基于Swin-Unet自适应多尺度训练、多类别分割、迁移学习：人体脊椎分割（6分割）【包含数据、代码、训练好的结果等等】

[train hyper-parameters: Namespace(batch_size=8, epochs=10, lr=0.005, lrf=0.01)] [epoch: 1] global correct: 0.9499 precision: ['0.9506', '0.1667', '0.1084', '0.1356', '0.0559', '0.0364'] recall: ['0.9997', '0.0001', '0.0002', '0.0082', '0.0002', '0.0005'] IoU: ['0.9503', '0.0001', '0.0002', '0.0078', '0.0002', '0.0005'] mean IoU: 0.1598 [epoch: 2] global correct: 0.9495 precision: ['0.9579', '0.2632', '0.2353', '0.2039', '0.1255', '0.0317'] recall: ['0.9976', '0.0001', '0.0136', '0.0987', '0.0499', '0.0024'] IoU: ['0.9556', '0.0001', '0.0130', '0.0712', '0.0370', '0.0023'] mean IoU: 0.1799 [epoch: 3] global correct: 0.9515 precision: ['0.9698', '0.0000', '0.1934', '0.2150', '0.1779', '0.0639'] recall: ['0.9966', '0.0000', '0.0178', '0.2456', '0.1826', '0.0018'] IoU: ['0.9666', '0.0000', '0.0166', '0.1295', '0.0990', '0.0017'] mean IoU: 0.2022 [epoch: 4] global correct: 0.9520 precision: ['0.9654', '0.0000', '0.1926', '0.2280', '0.1916', '0.1779'] recall: ['0.9980', '0.0000', '0.0033', '0.2057', '0.1512', '0.0011'] IoU: ['0.9636', '0.0000', '0.0033', '0.1212', '0.0923', '0.0011'] mean IoU: 0.1969 [epoch: 5] global correct: 0.9530 precision: ['0.9736', '0.0000', '0.1823', '0.2173', '0.2034', '0.2699'] recall: ['0.9971', '0.0000', '0.0078', '0.3020', '0.2338', '0.0037'] IoU: ['0.9708', '0.0000', '0.0075', '0.1446', '0.1221', '0.0037'] mean IoU: 0.2081 [epoch: 6] global correct: 0.9531 precision: ['0.9722', '0.0000', '0.1941', '0.2291', '0.1999', '0.2854'] recall: ['0.9973', '0.0000', '0.0062', '0.3057', '0.2084', '0.0084'] IoU: ['0.9697', '0.0000', '0.0060', '0.1507', '0.1136', '0.0083'] mean IoU: 0.2081 [epoch: 7] global correct: 0.9531 precision: ['0.9758', '0.0000', '0.2015', '0.2220', '0.1975', '0.3028'] recall: ['0.9966', '0.0000', '0.0086', '0.3185', '0.2660', '0.0114'] IoU: ['0.9725', '0.0000', '0.0083', '0.1505', '0.1278', '0.0111'] mean IoU: 0.2117 [epoch: 8] global correct: 0.9532 precision: ['0.9738', '0.0000', '0.2022', '0.2238', '0.2042', '0.3003'] recall: ['0.9971', '0.0000', '0.0090', '0.2894', '0.2516', '0.0146'] IoU: ['0.9710', '0.0000', '0.0087', '0.1444', '0.1270', '0.0141'] mean IoU: 0.2109 [epoch: 9] global correct: 0.9532 precision: ['0.9757', '0.0000', '0.1961', '0.2201', '0.2017', '0.2957'] recall: ['0.9967', '0.0000', '0.0086', '0.3082', '0.2696', '0.0165'] IoU: ['0.9725', '0.0000', '0.0083', '0.1473', '0.1304', '0.0159'] mean IoU: 0.2124 [epoch: 10] global correct: 0.9534 precision: ['0.9732', '0.0000', '0.2090', '0.2303', '0.2084', '0.2833'] recall: ['0.9974', '0.0000', '0.0073', '0.2876', '0.2480', '0.0170'] IoU: ['0.9707', '0.0000', '0.0071', '0.1466', '0.1277', '0.0163'] mean IoU: 0.2114