@vinyvince76 The sample pix2pix model is an image-to-image conversion model. Therefore, if it is possible to incorporate some setting information into the input image and create a correlation between the input image and the output image, learning should work well :)
"A Coupled Vegetation-Crust Model for Patchy Landscapes"を参考に実装したVegetation Solver
HeightFieldを元に乾燥地の植生パターンのシミュレーションを行えます
参考
https://t.co/woDZQJi9rl
vegetationcrust.hipnc
https://t.co/YwOatWIVym
@vinyvince76 The number of images used for training is 200.
PDG has changed the Virtual Environment requirements so that pytorch uses CUDA. Also, in the process of creating images to be trained, some changes have been made to make them suitable learning materials...
"A Coupled Vegetation-Crust Model for Patchy Landscapes"を参考に実装したVegetation Solver
HeightFieldを元に乾燥地の植生パターンのシミュレーションを行えます
参考
https://t.co/woDZQJi9rl
vegetationcrust.hipnc
https://t.co/YwOatWIVym