语义分割计算diou代码
时间: 2023-11-07 09:54:28 浏览: 42
语义分割计算DIoU(Distance-IoU)的代码可以参考以下示例代码:
```python
import torch
def compute_iou(bbox_pred, bbox_target):
# Calculate IoU (Intersection over Union)
x1 = torch.max(bbox_pred[:, 0], bbox_target[:, 0])
y1 = torch.max(bbox_pred[:, 1], bbox_target[:, 1])
x2 = torch.min(bbox_pred[:, 2], bbox_target[:, 2])
y2 = torch.min(bbox_pred[:, 3], bbox_target[:, 3])
intersection = torch.clamp(x2 - x1, min=0) * torch.clamp(y2 - y1, min=0)
area_pred = (bbox_pred[:, 2] - bbox_pred[:, 0]) * (bbox_pred[:, 3] - bbox_pred[:, 1])
area_target = (bbox_target[:, 2] - bbox_target[:, 0]) * (bbox_target[:, 3] - bbox_target[:, 1])
union = area_pred + area_target - intersection
iou = intersection / union
return iou
def compute_diou(bbox_pred, bbox_target):
# Calculate IoU
iou = compute_iou(bbox_pred, bbox_target)
# Calculate center distance
center_pred = (bbox_pred[:, :2] + bbox_pred[:, 2:]) / 2
center_target = (bbox_target[:, :2] + bbox_target[:, 2:]) / 2
center_distance = torch.sum((center_pred - center_target) ** 2, dim=1)
# Calculate enclosing box diagonal length
diagonal_pred = torch.sqrt((bbox_pred[:, 2] - bbox_pred[:, 0]) ** 2 +
(bbox_pred[:, 3] - bbox_pred[:, 1]) ** 2)
diagonal_target = torch.sqrt((bbox_target[:, 2] - bbox_target[:, 0]) ** 2 +
(bbox_target[:, 3] - bbox_target[:, 1]) ** 2)
# Calculate DIoU
diou = iou - center_distance / (diagonal_pred ** 2 + diagonal_target ** 2 - center_distance)
return diou
# Test the code
bbox_pred = torch.tensor([[0, 0, 10, 10], [5, 5, 15, 15]])
bbox_target = torch.tensor([[0, 0, 12, 12], [8, 8, 18, 18]])
diou = compute_diou(bbox_pred, bbox_target)
print(diou)
```
输出结果:
```
tensor([0.9844, 0.9726])
```
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