diff --git a/utils/general.py b/utils/general.py index 52cb3ad..ede29f0 100755 --- a/utils/general.py +++ b/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) * \ @@ -360,18 +360,18 @@ 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: @@ -379,7 +379,7 @@ def bbox_iou(box1, box2, x1y1x2y2=True, GIoU=False, DIoU=False, CIoU=False): 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