Created by: dklinzh

使用paddle_lite_opt转化用ppyolo_r18vd训练导出的模型

paddle_lite_opt --valid_targets=arm --optimize_out_type=naive_buffer --model_file=../__model__ --param_file=../__params__  --optimize_out=../opt --record_tailoring_info=true

提示错误:

WARNING: Logging before InitGoogleLogging() is written to STDERR E0828 10:50:40.061033 29392 opt_base.cc:445] Error: This model is not supported, because 1 ops are not supported on 'arm'. These unsupported ops are: 'matrix_nms'.

环境:

• PaddlePaddle 1.8.4.post107
• PaddleDetection release/0.4 9e38894
• paddlelite-2.6.1-cp37-cp37m-manylinux1_x86_64.whl
• Python 3.7.3

自定义的yml配置如下:

architecture: YOLOv3
use_gpu: true
max_iters: 100000
log_smooth_window: 20
log_iter: 20
snapshot_iter: 1000
metric: VOC
map_type: 11point # integral
pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams
weights: ../PaddleDetection_Output/model/ppyolo_r18vd_plate/T0/ppyolo_r18vd_plate/best_model
save_dir: ../PaddleDetection_Output/model/ppyolo_r18vd_plate/T0
num_classes: 1
use_fine_grained_loss: true
use_ema: true
ema_decay: 0.9998

YOLOv3:
  backbone: ResNet
  yolo_head: YOLOv3Head
  use_fine_grained_loss: true

ResNet:
  norm_type: sync_bn
  freeze_at: 0
  freeze_norm: false
  norm_decay: 0.
  depth: 18
  feature_maps: [4, 5]
  variant: d

YOLOv3Head:
  anchor_masks: [[3, 4, 5], [0, 1, 2]]
  anchors: [[10, 14], [23, 27], [37, 58],
            [81, 82], [135, 169], [344, 319]]
  norm_decay: 0.
  conv_block_num: 0
  scale_x_y: 1.05
  yolo_loss: YOLOv3Loss
  nms: MatrixNMS
  drop_block: true

YOLOv3Loss:
  batch_size: 8
  ignore_thresh: 0.7
  scale_x_y: 1.05
  label_smooth: false
  use_fine_grained_loss: true
  iou_loss: IouLoss

IouLoss:
  loss_weight: 2.5
  max_height: 608
  max_width: 608

MatrixNMS:
    background_label: -1
    keep_top_k: 100
    normalized: false
    score_threshold: 0.01
    post_threshold: 0.01

LearningRate:
  base_lr: 0.00025
  schedulers:
  - !PiecewiseDecay
    gamma: 0.1
    milestones:
    - 60000
    - 80000
  - !LinearWarmup
    start_factor: 0.
    steps: 1600

OptimizerBuilder:
  optimizer:
    momentum: 0.9
    type: Momentum
  regularizer:
    factor: 0.0005
    type: L2

_READER_: 'ppyolo_reader.yml'
TrainReader:
  inputs_def:
    fields: ['image', 'gt_bbox', 'gt_class', 'gt_score']
    num_max_boxes: 50
  dataset:
    !VOCDataSet
    dataset_dir: ../PaddleDetection_DataSet/plate_new
    anno_path: train.txt
    use_default_label: false
    with_background: false
  sample_transforms:
    - !DecodeImage
      to_rgb: True
      with_mixup: True
    - !MixupImage
      alpha: 1.5
      beta: 1.5
    - !ColorDistort {}
    - !RandomExpand
      fill_value: [123.675, 116.28, 103.53]
    - !RandomCrop {}
    - !RandomFlipImage
      is_normalized: false
    - !NormalizeBox {}
    - !PadBox
      num_max_boxes: 50
    - !BboxXYXY2XYWH {}
  batch_transforms:
  - !RandomShape
    sizes: [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]
    random_inter: True
  - !NormalizeImage
    mean: [0.485, 0.456, 0.406]
    std: [0.229, 0.224, 0.225]
    is_scale: True
    is_channel_first: false
  - !Permute
    to_bgr: false
    channel_first: True
  # Gt2YoloTarget is only used when use_fine_grained_loss set as true,
  # this operator will be deleted automatically if use_fine_grained_loss
  # is set as false
  - !Gt2YoloTarget
    anchor_masks: [[3, 4, 5], [0, 1, 2]]
    anchors: [[10, 14], [23, 27], [37, 58],
              [81, 82], [135, 169], [344, 319]]
    downsample_ratios: [32, 16]
  batch_size: 8
  shuffle: true
  mixup_epoch: 500
  drop_last: true
  worker_num: 16
  bufsize: 8
  use_process: true

EvalReader:
  inputs_def:
    fields: ['image', 'im_size', 'im_id', 'gt_bbox', 'gt_class', 'is_difficult']
    num_max_boxes: 50
  dataset:
    !VOCDataSet
    dataset_dir: ../PaddleDetection_DataSet/plate_new
    anno_path: val.txt
    use_default_label: false
    with_background: false
  sample_transforms:
    - !DecodeImage
      to_rgb: True
    - !ResizeImage
      target_size: 608
      interp: 2
    - !NormalizeImage
      mean: [0.485, 0.456, 0.406]
      std: [0.229, 0.224, 0.225]
      is_scale: True
      is_channel_first: false
    - !PadBox
      num_max_boxes: 50
    - !Permute
      to_bgr: false
      channel_first: True
  batch_size: 8
  drop_empty: false
  worker_num: 8
  bufsize: 4

TestReader:
  inputs_def:
    image_shape: [3, 608, 608]
    fields: ['image', 'im_size', 'im_id']
  dataset:
    !ImageFolder
    anno_path: ../PaddleDetection_DataSet/plate_new/label_list.txt
    use_default_label: false
    with_background: false
  sample_transforms:
    - !DecodeImage
      to_rgb: True
    - !ResizeImage
      target_size: 608
      interp: 2
    - !NormalizeImage
      mean: [0.485, 0.456, 0.406]
      std: [0.229, 0.224, 0.225]
      is_scale: True
      is_channel_first: false
    - !Permute
      to_bgr: false
      channel_first: True
  batch_size: 1