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janni_tutorial [2019/07/10 10:36] twagner [Denoise] |
janni_tutorial [2019/09/12 10:29] twagner [Training a model for your data] |
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* **movie_dir**: | * **movie_dir**: | ||
* **even_dir**: | * **even_dir**: | ||
- | * **odd_dir**: | + | * **odd_dir**: |
* **batch_size**: | * **batch_size**: | ||
* **learning_rate**: | * **learning_rate**: | ||
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* **saved_weights_name**: | * **saved_weights_name**: | ||
In principle you only have to adapt the paths. The other could keep as they are. | In principle you only have to adapt the paths. The other could keep as they are. | ||
- | We typically use at least 30 movies to train the model. Less might also work, more work often much better. | + | We typically use at least 30 movies |
To run the training on gpu 0: | To run the training on gpu 0: | ||
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Here is now how you do the actual denoising: | Here is now how you do the actual denoising: | ||
- | It is assumed that you run the command in a directory | + | It is assumed that you run the command in a directory with your model file '' |
The following command will run the denoising on GPU 0: | The following command will run the denoising on GPU 0: |