python – tensorflow对象检测从现有检查点微调模型

我正试图从现有的检查点训练一个模型
instructions.

我使用faster_rcnn_resnet101_voc07.config配置获得configured对象检测训练管道.

在检查点部分,我已经设置了预定义模型faster_rcnn_resnet101_coco.tar.gz的检查点文件所在的目录

根据这个issue,fine_tune_checkpoint可以是包含三个文件的目录的路径：(.data-00000-of-00001,.index,.Meta).

所以我设置了目录“/ home / docs / car_dataset / models / model / train”的路径

gradient_clipping_by_norm: 10.0
  fine_tune_checkpoint: "/home/docs/car_dataset/models/model/train"
  from_detection_checkpoint: true
  num_steps: 800000
  data_augmentation_options {
    random_horizontal_flip {
    }
  }

但是当我执行训练脚本时：

python object_detection/train.py     --logtostderr\
--pipeline_config_path=/home/docs/car_dataset/models/model/faster_rcnn_resnet101_voc07.config\
--train_dir=/home/docs/car_dataset/models/model/train\
--num_gpus=2

我收到了错误：

tensorflow.python.framework.errors_impl.DataLossError: Unable to open table file /home/docs/car_dataset/models/model/train: Failed precondition: /home/docs/car_dataset/models/model/train: perhaps your file is in a different file format and you need to use a different restore operator?

我也尝试过设置目录中每个文件的路径

fine_tune_checkpoint: "/home/docs/car_dataset/models/model/train/model.ckpt.Meta"

但我得到错误：

tensorflow.python.framework.errors_impl.DataLossError: Unable to open table file /home/docs/car_dataset/models/model/train/model.ckpt.Meta: Data loss: not an sstable (bad magic number): perhaps your file is in a different file format and you need to use a different restore operator?

在具有三个文件的管道配置中定义预训练模型的正确方法是什么：(.data-00000-of-00001,.index,.Meta).

Tensorflow版本：1.2.1

解决方法:

你要做的是指定没有“.Meta”,“.index”和“.data-00000-of-00001”扩展名的整个路径.在您的情况下,这看起来是：
“/home/docs/car_dataset/models/model/train/model.ckpt”(你会注意到它比目录更具体).