yolov8实现知识蒸馏
时间: 2024-05-30 20:07:13 浏览: 13
yolov8是一个支持知识蒸馏的目标检测模型,实现知识蒸馏可以选择logit和feature-based蒸馏方法,并且在进行蒸馏训练时需要设置好相应的蒸馏参数。以下是yolov8实现知识蒸馏的两个例子:
1. yolov8 logit蒸馏[^1]
```python
# 设置蒸馏参数
teacher_model = Yolov8(classes=NUM_CLASSES, weights=TEACHER_WEIGHTS)
student_model = Yolov8Tiny(classes=NUM_CLASSES, weights=None)
logit_config = DistillConfig(student_model=student_model,
teacher_model=teacher_model,
train_ds=train_ds,
val_ds=val_ds,
epochs=20,
steps_per_epoch=2000,
distill_type='logit',
alpha=0.1)
# 开始训练
logit_trainer = DistillTrainer(logit_config)
logit_trainer.train()
# 评估模型
metrics = student_model.evaluate(val_ds)
print(f"student model evaluate metrics: {metrics}")
```
2. yolov8 feature-based蒸馏
```python
# 设置蒸馏参数
teacher_model = Yolov8(classes=NUM_CLASSES, weights=TEACHER_WEIGHTS)
student_model = Yolov8Tiny(classes=NUM_CLASSES, weights=None)
feature_config = DistillConfig(student_model=student_model,
teacher_model=teacher_model,
train_ds=train_ds,
val_ds=val_ds,
epochs=20,
steps_per_epoch=2000,
distill_type='feature',
alpha=0.1,
distill_layers=[8, 16, 32])
# 开始训练
feature_trainer = DistillTrainer(feature_config)
feature_trainer.train()
# 评估模型
metrics = student_model.evaluate(val_ds)
print(f"student model evaluate metrics: {metrics}")
```
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