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https://github.com/hamedmp/imageflow
A simple wrapper of TensorFlow for Converting, Importing (and Soon, Training) Images in tensorflow.
https://github.com/hamedmp/imageflow
imageflow tensorflow wrapper
Last synced: 18 days ago
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A simple wrapper of TensorFlow for Converting, Importing (and Soon, Training) Images in tensorflow.
- Host: GitHub
- URL: https://github.com/hamedmp/imageflow
- Owner: HamedMP
- License: apache-2.0
- Created: 2015-11-22T22:17:31.000Z (almost 9 years ago)
- Default Branch: master
- Last Pushed: 2017-04-29T08:55:52.000Z (over 7 years ago)
- Last Synced: 2024-10-10T04:05:12.329Z (about 1 month ago)
- Topics: imageflow, tensorflow, wrapper
- Language: Python
- Homepage:
- Size: 61.5 KB
- Stars: 162
- Watchers: 17
- Forks: 59
- Open Issues: 8
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 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:
```python
import imageflow
```
#### Convert a directory of images and their labels to `.tfrecords`
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).
```python
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`
#### Read distorted and normal data from `.tfrecords` in multi-thread manner:
```python
# 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