我正在尝试按照本教程创建自定义对象检测模型：https://towardsdatascience.com/custom-object-detection-using-tensorflow-from-scratch-e61da2e10087
在步骤 10 之前一切正常，我必须使用 train.py 脚本(使用 tensorflow 1(训练我的模型。
当我运行脚本 (macOS( 时：
python3 train.py --alsologtostderr --train_dir=train --pipeline_config_path=/Users/sol.arabehety/Desktop/models-master/ssd_mobilenet_v2_coco.config
我收到此错误：
File "/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/contrib/framework/python/ops/arg_scope.py", line 152, in arg_scope
_name_op(op))
ValueError: ('%s is not decorated with @add_arg_scope', ('nets.mobilenet.mobilenet', 'depth_multiplier'))
我 https://stackoverflow.com/a/53038290/1269404 找到了这个解决方案，但我不知道在哪里添加@add_arg_scope标签，你能帮我吗？
这是arg_scope.py文件： https://github.com/google-research/tf-slim/blob/master/tf_slim/ops/arg_scope.py(第 152 行(
这是完整的错误：
models-master$ sudo python3 train.py --alsologtostderr --train_dir=train --pipeline_config_path=/Users/sol.arabehety/Desktop/models-master/ssd_mobilenet_v2_coco.config
/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/python/framework/dtypes.py:526: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/python/framework/dtypes.py:527: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/python/framework/dtypes.py:528: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/python/framework/dtypes.py:529: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/python/framework/dtypes.py:530: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/python/framework/dtypes.py:535: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
* https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
* https://github.com/tensorflow/addons
If you depend on functionality not listed there, please file an issue.
WARNING:tensorflow:From /Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/python/platform/app.py:125: main (from __main__) is deprecated and will be removed in a future version.
Instructions for updating:
Use object_detection/model_main.py.
WARNING:tensorflow:From /Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/object_detection/legacy/trainer.py:266: create_global_step (from tensorflow.contrib.framework.python.ops.variables) is deprecated and will be removed in a future version.
Instructions for updating:
Please switch to tf.train.create_global_step
WARNING:tensorflow:From /Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.
WARNING:tensorflow:From /Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/object_detection/core/preprocessor.py:188: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version.
Instructions for updating:
`seed2` arg is deprecated.Use sample_distorted_bounding_box_v2 instead.
WARNING:tensorflow:From /Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/object_detection/core/batcher.py:96: batch (from tensorflow.python.training.input) is deprecated and will be removed in a future version.
Instructions for updating:
Queue-based input pipelines have been replaced by `tf.data`. Use `tf.data.Dataset.batch(batch_size)` (or `padded_batch(...)` if `dynamic_pad=True`).
WARNING:tensorflow:From /Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/python/training/input.py:753: QueueRunner.__init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.
Instructions for updating:
To construct input pipelines, use the `tf.data` module.
WARNING:tensorflow:From /Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/python/training/input.py:753: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.
Instructions for updating:
To construct input pipelines, use the `tf.data` module.
WARNING:tensorflow:From /Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/python/training/input.py:784: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.cast instead.
Traceback (most recent call last):
File "train.py", line 186, in <module>
tf.app.run()
File "/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/python/util/deprecation.py", line 324, in new_func
return func(*args, **kwargs)
File "train.py", line 182, in main
graph_hook_fn=graph_rewriter_fn)
File "/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/object_detection/legacy/trainer.py", line 291, in train
clones = model_deploy.create_clones(deploy_config, model_fn, [input_queue])
File "/Users/sol.arabehety/Desktop/models-master/research/slim/deployment/model_deploy.py", line 192, in create_clones
outputs = model_fn(*args, **kwargs)
File "/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/object_detection/legacy/trainer.py", line 204, in _create_losses
prediction_dict = detection_model.predict(images, true_image_shapes)
File "/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/object_detection/meta_architectures/ssd_meta_arch.py", line 568, in predict
preprocessed_inputs)
File "/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/object_detection/models/ssd_mobilenet_v2_feature_extractor.py", line 118, in extract_features
[mobilenet.depth_multiplier], min_depth=self._min_depth):
File "/usr/local/Cellar/python/3.7.7/Frameworks/Python.framework/Versions/3.7/lib/python3.7/contextlib.py", line 112, in __enter__
return next(self.gen)
File "/Users/sol.arabehety/Library/Python/3.7/lib/python/site-packages/tensorflow/contrib/framework/python/ops/arg_scope.py", line 152, in arg_scope
_name_op(op))
ValueError: ('%s is not decorated with @add_arg_scope', ('nets.mobilenet.mobilenet', 'depth_multiplier'))
您的链接显示了问题。在那里，程序员必须找到主要的瓶颈功能。因此，在您的情况下，您必须在nets.mobilenet.mobilenet上找到depth_multiplier。如果最后一个是在为模型选择主干期间下载的内容，那么您就处于死胡同。抱歉，您必须使用 Tensorflow v2 进行训练。最好遵循Tensorflow github上的说明。如果你有，我很乐意帮忙。数据集。
如果我想训练，我会遵循这个。这是带有示例的最安全的解决方案。在里面你可以找到如何带上你自己的数据集。这是最难的部分，因为准备正确需要时间！
所以我有完全相同的问题，我相信。修复它的唯一方法是实际注释掉add_arg_scope的检查。就我而言，我必须找到E：\anaconda3\envs\myenv\Lib\site-packages\tensorflow_core\contrib\framework\python\ops\arg_scope.py并开始完成步骤。