darknet53的网络结构笔记
生活随笔
收集整理的這篇文章主要介紹了
darknet53的网络结构笔记
小編覺得挺不錯的,現在分享給大家,幫大家做個參考.
供自己備忘
本網絡結構從gluoncv/model_zoo/yolo/darknet.py調試得到
darknet layers = [1, 2, 8, 8, 4]
darknet channels = [64, 128, 256, 512, 1024]--------------------------------------------------------------------------------Layer (type) Output Shape Param #
================================================================================Input (1, 3, 512, 703) 0Conv2D-1 (1, 32, 512, 703) 864BatchNorm-2 (1, 32, 512, 703) 128LeakyReLU-3 (1, 32, 512, 703) 0
_conv2d 1Conv2D-4 (1, 64, 256, 352) 18432BatchNorm-5 (1, 64, 256, 352) 256LeakyReLU-6 (1, 64, 256, 352) 0
_conv2d 2Conv2D-7 (1, 32, 256, 352) 2048BatchNorm-8 (1, 32, 256, 352) 128LeakyReLU-9 (1, 32, 256, 352) 0Conv2D-10 (1, 64, 256, 352) 18432BatchNorm-11 (1, 64, 256, 352) 256LeakyReLU-12 (1, 64, 256, 352) 0
DarknetBasicBlockV3-13 (1, 64, 256, 352) 0
DarknetBasicBlockV3 3Conv2D-14 (1, 128, 128, 176) 73728BatchNorm-15 (1, 128, 128, 176) 512LeakyReLU-16 (1, 128, 128, 176) 0
_conv2d 4Conv2D-17 (1, 64, 128, 176) 8192BatchNorm-18 (1, 64, 128, 176) 256LeakyReLU-19 (1, 64, 128, 176) 0Conv2D-20 (1, 128, 128, 176) 73728BatchNorm-21 (1, 128, 128, 176) 512LeakyReLU-22 (1, 128, 128, 176) 0
DarknetBasicBlockV3-23 (1, 128, 128, 176) 0
DarknetBasicBlockV3 5Conv2D-24 (1, 64, 128, 176) 8192BatchNorm-25 (1, 64, 128, 176) 256LeakyReLU-26 (1, 64, 128, 176) 0Conv2D-27 (1, 128, 128, 176) 73728BatchNorm-28 (1, 128, 128, 176) 512LeakyReLU-29 (1, 128, 128, 176) 0
DarknetBasicBlockV3-30 (1, 128, 128, 176) 0
DarknetBasicBlockV3 6Conv2D-31 (1, 256, 64, 88) 294912BatchNorm-32 (1, 256, 64, 88) 1024LeakyReLU-33 (1, 256, 64, 88) 0
_conv2d 7Conv2D-34 (1, 128, 64, 88) 32768BatchNorm-35 (1, 128, 64, 88) 512LeakyReLU-36 (1, 128, 64, 88) 0Conv2D-37 (1, 256, 64, 88) 294912BatchNorm-38 (1, 256, 64, 88) 1024LeakyReLU-39 (1, 256, 64, 88) 0
DarknetBasicBlockV3-40 (1, 256, 64, 88) 0
DarknetBasicBlockV3 8Conv2D-41 (1, 128, 64, 88) 32768BatchNorm-42 (1, 128, 64, 88) 512LeakyReLU-43 (1, 128, 64, 88) 0Conv2D-44 (1, 256, 64, 88) 294912BatchNorm-45 (1, 256, 64, 88) 1024LeakyReLU-46 (1, 256, 64, 88) 0
DarknetBasicBlockV3-47 (1, 256, 64, 88) 0
DarknetBasicBlockV3 9Conv2D-48 (1, 128, 64, 88) 32768BatchNorm-49 (1, 128, 64, 88) 512LeakyReLU-50 (1, 128, 64, 88) 0Conv2D-51 (1, 256, 64, 88) 294912BatchNorm-52 (1, 256, 64, 88) 1024LeakyReLU-53 (1, 256, 64, 88) 0
DarknetBasicBlockV3-54 (1, 256, 64, 88) 0
DarknetBasicBlockV3 10Conv2D-55 (1, 128, 64, 88) 32768BatchNorm-56 (1, 128, 64, 88) 512LeakyReLU-57 (1, 128, 64, 88) 0Conv2D-58 (1, 256, 64, 88) 294912BatchNorm-59 (1, 256, 64, 88) 1024LeakyReLU-60 (1, 256, 64, 88) 0
DarknetBasicBlockV3-61 (1, 256, 64, 88) 0
DarknetBasicBlockV3 11Conv2D-62 (1, 128, 64, 88) 32768BatchNorm-63 (1, 128, 64, 88) 512LeakyReLU-64 (1, 128, 64, 88) 0Conv2D-65 (1, 256, 64, 88) 294912BatchNorm-66 (1, 256, 64, 88) 1024LeakyReLU-67 (1, 256, 64, 88) 0
DarknetBasicBlockV3-68 (1, 256, 64, 88) 0
DarknetBasicBlockV3 12Conv2D-69 (1, 128, 64, 88) 32768BatchNorm-70 (1, 128, 64, 88) 512LeakyReLU-71 (1, 128, 64, 88) 0Conv2D-72 (1, 256, 64, 88) 294912BatchNorm-73 (1, 256, 64, 88) 1024LeakyReLU-74 (1, 256, 64, 88) 0
DarknetBasicBlockV3-75 (1, 256, 64, 88) 0
DarknetBasicBlockV3 13Conv2D-76 (1, 128, 64, 88) 32768BatchNorm-77 (1, 128, 64, 88) 512LeakyReLU-78 (1, 128, 64, 88) 0Conv2D-79 (1, 256, 64, 88) 294912BatchNorm-80 (1, 256, 64, 88) 1024LeakyReLU-81 (1, 256, 64, 88) 0
DarknetBasicBlockV3-82 (1, 256, 64, 88) 0
DarknetBasicBlockV3 14Conv2D-83 (1, 128, 64, 88) 32768BatchNorm-84 (1, 128, 64, 88) 512LeakyReLU-85 (1, 128, 64, 88) 0Conv2D-86 (1, 256, 64, 88) 294912BatchNorm-87 (1, 256, 64, 88) 1024LeakyReLU-88 (1, 256, 64, 88) 0
DarknetBasicBlockV3-89 (1, 256, 64, 88) 0
DarknetBasicBlockV3 15
---------------------------------------------------------------------------------------------------------Conv2D-90 (1, 512, 32, 44) 1179648BatchNorm-91 (1, 512, 32, 44) 2048LeakyReLU-92 (1, 512, 32, 44) 0
_conv2d 16Conv2D-93 (1, 256, 32, 44) 131072BatchNorm-94 (1, 256, 32, 44) 1024LeakyReLU-95 (1, 256, 32, 44) 0Conv2D-96 (1, 512, 32, 44) 1179648BatchNorm-97 (1, 512, 32, 44) 2048LeakyReLU-98 (1, 512, 32, 44) 0
DarknetBasicBlockV3-99 (1, 512, 32, 44) 0
DarknetBasicBlockV3 17Conv2D-100 (1, 256, 32, 44) 131072BatchNorm-101 (1, 256, 32, 44) 1024LeakyReLU-102 (1, 256, 32, 44) 0Conv2D-103 (1, 512, 32, 44) 1179648BatchNorm-104 (1, 512, 32, 44) 2048LeakyReLU-105 (1, 512, 32, 44) 0
DarknetBasicBlockV3-106 (1, 512, 32, 44) 0
DarknetBasicBlockV3 18Conv2D-107 (1, 256, 32, 44) 131072BatchNorm-108 (1, 256, 32, 44) 1024LeakyReLU-109 (1, 256, 32, 44) 0Conv2D-110 (1, 512, 32, 44) 1179648BatchNorm-111 (1, 512, 32, 44) 2048LeakyReLU-112 (1, 512, 32, 44) 0
DarknetBasicBlockV3-113 (1, 512, 32, 44) 0
DarknetBasicBlockV3 19Conv2D-114 (1, 256, 32, 44) 131072BatchNorm-115 (1, 256, 32, 44) 1024LeakyReLU-116 (1, 256, 32, 44) 0Conv2D-117 (1, 512, 32, 44) 1179648BatchNorm-118 (1, 512, 32, 44) 2048LeakyReLU-119 (1, 512, 32, 44) 0
DarknetBasicBlockV3-120 (1, 512, 32, 44) 0
DarknetBasicBlockV3 20Conv2D-121 (1, 256, 32, 44) 131072BatchNorm-122 (1, 256, 32, 44) 1024LeakyReLU-123 (1, 256, 32, 44) 0Conv2D-124 (1, 512, 32, 44) 1179648BatchNorm-125 (1, 512, 32, 44) 2048LeakyReLU-126 (1, 512, 32, 44) 0
DarknetBasicBlockV3-127 (1, 512, 32, 44) 0
DarknetBasicBlockV3 21Conv2D-128 (1, 256, 32, 44) 131072BatchNorm-129 (1, 256, 32, 44) 1024LeakyReLU-130 (1, 256, 32, 44) 0Conv2D-131 (1, 512, 32, 44) 1179648BatchNorm-132 (1, 512, 32, 44) 2048LeakyReLU-133 (1, 512, 32, 44) 0
DarknetBasicBlockV3-134 (1, 512, 32, 44) 0
DarknetBasicBlockV3 22Conv2D-135 (1, 256, 32, 44) 131072BatchNorm-136 (1, 256, 32, 44) 1024LeakyReLU-137 (1, 256, 32, 44) 0Conv2D-138 (1, 512, 32, 44) 1179648BatchNorm-139 (1, 512, 32, 44) 2048LeakyReLU-140 (1, 512, 32, 44) 0
DarknetBasicBlockV3-141 (1, 512, 32, 44) 0
DarknetBasicBlockV3 23Conv2D-142 (1, 256, 32, 44) 131072BatchNorm-143 (1, 256, 32, 44) 1024LeakyReLU-144 (1, 256, 32, 44) 0Conv2D-145 (1, 512, 32, 44) 1179648BatchNorm-146 (1, 512, 32, 44) 2048LeakyReLU-147 (1, 512, 32, 44) 0
DarknetBasicBlockV3-148 (1, 512, 32, 44) 0
DarknetBasicBlockV3 24
---------------------------------------------------------------------------------------------------------Conv2D-149 (1, 1024, 16, 22) 4718592BatchNorm-150 (1, 1024, 16, 22) 4096LeakyReLU-151 (1, 1024, 16, 22) 0
_conv2d 25Conv2D-152 (1, 512, 16, 22) 524288BatchNorm-153 (1, 512, 16, 22) 2048LeakyReLU-154 (1, 512, 16, 22) 0Conv2D-155 (1, 1024, 16, 22) 4718592BatchNorm-156 (1, 1024, 16, 22) 4096LeakyReLU-157 (1, 1024, 16, 22) 0
DarknetBasicBlockV3-158 (1, 1024, 16, 22) 0
DarknetBasicBlockV3 26Conv2D-159 (1, 512, 16, 22) 524288BatchNorm-160 (1, 512, 16, 22) 2048LeakyReLU-161 (1, 512, 16, 22) 0Conv2D-162 (1, 1024, 16, 22) 4718592BatchNorm-163 (1, 1024, 16, 22) 4096LeakyReLU-164 (1, 1024, 16, 22) 0
DarknetBasicBlockV3-165 (1, 1024, 16, 22) 0
DarknetBasicBlockV3 27Conv2D-166 (1, 512, 16, 22) 524288BatchNorm-167 (1, 512, 16, 22) 2048LeakyReLU-168 (1, 512, 16, 22) 0Conv2D-169 (1, 1024, 16, 22) 4718592BatchNorm-170 (1, 1024, 16, 22) 4096LeakyReLU-171 (1, 1024, 16, 22) 0
DarknetBasicBlockV3-172 (1, 1024, 16, 22) 0
DarknetBasicBlockV3 28Conv2D-173 (1, 512, 16, 22) 524288BatchNorm-174 (1, 512, 16, 22) 2048LeakyReLU-175 (1, 512, 16, 22) 0Conv2D-176 (1, 1024, 16, 22) 4718592BatchNorm-177 (1, 1024, 16, 22) 4096LeakyReLU-178 (1, 1024, 16, 22) 0
DarknetBasicBlockV3-179 (1, 1024, 16, 22) 0
DarknetBasicBlockV3 29
---------------------------------------------------------------------------------------------------------Dense-180 (1, 1000) 1025000DarknetV3-181 (1, 1000) 0
================================================================================
?
總結
以上是生活随笔為你收集整理的darknet53的网络结构笔记的全部內容,希望文章能夠幫你解決所遇到的問題。
- 上一篇: mxnet 中的 DepthwiseCo
- 下一篇: yolov3网络结构笔记