tensorflow object detection for our own objects - python-3.x

Question

I am using tensorflow 1.9 for custom object detection and followed same steps as in https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/training.html#preparing-workspace.
But at training the model,i am getting error.
(tensorflow_cpu) C:\Users\Z004032A\Documents\Tensorflow\workspace\training_demo>python train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/ssd_inception_v2_coco.config
WARNING:tensorflow:From C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\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.
Traceback (most recent call last):
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 1460, in _ConsumeSingleByteString
result = text_encoding.CUnescape(text[1:-1])
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_encoding.py", line 115, in CUnescape
.decode('unicode_escape')
UnicodeDecodeError: 'unicodeescape' codec can't decode bytes in position 2-3: truncated \UXXXXXXXX escape
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "train.py", line 184, in <module>
tf.app.run()
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\tensorflow\python\platform\app.py", line 125, in run
_sys.exit(main(argv))
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\tensorflow\python\util\deprecation.py", line 250, in new_func
return func(*args, **kwargs)
File "train.py", line 93, in main
FLAGS.pipeline_config_path)
File "C:\Users\Z004032A\Documents\Tensorflow\models\research\object_detection\utils\config_util.py", line 100, in get_configs_from_pipeline_file
text_format.Merge(proto_str, pipeline_config)
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 685, in Merge
allow_unknown_field=allow_unknown_field)
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 752, in MergeLines
return parser.MergeLines(lines, message)
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 777, in MergeLines
self._ParseOrMerge(lines, message)
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 799, in _ParseOrMerge
self._MergeField(tokenizer, message)
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 924, in _MergeField
merger(tokenizer, message, field)
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 998, in _MergeMessageField
self._MergeField(tokenizer, sub_message)
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 924, in _MergeField
merger(tokenizer, message, field)
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 998, in _MergeMessageField
self._MergeField(tokenizer, sub_message)
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 924, in _MergeField
merger(tokenizer, message, field)
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 1049, in _MergeScalarField
value = tokenizer.ConsumeString()
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 1420, in ConsumeString
the_bytes = self.ConsumeByteString()
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 1435, in ConsumeByteString
the_list = [self._ConsumeSingleByteString()]
File "C:\Users\Z004032A\anaconda3\envs\tensorflow_cpu\lib\site-packages\google\protobuf\text_format.py", line 1462, in _ConsumeSingleByteString
raise self.ParseError(str(e))
google.protobuf.text_format.ParseError: 170:17 : ' input_path: "C:\Users\Z004032A\Documents\Tensorflow\workspace\trai': 'unicodeescape' codec can't decode bytes in position 2-3: truncated \UXXXXXXXX escape
Can anyone please help me how to resolve that problem and also tell which tensorflow version best suits for custom object detection

Answer 1

This is probably caused by Windows using C:\ as default user directory. When you use this user directory in Python in string form, you might get a unicode error, as the \U unicode escape is used.
Try duplicating backslashes. In other words, turn C:\User\Documents into C:\\User\\Documents.
As for which Tensorflow version is best, there isn't a "best" version. I'd recommend using the same TF version as whatever library you're using. I'd also recommend not coding this in raw TF. Instead, use an existing library, such as YOLO. Just Google "best object detection library tensorflow" and choose one of the existing libraries.