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| _base_ = './yolov7_l_syncbn_fast_8x16b-300e_coco.py' | |
| # ========================modified parameters======================== | |
| # -----model related----- | |
| # Data augmentation | |
| max_translate_ratio = 0.1 # YOLOv5RandomAffine | |
| scaling_ratio_range = (0.5, 1.6) # YOLOv5RandomAffine | |
| mixup_prob = 0.05 # YOLOv5MixUp | |
| randchoice_mosaic_prob = [0.8, 0.2] | |
| mixup_alpha = 8.0 # YOLOv5MixUp | |
| mixup_beta = 8.0 # YOLOv5MixUp | |
| # -----train val related----- | |
| loss_cls_weight = 0.5 | |
| loss_obj_weight = 1.0 | |
| lr_factor = 0.01 # Learning rate scaling factor | |
| # ===============================Unmodified in most cases==================== | |
| num_classes = _base_.num_classes | |
| num_det_layers = _base_.num_det_layers | |
| img_scale = _base_.img_scale | |
| pre_transform = _base_.pre_transform | |
| model = dict( | |
| backbone=dict( | |
| arch='Tiny', act_cfg=dict(type='LeakyReLU', negative_slope=0.1)), | |
| neck=dict( | |
| is_tiny_version=True, | |
| in_channels=[128, 256, 512], | |
| out_channels=[64, 128, 256], | |
| block_cfg=dict( | |
| _delete_=True, type='TinyDownSampleBlock', middle_ratio=0.25), | |
| act_cfg=dict(type='LeakyReLU', negative_slope=0.1), | |
| use_repconv_outs=False), | |
| bbox_head=dict( | |
| head_module=dict(in_channels=[128, 256, 512]), | |
| loss_cls=dict(loss_weight=loss_cls_weight * | |
| (num_classes / 80 * 3 / num_det_layers)), | |
| loss_obj=dict(loss_weight=loss_obj_weight * | |
| ((img_scale[0] / 640)**2 * 3 / num_det_layers)))) | |
| mosiac4_pipeline = [ | |
| dict( | |
| type='Mosaic', | |
| img_scale=img_scale, | |
| pad_val=114.0, | |
| pre_transform=pre_transform), | |
| dict( | |
| type='YOLOv5RandomAffine', | |
| max_rotate_degree=0.0, | |
| max_shear_degree=0.0, | |
| max_translate_ratio=max_translate_ratio, # change | |
| scaling_ratio_range=scaling_ratio_range, # change | |
| # img_scale is (width, height) | |
| border=(-img_scale[0] // 2, -img_scale[1] // 2), | |
| border_val=(114, 114, 114)), | |
| ] | |
| mosiac9_pipeline = [ | |
| dict( | |
| type='Mosaic9', | |
| img_scale=img_scale, | |
| pad_val=114.0, | |
| pre_transform=pre_transform), | |
| dict( | |
| type='YOLOv5RandomAffine', | |
| max_rotate_degree=0.0, | |
| max_shear_degree=0.0, | |
| max_translate_ratio=max_translate_ratio, # change | |
| scaling_ratio_range=scaling_ratio_range, # change | |
| border=(-img_scale[0] // 2, -img_scale[1] // 2), | |
| border_val=(114, 114, 114)), | |
| ] | |
| randchoice_mosaic_pipeline = dict( | |
| type='RandomChoice', | |
| transforms=[mosiac4_pipeline, mosiac9_pipeline], | |
| prob=randchoice_mosaic_prob) | |
| train_pipeline = [ | |
| *pre_transform, | |
| randchoice_mosaic_pipeline, | |
| dict( | |
| type='YOLOv5MixUp', | |
| alpha=mixup_alpha, | |
| beta=mixup_beta, | |
| prob=mixup_prob, # change | |
| pre_transform=[*pre_transform, randchoice_mosaic_pipeline]), | |
| dict(type='YOLOv5HSVRandomAug'), | |
| dict(type='mmdet.RandomFlip', prob=0.5), | |
| dict( | |
| type='mmdet.PackDetInputs', | |
| meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', 'flip', | |
| 'flip_direction')) | |
| ] | |
| train_dataloader = dict(dataset=dict(pipeline=train_pipeline)) | |
| default_hooks = dict(param_scheduler=dict(lr_factor=lr_factor)) | |