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)/(所有预测为1的样本数) = TP/(TP+FP)
Recall = (预测为1且正确预测的样本数)/(所有真实情况为1的样本数) = TP/(TP+FN)
F1 = 2*(Precision*Recall)/(Precision+Recall)
IOU的定义
IoU = TP/(TP+TN+FP)