
 
 def wh_iou(wh1, wh2):