line_net.yaml 904 B

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  1. image:
  2. mean: [109.730, 103.832, 98.681]
  3. stddev: [22.275, 22.124, 23.229]
  4. batch_size: 4
  5. batch_size_eval: 2
  6. # backbone multi-task parameters
  7. head_size: [[2], [1], [2]]
  8. loss_weight:
  9. jmap: 8.0
  10. lmap: 0.5
  11. joff: 0.25
  12. lpos: 1
  13. lneg: 1
  14. boxes: 1.0
  15. # backbone parameters
  16. backbone: resnet50_fpn
  17. #backbone: resnet18_fpn
  18. #backbone: mobilenet_v3_large_fpn
  19. # backbone: unet
  20. depth: 4
  21. num_stacks: 1
  22. num_blocks: 1
  23. num_classes: 2
  24. # sampler parameters
  25. ## static sampler
  26. n_stc_posl: 300
  27. n_stc_negl: 40
  28. ## dynamic sampler
  29. n_dyn_junc: 300
  30. n_dyn_posl: 300
  31. n_dyn_negl: 80
  32. n_dyn_othr: 600
  33. # LOIPool layer parameters
  34. n_pts0: 32
  35. n_pts1: 8
  36. # line verification network parameters
  37. dim_loi: 128
  38. dim_fc: 1024
  39. # maximum junction and line outputs
  40. n_out_junc: 250
  41. n_out_line: 2500
  42. # additional ablation study parameters
  43. use_cood: 0
  44. use_slop: 0
  45. use_conv: 0
  46. # junction threashold for evaluation (See #5)
  47. eval_junc_thres: 0.008