mmdetection-2.1.0训练数据

0.遇到训练问题

./tool/dish_train.sh

RuntimeError: Expected to have finished reduction in the prior iteration before starting a new one. This error indicates that your module has parameters that were not used in producing loss. You can enable unused parameter detection by (1) passing the keyword argument `find_unused_parameters=True` to `torch.nn.parallel.DistributedDataParallel`; (2) making sure all `forward` function outputs participate in calculating loss. If you already have done the above two steps, then the distributed data parallel module wasn't able to locate the output tensors in the return value of your module's `forward` function. Please include the loss function and the structure of the return value of `forward` of your module when reporting this issue (e.g. list, dict, iterable). (prepare_for_backward at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:518) 

问题解决：

vim mmdet/apis/train.py

    # put model on gpus
    if distributed:
        find_unused_parameters = True #cfg.get('find_unused_parameters', False)
        # Sets the `find_unused_parameters` parameter in
        # torch.nn.parallel.DistributedDataParallel
        model = MMDistributedDataParallel(
            model.cuda(),
            device_ids=[torch.cuda.current_device()],
            broadcast_buffers=False,
            find_unused_parameters=find_unused_parameters)
    else:
        model = MMDataParallel(
            model.cuda(cfg.gpu_ids[0]), device_ids=cfg.gpu_ids)

网上是这样修改，但是这是存在问题的

单卡用户建议使用python train.py

1.改类别数

vim configs/ms_rcnn/ms_rcnn_r50_fpn_1x_coco.py

vim configs/_base_/models/mask_rcnn_r50_fpn.py

新版本的改类别需要改这两个文件：

我是一类，所以num_classes=1