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- # Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
- enable_modelarts: False
- # Url for modelarts
- data_url: ""
- train_url: ""
- checkpoint_url: ""
- # Path for local
- data_path: "/home/ma-user/work/data_1220"
- output_path: "/home/ma-user/work/data_1220/output"
- load_path: "/home/ma-user/work/coco2017/checkpoint_path"
- device_target: "Ascend"
- need_modelarts_dataset_unzip: True
- modelarts_dataset_unzip_name: "coco"
-
- # ==============================================================================
- # Train options
- data_dir: "/home/ma-user/work/data_1220"
- per_batch_size: 8
- pretrained_backbone: "" #"../cspdarknet53_ascend_v120_imagenet2012_official_cv_bs64_top1acc7854_top5acc9428.ckpt"
- resume_yolov4: ""
- pretrained_checkpoint: "/home/ma-user/work/coco2017/checkpoint_path/yolov4_ascend_v170_coco2017_official_cv_acc44.ckpt"
- filter_weight: False
- lr_scheduler: "cosine_annealing"
- lr: 0.012
- lr_epochs: "220,250"
- lr_gamma: 0.1
- eta_min: 0.0
- t_max: 320
- max_epoch: 320
- warmup_epochs: 20
- weight_decay: 0.0005
- momentum: 0.9
- loss_scale: 64
- label_smooth: 0
- label_smooth_factor: 0.1
- log_interval: 100
- ckpt_path: "outputs/"
- ckpt_interval: -1
- is_save_on_master: 1
- is_distributed: 1
- rank: 0
- group_size: 1
- need_profiler: 0
- training_shape: ""
- run_eval: True
- save_best_ckpt: True
- eval_start_epoch: 200
- eval_interval: 1
- ann_file: ""
- transfer_train: False
-
- # Eval options
- pretrained: "./outputs/2022-12-20_time_14_35_45_mosaic_nopre_0.527/ckpt_0/best_map.ckpt"
- log_path: "./outputs/"
- ann_val_file: ""
- coco2xml: 0
-
-
- xml_dir : '../data_1220/train'
- jpg_src_path : '../data_1220/train'
- predict_result : './predict_result'
-
-
-
- # Test option
- test_nms_thresh: 0.45
- test_ignore_threshold: 0.001
-
-
-
- # Export options
- device_id: 0
- batch_size: 2
- testing_shape: 608
- ckpt_file: ""
- file_name: "yolov4"
- file_format: "MINDIR"
- keep_detect: True
-
- # Other default config
- hue: 0.1
- saturation: 1.5
- value: 1.5
- jitter: 0.3
- resize_rate: 10
-
- multi_scale: [[416, 416],
- [448, 448],
- [480, 480],
- [512, 512],
- [544, 544],
- [576, 576],
- [608, 608],
- [640, 640],
- [672, 672],
- [704, 704],
- [736, 736]
- ]
-
- max_box: 90
- backbone_input_shape: [32, 64, 128, 256, 512]
- backbone_shape: [64, 128, 256, 512, 1024]
- backbone_layers: [1, 2, 8, 8, 4]
-
- ignore_threshold: 0.7
- eval_ignore_threshold: 0.001
- nms_thresh: 0.5
- each_multiscale: True
- mosaic: True
- multi_label: False
- multi_label_thresh: 0.2
- detect_head_loss_coff: [1, 1, 1]
- bbox_class_loss_coff: [10, 1, 1]
- anchor_scales: [[12, 16],
- [19, 36],
- [40, 28],
- [36, 75],
- [76, 55],
- [72, 146],
- [142, 110],
- [192, 243],
- [459, 401]]
-
- test_img_shape: [608, 608]
- # labels: ['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']
- labels: ['no_mask', 'yes_mask']
- checkpoint_filter_list: ['feature_map.backblock0.conv6.weight', 'feature_map.backblock0.conv6.bias',
- 'feature_map.backblock1.conv6.weight', 'feature_map.backblock1.conv6.bias',
- 'feature_map.backblock2.conv6.weight', 'feature_map.backblock2.conv6.bias',
- 'feature_map.backblock3.conv6.weight', 'feature_map.backblock3.conv6.bias']
- img_id_file_path: ""
- result_files: './result_Files'
-
- ---
-
- # Help description for each configuration
- # Train options
- data_dir: "Train dataset directory."
- per_batch_size: "Batch size for Training."
- pretrained_backbone: "The ckpt file of CspDarkNet53."
- resume_yolov4: "The ckpt file of YOLOv4, which used to fine tune."
- pretrained_checkpoint: "The ckpt file of YoloV4CspDarkNet53."
- filter_weight: "Filter the last weight parameters"
- transfer_train: "If set it True, transfer training on other dataset, and set filter_weight True"
- lr_scheduler: "Learning rate scheduler, options: exponential, cosine_annealing."
- lr: "Learning rate."
- lr_epochs: "Epoch of changing of lr changing, split with ','."
- lr_gamma: "Decrease lr by a factor of exponential lr_scheduler."
- eta_min: "Eta_min in cosine_annealing scheduler."
- t_max: "T-max in cosine_annealing scheduler."
- max_epoch: "Max epoch num to train the model."
- warmup_epochs: "Warmup epochs."
- weight_decay: "Weight decay factor."
- momentum: "Momentum."
- loss_scale: "Static loss scale."
- label_smooth: "Whether to use label smooth in CE."
- label_smooth_factor: "Smooth strength of original one-hot."
- log_interval: "Logging interval steps."
- ckpt_path: "Checkpoint save location."
- ckpt_interval: "Save checkpoint interval."
- is_save_on_master: "Save ckpt on master or all rank, 1 for master, 0 for all ranks."
- is_distributed: "Distribute train or not, 1 for yes, 0 for no."
- rank: "Local rank of distributed."
- group_size: "World size of device."
- need_profiler: "Whether use profiler. 0 for no, 1 for yes."
- training_shape: "Fix training shape."
- resize_rate: "Resize rate for multi-scale training."
- run_eval: "Run evaluation when training."
- save_best_ckpt: "Save best checkpoint when run_eval is True."
- eval_start_epoch: "Evaluation start epoch when run_eval is True."
- eval_interval: "Evaluation interval when run_eval is True"
- ann_file: "path to annotation"
- each_multiscale: "Apply multi-scale for each scale"
- detect_head_loss_coff: "the loss coefficient of detect head.
- The order of coefficients is large head, medium head and small head"
- bbox_class_loss_coff: "bbox and class loss coefficient.
- The order of coefficients is ciou loss, confidence loss and class loss"
- labels: "the label of train data"
- mosaic: "use mosaic data augment"
- multi_label: "use multi label to nms"
- multi_label_thresh: "multi label thresh"
-
- # Eval options
- pretrained: "model_path, local pretrained model to load"
- log_path: "checkpoint save location"
- ann_val_file: "path to annotation"
- xml_dir : 'xml路径'
- jpg_src_path : 'jpg对应路径'
- predict_result : 'xml推理结果路径'
-
- # Export options
- device_id: "Device id for export"
- batch_size: "batch size for export"
- testing_shape: "shape for test"
- ckpt_file: "Checkpoint file path for export"
- file_name: "output file name for export"
- file_format: "file format for export"
- keep_detect: "keep the detect module or not, default: True"
- img_id_file_path: 'path of image dataset'
- result_files: 'path to 310 infer result floder'
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