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Docs: add examples to README.md

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Armour committed Jul 3, 2018
1 parent 9046ada commit e91dd8a0e482997a8e2161890e2b4973c03bbb20
Showing with 29 additions and 13 deletions.
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  147. +9 −10 test.py
@@ -39,6 +39,23 @@ This is a Tensorflow implementation of the Residual Encoder Network based on [Au
1. Change `testing_dir` to your directory that contains all your testing jpg images
2. Run `python test.py`

## Examples

* ![1](images/1.png)
* ![2](images/2.png)
* ![3](images/3.png)
* ![4](images/4.png)
* ![5](images/5.png)
* ![6](images/6.png)
* ![7](images/7.png)
* ![8](images/8.png)
* ![9](images/9.png)
* ![10](images/10.png)
* ![11](images/11.png)
* ![12](images/12.png)

More examples can be found at [sample_output_images](https://github.com/Armour/Automatic-Image-Colorization/blob/master/sample_output_images) folder.

## References

* [Automatic Colorization](http://tinyclouds.org/colorize/)
@@ -95,8 +95,8 @@ def init_model(train=True):
# Init tensorflow summaries.
print("⏳ Init tensorflow summaries...")
tf.summary.histogram("loss", loss)
tf.summary.image("gray_image", gray_image_three_channels, max_outputs=5)
tf.summary.image("predict_image", predict_rgb, max_outputs=5)
tf.summary.image("color_image", color_image_rgb, max_outputs=5)
tf.summary.image("gray_image", gray_image_three_channels, max_outputs=1)
tf.summary.image("predict_image", predict_rgb, max_outputs=1)
tf.summary.image("color_image", color_image_rgb, max_outputs=1)

return is_training, global_step, optimizer, loss, predict_rgb, color_image_rgb, gray_image_three_channels, file_paths
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