Comments (1)
The original neural-style generates random noise to initialize the generated image; setting the random seed with -seed ensures that the same random image is used to initialize each video frame. This project works very differently - it generates stylized images by processing the content images with a trained neural network. This feedforward processing does not involve generating any random numbers, so setting the random seed will not do anything.
In short, this means that there is no simple way to add a -seed option that does what you want.
from fast-neural-style.
Related Issues (20)
- cuda runtime error when training
- invalid argument: /path/to/output/file.h5
- Training image sizes
- train requirements.txt error 'ascii' codec can't decode byte 0xe2 in position 1178
- How to understand the gradient backward propagation of perceptual loss? HOT 1
- did you try it with nvidia jetson tx2 / nvidia xavier hardware?
- cannot open <starry_night.t7>
- Cannot run fast_neural_style.lua script(libjpeg library problem) HOT 1
- Diffrent results on diffrent machines HOT 1
- C# Implementation
- predict result is different when running opencv and fast_neural_style.lua script HOT 1
- get bad results after training candy
- unable to set v4l2 format: Invalid argument
- File.lua: unknown object HOT 2
- What is motivation of using 9x9 conv at first and last layer?
- tanh 150 constant - why? HOT 6
- could we apply fast-neural-transfer to image deformation?
- fork failed: cannot allocate memory HOT 1
- Problems with lua HOT 1
- Does anyone know the original source of the mosaic image?
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from fast-neural-style.