评价指标收集

TP/TN/FP/FN的定义

TP: 预测为1(Positive)，实际也为1(Truth-预测对了)

TN: 预测为0(Negative)，实际也为0(Truth-预测对了)

FP: 预测为1(Positive)，实际为0(False-预测错了)

FN: 预测为0(Negative)，实际为1(False-预测错了)

Accuracy/Precision/Recall/F1的定义

Accuracy = (预测正确的样本数)/(总样本数)=(TP+TN)/(TP+TN+FP+FN)

Precision = (预测为1且正确预测的样本数)/(全部预测为1的样本数) = TP/(TP+FP)

Recall = (预测为1且正确预测的样本数)/(全部真实状况为1的样本数) = TP/(TP+FN)

F1 = 2*(Precision*Recall)/(Precision+Recall)

IOU的定义

IoU = TP/(TP+TN+FP)