我试图从现有检查点跟随这些 instructions来训练模型。张量流对象检测从现有检查点微调模型
我有configured对象检测训练管道使用faster_rcnn_resnet101_voc07.config配置。
在检查站段我已经设置,其中位于预训练模型faster_rcnn_resnet101_coco.tar.gz
Acording的的检查点文件,这issue的fine_tune_checkpoint可以是包含三个文件的目录路径的目录:(。 data-00000-of-00001,.index,.meta)。
所以我设置的目录路径 “的/ home /文档/ car_dataset /模型/模型/火车”
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 {
}
}
然而,当我执行脚本的训练:
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
我得到了错误:
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?
我也试过设置pa TH到每个文件在目录
fine_tune_checkpoint: "/home/docs/car_dataset/models/model/train/model.ckpt.meta"
,但我得到的错误:
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?
什么是定义在具有三个文件管道配置训练模型前的正确方法:(。数据-00001,-index,.meta)。
Tensorflow版本: 1.2.1