| checkpoint_config = dict(interval=9) | |
| log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook')]) | |
| custom_hooks = [dict(type='NumClassCheckHook')] | |
| dist_params = dict(backend='nccl') | |
| log_level = 'INFO' | |
| load_from = None | |
| resume_from = None | |
| workflow = [('train', 1)] | |
| optimizer = dict( | |
| type='AdamW', | |
| lr=2.5e-05, | |
| betas=(0.9, 0.999), | |
| weight_decay=0.05, | |
| paramwise_cfg=dict( | |
| custom_keys=dict( | |
| absolute_pos_embed=dict(decay_mult=0.0), | |
| relative_position_bias_table=dict(decay_mult=0.0), | |
| norm=dict(decay_mult=0.0)))) | |
| optimizer_config = dict(grad_clip=None) | |
| lr_config = dict( | |
| policy='step', | |
| warmup='linear', | |
| warmup_iters=500, | |
| warmup_ratio=0.3333333333333333, | |
| step=[6]) | |
| runner = dict(type='EpochBasedRunner', max_epochs=9) | |
| pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.2/mask_rcnn_swin_tiny_patch4_window7.pth' | |
| is_video_model = True | |
| model = dict( | |
| type='STPN', | |
| detector=dict( | |
| type='FasterRCNN', | |
| backbone=dict( | |
| type='STPNSwinTransformer', | |
| embed_dims=96, | |
| depths=[2, 2, 6, 2], | |
| num_heads=[3, 6, 12, 24], | |
| window_size=7, | |
| mlp_ratio=4, | |
| qkv_bias=True, | |
| qk_scale=None, | |
| drop_rate=0.0, | |
| attn_drop_rate=0.0, | |
| drop_path_rate=0.2, | |
| patch_norm=True, | |
| with_cp=False, | |
| convert_weights=True, | |
| init_cfg=dict( | |
| type='Pretrained', | |
| checkpoint= | |
| 'https://github.com/SwinTransformer/storage/releases/download/v1.0.2/mask_rcnn_swin_tiny_patch4_window7.pth' | |
| ), | |
| prompt_cfg=dict( | |
| num_tokens=5, | |
| location='prepend', | |
| deep=False, | |
| dropout=0.0, | |
| initiation='random')), | |
| neck=dict( | |
| type='FPN', | |
| in_channels=[96, 192, 384, 768], | |
| out_channels=256, | |
| num_outs=5), | |
| rpn_head=dict( | |
| type='RPNHead', | |
| in_channels=256, | |
| feat_channels=256, | |
| anchor_generator=dict( | |
| type='AnchorGenerator', | |
| scales=[8], | |
| ratios=[0.5, 1.0, 2.0], | |
| strides=[4, 8, 16, 32, 64]), | |
| bbox_coder=dict( | |
| type='DeltaXYWHBBoxCoder', | |
| target_means=[0.0, 0.0, 0.0, 0.0], | |
| target_stds=[1.0, 1.0, 1.0, 1.0]), | |
| loss_cls=dict( | |
| type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0), | |
| loss_bbox=dict( | |
| type='SmoothL1Loss', beta=0.1111111111111111, | |
| loss_weight=1.0)), | |
| roi_head=dict( | |
| type='StandardRoIHead', | |
| bbox_roi_extractor=dict( | |
| type='SingleRoIExtractor', | |
| roi_layer=dict( | |
| type='RoIAlign', output_size=7, sampling_ratio=0), | |
| out_channels=256, | |
| featmap_strides=[4, 8, 16, 32]), | |
| bbox_head=dict( | |
| type='Shared2FCBBoxHead', | |
| in_channels=256, | |
| fc_out_channels=1024, | |
| roi_feat_size=7, | |
| num_classes=30, | |
| bbox_coder=dict( | |
| type='DeltaXYWHBBoxCoder', | |
| target_means=[0.0, 0.0, 0.0, 0.0], | |
| target_stds=[0.2, 0.2, 0.2, 0.2]), | |
| reg_class_agnostic=False, | |
| loss_cls=dict( | |
| type='CrossEntropyLoss', | |
| use_sigmoid=False, | |
| loss_weight=1.0), | |
| loss_bbox=dict( | |
| type='SmoothL1Loss', | |
| beta=0.1111111111111111, | |
| loss_weight=1.0))), | |
| train_cfg=dict( | |
| rpn=dict( | |
| assigner=dict( | |
| type='MaxIoUAssigner', | |
| pos_iou_thr=0.7, | |
| neg_iou_thr=0.3, | |
| min_pos_iou=0.3, | |
| match_low_quality=True, | |
| ignore_iof_thr=-1), | |
| sampler=dict( | |
| type='RandomSampler', | |
| num=256, | |
| pos_fraction=0.5, | |
| neg_pos_ub=-1, | |
| add_gt_as_proposals=False), | |
| allowed_border=-1, | |
| pos_weight=-1, | |
| debug=False), | |
| rpn_proposal=dict( | |
| nms_pre=1000, | |
| max_per_img=300, | |
| nms=dict(type='nms', iou_threshold=0.7), | |
| min_bbox_size=0), | |
| rcnn=dict( | |
| assigner=dict( | |
| type='MaxIoUAssigner', | |
| pos_iou_thr=0.5, | |
| neg_iou_thr=0.5, | |
| min_pos_iou=0.5, | |
| match_low_quality=True, | |
| ignore_iof_thr=-1), | |
| sampler=dict( | |
| type='RandomSampler', | |
| num=256, | |
| pos_fraction=0.25, | |
| neg_pos_ub=-1, | |
| add_gt_as_proposals=True), | |
| mask_size=28, | |
| pos_weight=-1, | |
| debug=False)), | |
| test_cfg=dict( | |
| rpn=dict( | |
| nms_pre=1000, | |
| max_per_img=300, | |
| nms=dict(type='nms', iou_threshold=0.7), | |
| min_bbox_size=0), | |
| rcnn=dict( | |
| score_thr=0.0001, | |
| nms=dict(type='nms', iou_threshold=0.5), | |
| max_per_img=100, | |
| mask_thr_binary=0.5)))) | |
| dataset_type = 'ImagenetVIDDataset' | |
| data_root = 'data/ILSVRC/' | |
| img_norm_cfg = dict( | |
| mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) | |
| train_pipeline = [ | |
| dict(type='LoadMultiImagesFromFile'), | |
| dict(type='SeqLoadAnnotations', with_bbox=True, with_mask=False), | |
| dict(type='SeqRandomFlip', share_params=True, flip_ratio=0.5), | |
| dict( | |
| type='AutoAugment', | |
| policies=[[{ | |
| 'type': | |
| 'SeqResize', | |
| 'img_scale': [(480, 1333), (512, 1333), (544, 1333), (576, 1333), | |
| (608, 1333), (640, 1333), (672, 1333), (704, 1333), | |
| (736, 1333), (768, 1333), (800, 1333)], | |
| 'multiscale_mode': | |
| 'value', | |
| 'keep_ratio': | |
| True | |
| }], | |
| [{ | |
| 'type': 'SeqResize', | |
| 'img_scale': [(400, 1333), (500, 1333), (600, 1333)], | |
| 'multiscale_mode': 'value', | |
| 'keep_ratio': True | |
| }, { | |
| 'type': 'SeqRandomCrop', | |
| 'crop_type': 'absolute_range', | |
| 'crop_size': (384, 600), | |
| 'allow_negative_crop': True | |
| }, { | |
| 'type': 'SeqMaxSizePad' | |
| }, { | |
| 'type': | |
| 'SeqResize2', | |
| 'img_scale': [(480, 1333), (512, 1333), (544, 1333), | |
| (576, 1333), (608, 1333), (640, 1333), | |
| (672, 1333), (704, 1333), (736, 1333), | |
| (768, 1333), (800, 1333)], | |
| 'multiscale_mode': | |
| 'value', | |
| 'keep_ratio': | |
| True | |
| }]]), | |
| dict( | |
| type='SeqNormalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| to_rgb=True), | |
| dict(type='SeqPad', size_divisor=16), | |
| dict(type='VideoCollect', keys=['img', 'gt_bboxes', 'gt_labels']), | |
| dict(type='ConcatVideoReferences'), | |
| dict(type='SeqDefaultFormatBundle', ref_prefix='ref') | |
| ] | |
| test_pipeline = [ | |
| dict(type='LoadMultiImagesFromFile'), | |
| dict(type='SeqResize', img_scale=(1000, 600), keep_ratio=True), | |
| dict(type='SeqRandomFlip', share_params=True, flip_ratio=0.0), | |
| dict( | |
| type='SeqNormalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| to_rgb=True), | |
| dict(type='SeqPad', size_divisor=16), | |
| dict( | |
| type='VideoCollect', | |
| keys=['img'], | |
| meta_keys=('num_left_ref_imgs', 'frame_stride')), | |
| dict(type='ConcatVideoReferences'), | |
| dict(type='MultiImagesToTensor', ref_prefix='ref'), | |
| dict(type='ToList') | |
| ] | |
| data = dict( | |
| samples_per_gpu=1, | |
| workers_per_gpu=4, | |
| train=[ | |
| dict( | |
| type='ImagenetVIDDataset', | |
| ann_file='data/ILSVRC/annotations/imagenet_vid_train.json', | |
| img_prefix='data/ILSVRC/Data/VID', | |
| ref_img_sampler=dict( | |
| num_ref_imgs=2, | |
| frame_range=9, | |
| filter_key_img=True, | |
| method='bilateral_uniform'), | |
| pipeline=[ | |
| dict(type='LoadMultiImagesFromFile'), | |
| dict( | |
| type='SeqLoadAnnotations', with_bbox=True, | |
| with_mask=False), | |
| dict(type='SeqRandomFlip', share_params=True, flip_ratio=0.5), | |
| dict( | |
| type='AutoAugment', | |
| policies=[[{ | |
| 'type': | |
| 'SeqResize', | |
| 'img_scale': [(480, 1333), (512, 1333), (544, 1333), | |
| (576, 1333), (608, 1333), (640, 1333), | |
| (672, 1333), (704, 1333), (736, 1333), | |
| (768, 1333), (800, 1333)], | |
| 'multiscale_mode': | |
| 'value', | |
| 'keep_ratio': | |
| True | |
| }], | |
| [{ | |
| 'type': | |
| 'SeqResize', | |
| 'img_scale': [(400, 1333), (500, 1333), | |
| (600, 1333)], | |
| 'multiscale_mode': | |
| 'value', | |
| 'keep_ratio': | |
| True | |
| }, { | |
| 'type': 'SeqRandomCrop', | |
| 'crop_type': 'absolute_range', | |
| 'crop_size': (384, 600), | |
| 'allow_negative_crop': True | |
| }, { | |
| 'type': 'SeqMaxSizePad' | |
| }, { | |
| 'type': | |
| 'SeqResize2', | |
| 'img_scale': [(480, 1333), (512, 1333), | |
| (544, 1333), (576, 1333), | |
| (608, 1333), (640, 1333), | |
| (672, 1333), (704, 1333), | |
| (736, 1333), (768, 1333), | |
| (800, 1333)], | |
| 'multiscale_mode': | |
| 'value', | |
| 'keep_ratio': | |
| True | |
| }]]), | |
| dict( | |
| type='SeqNormalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| to_rgb=True), | |
| dict(type='SeqPad', size_divisor=16), | |
| dict( | |
| type='VideoCollect', | |
| keys=['img', 'gt_bboxes', 'gt_labels']), | |
| dict(type='ConcatVideoReferences'), | |
| dict(type='SeqDefaultFormatBundle', ref_prefix='ref') | |
| ]), | |
| dict( | |
| type='ImagenetVIDDataset', | |
| load_as_video=False, | |
| ann_file='data/ILSVRC/annotations/imagenet_det_30plus1cls.json', | |
| img_prefix='data/ILSVRC/Data/DET', | |
| ref_img_sampler=dict( | |
| num_ref_imgs=2, | |
| frame_range=0, | |
| filter_key_img=False, | |
| method='bilateral_uniform'), | |
| pipeline=[ | |
| dict(type='LoadMultiImagesFromFile'), | |
| dict( | |
| type='SeqLoadAnnotations', with_bbox=True, | |
| with_mask=False), | |
| dict(type='SeqRandomFlip', share_params=True, flip_ratio=0.5), | |
| dict( | |
| type='AutoAugment', | |
| policies=[[{ | |
| 'type': | |
| 'SeqResize', | |
| 'img_scale': [(480, 1333), (512, 1333), (544, 1333), | |
| (576, 1333), (608, 1333), (640, 1333), | |
| (672, 1333), (704, 1333), (736, 1333), | |
| (768, 1333), (800, 1333)], | |
| 'multiscale_mode': | |
| 'value', | |
| 'keep_ratio': | |
| True | |
| }], | |
| [{ | |
| 'type': | |
| 'SeqResize', | |
| 'img_scale': [(400, 1333), (500, 1333), | |
| (600, 1333)], | |
| 'multiscale_mode': | |
| 'value', | |
| 'keep_ratio': | |
| True | |
| }, { | |
| 'type': 'SeqRandomCrop', | |
| 'crop_type': 'absolute_range', | |
| 'crop_size': (384, 600), | |
| 'allow_negative_crop': True | |
| }, { | |
| 'type': 'SeqMaxSizePad' | |
| }, { | |
| 'type': | |
| 'SeqResize2', | |
| 'img_scale': [(480, 1333), (512, 1333), | |
| (544, 1333), (576, 1333), | |
| (608, 1333), (640, 1333), | |
| (672, 1333), (704, 1333), | |
| (736, 1333), (768, 1333), | |
| (800, 1333)], | |
| 'multiscale_mode': | |
| 'value', | |
| 'keep_ratio': | |
| True | |
| }]]), | |
| dict( | |
| type='SeqNormalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| to_rgb=True), | |
| dict(type='SeqPad', size_divisor=16), | |
| dict( | |
| type='VideoCollect', | |
| keys=['img', 'gt_bboxes', 'gt_labels']), | |
| dict(type='ConcatVideoReferences'), | |
| dict(type='SeqDefaultFormatBundle', ref_prefix='ref') | |
| ]) | |
| ], | |
| val=dict( | |
| type='ImagenetVIDDataset', | |
| ann_file='data/ILSVRC/annotations/imagenet_vid_val.json', | |
| img_prefix='data/ILSVRC/Data/VID', | |
| ref_img_sampler=dict( | |
| num_ref_imgs=14, | |
| frame_range=[-7, 7], | |
| method='test_with_adaptive_stride'), | |
| pipeline=[ | |
| dict(type='LoadMultiImagesFromFile'), | |
| dict(type='SeqResize', img_scale=(1000, 600), keep_ratio=True), | |
| dict(type='SeqRandomFlip', share_params=True, flip_ratio=0.0), | |
| dict( | |
| type='SeqNormalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| to_rgb=True), | |
| dict(type='SeqPad', size_divisor=16), | |
| dict( | |
| type='VideoCollect', | |
| keys=['img'], | |
| meta_keys=('num_left_ref_imgs', 'frame_stride')), | |
| dict(type='ConcatVideoReferences'), | |
| dict(type='MultiImagesToTensor', ref_prefix='ref'), | |
| dict(type='ToList') | |
| ], | |
| test_mode=True), | |
| test=dict( | |
| type='ImagenetVIDDataset', | |
| ann_file='data/ILSVRC/annotations/imagenet_vid_val.json', | |
| img_prefix='data/ILSVRC/Data/VID', | |
| ref_img_sampler=dict( | |
| num_ref_imgs=14, | |
| frame_range=[-7, 7], | |
| method='test_with_adaptive_stride'), | |
| pipeline=[ | |
| dict(type='LoadMultiImagesFromFile'), | |
| dict(type='SeqResize', img_scale=(1000, 600), keep_ratio=True), | |
| dict(type='SeqRandomFlip', share_params=True, flip_ratio=0.0), | |
| dict( | |
| type='SeqNormalize', | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| to_rgb=True), | |
| dict(type='SeqPad', size_divisor=16), | |
| dict( | |
| type='VideoCollect', | |
| keys=['img'], | |
| meta_keys=('num_left_ref_imgs', 'frame_stride')), | |
| dict(type='ConcatVideoReferences'), | |
| dict(type='MultiImagesToTensor', ref_prefix='ref'), | |
| dict(type='ToList') | |
| ], | |
| test_mode=True)) | |
| total_epochs = 9 | |
| evaluation = dict(metric=['bbox'], vid_style=True, interval=9) | |
| work_dir = './work_dirs/stpn_swint_adam_9x' | |
| gpu_ids = range(0, 8) | |