问题
I m using Unet architecture for lung segmentation it show me better training and Val loss but when I call predict function and give one image of training set as input.its gives me blank image as output .I am understanding why is doing so when it show good validation accuracy. I'm using keras
回答1:
Accuracy is not a good metrics for segmentation, especially for medical cases. Your dataset is most likely imbalanced which is why you are getting high accuracy (most of the ground truth mask pixels are "0"). You should use metrics like Dice, precision/recall/F1 to track results
来源：https://stackoverflow.com/questions/50181116/unet-segmentation-model-predicts-blank-image