سلام و عرض ادب
من یک دیتاست بزرگ دارم حدود 4240 تا عکس.میخوام با پایتون براشون یک فایل متنی درست کنم و از اون به عنوان لیبل دیتاستم استفاده کنم.
مثلا:
img1 1
img2 1
با متلب هم سعی کردم و در نهایت نتونستم؟
لطفا اگر کسی میدونه راهنمایی کنه ؟
ممنون
ایا این کد میتونه همچین کاری رو انجام بده؟
# Copyright 2016 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Small library that points to a data set.
Methods of Data class:
data_files: Returns a python list of all (sharded) data set files.
num_examples_per_epoch: Returns the number of examples in the data set.
num_classes: Returns the number of classes in the data set.
reader: Return a reader for a single entry from the data set.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from abc import ABCMeta
from abc import abstractmethod
import os
import tensorflow as tf
FLAGS = tf.app.flags.FLAGS
# Basic model parameters.
tf.app.flags.DEFINE_string('data_dir', '/tmp/mydata',
"""Path to the processed data, i.e. """
"""TFRecord of Example protos.""")
class Dataset(object):
"""A simple class for handling data sets."""
__metaclass__ = ABCMeta
def __init__(self, name, subset):
"""Initialize dataset using a subset and the path to the data."""
assert subset in self.available_subsets(), self.available_subsets()
self.name = name
self.subset = subset
@abstractmethod
def num_classes(self):
"""Returns the number of classes in the data set."""
pass
# return 10
@abstractmethod
def num_examples_per_epoch(self):
"""Returns the number of examples in the data subset."""
pass
# if self.subset == 'train':
# return 10000
# if self.subset == 'validation':
# return 1000
@abstractmethod
def download_message(self):
"""Prints a download message for the Dataset."""
pass
def available_subsets(self):
"""Returns the list of available subsets."""
return ['train', 'validation']
def data_files(self):
"""Returns a python list of all (sharded) data subset files.
Returns:
python list of all (sharded) data set files.
Raises:
ValueError: if there are not data_files matching the subset.
"""
tf_record_pattern = os.path.join(FLAGS.data_dir, '%s-*' % self.subset)
data_files = tf.gfile.Glob(tf_record_pattern)
if not data_files:
print('No files found for dataset %s/%s at %s' % (self.name,
self.subset,
FLAGS.data_dir))
self.download_message()
exit(-1)
return data_files
def reader(self):
"""Return a reader for a single entry from the data set.
See io_ops.py for details of Reader class.
Returns:
Reader object that reads the data set.
"""
return tf.TFRecordReader()