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33 lines
1.7 KiB
33 lines
1.7 KiB
# Ultralytics YOLO 🚀, AGPL-3.0 license |
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""" |
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Ultralytics modules. |
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Example: |
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Visualize a module with Netron. |
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```python |
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from ultralytics.nn.modules import * |
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import torch |
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import os |
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x = torch.ones(1, 128, 40, 40) |
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m = Conv(128, 128) |
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f = f'{m._get_name()}.onnx' |
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torch.onnx.export(m, x, f) |
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os.system(f'onnxsim {f} {f} && open {f}') |
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``` |
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""" |
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from .block import (C1, C2, C3, C3TR, DFL, SPP, SPPF, Bottleneck, BottleneckCSP, C2f, C3Ghost, C3x, GhostBottleneck, |
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HGBlock, HGStem, Proto, RepC3, ResNetLayer) |
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from .conv import (CBAM, ChannelAttention, Concat, Conv, Conv2, ConvTranspose, DWConv, DWConvTranspose2d, Focus, |
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GhostConv, LightConv, RepConv, SpatialAttention) |
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from .head import Classify, Detect, Pose, RTDETRDecoder, Segment |
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from .transformer import (AIFI, MLP, DeformableTransformerDecoder, DeformableTransformerDecoderLayer, LayerNorm2d, |
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MLPBlock, MSDeformAttn, TransformerBlock, TransformerEncoderLayer, TransformerLayer) |
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__all__ = ('Conv', 'Conv2', 'LightConv', 'RepConv', 'DWConv', 'DWConvTranspose2d', 'ConvTranspose', 'Focus', |
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'GhostConv', 'ChannelAttention', 'SpatialAttention', 'CBAM', 'Concat', 'TransformerLayer', |
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'TransformerBlock', 'MLPBlock', 'LayerNorm2d', 'DFL', 'HGBlock', 'HGStem', 'SPP', 'SPPF', 'C1', 'C2', 'C3', |
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'C2f', 'C3x', 'C3TR', 'C3Ghost', 'GhostBottleneck', 'Bottleneck', 'BottleneckCSP', 'Proto', 'Detect', |
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'Segment', 'Pose', 'Classify', 'TransformerEncoderLayer', 'RepC3', 'RTDETRDecoder', 'AIFI', |
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'DeformableTransformerDecoder', 'DeformableTransformerDecoderLayer', 'MSDeformAttn', 'MLP', 'ResNetLayer')
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