Global: model: MaskRCNN-ResNet50 mode: check_dataset # check_dataset/train/evaluate/predict dataset_dir: "/paddle/dataset/paddlex/instance_seg/instance_seg_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: 2 epochs_iters: 40 batch_size: 2 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/mask_rcnn_r50_1x_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_instance_segmentation_004.png" kernel_option: run_mode: paddle