ValueError: Tried to convert 't' to a tensor and failed. Error: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted [].

[gharis]

(tensorflow1) C:\tensorflow1\models\research\object_detection>python train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_inception_v2_pets.config
INFO:tensorflow:Scale of 0 disables regularizer.
INFO:tensorflow:Scale of 0 disables regularizer.
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\trainer.py:228: 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
INFO:tensorflow:Scale of 0 disables regularizer.
INFO:tensorflow:Scale of 0 disables regularizer.
INFO:tensorflow:depth of additional conv before box predictor: 0
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\core\box_predictor.py:396: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\core\losses.py:316: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.
Instructions for updating:

Future major versions of TensorFlow will allow gradients to flow
into the labels input on backprop by default.

See tf.nn.softmax_cross_entropy_with_logits_v2.

Traceback (most recent call last):
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 510, in _apply_op_helper
preferred_dtype=default_dtype)
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\ops.py", line 1036, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\constant_op.py", line 235, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\constant_op.py", line 214, in constant
value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 442, in make_tensor_proto
_GetDenseDimensions(values)))
ValueError: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted [].

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 524, in _apply_op_helper
values, as_ref=input_arg.is_ref).dtype.name
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\ops.py", line 1036, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\constant_op.py", line 235, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\constant_op.py", line 214, in constant
value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 442, in make_tensor_proto
_GetDenseDimensions(values)))
ValueError: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted [].

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "train.py", line 167, in
tf.app.run()
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\platform\app.py", line 126, in run
_sys.exit(main(argv))
File "train.py", line 163, in main
worker_job_name, is_chief, FLAGS.train_dir)
File "C:\tensorflow1\models\research\object_detection\trainer.py", line 255, in train
train_config.optimizer)
File "C:\tensorflow1\models\research\object_detection\builders\optimizer_builder.py", line 50, in build
learning_rate = _create_learning_rate(config.learning_rate)
File "C:\tensorflow1\models\research\object_detection\builders\optimizer_builder.py", line 109, in _create_learning_rate
learning_rate_sequence, config.warmup)
File "C:\tensorflow1\models\research\object_detection\utils\learning_schedules.py", line 169, in manual_stepping
[0] * num_boundaries))
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\ops\array_ops.py", line 2619, in where
return gen_math_ops._select(condition=condition, x=x, y=y, name=name)
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 4503, in _select
"Select", condition=condition, t=x, e=y, name=name)
File "C:\anaconda\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 528, in _apply_op_helper
(input_name, err))
ValueError: Tried to convert 't' to a tensor and failed. Error: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted [].

(tensorflow1) C:\tensorflow1\models\research\object_detection>

I got this error when running train.py command. can you help?

[epratheeban]

It's easy. Go to the utils folder. Find the learning_schedules.py file. Go to the line 167. And replace the line 167 with below

rate_index = tf.reduce_max(tf.where(tf.greater_equal(global_step, boundaries),
                                      list(range(num_boundaries)),
                                      [0] * num_boundaries))

[EdjeElectronics]

Thanks epratheeban! gharis, please re-open this issue if that did not fix the problem.

[dharanidhar12]

sir can you please help me with this am getting this error...

(tensorflow1) C:\tensorflow1\models\research\object_detection>python train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_inception_v2_pets.config
WARNING:tensorflow:From C:\Users\SBI\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\contrib\learn\python\learn
datasets\base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed
in a future version.
Instructions for updating:
Use the retry module or similar alternatives.
Traceback (most recent call last):
File "train.py", line 49, in
from object_detection import trainer
File "C:\Users\SBI\Anaconda3\envs\tensorflow1\lib\site-packages\object_detection-0.1-py3.6.egg\object_detection
trainer.py", line 33, in
from deployment import model_deploy
ModuleNotFoundError: No module named 'deployment'

(tensorflow1) C:\tensorflow1\models\research\object_detection>

[F4H4D-87]

WARNING:tensorflow:From C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Use the retry module or similar alternatives.
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\trainer.py:257: 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
INFO:tensorflow:Scale of 0 disables regularizer.
INFO:tensorflow:Scale of 0 disables regularizer.
INFO:tensorflow:depth of additional conv before box predictor: 0
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\core\box_predictor.py:400: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
INFO:tensorflow:Scale of 0 disables regularizer.
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\core\losses.py:316: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.
Instructions for updating:

Future major versions of TensorFlow will allow gradients to flow
into the labels input on backprop by default.

See tf.nn.softmax_cross_entropy_with_logits_v2.

Traceback (most recent call last):
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 510, in _apply_op_helper
preferred_dtype=default_dtype)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\ops.py", line 1040, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\constant_op.py", line 235, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\constant_op.py", line 214, in constant
value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 442, in make_tensor_proto
_GetDenseDimensions(values)))
ValueError: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted [].

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 524, in _apply_op_helper
values, as_ref=input_arg.is_ref).dtype.name
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\ops.py", line 1040, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\constant_op.py", line 235, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\constant_op.py", line 214, in constant
value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 442, in make_tensor_proto
_GetDenseDimensions(values)))
ValueError: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted [].

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "train.py", line 167, in
tf.app.run()
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\platform\app.py", line 126, in run
_sys.exit(main(argv))
File "train.py", line 163, in main
worker_job_name, is_chief, FLAGS.train_dir)
File "C:\tensorflow1\models\research\object_detection\trainer.py", line 284, in train
train_config.optimizer)
File "C:\tensorflow1\models\research\object_detection\builders\optimizer_builder.py", line 50, in build
learning_rate = _create_learning_rate(config.learning_rate)
File "C:\tensorflow1\models\research\object_detection\builders\optimizer_builder.py", line 109, in _create_learning_rate
learning_rate_sequence, config.warmup)
File "C:\tensorflow1\models\research\object_detection\utils\learning_schedules.py", line 169, in manual_stepping
[0] * num_boundaries))
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\ops\array_ops.py", line 2650, in where
return gen_math_ops.select(condition=condition, x=x, y=y, name=name)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 7112, in select
"Select", condition=condition, t=x, e=y, name=name)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 528, in _apply_op_helper
(input_name, err))
ValueError: Tried to convert 't' to a tensor and failed. Error: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted [].

(tensorflow1) C:\tensorflow1\models\research\object_detection>python train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_inception_v2_pets.config
WARNING:tensorflow:From C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Use the retry module or similar alternatives.
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\trainer.py:257: 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
INFO:tensorflow:Scale of 0 disables regularizer.
INFO:tensorflow:Scale of 0 disables regularizer.
INFO:tensorflow:depth of additional conv before box predictor: 0
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\core\box_predictor.py:400: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
INFO:tensorflow:Scale of 0 disables regularizer.
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\core\losses.py:316: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.
Instructions for updating:

Future major versions of TensorFlow will allow gradients to flow
into the labels input on backprop by default.

See tf.nn.softmax_cross_entropy_with_logits_v2.

Traceback (most recent call last):
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 510, in _apply_op_helper
preferred_dtype=default_dtype)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\ops.py", line 1040, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\constant_op.py", line 235, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\constant_op.py", line 214, in constant
value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 442, in make_tensor_proto
_GetDenseDimensions(values)))
ValueError: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted [].

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 524, in _apply_op_helper
values, as_ref=input_arg.is_ref).dtype.name
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\ops.py", line 1040, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\constant_op.py", line 235, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\constant_op.py", line 214, in constant
value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 442, in make_tensor_proto
_GetDenseDimensions(values)))
ValueError: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted [].

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "train.py", line 167, in
tf.app.run()
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\platform\app.py", line 126, in run
_sys.exit(main(argv))
File "train.py", line 163, in main
worker_job_name, is_chief, FLAGS.train_dir)
File "C:\tensorflow1\models\research\object_detection\trainer.py", line 284, in train
train_config.optimizer)
File "C:\tensorflow1\models\research\object_detection\builders\optimizer_builder.py", line 50, in build
learning_rate = _create_learning_rate(config.learning_rate)
File "C:\tensorflow1\models\research\object_detection\builders\optimizer_builder.py", line 109, in _create_learning_rate
learning_rate_sequence, config.warmup)
File "C:\tensorflow1\models\research\object_detection\utils\learning_schedules.py", line 169, in manual_stepping
[0] * num_boundaries))
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\ops\array_ops.py", line 2650, in where
return gen_math_ops.select(condition=condition, x=x, y=y, name=name)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 7112, in select
"Select", condition=condition, t=x, e=y, name=name)
File "C:\Users\fahad\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 528, in _apply_op_helper
(input_name, err))
ValueError: Tried to convert 't' to a tensor and failed. Error: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted [].

i go this error then i did like (epratheeban ) i changed 167 line then i got another error

Traceback (most recent call last):
File "train.py", line 49, in
from object_detection import trainer
File "C:\tensorflow1\models\research\object_detection\trainer.py", line 26, in
from object_detection.builders import optimizer_builder
File "C:\tensorflow1\models\research\object_detection\builders\optimizer_builder.py", line 19, in
from object_detection.utils import learning_schedules
File "C:\tensorflow1\models\research\object_detection\utils\learning_schedules.py", line 167
rate_index = tf.reduce_max(tf.where(tf.greater_equal(global_step, boundaries),
^
IndentationError: unindent does not match any outer indentation level

please help me i need it sooooooo bad

[italojs]

see this solution here: #3705 (comment)

[doggy0116]

(tensorflow1) C:\tensorflow1\models\research\object_detection>python train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_inception_v2_pets.config
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\trainer.py:257: 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
INFO:tensorflow:Scale of 0 disables regularizer.
INFO:tensorflow:Scale of 0 disables regularizer.
INFO:tensorflow:depth of additional conv before box predictor: 0
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\core\box_predictor.py:400: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
INFO:tensorflow:Scale of 0 disables regularizer.
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\core\losses.py:316: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.
Instructions for updating:

Future major versions of TensorFlow will allow gradients to flow
into the labels input on backprop by default.

See @{tf.nn.softmax_cross_entropy_with_logits_v2}.

Traceback (most recent call last):
File "train.py", line 167, in
tf.app.run()
File "C:\Users\DEVIP\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\platform\app.py", line 126, in run
_sys.exit(main(argv))
File "train.py", line 163, in main
worker_job_name, is_chief, FLAGS.train_dir)
File "C:\tensorflow1\models\research\object_detection\trainer.py", line 284, in train
train_config.optimizer)
File "C:\tensorflow1\models\research\object_detection\builders\optimizer_builder.py", line 50, in build
learning_rate = _create_learning_rate(config.learning_rate)
File "C:\tensorflow1\models\research\object_detection\builders\optimizer_builder.py", line 109, in _create_learning_rate
learning_rate_sequence, config.warmup)
File "C:\tensorflow1\models\research\object_detection\utils\learning_schedules.py", line 156, in manual_stepping
raise ValueError('First step cannot be zero.')
ValueError: First step cannot be zero.

(tensorflow1) C:\tensorflow1\models\research\object_detection>

---

I got this error when I run the trainning.
Please help me...
I'll really appreciate you.

[hashirali2604]

C:\models-master\research\object_detection\legacy>python train.py --logtostderr --train_dir=../training/ --pipeline_config_path=../training/ssd_mobilenet_v2_coco.config
WARNING:tensorflow:From C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\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.
W1009 19:40:49.990331 15724 tf_logging.py:125] From C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\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 C:\models-master\research\object_detection\legacy\trainer.py:265: 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
W1009 19:40:50.134185 15724 tf_logging.py:125] From C:\models-master\research\object_detection\legacy\trainer.py:265: 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
Traceback (most recent call last):
File "C:\models-master\research\object_detection\utils\label_map_util.py", line 136, in load_labelmap
text_format.Merge(label_map_string, label_map)
File "C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\site-packages\google\protobuf\text_format.py", line 536, in Merge
descriptor_pool=descriptor_pool)
File "C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\site-packages\google\protobuf\text_format.py", line 590, in MergeLines
return parser.MergeLines(lines, message)
File "C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\site-packages\google\protobuf\text_format.py", line 623, in MergeLines
self._ParseOrMerge(lines, message)
File "C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\site-packages\google\protobuf\text_format.py", line 638, in _ParseOrMerge
self._MergeField(tokenizer, message)
File "C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\site-packages\google\protobuf\text_format.py", line 763, in _MergeField
merger(tokenizer, message, field)
File "C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\site-packages\google\protobuf\text_format.py", line 837, in _MergeMessageField
self._MergeField(tokenizer, sub_message)
File "C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\site-packages\google\protobuf\text_format.py", line 763, in _MergeField
merger(tokenizer, message, field)
File "C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\site-packages\google\protobuf\text_format.py", line 888, in _MergeScalarField
value = tokenizer.ConsumeString()
File "C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\site-packages\google\protobuf\text_format.py", line 1251, in ConsumeString
the_bytes = self.ConsumeByteString()
File "C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\site-packages\google\protobuf\text_format.py", line 1266, in ConsumeByteString
the_list = [self._ConsumeSingleByteString()]
File "C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\site-packages\google\protobuf\text_format.py", line 1285, in _ConsumeSingleByteString
raise self.ParseError('Expected string but found: %r' % (text,))
google.protobuf.text_format.ParseError: 3:8 : Expected string but found: 'amalgam_gun'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "train.py", line 184, in
tf.app.run()
File "C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\platform\app.py", line 125, in run
_sys.exit(main(argv))
File "C:\Users\Hashir Ali\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\util\deprecation.py", line 306, in new_func
return func(*args, **kwargs)
File "train.py", line 180, in main
graph_hook_fn=graph_rewriter_fn)
File "C:\models-master\research\object_detection\legacy\trainer.py", line 279, in train
train_config.prefetch_queue_capacity, data_augmentation_options)
File "C:\models-master\research\object_detection\legacy\trainer.py", line 59, in create_input_queue
tensor_dict = create_tensor_dict_fn()
File "train.py", line 121, in get_next
dataset_builder.build(config)).get_next()
File "C:\models-master\research\object_detection\builders\dataset_builder.py", line 123, in build
num_additional_channels=input_reader_config.num_additional_channels)
File "C:\models-master\research\object_detection\data_decoders\tf_example_decoder.py", line 297, in init
default_value=''),
File "C:\models-master\research\object_detection\data_decoders\tf_example_decoder.py", line 59, in init
label_map_proto_file, use_display_name=False)
File "C:\models-master\research\object_detection\utils\label_map_util.py", line 164, in get_label_map_dict
label_map = load_labelmap(label_map_path)
File "C:\models-master\research\object_detection\utils\label_map_util.py", line 138, in load_labelmap
label_map.ParseFromString(label_map_string)
TypeError: a bytes-like object is required, not 'str'

getting this error upon running train.py..... can anyone giude me please???
tried rewriting commas "" but still not solve

[gnanimail]

I got the below error when I hit

python train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_inception_v2_pets.config

Traceback (most recent call last):
File "train.py", line 184, in
tf.app.run()
File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\platform\app.py", line 125, in run
_sys.exit(main(argv))
File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\util\deprecation.py", line 272, in new_func
return func(*args, **kwargs)
File "train.py", line 180, in main
graph_hook_fn=graph_rewriter_fn)
File "C:..\models\research\object_detection\legacy\trainer.py", line 303, in train
train_config.optimizer)
File "C:..\models\research\object_detection\builders\optimizer_builder.py", line 50, in build
learning_rate = _create_learning_rate(config.learning_rate)
File "C:..\models\research\object_detection\builders\optimizer_builder.py", line 112, in _create_learning_rate
learning_rate_sequence, config.warmup)
File "C:..\models\research\object_detection\utils\learning_schedules.py", line 160, in manual_stepping
raise ValueError('First step cannot be zero.')
ValueError: First step cannot be zero.

Appreciate your help thanks

[daiguel]

did you find out how to solve your error @gnanimail
???§§§

[aminemosbah]

(tensorflow1) C:\tensorflow1\models\research\object_detection>python train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_inception_v2_pets.config
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\trainer.py:257: 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
INFO:tensorflow:Scale of 0 disables regularizer.
INFO:tensorflow:Scale of 0 disables regularizer.
INFO:tensorflow:depth of additional conv before box predictor: 0
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\core\box_predictor.py:400: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
INFO:tensorflow:Scale of 0 disables regularizer.
WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\core\losses.py:316: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.
Instructions for updating:

Future major versions of TensorFlow will allow gradients to flow
into the labels input on backprop by default.

See @{tf.nn.softmax_cross_entropy_with_logits_v2}.

Traceback (most recent call last):
File "train.py", line 167, in
tf.app.run()
File "C:\Users\DEVIP\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\platform\app.py", line 126, in run
_sys.exit(main(argv))
File "train.py", line 163, in main
worker_job_name, is_chief, FLAGS.train_dir)
File "C:\tensorflow1\models\research\object_detection\trainer.py", line 284, in train
train_config.optimizer)
File "C:\tensorflow1\models\research\object_detection\builders\optimizer_builder.py", line 50, in build
learning_rate = _create_learning_rate(config.learning_rate)
File "C:\tensorflow1\models\research\object_detection\builders\optimizer_builder.py", line 109, in _create_learning_rate
learning_rate_sequence, config.warmup)
File "C:\tensorflow1\models\research\object_detection\utils\learning_schedules.py", line 156, in manual_stepping
raise ValueError('First step cannot be zero.')
ValueError: First step cannot be zero.

(tensorflow1) C:\tensorflow1\models\research\object_detection>

I got this error when I run the trainning.
Please help me...
I'll really appreciate you.

the same problem here seems unmitigated error ????

[Harshavardhan18]

Hi, that was a great tutorial on implementing the API for custom object detection but unfortunately i'm stuck in step 6 i.e, training the rcnn. When i ran the command for training i'm getting the following exceptions. Can you please help me to sort it.
Thanks in advance
Please switch to tf.train.create_global_step
Traceback (most recent call last):
File "D:\tensorflow\models\research\object_detection\utils\label_map_util.py", line 136, in load_labelmap
text_format.Merge(label_map_string, label_map)
File "C:\Users\Harsha527\Miniconda3\envs\tensorflow\lib\site-packages\google\protobuf\text_format.py", line 536, in Merge
descriptor_pool=descriptor_pool)
File "C:\Users\Harsha527\Miniconda3\envs\tensorflow\lib\site-packages\google\protobuf\text_format.py", line 590, in MergeLines
return parser.MergeLines(lines, message)
File "C:\Users\Harsha527\Miniconda3\envs\tensorflow\lib\site-packages\google\protobuf\text_format.py", line 623, in MergeLines
self._ParseOrMerge(lines, message)
File "C:\Users\Harsha527\Miniconda3\envs\tensorflow\lib\site-packages\google\protobuf\text_format.py", line 638, in _ParseOrMerge
self._MergeField(tokenizer, message)
File "C:\Users\Harsha527\Miniconda3\envs\tensorflow\lib\site-packages\google\protobuf\text_format.py", line 763, in _MergeField
merger(tokenizer, message, field)
File "C:\Users\Harsha527\Miniconda3\envs\tensorflow\lib\site-packages\google\protobuf\text_format.py", line 837, in _MergeMessageField
self._MergeField(tokenizer, sub_message)
File "C:\Users\Harsha527\Miniconda3\envs\tensorflow\lib\site-packages\google\protobuf\text_format.py", line 763, in _MergeField
merger(tokenizer, message, field)
File "C:\Users\Harsha527\Miniconda3\envs\tensorflow\lib\site-packages\google\protobuf\text_format.py", line 888, in _MergeScalarField
value = tokenizer.ConsumeString()
File "C:\Users\Harsha527\Miniconda3\envs\tensorflow\lib\site-packages\google\protobuf\text_format.py", line 1251, in ConsumeString
the_bytes = self.ConsumeByteString()
File "C:\Users\Harsha527\Miniconda3\envs\tensorflow\lib\site-packages\google\protobuf\text_format.py", line 1266, in ConsumeByteString
the_list = [self._ConsumeSingleByteString()]
File "C:\Users\Harsha527\Miniconda3\envs\tensorflow\lib\site-packages\google\protobuf\text_format.py", line 1285, in _ConsumeSingleByteString
raise self.ParseError('Expected string but found: %r' % (text,))
google.protobuf.text_format.ParseError: 2555:9 : Expected string but found: 'Amoonguss'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "train.py", line 184, in
tf.app.run()
File "C:\Users\Harsha527\Miniconda3\envs\tensorflow\lib\site-packages\tensorflow\python\platform\app.py", line 125, in run
_sys.exit(main(argv))
File "C:\Users\Harsha527\Miniconda3\envs\tensorflow\lib\site-packages\tensorflow\python\util\deprecation.py", line 306, in new_func
return func(*args, **kwargs)
File "train.py", line 180, in main
graph_hook_fn=graph_rewriter_fn)
File "D:\tensorflow\models\research\object_detection\legacy\trainer.py", line 280, in train
train_config.prefetch_queue_capacity, data_augmentation_options)
File "D:\tensorflow\models\research\object_detection\legacy\trainer.py", line 59, in create_input_queue
tensor_dict = create_tensor_dict_fn()
File "train.py", line 121, in get_next
dataset_builder.build(config)).get_next()
File "D:\tensorflow\models\research\object_detection\builders\dataset_builder.py", line 123, in build
num_additional_channels=input_reader_config.num_additional_channels)
File "D:\tensorflow\models\research\object_detection\data_decoders\tf_example_decoder.py", line 297, in init
default_value=''),
File "D:\tensorflow\models\research\object_detection\data_decoders\tf_example_decoder.py", line 59, in init
label_map_proto_file, use_display_name=False)
File "D:\tensorflow\models\research\object_detection\utils\label_map_util.py", line 164, in get_label_map_dict
label_map = load_labelmap(label_map_path)
File "D:\tensorflow\models\research\object_detection\utils\label_map_util.py", line 138, in load_labelmap
label_map.ParseFromString(label_map_string)
TypeError: a bytes-like object is required, not 'str'

[dbedant]

from object_detection.protos import calibration_pb2 as object__detection_dot_protos_dot_calibration__pb2

ImportError: cannot import name 'calibration_pb2' from 'object_detection.protos' (C:\Anaconda3\lib\site-packages\object_detection-0.1-py3.7.egg\object_detection\protos_init_.py)
i have this error is there any solution to clear this out .
Presently i try in cpu mode as i do not have nvidea graphics card

[RafaelANNO]

I have the same problem but i think it's because of the init.py which is empty

[saifhamza]

can anyone help me with the below error, please?

(base) C:\WINDOWS\system32>cd C:/tensorflow1\models\research\object_detection

(base) C:\tensorflow1\models\research\object_detection>activate tensorflow1

(tensorflow1) C:\tensorflow1\models\research\object_detection>python legacy\train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_inception_v2_pets.config
Traceback (most recent call last):
File "legacy\train.py", line 47, in
import tensorflow as tf
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow_init_.py", line 29, in
from tensorflow.api.v1 import compat
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow_api\v1\compat_init.py", line 21, in
from tensorflow.api.v1.compat import v1
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow_api\v1\compat\v1_init.py", line 626, in
child_package_str=('tensorflow_estimator.python.estimator.api.estimator'))
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\tools\component_api_helper.py", line 56, in package_hook
child_pkg = importlib.import_module(child_package_str)
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\importlib_init_.py", line 127, in import_module
return bootstrap.gcd_import(name[level:], package, level)
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow_estimator_init.py", line 8, in
from tensorflow_estimator.api.v1 import estimator
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow_estimator_api\v1\estimator_init.py", line 8, in
from tensorflow_estimator.api.v1.estimator import experimental
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow_estimator_api\v1\estimator\experimental_init.py", line 8, in
from tensorflow_estimator.python.estimator.canned.dnn import dnn_logit_fn_builder
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow_estimator\python\estimator_init.py", line 25, in
import tensorflow_estimator.python.estimator.estimator_lib
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow_estimator\python\estimator\estimator_lib.py", line 22, in
from tensorflow_estimator.python.estimator.canned.baseline import BaselineClassifier
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow_estimator\python\estimator\canned\baseline.py", line 64, in
from tensorflow_estimator.python.estimator import estimator
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 66, in
from tensorflow_estimator.python.estimator import model_fn as model_fn_lib
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow_estimator\python\estimator\model_fn.py", line 36, in
from tensorflow_estimator.python.estimator.export import export_lib
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow_estimator\python\estimator\export\export_lib.py", line 25, in
from tensorflow.python.saved_model.model_utils import build_all_signature_defs
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\saved_model\model_utils_init_.py", line 22, in
from tensorflow.python.saved_model.model_utils.export_utils import build_all_signature_defs
File "C:\Users\Athar\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\saved_model\model_utils\export_utils.py", line 51, in
ModeKeys.TRAIN: signature_constants.DEFAULT_TRAIN_SIGNATURE_DEF_KEY,
AttributeError: module 'tensorflow.python.saved_model.signature_constants' has no attribute 'DEFAULT_TRAIN_SIGNATURE_DEF_KEY'

(tensorflow1) C:\tensorflow1\models\research\object_detection>

[KhurshidFF]

Hi there,
when I tried to run train.py I got this error:

(tensorflow1) C:\tensorflow1\models\research\object_detection>python train.py --logtostderr --train_dir=training/ --pipline_config_path=training/faster_rcnn_inception_v2_pets.config

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.

Traceback (most recent call last):
File "train.py", line 51, in
from object_detection.builders import model_builder
File "C:\Users\LifeSTYLE\Anaconda3\envs\tensorflow1\lib\site-packages\object_detection-0.1-py3.7.egg\object_detection\builders\model_builder.py", line 20, in
from object_detection.builders import anchor_generator_builder
File "C:\Users\LifeSTYLE\Anaconda3\envs\tensorflow1\lib\site-packages\object_detection-0.1-py3.7.egg\object_detection\builders\anchor_generator_builder.py", line 22, in
from object_detection.protos import anchor_generator_pb2
File "C:\Users\LifeSTYLE\Anaconda3\envs\tensorflow1\lib\site-packages\object_detection-0.1-py3.7.egg\object_detection\protos\anchor_generator_pb2.py", line 16, in
from object_detection.protos import flexible_grid_anchor_generator_pb2 as object__detection_dot_protos_dot_flexible__grid__anchor__generator__pb2
ImportError: cannot import name 'flexible_grid_anchor_generator_pb2' from 'object_detection.protos' (C:\Users\LifeSTYLE\Anaconda3\envs\tensorflow1\lib\site-packages\object_detection-0.1-py3.7.egg\object_detection\protos_init_.py)

please help
I would appreciate thanks