use_gpu: true log_iter: 5 save_dir: output snapshot_epoch: 10 weights: output/hrnet_w32_384x288/model_final epoch: 210 num_joints: &num_joints 17 pixel_std: &pixel_std 200 metric: KeyPointTopDownCOCOEval num_classes: 1 train_height: &train_height 384 train_width: &train_width 288 trainsize: &trainsize [*train_width, *train_height] hmsize: &hmsize [72, 96] flip_perm: &flip_perm [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10], [11, 12], [13, 14], [15, 16]] #####model architecture: TopDownHRNet pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/Trunc_HRNet_W32_C_pretrained.pdparams TopDownHRNet: backbone: HRNet post_process: HRNetPostProcess flip_perm: *flip_perm num_joints: *num_joints width: &width 32 loss: KeyPointMSELoss flip: true HRNet: width: *width freeze_at: -1 freeze_norm: false return_idx: [0] KeyPointMSELoss: use_target_weight: true #####optimizer LearningRate: base_lr: 0.0005 schedulers: - !PiecewiseDecay milestones: [170, 200] gamma: 0.1 - !LinearWarmup start_factor: 0.001 steps: 1000 OptimizerBuilder: optimizer: type: Adam regularizer: factor: 0.0 type: L2 #####data TrainDataset: !KeypointTopDownCocoDataset image_dir: train2017 anno_path: annotations/person_keypoints_train2017.json dataset_dir: dataset/coco num_joints: *num_joints trainsize: *trainsize pixel_std: *pixel_std use_gt_bbox: True EvalDataset: !KeypointTopDownCocoDataset image_dir: val2017 anno_path: annotations/person_keypoints_val2017.json dataset_dir: dataset/coco bbox_file: bbox.json num_joints: *num_joints trainsize: *trainsize pixel_std: *pixel_std use_gt_bbox: True image_thre: 0.0 TestDataset: !ImageFolder anno_path: dataset/coco/keypoint_imagelist.txt worker_num: 2 global_mean: &global_mean [0.485, 0.456, 0.406] global_std: &global_std [0.229, 0.224, 0.225] TrainReader: sample_transforms: - RandomFlipHalfBodyTransform: scale: 0.5 rot: 40 num_joints_half_body: 8 prob_half_body: 0.3 pixel_std: *pixel_std trainsize: *trainsize upper_body_ids: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] flip_pairs: *flip_perm - TopDownAffine: trainsize: *trainsize - ToHeatmapsTopDown: hmsize: *hmsize sigma: 2 batch_transforms: - NormalizeImage: mean: *global_mean std: *global_std is_scale: true - Permute: {} batch_size: 64 shuffle: true drop_last: false EvalReader: sample_transforms: - TopDownAffine: trainsize: *trainsize batch_transforms: - NormalizeImage: mean: *global_mean std: *global_std is_scale: true - Permute: {} batch_size: 16 TestReader: inputs_def: image_shape: [3, *train_height, *train_width] sample_transforms: - Decode: {} - TopDownEvalAffine: trainsize: *trainsize - NormalizeImage: mean: *global_mean std: *global_std is_scale: true - Permute: {} batch_size: 1