DWTP_descreenton_H_esrgan
Good for
I've been experimenting a lot since the last descripton was released to save even more detail, and to get rid of some of the beginner's soreness. All three models are not yet perfect and I will develop them, but what is the essence of the three models, the models on omni is just a division of VL eats less large screenton, VH is just a re-trained model on a modified dataset and with VL as a prevoritolnoy shadowing that it would demolish more screenton, while not going to demolish all the textures and very large screenton. Esrgan model was trained on a dataset VH for use in the colab, it works in some places worse than Omni, so could not fight with overlapping screenton.
Training details (7)
- Date
- 2023-10-04
- Dataset
- custom dataset
- Dataset size
- 76000
- Training iterations
- 108000
- Training epochs
- 8
- Training batch size
- 6
- Training HR size
- 192

