测试Tensorflow对象检测时出错

时间:2017-06-19 21:01:35

标签: tensorflow object-detection

我已经尝试了所提到的object_detection模型安装的所有步骤 https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/installation.md

在测试文章最后一步中提到的安装时,我收到了以下错误。

ERROR: test_create_ssd_mobilenet_v1_model_from_config (__main__.ModelBuilderTest)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/Users/RonakBhavsar/eDAM/ML/ObjectRecognition/models/object_detection/builders/model_builder_test.py", line 193, in test_create_ssd_mobilenet_v1_model_from_config
    model = self.create_model(model_proto)
  File "/Users/RonakBhavsar/eDAM/ML/ObjectRecognition/models/object_detection/builders/model_builder_test.py", line 53, in create_model
    return model_builder.build(model_config, is_training=False)
  File "/Users/RonakBhavsar/eDAM/ML/ObjectRecognition/models/object_detection/builders/model_builder.py", line 73, in build
    return _build_ssd_model(model_config.ssd, is_training)
  File "/Users/RonakBhavsar/eDAM/ML/ObjectRecognition/models/object_detection/builders/model_builder.py", line 126, in _build_ssd_model
    is_training)
  File "/Users/RonakBhavsar/eDAM/ML/ObjectRecognition/models/object_detection/builders/model_builder.py", line 98, in _build_ssd_feature_extractor
    feature_extractor_config.conv_hyperparams, is_training)
  File "/Users/RonakBhavsar/eDAM/ML/ObjectRecognition/models/object_detection/builders/hyperparams_builder.py", line 70, in build
    hyperparams_config.regularizer),
  File "/Users/RonakBhavsar/eDAM/ML/ObjectRecognition/models/object_detection/builders/hyperparams_builder.py", line 119, in _build_regularizer
    return slim.l2_regularizer(scale=regularizer.l2_regularizer.weight)
  File "/Users/RonakBhavsar/anaconda2/lib/python2.7/site-packages/tensorflow/contrib/layers/python/layers/regularizers.py", line 92, in l2_regularizer
    raise ValueError('scale cannot be an integer: %s' % (scale,))
ValueError: scale cannot be an integer: 1

我在测试脚本中提到的所有模型都出现此错误。有人有什么想法吗?

1 个答案:

答案 0 :(得分:1)

我们有一个pull request可以解决这个问题。请试一试。