ppyolo_tiny.yml 1.1 KB

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  1. architecture: YOLOv3
  2. pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_large_x0_5_pretrained.pdparams
  3. norm_type: sync_bn
  4. use_ema: true
  5. ema_decay: 0.9998
  6. YOLOv3:
  7. backbone: MobileNetV3
  8. neck: PPYOLOTinyFPN
  9. yolo_head: YOLOv3Head
  10. post_process: BBoxPostProcess
  11. MobileNetV3:
  12. model_name: large
  13. scale: .5
  14. with_extra_blocks: false
  15. extra_block_filters: []
  16. feature_maps: [7, 13, 16]
  17. PPYOLOTinyFPN:
  18. detection_block_channels: [160, 128, 96]
  19. spp: true
  20. drop_block: true
  21. YOLOv3Head:
  22. anchors: [[10, 15], [24, 36], [72, 42],
  23. [35, 87], [102, 96], [60, 170],
  24. [220, 125], [128, 222], [264, 266]]
  25. anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
  26. loss: YOLOv3Loss
  27. YOLOv3Loss:
  28. ignore_thresh: 0.5
  29. downsample: [32, 16, 8]
  30. label_smooth: false
  31. scale_x_y: 1.05
  32. iou_loss: IouLoss
  33. IouLoss:
  34. loss_weight: 2.5
  35. loss_square: true
  36. BBoxPostProcess:
  37. decode:
  38. name: YOLOBox
  39. conf_thresh: 0.005
  40. downsample_ratio: 32
  41. clip_bbox: true
  42. scale_x_y: 1.05
  43. nms:
  44. name: MultiClassNMS
  45. keep_top_k: 100
  46. nms_threshold: 0.45
  47. nms_top_k: 1000
  48. score_threshold: 0.005