# YOLOx Config yolox_cfg = { 'yolox_n':{ # ---------------- Model config ---------------- ## Backbone 'backbone': 'cspdarknet', 'pretrained': True, 'bk_act': 'silu', 'bk_norm': 'BN', 'bk_dpw': False, 'width': 0.25, 'depth': 0.34, 'stride': [8, 16, 32], # P3, P4, P5 'max_stride': 32, ## FPN 'fpn': 'yolov5_pafpn', 'fpn_reduce_layer': 'Conv', 'fpn_downsample_layer': 'Conv', 'fpn_core_block': 'CSPBlock', 'fpn_act': 'silu', 'fpn_norm': 'BN', 'fpn_depthwise': False, ## Head 'head': 'decoupled_head', 'head_act': 'silu', 'head_norm': 'BN', 'num_cls_head': 2, 'num_reg_head': 2, 'head_depthwise': False, # ---------------- Train config ---------------- ## input 'multi_scale': [0.5, 1.5], # 320 -> 960 'trans_type': 'yolox_tiny', # ---------------- Assignment config ---------------- ## matcher 'matcher': {'center_sampling_radius': 2.5, 'topk_candicate': 10}, # ---------------- Loss config ---------------- ## loss weight 'loss_obj_weight': 1.0, 'loss_cls_weight': 1.0, 'loss_box_weight': 5.0, # ---------------- Train config ---------------- ## close strong augmentation 'no_aug_epoch': 20, ## optimizer 'optimizer': 'sgd', # optional: sgd, AdamW 'momentum': 0.9, # SGD: 0.9; AdamW: None 'weight_decay': 5e-4, # SGD: 5e-4; AdamW: 5e-2 'clip_grad': 10, # SGD: 10.0; AdamW: -1 ## model EMA 'ema_decay': 0.9999, # SGD: 0.9999; AdamW: 0.9998 'ema_tau': 2000, ## lr schedule 'scheduler': 'linear', 'lr0': 0.01, # SGD: 0.01; AdamW: 0.001 'lrf': 0.01, # SGD: 0.01; AdamW: 0.01 'warmup_momentum': 0.8, 'warmup_bias_lr': 0.1, }, 'yolox_s':{ # ---------------- Model config ---------------- ## Backbone 'backbone': 'cspdarknet', 'pretrained': True, 'bk_act': 'silu', 'bk_norm': 'BN', 'bk_dpw': False, 'width': 0.50, 'depth': 0.34, 'stride': [8, 16, 32], # P3, P4, P5 'max_stride': 32, ## FPN 'fpn': 'yolov5_pafpn', 'fpn_reduce_layer': 'Conv', 'fpn_downsample_layer': 'Conv', 'fpn_core_block': 'CSPBlock', 'fpn_act': 'silu', 'fpn_norm': 'BN', 'fpn_depthwise': False, ## Head 'head': 'decoupled_head', 'head_act': 'silu', 'head_norm': 'BN', 'num_cls_head': 2, 'num_reg_head': 2, 'head_depthwise': False, # ---------------- Train config ---------------- ## input 'multi_scale': [0.5, 1.5], # 320 -> 960 'trans_type': 'yolox_small', # ---------------- Assignment config ---------------- ## matcher 'matcher': {'center_sampling_radius': 2.5, 'topk_candicate': 10}, # ---------------- Loss config ---------------- ## loss weight 'loss_obj_weight': 1.0, 'loss_cls_weight': 1.0, 'loss_box_weight': 5.0, # ---------------- Train config ---------------- ## close strong augmentation 'no_aug_epoch': 20, ## optimizer 'optimizer': 'sgd', # optional: sgd, AdamW 'momentum': 0.9, # SGD: 0.9; AdamW: None 'weight_decay': 5e-4, # SGD: 5e-4; AdamW: 5e-2 'clip_grad': 10, # SGD: 10.0; AdamW: -1 ## model EMA 'ema_decay': 0.9999, # SGD: 0.9999; AdamW: 0.9998 'ema_tau': 2000, ## lr schedule 'scheduler': 'linear', 'lr0': 0.01, # SGD: 0.01; AdamW: 0.001 'lrf': 0.01, # SGD: 0.01; AdamW: 0.01 'warmup_momentum': 0.8, 'warmup_bias_lr': 0.1, }, 'yolox_m':{ # ---------------- Model config ---------------- ## Backbone 'backbone': 'cspdarknet', 'pretrained': True, 'bk_act': 'silu', 'bk_norm': 'BN', 'bk_dpw': False, 'width': 0.75, 'depth': 0.67, 'stride': [8, 16, 32], # P3, P4, P5 'max_stride': 32, ## FPN 'fpn': 'yolov5_pafpn', 'fpn_reduce_layer': 'Conv', 'fpn_downsample_layer': 'Conv', 'fpn_core_block': 'CSPBlock', 'fpn_act': 'silu', 'fpn_norm': 'BN', 'fpn_depthwise': False, ## Head 'head': 'decoupled_head', 'head_act': 'silu', 'head_norm': 'BN', 'num_cls_head': 2, 'num_reg_head': 2, 'head_depthwise': False, # ---------------- Train config ---------------- ## input 'multi_scale': [0.5, 1.5], # 320 -> 960 'trans_type': 'yolox_medium', # ---------------- Assignment config ---------------- ## matcher 'matcher': {'center_sampling_radius': 2.5, 'topk_candicate': 10}, # ---------------- Loss config ---------------- ## loss weight 'loss_obj_weight': 1.0, 'loss_cls_weight': 1.0, 'loss_box_weight': 5.0, # ---------------- Train config ---------------- ## close strong augmentation 'no_aug_epoch': 20, ## optimizer 'optimizer': 'sgd', # optional: sgd, AdamW 'momentum': 0.9, # SGD: 0.9; AdamW: None 'weight_decay': 5e-4, # SGD: 5e-4; AdamW: 5e-2 'clip_grad': 10, # SGD: 10.0; AdamW: -1 ## model EMA 'ema_decay': 0.9999, # SGD: 0.9999; AdamW: 0.9998 'ema_tau': 2000, ## lr schedule 'scheduler': 'linear', 'lr0': 0.01, # SGD: 0.01; AdamW: 0.001 'lrf': 0.01, # SGD: 0.01; AdamW: 0.01 'warmup_momentum': 0.8, 'warmup_bias_lr': 0.1, }, 'yolox_l':{ # ---------------- Model config ---------------- ## Backbone 'backbone': 'cspdarknet', 'pretrained': False, 'bk_act': 'silu', 'bk_norm': 'BN', 'bk_dpw': False, 'width': 1.0, 'depth': 1.0, 'stride': [8, 16, 32], # P3, P4, P5 'max_stride': 32, ## FPN 'fpn': 'yolov5_pafpn', 'fpn_reduce_layer': 'Conv', 'fpn_downsample_layer': 'Conv', 'fpn_core_block': 'CSPBlock', 'fpn_act': 'silu', 'fpn_norm': 'BN', 'fpn_depthwise': False, ## Head 'head': 'decoupled_head', 'head_act': 'silu', 'head_norm': 'BN', 'num_cls_head': 2, 'num_reg_head': 2, 'head_depthwise': False, # ---------------- Train config ---------------- ## input 'multi_scale': [0.5, 1.25], # 320 -> 800 'trans_type': 'yolox_large', # ---------------- Assignment config ---------------- ## matcher 'matcher': {'center_sampling_radius': 2.5, 'topk_candicate': 10}, # ---------------- Loss config ---------------- ## loss weight 'loss_obj_weight': 1.0, 'loss_cls_weight': 1.0, 'loss_box_weight': 5.0, # ---------------- Train config ---------------- ## close strong augmentation 'no_aug_epoch': 20, ## optimizer 'optimizer': 'sgd', # optional: sgd, AdamW 'momentum': 0.9, # SGD: 0.9; AdamW: None 'weight_decay': 5e-4, # SGD: 5e-4; AdamW: 5e-2 'clip_grad': 10, # SGD: 10.0; AdamW: -1 ## model EMA 'ema_decay': 0.9999, # SGD: 0.9999; AdamW: 0.9998 'ema_tau': 2000, ## lr schedule 'scheduler': 'linear', 'lr0': 0.01, # SGD: 0.01; AdamW: 0.001 'lrf': 0.01, # SGD: 0.01; AdamW: 0.01 'warmup_momentum': 0.8, 'warmup_bias_lr': 0.1, }, 'yolox_x':{ # ---------------- Model config ---------------- ## Backbone 'backbone': 'cspdarknet', 'pretrained': True, 'bk_act': 'silu', 'bk_norm': 'BN', 'bk_dpw': False, 'width': 1.25, 'depth': 1.34, 'stride': [8, 16, 32], # P3, P4, P5 'max_stride': 32, ## FPN 'fpn': 'yolov5_pafpn', 'fpn_reduce_layer': 'Conv', 'fpn_downsample_layer': 'Conv', 'fpn_core_block': 'CSPBlock', 'fpn_act': 'silu', 'fpn_norm': 'BN', 'fpn_depthwise': False, ## Head 'head': 'decoupled_head', 'head_act': 'silu', 'head_norm': 'BN', 'num_cls_head': 2, 'num_reg_head': 2, 'head_depthwise': False, # ---------------- Train config ---------------- ## input 'multi_scale': [0.5, 1.25], # 320 -> 800 'trans_type': 'yolox_huge', # ---------------- Assignment config ---------------- ## matcher 'matcher': {'center_sampling_radius': 2.5, 'topk_candicate': 10}, # ---------------- Loss config ---------------- ## loss weight 'loss_obj_weight': 1.0, 'loss_cls_weight': 1.0, 'loss_box_weight': 5.0, # ---------------- Train config ---------------- ## close strong augmentation 'no_aug_epoch': 20, ## optimizer 'optimizer': 'sgd', # optional: sgd, AdamW 'momentum': 0.9, # SGD: 0.9; AdamW: None 'weight_decay': 5e-4, # SGD: 5e-4; AdamW: 5e-2 'clip_grad': 10, # SGD: 10.0; AdamW: -1 ## model EMA 'ema_decay': 0.9999, # SGD: 0.9999; AdamW: 0.9998 'ema_tau': 2000, ## lr schedule 'scheduler': 'linear', 'lr0': 0.01, # SGD: 0.01; AdamW: 0.001 'lrf': 0.01, # SGD: 0.01; AdamW: 0.01 'warmup_momentum': 0.8, 'warmup_bias_lr': 0.1, }, }