我正在尝试在包含苹果和辣椒的数据集上训练Tensorflow对象检测API . 为此,我生成了所需的文件(TFrecords和带注释的图像)并将它们放在models / research / object_detection目录中 . 然后,我从github分叉了Object detection api,并将我的文件推送到了forked repo . 然后,我在Google Collaboratory中克隆这个repo并运行train.py文件,但是我得到了DuplicateFlagError:master错误 .
---------------------------------------------------------------------------
DuplicateFlagError Traceback (most recent call last)
/content/models/research/object_detection/train.py in <module>()
56
57 flags = tf.app.flags
---> 58 flags.DEFINE_string('master', '', 'Name of the TensorFlow master to use.')
59 flags.DEFINE_integer('task', 0, 'task id')
60 flags.DEFINE_integer('num_clones', 1, 'Number of clones to deploy per worker.')
/usr/local/lib/python3.6/dist-packages/tensorflow/python/platform/flags.py in wrapper(*args, **kwargs)
56 'Use of the keyword argument names (flag_name, default_value, '
57 'docstring) is deprecated, please use (name, default, help) instead.')
---> 58 return original_function(*args, **kwargs)
59
60 return tf_decorator.make_decorator(original_function, wrapper)
/usr/local/lib/python3.6/dist-packages/absl/flags/_defines.py in DEFINE_string(name, default, help, flag_values, **args)
239 parser = _argument_parser.ArgumentParser()
240 serializer = _argument_parser.ArgumentSerializer()
--> 241 DEFINE(parser, name, default, help, flag_values, serializer, **args)
242
243
/usr/local/lib/python3.6/dist-packages/absl/flags/_defines.py in DEFINE(parser, name, default, help, flag_values, serializer, module_name, **args)
80 """
81 DEFINE_flag(_flag.Flag(parser, serializer, name, default, help, **args),
---> 82 flag_values, module_name)
83
84
/usr/local/lib/python3.6/dist-packages/absl/flags/_defines.py in DEFINE_flag(flag, flag_values, module_name)
102 # Copying the reference to flag_values prevents pychecker warnings.
103 fv = flag_values
--> 104 fv[flag.name] = flag
105 # Tell flag_values who's defining the flag.
106 if module_name:
/usr/local/lib/python3.6/dist-packages/absl/flags/_flagvalues.py in __setitem__(self, name, flag)
425 # module is simply being imported a subsequent time.
426 return
--> 427 raise _exceptions.DuplicateFlagError.from_flag(name, self)
428 short_name = flag.short_name
429 # If a new flag overrides an old one, we need to cleanup the old flag's
DuplicateFlagError: The flag 'master' is defined twice. First from object_detection/train.py, Second from object_detection/train.py. Description from first occurrence: Name of the TensorFlow master to use.
为了解决这个问题,我尝试对该行进行注释,但后来我在下一个标志上得到了DuplicateFlagError,即下一行 . 因此,为了尝试解决这个问题,我评论了train.py中声明这些标志的所有行,即我从第58行注释到第82行 . 但是,我得到了错误NotFoundError :;
---------------------------------------------------------------------------
NotFoundError Traceback (most recent call last)
/content/models/research/object_detection/train.py in <module>()
165
166 if __name__ == '__main__':
--> 167 tf.app.run()
/usr/local/lib/python3.6/dist-packages/tensorflow/python/platform/app.py in run(main, argv)
124 # Call the main function, passing through any arguments
125 # to the final program.
--> 126 _sys.exit(main(argv))
127
128
/content/models/research/object_detection/train.py in main(_)
105 ('input.config', FLAGS.input_config_path)]:
106 tf.gfile.Copy(config, os.path.join(FLAGS.train_dir, name),
--> 107 overwrite=True)
108
109 model_config = configs['model']
/usr/local/lib/python3.6/dist-packages/tensorflow/python/lib/io/file_io.py in copy(oldpath, newpath, overwrite)
390 with errors.raise_exception_on_not_ok_status() as status:
391 pywrap_tensorflow.CopyFile(
--> 392 compat.as_bytes(oldpath), compat.as_bytes(newpath), overwrite, status)
393
394
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/errors_impl.py in __exit__(self, type_arg, value_arg, traceback_arg)
514 None, None,
515 compat.as_text(c_api.TF_Message(self.status.status)),
--> 516 c_api.TF_GetCode(self.status.status))
517 # Delete the underlying status object from memory otherwise it stays alive
518 # as there is a reference to status from this from the traceback due to
NotFoundError: ; No such file or directory
我该怎么解决?这是我的Collab笔记本 - https://drive.google.com/file/d/1mZGOKX3JZXyG4XYkI6WHIXoNbRSpkE_F/view?usp=sharing
2 回答
从tensorflow / models Github存储库浏览你的colab笔记本和你修改过的fork之后,我就可以在本地机器上运行了 .
我得到了最新的tensorflow版本,即1.6,与Google Colab相同 .
您在
ssd_mobilenet_v1_coco.config
中指定的路径是data/object-detection.pbtxt
. 所以从models/research/object_detection
目录执行train.py .train.py
期望--pipeline_config_path
作为参数,但您已指定--pipeline_config
. 因此,如果您通过train.py
代码,您将意识到如果未指定--pipeline_config_path
,则它将配置文件名默认为models.config
,因此您将获得NotFoundError: ; No such file or directory
所以最后的命令应该是这样的:
正如上面链接中的评论建议:在第109行的
object_detection/data_decoders/tf_example_decoder.py
中删除dct_method=dct_method
.希望这可以帮助 .