ppyoloe_crn_l_36e_bdd100kdet.yml

_BASE_: [
  '../datasets/coco_detection.yml',
  '../runtime.yml',
  '../ppyoloe/_base_/optimizer_300e.yml',
  '../ppyoloe/_base_/ppyoloe_crn.yml',
  '../ppyoloe/_base_/ppyoloe_reader.yml',
]
log_iter: 100
snapshot_epoch: 4
weights: output/ppyoloe_crn_l_36e_bdd100kdet/model_final

pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_300e_coco.pdparams
depth_mult: 1.0
width_mult: 1.0

num_classes: 10

TrainDataset:
  !COCODataSet
    image_dir: images/100k/train
    anno_path: labels/det_20/det_train_cocofmt.json
    dataset_dir: dataset/bdd100k
    data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd']

EvalDataset:
  !COCODataSet
    image_dir: images/100k/val
    anno_path: labels/det_20/det_val_cocofmt.json
    dataset_dir: dataset/bdd100k

TestDataset:
  !ImageFolder
    anno_path: labels/det_20/det_val_cocofmt.json
    dataset_dir: dataset/bdd100k

TrainReader:
  batch_size: 8

epoch: 36
LearningRate:
  base_lr: 0.001
  schedulers:
    - !CosineDecay
      max_epochs: 43
    - !LinearWarmup
      start_factor: 0.
      epochs: 1

PPYOLOEHead:
  static_assigner_epoch: -1
  nms:
    name: MultiClassNMS
    nms_top_k: 1000
    keep_top_k: 100
    score_threshold: 0.01
    nms_threshold: 0.6