[LAB 10 · 从 RGB 图像训练小型检测器](/course/notebooks/a14237bfa9dd413d959ab4e458e11f42.html)

# 实际训练与可复查的输出 · 实现代码
[独立阅读](/course/notebook-blocks/e4979dd3569c4ce4855112dd4b062c23.html)
主线阅读与优先实验

RGB图像、单特征层锚框检测器、分类/位置损失、NMS、独立检测评价
展开完整实现代码
```
import subprocess,sys,json
subprocess.run([sys.executable,'lab10_detector.py','--out','lab10-results-rerun','--epochs','28'],check=True)
R=json.loads(Path('lab10-results-rerun/run.json').read_text())
for setting in ['random_initialization','validation','heldout','condition_half_object_scale','condition_NMS_065']:
    r=R[setting]
    print(setting, 'mAP50=',round(r['AP50']['mAP'],4),'mAP75=',round(r['AP75']['mAP'],4),
          'P@.4=',round(r['operating_point']['precision'],4),'R@.4=',round(r['operating_point']['recall'],4))
print(R['provenance'])
from IPython.display import Image,display
for filename in ['heldout-predictions.png','failure-predictions.png','half-scale-predictions.png','training-curve.png']:
    display(Image(filename='lab10-results-rerun/'+filename))
```