File "E:/Swin-Transformer-Semantic-Segmentation-main/tools/train.py", line 163, in
main()
File "E:/Swin-Transformer-Semantic-Segmentation-main/tools/train.py", line 152, in main
train_segmentor(
File "E:\Swin-Transformer-Semantic-Segmentation-main\mmseg\apis\train.py", line 118, in train_segmentor
runner.run(data_loaders, cfg.workflow)
File "D:\anaconda\envs\swinseg\lib\site-packages\mmcv\runner\iter_based_runner.py", line 134, in run
iter_runner(iter_loaders[i], **kwargs)
File "D:\anaconda\envs\swinseg\lib\site-packages\mmcv\runner\iter_based_runner.py", line 67, in train
self.call_hook('after_train_iter')
File "D:\anaconda\envs\swinseg\lib\site-packages\mmcv\runner\base_runner.py", line 309, in call_hook
getattr(hook, fn_name)(self)
File "E:\Swin-Transformer-Semantic-Segmentation-main\mmseg\core\evaluation\eval_hooks.py", line 31, in after_train_iter
self.evaluate(runner, results)
File "E:\Swin-Transformer-Semantic-Segmentation-main\mmseg\core\evaluation\eval_hooks.py", line 44, in evaluate
eval_res = self.dataloader.dataset.evaluate(
File "E:\Swin-Transformer-Semantic-Segmentation-main\mmseg\datasets\custom.py", line 337, in evaluate
ret_metrics = eval_metrics(
File "E:\Swin-Transformer-Semantic-Segmentation-main\mmseg\core\evaluation\metrics.py", line 210, in eval_metrics
total_area_label = total_intersect_and_union(results, gt_seg_maps,
File "E:\Swin-Transformer-Semantic-Segmentation-main\mmseg\core\evaluation\metrics.py", line 95, in total_intersect_and_union
intersect_and_union(results[i], gt_seg_maps[i], num_classes,
File "E:\Swin-Transformer-Semantic-Segmentation-main\mmseg\core\evaluation\metrics.py", line 48, in intersect_and_union
pred_label = pred_label[mask]
IndexError: boolean index did not match indexed array along dimension 0; dimension is 1500 but corresponding boolean dimension is 3001
When I used swin Transformer training my datasets, it came out this kind of problem, is that the reason?
microsoft
