替换Inner CIoU损失函数(基于MMYOLO)
由于MMYOLO中没有实现Inner CIoU损失函数,所以需要在mmyolo/models/iou_loss.py中添加Inner CIoU的计算和对应的iou_mode,修改完以后在终端运行
python setup.py install
再在配置文件中进行修改即可。修改例子如下:
elif iou_mode == "innerciou":
ratio=1.0
w1_, h1_, w2_, h2_ = w1 / 2, h1 / 2, w2 / 2, h2 / 2
x1 = bbox1_x1 + w1_
y1 = bbox1_y1 + h1_
x2 = bbox2_x1 + w2_
y2 = bbox2_y1 + h2_
inner_b1_x1, inner_b1_x2, inner_b1_y1, inner_b1_y2 = x1 - w1_ * ratio, x1 + w1_ * ratio, \
y1 - h1_ * ratio, y1 + h1_ * ratio
inner_b2_x1, inner_b2_x2, inner_b2_y1, inner_b2_y2 = x2 - w2_ * ratio, x2 + w2_ * ratio, \
y2 - h2_ * ratio, y2 + h2_ * ratio
inner_inter = (torch.min(inner_b1_x2, inner_b2_x2) - torch.max(inner_b1_x1, inner_b2_x1)).clamp(0) * \
(torch.min(inner_b1_y2, inner_b2_y2) - torch.max(inner_b1_y1, inner_b2_y1)).clamp(0)
inner_union = w1 * ratio * h1 * ratio + w2 * ratio * h2 * ratio - inner_inter + eps
inner_iou = inner_inter / inner_union
# CIoU = IoU - ( (ρ^2(b_pred,b_gt) / c^2) + (alpha x v) )
# calculate enclose area (c^2)
enclose_area = enclose_w**2 + enclose_h**2 + eps
# calculate ρ^2(b_pred,b_gt):
# euclidean distance between b_pred(bbox2) and b_gt(bbox1)
# center point, because bbox format is xyxy -> left-top xy and
# right-bottom xy, so need to / 4 to get center point.
rho2_left_item = ((bbox2_x1 + bbox2_x2) - (bbox1_x1 + bbox1_x2))**2 / 4
rho2_right_item = ((bbox2_y1 + bbox2_y2) -
(bbox1_y1 + bbox1_y2))**2 / 4
rho2 = rho2_left_item + rho2_right_item # rho^2 (ρ^2)
# Width and height ratio (v)
wh_ratio = (4 / (math.pi**2)) * torch.pow(
torch.atan(w2 / h2) - torch.atan(w1 / h1), 2)
with torch.no_grad():
alpha = wh_ratio / (wh_ratio - ious + (1 + eps))
# innerCIoU
ious = inner_iou - ((rho2 / enclose_area) + (alpha * wh_ratio))
修改后的配置文件(以configs/yolov5/yolov5_s-v61_syncbn_8xb16-300e_coco.py为例)
_base_ = ['../_base_/default_runtime.py',