mirror of https://github.com/open-mmlab/mmyolo.git
41 lines
1.6 KiB
Markdown
41 lines
1.6 KiB
Markdown
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# 应用多个 Neck
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如果你想堆叠多个 Neck，可以直接在配置文件中的 Neck 参数，MMYOLO 支持以 `List` 形式拼接多个 Neck 配置，你需要保证上一个 Neck 的输出通道与下一个 Neck
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的输入通道相匹配。如需要调整通道，可以插入 `mmdet.ChannelMapper` 模块用来对齐多个 Neck 之间的通道数量。具体配置如下：
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```python
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_base_ = './yolov5_s-v61_syncbn_8xb16-300e_coco.py'
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deepen_factor = _base_.deepen_factor
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widen_factor = _base_.widen_factor
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model = dict(
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type='YOLODetector',
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neck=[
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dict(
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type='YOLOv5PAFPN',
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deepen_factor=deepen_factor,
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widen_factor=widen_factor,
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in_channels=[256, 512, 1024],
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out_channels=[256, 512, 1024],
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# 因为 out_channels 由 widen_factor 控制，YOLOv5PAFPN 的 out_channels = out_channels * widen_factor
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num_csp_blocks=3,
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norm_cfg=dict(type='BN', momentum=0.03, eps=0.001),
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act_cfg=dict(type='SiLU', inplace=True)),
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dict(
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type='mmdet.ChannelMapper',
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in_channels=[128, 256, 512],
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out_channels=128,
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),
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dict(
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type='mmdet.DyHead',
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in_channels=128,
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out_channels=256,
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num_blocks=2,
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# disable zero_init_offset to follow official implementation
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zero_init_offset=False)
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],
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bbox_head=dict(head_module=dict(in_channels=[512, 512, 512]))
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# 因为 out_channels 由 widen_factor 控制，YOLOv5HeadModuled 的 in_channels * widen_factor 才会等于最后一个 neck 的 out_channels
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)
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```
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