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| author | Cameron <cysmith1010@gmail.com> | 2016-10-11 16:04:04 -0600 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2016-10-11 16:04:04 -0600 |
| commit | 973e2e77a7514c7c4dfb338a021ef2c14b5efbd0 (patch) | |
| tree | 7f74dced276647cd01729063d8ffc131a46abd11 | |
| parent | 0ec87841223f5f48c82e00a1039209037a97f516 (diff) | |
Modified README
| -rw-r--r-- | README.md | 14 |
1 files changed, 11 insertions, 3 deletions
@@ -43,7 +43,7 @@ Here we reproduce Figure 2 from the first paper, which renders a photograph of t ### Content / Style Tradeoff -The relative weights of the style and content transfer can be controlled. +The algorithm allows the user to trade-off the relative weight of the style and content reconstruction terms. Here we render with an increasing style weight applied to [Red Canna](http://www.georgiaokeeffe.net/red-canna.jsp): <p align="center"> @@ -71,7 +71,7 @@ More than one style image can be used to blend multiple artistic styles. </p> ### Style Interpolation -When using multiple style images, the degree of blending between the images can be controlled. +When using multiple style images, the degree to which they are blended can be controlled. <p align="center"> <img src="image_input/taj_mahal.jpg" height="178px"> <img src="examples/style_interpolation/taj_mahal_scream_2_starry_8.png" height="178px"> @@ -83,7 +83,7 @@ When using multiple style images, the degree of blending between the images can </p> ### Transfer style but not color -The color scheme of the original image can be preserved by including the flag `--original_colors`. +By including the flag `--original_colors` the output image will retain the colors of the original image. *Left to right*: content image, stylized image, stylized image with the original colors of the content image <p align="center"> @@ -270,6 +270,10 @@ python neural_style.py --video \ * `--learning_rate`: Learning-rate parameter for the Adam optimizer. *Default*: `1e1` * `--max_iterations`: Max number of iterations for the Adam or L-BFGS optimizer. *Default*: `1000` * `--print_iterations`: Number of iterations between optimizer print statements. *Default*: `50` +* `--content_loss_function`: Different constants K in the content loss function. *Choices*: `1`, `2`, `3`. *Default*: `1` +<p align="center"> +<img src="examples/equations/content.png" width="321px"> +</p> #### Video Frame Arguments * `--video`: Boolean flag indicating if the user is creating a video. @@ -291,6 +295,10 @@ python neural_style.py --video \ Send questions or issues: cysmith1010@gmail.com +If you want to contribute, please try to: +* Avoid esoteric one-liners. +* Avoid unnecessary or nested lambda expressions. + ## Memory By default, `neural-style-tf` uses the NVIDIA cuDNN GPU backend for convolutions and L-BFGS for optimization. These produce better and faster results, but can consume a lot of memory. You can reduce memory usage with the following: |
