HamedMP / Imageflow
Licence: apache-2.0
A simple wrapper of TensorFlow for Converting, Importing (and Soon, Training) Images in tensorflow.
Stars: ✭ 166
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Notice - This version of imageflow is no longer under maintenance and major update is required.
The tensorflow version is too old and the library is not working as expected. You are welcome to add your use-cases in the Issues as Feature request to be considered in the new versions. Sorry for the inconvenience.
ImageFlow
A simple wrapper of TensorFlow for Converting, Importing (and Soon, Training) Images in tensorflow.
Installation:
pip install imageflow
Usage:
import imageflow
.tfrecords
Convert a directory of images and their labels to Just calling the following function will make a filename.tfrecords
file in the directory converted_data
in your projects root(where you call this method).
convert_images(images, labels, filename)
The images
should be an array of shape [-1, height, width, channel]
and has the same rows as the labels
.tfrecords
in multi-thread manner:
Read distorted and normal data from # Distorted images for training
images, labels = distorted_inputs(filename='../my_data_raw/train.tfrecords', batch_size=FLAGS.batch_size,
num_epochs=FLAGS.num_epochs,
num_threads=5, imshape=[32, 32, 3], imsize=32)
# Normal images for validation
val_images, val_labels = inputs(filename='../my_data_raw/validation.tfrecords', batch_size=FLAGS.batch_size,
num_epochs=FLAGS.num_epochs,
num_threads=5, imshape=[32, 32, 3])
Dependencies:
- TensorFlow ( => version 0.7.0)
- Numpy
- Pillow
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