Lecture 03实际训练与可复查的输出 · 实现代码
实际训练与可复查的输出 · 实现代码
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))