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- architecture: SSD
- use_gpu: true
- max_iters: 400000
- snapshot_iter: 20000
- log_iter: 20
- metric: COCO
- pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/GhostNet_x1_3_ssld_pretrained.tar
- save_dir: output
- weights: output/ssdlite_ghostnet/model_final
- # 80(label_class) + 1(background)
- num_classes: 81
- SSD:
- backbone: GhostNet
- multi_box_head: SSDLiteMultiBoxHead
- output_decoder:
- background_label: 0
- keep_top_k: 200
- nms_eta: 1.0
- nms_threshold: 0.45
- nms_top_k: 400
- score_threshold: 0.01
- GhostNet:
- scale: 1.3
- extra_block_filters: [[256, 512], [128, 256], [128, 256], [64, 128]]
- feature_maps: [5, 7, 8, 9, 10, 11]
- conv_decay: 0.00004
- lr_mult_list: [0.25, 0.25, 0.5, 0.5, 0.75]
- SSDLiteMultiBoxHead:
- aspect_ratios: [[2.], [2., 3.], [2., 3.], [2., 3.], [2., 3.], [2., 3.]]
- base_size: 320
- steps: [16, 32, 64, 107, 160, 320]
- flip: true
- clip: true
- max_ratio: 95
- min_ratio: 20
- offset: 0.5
- conv_decay: 0.00004
- LearningRate:
- base_lr: 0.2
- schedulers:
- - !CosineDecay
- max_iters: 400000
- - !LinearWarmup
- start_factor: 0.33333
- steps: 2000
- OptimizerBuilder:
- optimizer:
- momentum: 0.9
- type: Momentum
- regularizer:
- factor: 0.0005
- type: L2
- TrainReader:
- inputs_def:
- image_shape: [3, 320, 320]
- fields: ['image', 'gt_bbox', 'gt_class']
- dataset:
- !COCODataSet
- dataset_dir: dataset/coco
- anno_path: annotations/instances_train2017.json
- image_dir: train2017
- sample_transforms:
- - !DecodeImage
- to_rgb: true
- - !RandomDistort
- brightness_lower: 0.875
- brightness_upper: 1.125
- is_order: true
- - !RandomExpand
- fill_value: [123.675, 116.28, 103.53]
- - !RandomCrop
- allow_no_crop: false
- - !NormalizeBox {}
- - !ResizeImage
- interp: 1
- target_size: 320
- use_cv2: false
- - !RandomFlipImage
- is_normalized: false
- - !NormalizeImage
- mean: [0.485, 0.456, 0.406]
- std: [0.229, 0.224, 0.225]
- is_scale: true
- is_channel_first: false
- - !Permute
- to_bgr: false
- channel_first: true
- batch_size: 64
- shuffle: true
- drop_last: true
- # Number of working threads/processes. To speed up, can be set to 16 or 32 etc.
- worker_num: 8
- # Size of shared memory used in result queue. After increasing `worker_num`, need expand `memsize`.
- memsize: 8G
- # Buffer size for multi threads/processes.one instance in buffer is one batch data.
- # To speed up, can be set to 64 or 128 etc.
- bufsize: 32
- use_process: true
- EvalReader:
- inputs_def:
- image_shape: [3, 320, 320]
- fields: ['image', 'gt_bbox', 'gt_class', 'im_shape', 'im_id']
- dataset:
- !COCODataSet
- dataset_dir: dataset/coco
- anno_path: annotations/instances_val2017.json
- image_dir: val2017
- sample_transforms:
- - !DecodeImage
- to_rgb: true
- - !NormalizeBox {}
- - !ResizeImage
- interp: 1
- target_size: 320
- use_cv2: false
- - !NormalizeImage
- mean: [0.485, 0.456, 0.406]
- std: [0.229, 0.224, 0.225]
- is_scale: true
- is_channel_first: false
- - !Permute
- to_bgr: false
- channel_first: True
- batch_size: 8
- worker_num: 8
- bufsize: 32
- use_process: false
- TestReader:
- inputs_def:
- image_shape: [3,320,320]
- fields: ['image', 'im_id', 'im_shape']
- dataset:
- !ImageFolder
- anno_path: annotations/instances_val2017.json
- sample_transforms:
- - !DecodeImage
- to_rgb: true
- - !ResizeImage
- interp: 1
- max_size: 0
- target_size: 320
- use_cv2: true
- - !NormalizeImage
- mean: [0.485, 0.456, 0.406]
- std: [0.229, 0.224, 0.225]
- is_scale: true
- is_channel_first: false
- - !Permute
- to_bgr: false
- channel_first: True
- batch_size: 1
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