CIoU nan bug fix (#736)

utils/general.py

@@ -1,15 +1,15 @@
 import glob
+import logging
 import math
 import os
+import platform
 import random
 import shutil
 import subprocess
 import time
-import logging
 from contextlib import contextmanager
 from copy import copy
 from pathlib import Path
-import platform
 
 import cv2
 import matplotlib
@@ -339,19 +339,19 @@ def compute_ap(recall, precision):
     return ap
 
 
-def bbox_iou(box1, box2, x1y1x2y2=True, GIoU=False, DIoU=False, CIoU=False):
+def bbox_iou(box1, box2, x1y1x2y2=True, GIoU=False, DIoU=False, CIoU=False, eps=1e-12):
     # Returns the IoU of box1 to box2. box1 is 4, box2 is nx4
     box2 = box2.T
 
     # Get the coordinates of bounding boxes
     if x1y1x2y2:  # x1, y1, x2, y2 = box1
-        b1_x1, b1_y1, b1_x2, b1_y2 = box1[0], box1[1], box1[2], box1[3]
-        b2_x1, b2_y1, b2_x2, b2_y2 = box2[0], box2[1], box2[2], box2[3]
+        b1_x1, b1_y1, b1_x2, b1_y2 = box1[0], box1[1], box1[2] + eps, box1[3] + eps
+        b2_x1, b2_y1, b2_x2, b2_y2 = box2[0], box2[1], box2[2] + eps, box2[3] + eps
     else:  # transform from xywh to xyxy
-        b1_x1, b1_x2 = box1[0] - box1[2] / 2, box1[0] + box1[2] / 2
-        b1_y1, b1_y2 = box1[1] - box1[3] / 2, box1[1] + box1[3] / 2
-        b2_x1, b2_x2 = box2[0] - box2[2] / 2, box2[0] + box2[2] / 2
-        b2_y1, b2_y2 = box2[1] - box2[3] / 2, box2[1] + box2[3] / 2
+        b1_x1, b1_x2 = box1[0] - box1[2] / 2, box1[0] + box1[2] / 2 + eps
+        b1_y1, b1_y2 = box1[1] - box1[3] / 2, box1[1] + box1[3] / 2 + eps
+        b2_x1, b2_x2 = box2[0] - box2[2] / 2, box2[0] + box2[2] / 2 + eps
+        b2_y1, b2_y2 = box2[1] - box2[3] / 2, box2[1] + box2[3] / 2 + eps
 
     # Intersection area
     inter = (torch.min(b1_x2, b2_x2) - torch.max(b1_x1, b2_x1)).clamp(0) * \
@@ -360,26 +360,26 @@ def bbox_iou(box1, box2, x1y1x2y2=True, GIoU=False, DIoU=False, CIoU=False):
     # Union Area
     w1, h1 = b1_x2 - b1_x1, b1_y2 - b1_y1
     w2, h2 = b2_x2 - b2_x1, b2_y2 - b2_y1
-    union = (w1 * h1 + 1e-16) + w2 * h2 - inter
+    union = w1 * h1 + w2 * h2 - inter
 
     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
+            c_area = cw * ch  # convex area
             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
+            c2 = cw ** 2 + ch ** 2
             # centerpoint distance squared
             rho2 = ((b2_x1 + b2_x2) - (b1_x1 + b1_x2)) ** 2 / 4 + ((b2_y1 + b2_y2) - (b1_y1 + b1_y2)) ** 2 / 4
             if DIoU:
                 return iou - rho2 / c2  # DIoU
             elif CIoU:  # https://github.com/Zzh-tju/DIoU-SSD-pytorch/blob/master/utils/box/box_utils.py#L47
                 v = (4 / math.pi ** 2) * torch.pow(torch.atan(w2 / h2) - torch.atan(w1 / h1), 2)
                 with torch.no_grad():
-                    alpha = v / (1 - iou + v + 1e-16)
+                    alpha = v / ((1 + eps) - iou + v)
                 return iou - (rho2 / c2 + v * alpha)  # CIoU
 
     return iou