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- # Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
- pretrain_path: ''
- enable_modelarts: True
- # data_url: ""
- train_url: ""
- # ckpt_url: ""
- multi_data_url: ""
- pretrain_url: ""
- ckpt_url: ""
- data_path: "/cache/data"
- # output_path: "/cache/train"
- output_path: "cache/output"
- load_path: "/cache/checkpoint_path.ckpt"
- device_target: Ascend
- enable_profiling: False
- need_modelarts_dataset_unzip: True
- modelarts_dataset_unzip_name: "MindRecord_COCO"
-
- # 数据集位置存储在运行参数 multi_data_url 中,预训练模型存放在运行参数 pretrain_url 中,训练输出请存储在 /cache/output 中以供后续下载。
- # ==============================================================================
- img_shape: [600, 600]
- num_retinanet_boxes: 7555
- match_thershold: 0.5
- softnms_sigma: 0.5
- nms_thershold: 0.6
- min_score: 0.1
- max_boxes: 100
-
- # learing rate settings
- global_step: 0
- lr_init: 0.000001
- lr_end_rate: 0.005
- warmup_epochs1: 2
- warmup_epochs2: 5
- warmup_epochs3: 23
- warmup_epochs4: 60
- warmup_epochs5: 160
- momentum: 0.9
- weight_decay: 0.00015
-
- # network
- num_default: [1, 1, 1, 1, 1]
- 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: 0.25
-
- # `mindrecord_dir` and `coco_root` are better to use absolute path.
- mindrecord_dir: "/cache/data/MindRecord_COCO"
- coco_root: "/cache/data"
- train_data_type: "train2017"
- val_data_type: "val2017"
- instances_set: "annotations/instances_{}.json"
- coco_classes: ['background','person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus',
- 'train', 'truck', 'boat', 'traffic light', 'fire hydrant',
- 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog',
- 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra',
- 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie',
- 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball',
- 'kite', 'baseball bat', 'baseball glove', 'skateboard',
- 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup',
- 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple',
- 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza',
- 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed',
- 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote',
- 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink',
- 'refrigerator', 'book', 'clock', 'vase', 'scissors',
- 'teddy bear', 'hair drier', 'toothbrush']
- num_classes: 81
- # The annotation.json position of voc validation dataset.
- voc_root: ""
- # voc original dataset.
- voc_dir: ""
- # if coco or voc used, `image_dir` and `anno_path` are useless.
- image_dir: ""
- anno_path: ""
- save_checkpoint: True
- keep_checkpoint_max: 100
- save_checkpoint_path: "/cache/train"
- finish_epoch: 0
- checkpoint_path: "/cache/checkpoint_path.ckpt"
-
- # train.py sabl training
- only_create_dataset: False
- distribute: True
- device_id: 0
- device_num: 8
- lr: 0.05
- train_mode: "Graph"
- sink_mode: True
- dataset: "coco"
- epoch_size: 500
- batch_size: 16
- pre_trained: ''
- save_checkpoint_epochs: 1
- loss_scale: 1024
- filter_weight: False
- run_platform: "Ascend"
-
- # export.py sabl evaluation
- file_format: "MINDIR" # MINDIR/AIR
- # batch_size: 1
- file_name: "sabl"
-
- # postprocess.py sabl evaluation
- result_path: ''
- img_path: ''
- img_id_file: ''
-
- ---
- # Config description for each option
- only_create_dataset: 'If set it true, only create Mindrecord, default is False.'
- distribute: 'Run distribute, default is False.'
- device_id: 'Device id, default is 0.'
- device_num: 'Use device nums, default is 1.'
- lr: 'Learning rate, default is 0.1.'
- mode: 'Run sink mode or not, default is sink.'
- dataset: 'Dataset, default is coco.'
- 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.'
- run_platform: 'Run platform, only support Ascend and GPU.'
- file_format: 'file format'
- file_name: 'output file name.'
- result_path: 'result file path.'
- img_path: 'image file path.'
- img_id_file: 'image id file.'
-
- enable_modelarts: 'Whether training on modelarts, default: False'
- data_url: 'Dataset url for obs'
- train_url: 'Training output url for obs'
- data_path: 'Dataset path for local'
-
- ---
- run_platform: ['Ascend', 'GPU']
- file_format: ["AIR", "MINDIR"]
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