# global configs Global: checkpoints: null pretrained_model: null output_dir: "./output/" device: "gpu" save_interval: 40 eval_during_train: True eval_interval: 10 epochs: 120 print_batch_step: 20 use_visualdl: False eval_mode: "retrieval" re_ranking: False feat_from: "backbone" # 'backbone' or 'neck' # used for static mode and model export image_shape: [3, 256, 128] save_inference_dir: "./inference" # model architecture Arch: name: "RecModel" infer_output_key: "features" infer_add_softmax: False Backbone: name: "ResNet50_last_stage_stride1" pretrained: True stem_act: null BackboneStopLayer: name: "flatten" Head: name: "FC" embedding_size: 2048 class_num: 751 weight_attr: initializer: name: Normal std: 0.001 bias_attr: False # loss function config for traing/eval process Loss: Train: - CELoss: weight: 1.0 epsilon: 0.1 - TripletLossV2: weight: 1.0 margin: 0.3 normalize_feature: false feat_from: "backbone" Eval: - CELoss: weight: 1.0 Optimizer: name: Momentum momentum: 0.9 lr: name: Piecewise decay_epochs: [30, 60] values: [0.00035, 0.000035, 0.0000035] warmup_epoch: 10 warmup_start_lr: 0.0000035 regularizer: name: 'L2' coeff: 0.0005 # data loader for train and eval DataLoader: Train: dataset: name: "Market1501" image_root: "./dataset/" cls_label_path: "bounding_box_train" transform_ops: - ResizeImage: size: [128, 256] - RandFlipImage: flip_code: 1 - Pad: padding: 10 - RandCropImage: size: [128, 256] scale: [0.8022, 0.8022] ratio: [0.5, 0.5] - NormalizeImage: mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225] order: '' sampler: name: DistributedRandomIdentitySampler batch_size: 64 num_instances: 4 drop_last: True shuffle: True loader: num_workers: 4 use_shared_memory: True Eval: Query: dataset: name: "Market1501" image_root: "./dataset/" cls_label_path: "query" transform_ops: - ResizeImage: size: [128, 256] - NormalizeImage: mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225] order: '' sampler: name: DistributedBatchSampler batch_size: 128 drop_last: False shuffle: False loader: num_workers: 4 use_shared_memory: True Gallery: dataset: name: "Market1501" image_root: "./dataset/" cls_label_path: "bounding_box_test" transform_ops: - ResizeImage: size: [128, 256] - NormalizeImage: mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225] order: '' sampler: name: DistributedBatchSampler batch_size: 128 drop_last: False shuffle: False loader: num_workers: 4 use_shared_memory: True Metric: Eval: - Recallk: topk: [1, 5] - mAP: {}