Efficient AI4EO OpenSource framework
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  1. # Neat-EO.pink Configuration
  2. # Input channels configuration
  3. # You can, add several channels blocks to compose your input Tensor. Order is meaningful.
  4. #
  5. # name: dataset subdirectory name
  6. # bands: bands to keep from sub source. Order is meaningful
  7. [[channels]]
  8. name = "images"
  9. bands = [1, 2, 3]
  10. # Output Classes configuration
  11. # Nota: available colors are either CSS3 colors names or #RRGGBB hexadecimal representation.
  12. # Nota: special color name "transparent" could be use on a single class to apply transparency
  13. # Nota: default weight is 1.0 for each class, or 0.0 if a transparent color one.
  14. [[classes]]
  15. title = "Background"
  16. color = "transparent"
  17. [[classes]]
  18. title = "Building"
  19. color = "deeppink"
  20. [[classes]]
  21. title = "Road"
  22. color = "deepskyblue"
  23. [model]
  24. # Neurals Network name
  25. nn = "Albunet"
  26. # Encoder name
  27. encoder = "resnet50"
  28. # Dataset loader name
  29. loader = "SemSeg"
  30. # Model internal input tile size [W, H]
  31. #ts = [512, 512]
  32. [train]
  33. # Pretrained Encoder
  34. #pretrained = true
  35. # Batch size
  36. #bs = 4
  37. # Data Augmentation to apply, to whole input tensor, with associated probability
  38. da = {name="RGB", p=1.0}
  39. # Loss function name
  40. loss = "Lovasz"
  41. # Eval Metrics
  42. metrics = ["IoU", "MCC", "QoD"]
  43. # Optimizer, cf https://pytorch.org/docs/stable/optim.html
  44. #optimizer = {name="Adam", lr=0.0001}