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- Global:
- model: OCRNet_HRNet-W18
- mode: check_dataset # check_dataset/train/evaluate/predict
- dataset_dir: "/paddle/dataset/paddlex/seg/seg_optic_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:
- epochs_iters: 500
- num_classes: 2
- batch_size: 2
- learning_rate: 0.01
- pretrain_weight_path: null
- warmup_steps: 0
- resume_path: null
- log_interval: 10
- eval_interval: 100
- Evaluate:
- weight_path: "output/best_model/model.pdparams"
- log_interval: 10
- Export:
- weight_path: https://bj.bcebos.com/paddleseg/dygraph/cityscapes/ocrnet_hrnetw18_cityscapes_1024x512_160k/model.pdparams
- Predict:
- model_dir: "output/best_model/model"
- input_path: "https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_semantic_segmentation_002.png"
- kernel_option:
- run_mode: paddle
- batch_size: 1
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