YOLOX-N.yaml

Global:
  model: YOLOX-N
  mode: check_dataset # check_dataset/train/evaluate/predict
  dataset_dir: "/paddle/dataset/paddlex/det/det_coco_examples"
  device: gpu:0,1,2,3
  output: "output"

CheckDataset:
  convert:
    enable: False
    src_dataset_type: null
  split:
    enable: False
    train_percent: null
    val_percent: null

Train:
  num_classes: 4
  epochs_iters: 10
  batch_size: 8
  learning_rate: 0.01
  pretrain_weight_path: null
  warmup_steps: 100
  resume_path: null
  log_interval: 10
  eval_interval: 1

Evaluate:
  weight_path: "output/best_model/best_model.pdparams"
  log_interval: 10

Export:
  weight_path: https://paddledet.bj.bcebos.com/models/yolox_nano_300e_coco.pdparams

Predict:
  batch_size: 1
  model_dir: "output/best_model/inference"
  input: "https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_object_detection_002.png"
  kernel_option:
    run_mode: paddle