def addLossResults(self, i_epoch, loss, dataset_instance, show=1):
#function to save loss and print it
self.list_loss[dataset_instance].append(loss)
self.list_loss_register[dataset_instance].append(i_epoch)
if show:
#color given the dataset instance
if dataset_instance == 0: color = (19, 161, 14)
elif dataset_instance == 1: color = (193, 156, 0)
else: color = (204, 0, 0)
print(ost.PRINTCOLOR(*color), end="") #set color
text = self.dataset_names[dataset_instance]
print('Epoch %3d -> %s Loss: %1.6f' % (i_epoch, text, loss))
print(ost.RESETCOLOR, end="") #reset color
def addFullResults(self, i_epoch, cm, loss, dataset_instance, show=1):
#function to save loss and other metric from CM
#RETURN : IS_BEST only if dataset instance is 1 (VALIDATION set)
#ISBEST is TRUE if current epoch got best mIoU ever
#color given the dataset instance
if dataset_instance == 0: color = (19, 161, 14)
elif dataset_instance == 1: color = (193, 156, 0)
else: color = (204, 0, 0)
#get dataset instance name (train/val/test)
text = self.dataset_names[dataset_instance]
print(ost.PRINTCOLOR(*color), end="") #set color
mIoU, ious = cm.class_IoU(show) #calcul iou and miou and display IoU
oa = cm.overall_accuracy() #calcul OA
#display general metrics
if show:
print('Epoch %3d -> %s Overall Accuracy: %3.2f%% %s mIoU : %3.2f%% %s Loss: %1.6f' \
% (i_epoch, text, oa,text, mIoU,text, loss))
print(ost.RESETCOLOR, end="") #reset color
#save metric values in containers
self.list_cm[dataset_instance].append(cm)
self.list_loss[dataset_instance].append(loss)
self.list_mIoU[dataset_instance].append(mIoU)
self.list_ious[dataset_instance].append(ious)
self.list_oa[dataset_instance].append(oa)
self.list_register[dataset_instance].append(i_epoch)
self.list_loss_register[dataset_instance].append(i_epoch)
#check if current epoch is best epoch by comparing mIoU
isBest = True if mIoU >= max(
self.list_mIoU[dataset_instance]) else False
if isBest and dataset_instance == 1: #verif if we really are in VALIDATION DATASET INSTANCE
self.best = i_epoch
self.best_id = self.list_mIoU[dataset_instance].index(mIoU)
return isBest