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- # Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unlesee you know exactly what you are doing)
- enable_modelarts: False
- # url for modelarts
- data_url: ""
- train_url: ""
- checkpoint_url: ""
- # path for local
- data_path: "./data"
- output_path: "./train"
- load_path: ""
- #device_target: "Ascend"
- device_target: "CPU"
- enable_profiling: False
- need_modelarts_dataset_unzip: False
- modelarts_dataset_unzip_name: "MindRecord_COCO"
-
- # ======================================================================================
- # common options
- distribute: False
-
- # ======================================================================================
- # create dataset
- create_dataset: "facemask"
- prefix: "retinanet.mindrecord"
- is_training: True
- python_multiprocessing: False
-
- # ======================================================================================
- # Training options
- img_shape: [600,600]
- num_retinanet_boxes: 67995
- match_thershold: 0.5
- nms_thershold: 0.6
- min_score: 0.1
- max_boxes: 100
-
- # learning rate settings
- lr: 0.009
- global_step: 0
- lr_init: 1e-5
- lr_end_rate: 5e-4
- warmup_epochs1: 0
- warmup_epochs2: 1
- warmup_epochs3: 4
- warmup_epochs4: 12
- warmup_epochs5: 30
- momentum: 0.9
- weight_decay: 1.5e-4
-
- # network
- num_default: [9, 9, 9, 9, 9]
- extras_out_channels: [256, 256, 256, 256, 256]
- feature_size: [75, 38, 19, 10, 5]
- aspect_ratios: [[0.5, 1.0, 2.0], [0.5, 1.0, 2.0], [0.5, 1.0, 2.0], [0.5, 1.0, 2.0], [0.5, 1.0, 2.0]]
- steps: [8, 16, 32, 64, 128]
- anchor_size: [32, 64, 128, 256, 512]
- prior_scaling: [0.1, 0.2]
- gamma: 2.0
- alpha: 0.75
- num_classes: 4
-
- # `mindrecord_dir` and `coco_root` are better to use absolute path.
- mindrecord_dir: "./mindrecord"
- dataset_root: "./dataset"
- train_data_type: "train"
- val_data_type: "val"
- instances_set: "annotation/instances_{}.json"
- coco_classes: ["background","mask_weared_incorrect", "with_mask", "without_mask"]
-
-
- # The annotation.json position of voc validation dataset
- voc_root: "./dataset"
- facemask_root: "./dataset"
-
- # voc original dataset
- voc_dir: "./dataset"
- facemask_dir: "./dataset"
-
- # if coco or voc used, `image_dir` and `anno_path` are useless
- image_dir: ""
- anno_path: ""
- save_checkpoint: True
- save_checkpoint_epochs: 1
- keep_checkpoint_max: 10
- save_checkpoint_path: "./ckpt"
- finish_epoch: 0
-
- # optimiter options
- workers: 8
- mode: "sink"
- epoch_size: 95
- batch_size: 16
- pre_trained: "/home/mindspore/retinanet/retinanet_ascend_v170_coco2017_official_cv_acc35.ckpt"
- pre_trained_epoch_size: 90
- loss_scale: 200
- filter_weight: True
- finetune: True
-
- # ======================================================================================
- # Eval options
- dataset: "facemask"
- checkpoint_path: "./ckpt/retinanet_1-95_42.ckpt"
-
- # ======================================================================================
- # export options
- device_id: 0
- file_format: "MINDIR"
- export_batch_size: 1
- file_name: "retinanet"
-
- # ======================================================================================
- # postprocess options
- result_path: ""
- img_path: ""
- img_id_file: ""
-
- ---
- # Help description for each configuration
- enable_modelarts: "Whether training on modelarts default: False"
- data_url: "Url for modelarts"
- train_url: "Url for modelarts"
- data_path: "The location of input data"
- output_pah: "The location of the output file"
- device_target: "device id of GPU or Ascend. (Default: None)"
- enable_profiling: "Whether enable profiling while training default: False"
- workers: "Num parallel workers."
- lr: "Learning rate, default is 0.1."
- mode: "Run sink mode or not, default is sink."
- epoch_size: "Epoch size, default is 500."
- batch_size: "Batch size, default is 32."
- pre_trained: "Pretrained Checkpoint file path."
- pre_trained_epoch_size: "Pretrained epoch size."
- save_checkpoint_epochs: "Save checkpoint epochs, default is 1."
- loss_scale: "Loss scale, default is 1024."
- filter_weight: "Filter weight parameters, default is False."
- dataset: "Dataset, default is coco."
- device_id: "Device id, default is 0."
- file_format: "file format choices [AIR, MINDIR]"
- file_name: "output file name."
- export_batch_size: "batch size"
- result_path: "result file path."
- img_path: "image file path."
- img_id_file: "image id file."
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