基于Unet 对胰腺癌症数据的分割【包含数据集、完整代码、训练的结果文件】

[train hyper-parameters: Namespace(base_size=500, batch_size=8, crop_size=480, epochs=50, lr=0.01, lrf=0.001)] [epoch: 1] global correct: 0.9507 precision: ['0.9582', '0.8713', '0.0000'] recall: ['0.9918', '0.6785', '0.0000'] IoU: ['0.9507', '0.6167', '0.0000'] mean IoU: 0.5224 [epoch: 2] global correct: 0.9679 precision: ['0.9744', '0.9091', '0.8995'] recall: ['0.9936', '0.8183', '0.0152'] IoU: ['0.9683', '0.7564', '0.0152'] mean IoU: 0.5800 [epoch: 3] global correct: 0.9270 precision: ['0.9290', '0.9148', '0.3359'] recall: ['0.9957', '0.4257', '0.1168'] IoU: ['0.9253', '0.4095', '0.0949'] mean IoU: 0.4765 [epoch: 4] global correct: 0.9799 precision: ['0.9939', '0.8838', '0.7696'] recall: ['0.9868', '0.9518', '0.5050'] IoU: ['0.9809', '0.8459', '0.4387'] mean IoU: 0.7552 [epoch: 5] global correct: 0.9822 precision: ['0.9919', '0.9093', '0.8941'] recall: ['0.9915', '0.9392', '0.4398'] IoU: ['0.9836', '0.8587', '0.4180'] mean IoU: 0.7534 [epoch: 6] global correct: 0.9808 precision: ['0.9968', '0.8756', '0.7697'] recall: ['0.9848', '0.9722', '0.5852'] IoU: ['0.9817', '0.8542', '0.4980'] mean IoU: 0.7780 [epoch: 7] global correct: 0.9865 precision: ['0.9934', '0.9372', '0.8584'] recall: ['0.9944', '0.9476', '0.5807'] IoU: ['0.9878', '0.8910', '0.5299'] mean IoU: 0.8029 [epoch: 8] global correct: 0.9839 precision: ['0.9958', '0.9218', '0.5989'] recall: ['0.9890', '0.9542', '0.7965'] IoU: ['0.9850', '0.8827', '0.5194'] mean IoU: 0.7957 [epoch: 9] global correct: 0.9872 precision: ['0.9947', '0.9336', '0.8731'] recall: ['0.9936', '0.9566', '0.6351'] IoU: ['0.9883', '0.8957', '0.5814'] mean IoU: 0.8218 [epoch: 10] global correct: 0.9865 precision: ['0.9918', '0.9503', '0.8240'] recall: ['0.9956', '0.9331', '0.6493'] IoU: ['0.9875', '0.8897', '0.5702'] mean IoU: 0.8158 [epoch: 11] global correct: 0.9870 precision: ['0.9959', '0.9237', '0.8804'] recall: ['0.9920', '0.9660', '0.6659'] IoU: ['0.9879', '0.8946', '0.6107'] mean IoU: 0.8311 [epoch: 12] global correct: 0.9870 precision: ['0.9912', '0.9576', '0.8705'] recall: ['0.9966', '0.9281', '0.6845'] IoU: ['0.9878', '0.8914', '0.6213'] mean IoU: 0.8335 [epoch: 13] global correct: 0.9868 precision: ['0.9929', '0.9533', '0.7224'] recall: ['0.9950', '0.9364', '0.7304'] IoU: ['0.9880', '0.8953', '0.5704'] mean IoU: 0.8179 [epoch: 14] global correct: 0.9882 precision: ['0.9958', '0.9363', '0.8568'] recall: ['0.9932', '0.9636', '0.7386'] IoU: ['0.9890', '0.9042', '0.6574'] mean IoU: 0.8502 [epoch: 15] global correct: 0.9900 precision: ['0.9949', '0.9578', '0.8632'] recall: ['0.9958', '0.9566', '0.7718'] IoU: ['0.9907', '0.9179', '0.6877'] mean IoU: 0.8654 [epoch: 16] global correct: 0.9883 precision: ['0.9934', '0.9515', '0.9021'] recall: ['0.9956', '0.9490', '0.6649'] IoU: ['0.9890', '0.9052', '0.6202'] mean IoU: 0.8381 [epoch: 17] global correct: 0.9872 precision: ['0.9968', '0.9233', '0.8308'] recall: ['0.9909', '0.9695', '0.7930'] IoU: ['0.9877', '0.8972', '0.6827'] mean IoU: 0.8559 [epoch: 18] global correct: 0.9892 precision: ['0.9956', '0.9533', '0.7558'] recall: ['0.9950', '0.9542', '0.8092'] IoU: ['0.9906', '0.9115', '0.6415'] mean IoU: 0.8479 [epoch: 19] global correct: 0.9900 precision: ['0.9953', '0.9607', '0.7851'] recall: ['0.9955', '0.9541', '0.8466'] IoU: ['0.9908', '0.9182', '0.6873'] mean IoU: 0.8655 [epoch: 20] global correct: 0.9908 precision: ['0.9958', '0.9579', '0.8697'] recall: ['0.9959', '0.9627', '0.7820'] IoU: ['0.9917', '0.9236', '0.6999'] mean IoU: 0.8718 [epoch: 21] global correct: 0.9909 precision: ['0.9958', '0.9620', '0.8168'] recall: ['0.9960', '0.9587', '0.8421'] IoU: ['0.9919', '0.9237', '0.7083'] mean IoU: 0.8746 [epoch: 22] global correct: 0.9901 precision: ['0.9958', '0.9555', '0.8057'] recall: ['0.9952', '0.9582', '0.8370'] IoU: ['0.9910', '0.9172', '0.6965'] mean IoU: 0.8682 [epoch: 23] global correct: 0.9892 precision: ['0.9941', '0.9596', '0.8125'] recall: ['0.9960', '0.9484', '0.7602'] IoU: ['0.9901', '0.9120', '0.6467'] mean IoU: 0.8496 [epoch: 24] global correct: 0.9914 precision: ['0.9954', '0.9646', '0.8794'] recall: ['0.9966', '0.9601', '0.8163'] IoU: ['0.9920', '0.9274', '0.7341'] mean IoU: 0.8845 [epoch: 25] global correct: 0.9915 precision: ['0.9966', '0.9581', '0.8648'] recall: ['0.9956', '0.9679', '0.8248'] IoU: ['0.9922', '0.9285', '0.7306'] mean IoU: 0.8838 [epoch: 26] global correct: 0.9911 precision: ['0.9954', '0.9677', '0.8118'] recall: ['0.9968', '0.9549', '0.8419'] IoU: ['0.9922', '0.9254', '0.7044'] mean IoU: 0.8740 [epoch: 27] global correct: 0.9909 precision: ['0.9949', '0.9668', '0.8507'] recall: ['0.9968', '0.9547', '0.8156'] IoU: ['0.9917', '0.9244', '0.7135'] mean IoU: 0.8765 [epoch: 28] global correct: 0.9915 precision: ['0.9961', '0.9622', '0.8627'] recall: ['0.9962', '0.9638', '0.8256'] IoU: ['0.9923', '0.9287', '0.7298'] mean IoU: 0.8836 [epoch: 29] global correct: 0.9918 precision: ['0.9965', '0.9638', '0.8329'] recall: ['0.9961', '0.9640', '0.8737'] IoU: ['0.9926', '0.9303', '0.7434'] mean IoU: 0.8888 [epoch: 30] global correct: 0.9922 precision: ['0.9967', '0.9640', '0.8614'] recall: ['0.9963', '0.9678', '0.8536'] IoU: ['0.9930', '0.9341', '0.7505'] mean IoU: 0.8925 [epoch: 31] global correct: 0.9918 precision: ['0.9957', '0.9682', '0.8608'] recall: ['0.9968', '0.9600', '0.8495'] IoU: ['0.9925', '0.9307', '0.7469'] mean IoU: 0.8900 [epoch: 32] global correct: 0.9925 precision: ['0.9964', '0.9676', '0.8808'] recall: ['0.9968', '0.9671', '0.8422'] IoU: ['0.9932', '0.9367', '0.7561'] mean IoU: 0.8953 [epoch: 33] global correct: 0.9921 precision: ['0.9967', '0.9640', '0.8487'] recall: ['0.9961', '0.9671', '0.8728'] IoU: ['0.9928', '0.9334', '0.7553'] mean IoU: 0.8938 [epoch: 34] global correct: 0.9924 precision: ['0.9966', '0.9689', '0.8306'] recall: ['0.9967', '0.9646', '0.8842'] IoU: ['0.9933', '0.9356', '0.7491'] mean IoU: 0.8927 [epoch: 35] global correct: 0.9924 precision: ['0.9966', '0.9677', '0.8564'] recall: ['0.9966', '0.9662', '0.8712'] IoU: ['0.9932', '0.9360', '0.7601'] mean IoU: 0.8964 [epoch: 36] global correct: 0.9925 precision: ['0.9969', '0.9636', '0.8933'] recall: ['0.9964', '0.9710', '0.8362'] IoU: ['0.9933', '0.9366', '0.7603'] mean IoU: 0.8967 [epoch: 37] global correct: 0.9923 precision: ['0.9967', '0.9662', '0.8411'] recall: ['0.9963', '0.9659', '0.8858'] IoU: ['0.9930', '0.9343', '0.7588'] mean IoU: 0.8954 [epoch: 38] global correct: 0.9925 precision: ['0.9965', '0.9680', '0.8575'] recall: ['0.9967', '0.9659', '0.8707'] IoU: ['0.9932', '0.9359', '0.7606'] mean IoU: 0.8966 [epoch: 39] global correct: 0.9926 precision: ['0.9964', '0.9690', '0.8756'] recall: ['0.9969', '0.9659', '0.8597'] IoU: ['0.9933', '0.9370', '0.7661'] mean IoU: 0.8988 [epoch: 40] global correct: 0.9927 precision: ['0.9962', '0.9697', '0.8911'] recall: ['0.9971', '0.9657', '0.8434'] IoU: ['0.9934', '0.9374', '0.7646'] mean IoU: 0.8985 [epoch: 41] global correct: 0.9928 precision: ['0.9967', '0.9684', '0.8846'] recall: ['0.9969', '0.9687', '0.8555'] IoU: ['0.9936', '0.9391', '0.7697'] mean IoU: 0.9008 [epoch: 42] global correct: 0.9927 precision: ['0.9966', '0.9677', '0.8726'] recall: ['0.9967', '0.9678', '0.8618'] IoU: ['0.9934', '0.9375', '0.7655'] mean IoU: 0.8988 [epoch: 43] global correct: 0.9928 precision: ['0.9965', '0.9690', '0.8867'] recall: ['0.9970', '0.9675', '0.8544'] IoU: ['0.9935', '0.9384', '0.7703'] mean IoU: 0.9007 [epoch: 44] global correct: 0.9929 precision: ['0.9969', '0.9659', '0.8952'] recall: ['0.9966', '0.9716', '0.8468'] IoU: ['0.9936', '0.9394', '0.7704'] mean IoU: 0.9011 [epoch: 45] global correct: 0.9928 precision: ['0.9966', '0.9688', '0.8891'] recall: ['0.9970', '0.9682', '0.8522'] IoU: ['0.9935', '0.9389', '0.7703'] mean IoU: 0.9009 [epoch: 46] global correct: 0.9928 precision: ['0.9966', '0.9693', '0.8773'] recall: ['0.9969', '0.9673', '0.8658'] IoU: ['0.9935', '0.9386', '0.7723'] mean IoU: 0.9014 [epoch: 47] global correct: 0.9929 precision: ['0.9968', '0.9677', '0.8852'] re