基于 FCN 网络对DRIVE数据集的分割实战

[train hyper-parameters: Namespace(backbone='resnet50', base_size=600, batch_size=2, crop_size=480, epochs=20, img_f='.png', lr=0.001, lrf=0.01, mask_f='.png', pretrained=True, visTrainSets=True)] [epoch: 1] global correct: 0.9083 precision: ['0.9119', '0.5425'] recall: ['0.9951', '0.0575'] IoU: ['0.9078', '0.0549'] mean IoU: 0.4813 [epoch: 2] global correct: 0.9074 precision: ['0.9346', '0.4995'] recall: ['0.9655', '0.3379'] IoU: ['0.9044', '0.2524'] mean IoU: 0.5784 [epoch: 3] global correct: 0.9169 precision: ['0.9229', '0.6872'] recall: ['0.9913', '0.1880'] IoU: ['0.9155', '0.1732'] mean IoU: 0.5443 [epoch: 4] global correct: 0.9275 precision: ['0.9417', '0.6821'] recall: ['0.9808', '0.4049'] IoU: ['0.9247', '0.3406'] mean IoU: 0.6326 [epoch: 5] global correct: 0.9304 precision: ['0.9424', '0.7151'] recall: ['0.9833', '0.4111'] IoU: ['0.9276', '0.3532'] mean IoU: 0.6404 [epoch: 6] global correct: 0.9340 precision: ['0.9596', '0.6567'] recall: ['0.9680', '0.5999'] IoU: ['0.9301', '0.4567'] mean IoU: 0.6934 [epoch: 7] global correct: 0.9336 precision: ['0.9503', '0.6983'] recall: ['0.9781', '0.4979'] IoU: ['0.9304', '0.4098'] mean IoU: 0.6701 [epoch: 8] global correct: 0.9357 precision: ['0.9545', '0.6952'] recall: ['0.9757', '0.5441'] IoU: ['0.9323', '0.4393'] mean IoU: 0.6858 [epoch: 9] global correct: 0.9354 precision: ['0.9525', '0.7030'] recall: ['0.9775', '0.5223'] IoU: ['0.9321', '0.4278'] mean IoU: 0.6800 [epoch: 10] global correct: 0.9368 precision: ['0.9526', '0.7182'] recall: ['0.9791', '0.5225'] IoU: ['0.9336', '0.4336'] mean IoU: 0.6836 [epoch: 11] global correct: 0.9350 precision: ['0.9565', '0.6783'] recall: ['0.9726', '0.5665'] IoU: ['0.9314', '0.4465'] mean IoU: 0.6890 [epoch: 12] global correct: 0.9351 precision: ['0.9552', '0.6857'] recall: ['0.9742', '0.5517'] IoU: ['0.9316', '0.4404'] mean IoU: 0.6860 [epoch: 13] global correct: 0.9347 precision: ['0.9493', '0.7163'] recall: ['0.9803', '0.4867'] IoU: ['0.9316', '0.4080'] mean IoU: 0.6698 [epoch: 14] global correct: 0.9355 precision: ['0.9541', '0.6953'] recall: ['0.9759', '0.5399'] IoU: ['0.9321', '0.4366'] mean IoU: 0.6844 [epoch: 15] global correct: 0.9356 precision: ['0.9514', '0.7128'] recall: ['0.9790', '0.5100'] IoU: ['0.9325', '0.4231'] mean IoU: 0.6778 [epoch: 16] global correct: 0.9358 precision: ['0.9526', '0.7073'] recall: ['0.9780', '0.5225'] IoU: ['0.9325', '0.4296'] mean IoU: 0.6811 [epoch: 17] global correct: 0.9357 precision: ['0.9543', '0.6953'] recall: ['0.9758', '0.5421'] IoU: ['0.9323', '0.4381'] mean IoU: 0.6852 [epoch: 18] global correct: 0.9354 precision: ['0.9513', '0.7107'] recall: ['0.9789', '0.5086'] IoU: ['0.9322', '0.4213'] mean IoU: 0.6768 [epoch: 19] global correct: 0.9354 precision: ['0.9530', '0.7004'] recall: ['0.9770', '0.5272'] IoU: ['0.9321', '0.4302'] mean IoU: 0.6811 [epoch: 20] global correct: 0.9359 precision: ['0.9525', '0.7086'] recall: ['0.9781', '0.5213'] IoU: ['0.9326', '0.4293'] mean IoU: 0.6810