退购1.1定位算法

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jiajie555
2023-08-10 12:25:23 +08:00
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description: Explore ultralytics.nn.modules.block to build powerful YOLO object detection models. Master DFL, HGStem, SPP, CSP components and more.
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# DFL
---
:::ultralytics.nn.modules.block.DFL
<br><br>
# Proto
---
:::ultralytics.nn.modules.block.Proto
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# HGStem
---
:::ultralytics.nn.modules.block.HGStem
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# HGBlock
---
:::ultralytics.nn.modules.block.HGBlock
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# SPP
---
:::ultralytics.nn.modules.block.SPP
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# SPPF
---
:::ultralytics.nn.modules.block.SPPF
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# C1
---
:::ultralytics.nn.modules.block.C1
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# C2
---
:::ultralytics.nn.modules.block.C2
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# C2f
---
:::ultralytics.nn.modules.block.C2f
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# C3
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:::ultralytics.nn.modules.block.C3
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# C3x
---
:::ultralytics.nn.modules.block.C3x
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# RepC3
---
:::ultralytics.nn.modules.block.RepC3
<br><br>
# C3TR
---
:::ultralytics.nn.modules.block.C3TR
<br><br>
# C3Ghost
---
:::ultralytics.nn.modules.block.C3Ghost
<br><br>
# GhostBottleneck
---
:::ultralytics.nn.modules.block.GhostBottleneck
<br><br>
# Bottleneck
---
:::ultralytics.nn.modules.block.Bottleneck
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# BottleneckCSP
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:::ultralytics.nn.modules.block.BottleneckCSP
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description: Explore convolutional neural network modules & techniques such as LightConv, DWConv, ConvTranspose, GhostConv, CBAM & autopad with Ultralytics Docs.
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# Conv
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:::ultralytics.nn.modules.conv.Conv
<br><br>
# LightConv
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:::ultralytics.nn.modules.conv.LightConv
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# DWConv
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:::ultralytics.nn.modules.conv.DWConv
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# DWConvTranspose2d
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:::ultralytics.nn.modules.conv.DWConvTranspose2d
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# ConvTranspose
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:::ultralytics.nn.modules.conv.ConvTranspose
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# Focus
---
:::ultralytics.nn.modules.conv.Focus
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# GhostConv
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:::ultralytics.nn.modules.conv.GhostConv
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# RepConv
---
:::ultralytics.nn.modules.conv.RepConv
<br><br>
# ChannelAttention
---
:::ultralytics.nn.modules.conv.ChannelAttention
<br><br>
# SpatialAttention
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:::ultralytics.nn.modules.conv.SpatialAttention
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# CBAM
---
:::ultralytics.nn.modules.conv.CBAM
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# Concat
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:::ultralytics.nn.modules.conv.Concat
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# autopad
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:::ultralytics.nn.modules.conv.autopad
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description: 'Learn about Ultralytics YOLO modules: Segment, Classify, and RTDETRDecoder. Optimize object detection and classification in your project.'
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# Detect
---
:::ultralytics.nn.modules.head.Detect
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# Segment
---
:::ultralytics.nn.modules.head.Segment
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# Pose
---
:::ultralytics.nn.modules.head.Pose
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# Classify
---
:::ultralytics.nn.modules.head.Classify
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# RTDETRDecoder
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:::ultralytics.nn.modules.head.RTDETRDecoder
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description: Explore the Ultralytics nn modules pages on Transformer and MLP blocks, LayerNorm2d, and Deformable Transformer Decoder Layer.
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# TransformerEncoderLayer
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:::ultralytics.nn.modules.transformer.TransformerEncoderLayer
<br><br>
# AIFI
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:::ultralytics.nn.modules.transformer.AIFI
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# TransformerLayer
---
:::ultralytics.nn.modules.transformer.TransformerLayer
<br><br>
# TransformerBlock
---
:::ultralytics.nn.modules.transformer.TransformerBlock
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# MLPBlock
---
:::ultralytics.nn.modules.transformer.MLPBlock
<br><br>
# MLP
---
:::ultralytics.nn.modules.transformer.MLP
<br><br>
# LayerNorm2d
---
:::ultralytics.nn.modules.transformer.LayerNorm2d
<br><br>
# MSDeformAttn
---
:::ultralytics.nn.modules.transformer.MSDeformAttn
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# DeformableTransformerDecoderLayer
---
:::ultralytics.nn.modules.transformer.DeformableTransformerDecoderLayer
<br><br>
# DeformableTransformerDecoder
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:::ultralytics.nn.modules.transformer.DeformableTransformerDecoder
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description: 'Learn about Ultralytics NN modules: get_clones, linear_init_, and multi_scale_deformable_attn_pytorch. Code examples and usage tips.'
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# _get_clones
---
:::ultralytics.nn.modules.utils._get_clones
<br><br>
# bias_init_with_prob
---
:::ultralytics.nn.modules.utils.bias_init_with_prob
<br><br>
# linear_init_
---
:::ultralytics.nn.modules.utils.linear_init_
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# inverse_sigmoid
---
:::ultralytics.nn.modules.utils.inverse_sigmoid
<br><br>
# multi_scale_deformable_attn_pytorch
---
:::ultralytics.nn.modules.utils.multi_scale_deformable_attn_pytorch
<br><br>