s2anet.yml 1.1 KB

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  1. architecture: S2ANet
  2. pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_v2_pretrained.pdparams
  3. weights: output/s2anet_r50_fpn_1x_dota/model_final.pdparams
  4. # Model Achitecture
  5. S2ANet:
  6. backbone: ResNet
  7. neck: FPN
  8. s2anet_head: S2ANetHead
  9. s2anet_bbox_post_process: S2ANetBBoxPostProcess
  10. ResNet:
  11. depth: 50
  12. variant: d
  13. norm_type: bn
  14. return_idx: [1,2,3]
  15. num_stages: 4
  16. FPN:
  17. in_channels: [256, 512, 1024]
  18. out_channel: 256
  19. spatial_scales: [0.25, 0.125, 0.0625]
  20. has_extra_convs: True
  21. extra_stage: 2
  22. relu_before_extra_convs: False
  23. S2ANetHead:
  24. anchor_strides: [8, 16, 32, 64, 128]
  25. anchor_scales: [4]
  26. anchor_ratios: [1.0]
  27. anchor_assign: RBoxAssigner
  28. stacked_convs: 2
  29. feat_in: 256
  30. feat_out: 256
  31. num_classes: 15
  32. align_conv_type: 'AlignConv' # AlignConv Conv
  33. align_conv_size: 3
  34. use_sigmoid_cls: True
  35. RBoxAssigner:
  36. pos_iou_thr: 0.5
  37. neg_iou_thr: 0.4
  38. min_iou_thr: 0.0
  39. ignore_iof_thr: -2
  40. S2ANetBBoxPostProcess:
  41. nms_pre: 2000
  42. min_bbox_size: 0.0
  43. nms:
  44. name: MultiClassNMS
  45. keep_top_k: -1
  46. score_threshold: 0.05
  47. nms_threshold: 0.1
  48. normalized: False