Python object_detection.utils.dataset_util.read_dataset() Examples

The following are 7 code examples of object_detection.utils.dataset_util.read_dataset(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module object_detection.utils.dataset_util , or try the search function .
Example #1
Source File: dataset_util_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up 
def _get_dataset_next(self, files, config, batch_size):
    def decode_func(value):
      return [tf.string_to_number(value, out_type=tf.int32)]

    dataset = dataset_util.read_dataset(
        tf.data.TextLineDataset, decode_func, files, config)
    dataset = dataset.batch(batch_size)
    return dataset.make_one_shot_iterator().get_next()
Example #2
Source File: dataset_util_test.py    From Person-Detection-and-Tracking with MIT License 5 votes vote down vote up 
def _get_dataset_next(self, files, config, batch_size):
    def decode_func(value):
      return [tf.string_to_number(value, out_type=tf.int32)]

    dataset = dataset_util.read_dataset(
        tf.data.TextLineDataset, decode_func, files, config)
    dataset = dataset.batch(batch_size)
    return dataset.make_one_shot_iterator().get_next()
Example #3
Source File: dataset_util_test.py    From Traffic-Rule-Violation-Detection-System with MIT License 5 votes vote down vote up 
def _get_dataset_next(self, files, config, batch_size):
    def decode_func(value):
      return [tf.string_to_number(value, out_type=tf.int32)]

    dataset = dataset_util.read_dataset(
        tf.data.TextLineDataset, decode_func, files, config)
    dataset = dataset.batch(batch_size)
    return dataset.make_one_shot_iterator().get_next()
Example #4
Source File: dataset_util_test.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up 
def _get_dataset_next(self, files, config, batch_size):
    def decode_func(value):
      return [tf.string_to_number(value, out_type=tf.int32)]

    dataset = dataset_util.read_dataset(
        tf.data.TextLineDataset, decode_func, files, config)
    dataset = dataset.batch(batch_size)
    return dataset.make_one_shot_iterator().get_next()
Example #5
Source File: dataset_util_test.py    From ros_tensorflow with Apache License 2.0 5 votes vote down vote up 
def _get_dataset_next(self, files, config, batch_size):
    def decode_func(value):
      return [tf.string_to_number(value, out_type=tf.int32)]

    dataset = dataset_util.read_dataset(
        tf.data.TextLineDataset, decode_func, files, config)
    dataset = dataset.batch(batch_size)
    return dataset.make_one_shot_iterator().get_next()
Example #6
Source File: dataset_util_test.py    From Elphas with Apache License 2.0 5 votes vote down vote up 
def _get_dataset_next(self, files, config, batch_size):
    def decode_func(value):
      return [tf.string_to_number(value, out_type=tf.int32)]

    dataset = dataset_util.read_dataset(
        tf.data.TextLineDataset, decode_func, files, config)
    dataset = dataset.batch(batch_size)
    return dataset.make_one_shot_iterator().get_next()
Example #7
Source File: dataset_util_test.py    From AniSeg with Apache License 2.0 5 votes vote down vote up 
def _get_dataset_next(self, files, config, batch_size):
    def decode_func(value):
      return [tf.string_to_number(value, out_type=tf.int32)]

    dataset = dataset_util.read_dataset(
        tf.data.TextLineDataset, decode_func, files, config)
    dataset = dataset.batch(batch_size)
    return dataset.make_one_shot_iterator().get_next()