yikestone/ros_openvino_tiny-yolov3
1
0
Fork 0
mirror of https://gitlab.com/yikestone/ros_openvino_tiny-yolov3.git synced 2025-08-03 21:54:10 +05:30
Code Issues Projects Releases Wiki Activity
ros_openvino_tiny-yolov3/irmodels/tiny-YoloV3/FP32/frozen_tiny_yolo_v3.xml
yikestone 7da068af7a Added robosub weights
2019-08-03 23:22:24 -07:00

784 lines
21 KiB
XML
Raw Permalink Blame History

<?xml version="1.0" ?>
<net batch="1" name="frozen_tiny_yolo_v3" version="4">
<layers>
<layer id="0" name="inputs" precision="FP32" type="Input">
<output>
<port id="0">
<dim>1</dim>
<dim>3</dim>
<dim>416</dim>
<dim>416</dim>
</port>
</output>
</layer>
<layer id="1" name="detector/yolo-v3-tiny/Conv/Conv2D" precision="FP32" type="Convolution">
<data auto_pad="same_upper" dilations="1,1" group="1" kernel="3,3" output="16" pads_begin="1,1" pads_end="1,1" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>3</dim>
<dim>416</dim>
<dim>416</dim>
</port>
</input>
<output>
<port id="3">
<dim>1</dim>
<dim>16</dim>
<dim>416</dim>
<dim>416</dim>
</port>
</output>
<blobs>
<weights offset="0" size="1728"/>
<biases offset="1728" size="64"/>
</blobs>
</layer>
<layer id="2" name="LeakyReLU_857" precision="FP32" type="ReLU">
<data negative_slope="0.10000000149011612"/>
<input>
<port id="0">
<dim>1</dim>
<dim>16</dim>
<dim>416</dim>
<dim>416</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>16</dim>
<dim>416</dim>
<dim>416</dim>
</port>
</output>
</layer>
<layer id="3" name="detector/yolo-v3-tiny/pool2/MaxPool" precision="FP32" type="Pooling">
<data auto_pad="valid" exclude-pad="true" kernel="2,2" pads_begin="0,0" pads_end="0,0" pool-method="max" strides="2,2"/>
<input>
<port id="0">
<dim>1</dim>
<dim>16</dim>
<dim>416</dim>
<dim>416</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>16</dim>
<dim>208</dim>
<dim>208</dim>
</port>
</output>
</layer>
<layer id="4" name="detector/yolo-v3-tiny/Conv_1/Conv2D" precision="FP32" type="Convolution">
<data auto_pad="same_upper" dilations="1,1" group="1" kernel="3,3" output="32" pads_begin="1,1" pads_end="1,1" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>16</dim>
<dim>208</dim>
<dim>208</dim>
</port>
</input>
<output>
<port id="3">
<dim>1</dim>
<dim>32</dim>
<dim>208</dim>
<dim>208</dim>
</port>
</output>
<blobs>
<weights offset="1792" size="18432"/>
<biases offset="20224" size="128"/>
</blobs>
</layer>
<layer id="5" name="LeakyReLU_856" precision="FP32" type="ReLU">
<data negative_slope="0.10000000149011612"/>
<input>
<port id="0">
<dim>1</dim>
<dim>32</dim>
<dim>208</dim>
<dim>208</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>32</dim>
<dim>208</dim>
<dim>208</dim>
</port>
</output>
</layer>
<layer id="6" name="detector/yolo-v3-tiny/pool2_1/MaxPool" precision="FP32" type="Pooling">
<data auto_pad="valid" exclude-pad="true" kernel="2,2" pads_begin="0,0" pads_end="0,0" pool-method="max" strides="2,2"/>
<input>
<port id="0">
<dim>1</dim>
<dim>32</dim>
<dim>208</dim>
<dim>208</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>32</dim>
<dim>104</dim>
<dim>104</dim>
</port>
</output>
</layer>
<layer id="7" name="detector/yolo-v3-tiny/Conv_2/Conv2D" precision="FP32" type="Convolution">
<data auto_pad="same_upper" dilations="1,1" group="1" kernel="3,3" output="64" pads_begin="1,1" pads_end="1,1" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>32</dim>
<dim>104</dim>
<dim>104</dim>
</port>
</input>
<output>
<port id="3">
<dim>1</dim>
<dim>64</dim>
<dim>104</dim>
<dim>104</dim>
</port>
</output>
<blobs>
<weights offset="20352" size="73728"/>
<biases offset="94080" size="256"/>
</blobs>
</layer>
<layer id="8" name="LeakyReLU_859" precision="FP32" type="ReLU">
<data negative_slope="0.10000000149011612"/>
<input>
<port id="0">
<dim>1</dim>
<dim>64</dim>
<dim>104</dim>
<dim>104</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>64</dim>
<dim>104</dim>
<dim>104</dim>
</port>
</output>
</layer>
<layer id="9" name="detector/yolo-v3-tiny/pool2_2/MaxPool" precision="FP32" type="Pooling">
<data auto_pad="valid" exclude-pad="true" kernel="2,2" pads_begin="0,0" pads_end="0,0" pool-method="max" strides="2,2"/>
<input>
<port id="0">
<dim>1</dim>
<dim>64</dim>
<dim>104</dim>
<dim>104</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>64</dim>
<dim>52</dim>
<dim>52</dim>
</port>
</output>
</layer>
<layer id="10" name="detector/yolo-v3-tiny/Conv_3/Conv2D" precision="FP32" type="Convolution">
<data auto_pad="same_upper" dilations="1,1" group="1" kernel="3,3" output="128" pads_begin="1,1" pads_end="1,1" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>64</dim>
<dim>52</dim>
<dim>52</dim>
</port>
</input>
<output>
<port id="3">
<dim>1</dim>
<dim>128</dim>
<dim>52</dim>
<dim>52</dim>
</port>
</output>
<blobs>
<weights offset="94336" size="294912"/>
<biases offset="389248" size="512"/>
</blobs>
</layer>
<layer id="11" name="LeakyReLU_865" precision="FP32" type="ReLU">
<data negative_slope="0.10000000149011612"/>
<input>
<port id="0">
<dim>1</dim>
<dim>128</dim>
<dim>52</dim>
<dim>52</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>128</dim>
<dim>52</dim>
<dim>52</dim>
</port>
</output>
</layer>
<layer id="12" name="detector/yolo-v3-tiny/pool2_3/MaxPool" precision="FP32" type="Pooling">
<data auto_pad="valid" exclude-pad="true" kernel="2,2" pads_begin="0,0" pads_end="0,0" pool-method="max" strides="2,2"/>
<input>
<port id="0">
<dim>1</dim>
<dim>128</dim>
<dim>52</dim>
<dim>52</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>128</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</output>
</layer>
<layer id="13" name="detector/yolo-v3-tiny/Conv_4/Conv2D" precision="FP32" type="Convolution">
<data auto_pad="same_upper" dilations="1,1" group="1" kernel="3,3" output="256" pads_begin="1,1" pads_end="1,1" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>128</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</input>
<output>
<port id="3">
<dim>1</dim>
<dim>256</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</output>
<blobs>
<weights offset="389760" size="1179648"/>
<biases offset="1569408" size="1024"/>
</blobs>
</layer>
<layer id="14" name="LeakyReLU_863" precision="FP32" type="ReLU">
<data negative_slope="0.10000000149011612"/>
<input>
<port id="0">
<dim>1</dim>
<dim>256</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>256</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</output>
</layer>
<layer id="15" name="detector/yolo-v3-tiny/pool2_4/MaxPool" precision="FP32" type="Pooling">
<data auto_pad="valid" exclude-pad="true" kernel="2,2" pads_begin="0,0" pads_end="0,0" pool-method="max" strides="2,2"/>
<input>
<port id="0">
<dim>1</dim>
<dim>256</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>256</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
</layer>
<layer id="16" name="detector/yolo-v3-tiny/Conv_5/Conv2D" precision="FP32" type="Convolution">
<data auto_pad="same_upper" dilations="1,1" group="1" kernel="3,3" output="512" pads_begin="1,1" pads_end="1,1" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>256</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="3">
<dim>1</dim>
<dim>512</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
<blobs>
<weights offset="1570432" size="4718592"/>
<biases offset="6289024" size="2048"/>
</blobs>
</layer>
<layer id="17" name="LeakyReLU_864" precision="FP32" type="ReLU">
<data negative_slope="0.10000000149011612"/>
<input>
<port id="0">
<dim>1</dim>
<dim>512</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>512</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
</layer>
<layer id="18" name="detector/yolo-v3-tiny/pool2_5/MaxPool" precision="FP32" type="Pooling">
<data auto_pad="same_upper" exclude-pad="true" kernel="2,2" pads_begin="0,0" pads_end="1,1" pool-method="max" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>512</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>512</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
</layer>
<layer id="19" name="detector/yolo-v3-tiny/Conv_6/Conv2D" precision="FP32" type="Convolution">
<data auto_pad="same_upper" dilations="1,1" group="1" kernel="3,3" output="1024" pads_begin="1,1" pads_end="1,1" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>512</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="3">
<dim>1</dim>
<dim>1024</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
<blobs>
<weights offset="6291072" size="18874368"/>
<biases offset="25165440" size="4096"/>
</blobs>
</layer>
<layer id="20" name="LeakyReLU_862" precision="FP32" type="ReLU">
<data negative_slope="0.10000000149011612"/>
<input>
<port id="0">
<dim>1</dim>
<dim>1024</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>1024</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
</layer>
<layer id="21" name="detector/yolo-v3-tiny/Conv_7/Conv2D" precision="FP32" type="Convolution">
<data auto_pad="same_upper" dilations="1,1" group="1" kernel="1,1" output="256" pads_begin="0,0" pads_end="0,0" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>1024</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="3">
<dim>1</dim>
<dim>256</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
<blobs>
<weights offset="25169536" size="1048576"/>
<biases offset="26218112" size="1024"/>
</blobs>
</layer>
<layer id="22" name="LeakyReLU_861" precision="FP32" type="ReLU">
<data negative_slope="0.10000000149011612"/>
<input>
<port id="0">
<dim>1</dim>
<dim>256</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>256</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
</layer>
<layer id="23" name="detector/yolo-v3-tiny/Conv_10/Conv2D" precision="FP32" type="Convolution">
<data auto_pad="same_upper" dilations="1,1" group="1" kernel="1,1" output="128" pads_begin="0,0" pads_end="0,0" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>256</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="3">
<dim>1</dim>
<dim>128</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
<blobs>
<weights offset="26219136" size="131072"/>
<biases offset="26350208" size="512"/>
</blobs>
</layer>
<layer id="24" name="LeakyReLU_858" precision="FP32" type="ReLU">
<data negative_slope="0.10000000149011612"/>
<input>
<port id="0">
<dim>1</dim>
<dim>128</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>128</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
</layer>
<layer id="25" name="detector/yolo-v3-tiny/ResizeNearestNeighbor" precision="FP32" type="Resample">
<data antialias="0" factor="2.0" type="caffe.ResampleParameter.NEAREST"/>
<input>
<port id="0">
<dim>1</dim>
<dim>128</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>128</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</output>
</layer>
<layer id="26" name="detector/yolo-v3-tiny/concat_3" precision="FP32" type="Concat">
<data axis="1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>128</dim>
<dim>26</dim>
<dim>26</dim>
</port>
<port id="1">
<dim>1</dim>
<dim>256</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</input>
<output>
<port id="2">
<dim>1</dim>
<dim>384</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</output>
</layer>
<layer id="27" name="detector/yolo-v3-tiny/Conv_11/Conv2D" precision="FP32" type="Convolution">
<data auto_pad="same_upper" dilations="1,1" group="1" kernel="3,3" output="256" pads_begin="1,1" pads_end="1,1" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>384</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</input>
<output>
<port id="3">
<dim>1</dim>
<dim>256</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</output>
<blobs>
<weights offset="26350720" size="3538944"/>
<biases offset="29889664" size="1024"/>
</blobs>
</layer>
<layer id="28" name="LeakyReLU_860" precision="FP32" type="ReLU">
<data negative_slope="0.10000000149011612"/>
<input>
<port id="0">
<dim>1</dim>
<dim>256</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>256</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</output>
</layer>
<layer id="29" name="detector/yolo-v3-tiny/Conv_12/Conv2D" precision="FP32" type="Convolution">
<data auto_pad="same_upper" dilations="1,1" group="1" kernel="1,1" output="255" pads_begin="0,0" pads_end="0,0" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>256</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</input>
<output>
<port id="3">
<dim>1</dim>
<dim>255</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</output>
<blobs>
<weights offset="29890688" size="261120"/>
<biases offset="30151808" size="1020"/>
</blobs>
</layer>
<layer id="30" name="detector/yolo-v3-tiny/Conv_12/BiasAdd/YoloRegion" precision="FP32" type="RegionYolo">
<data anchors="10,14,23,27,37,58,81,82,135,169,344,319" axis="1" classes="80" coords="4" do_softmax="0" end_axis="3" mask="0,1,2" num="6"/>
<input>
<port id="0">
<dim>1</dim>
<dim>255</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>255</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</output>
</layer>
<layer id="31" name="detector/yolo-v3-tiny/Conv_8/Conv2D" precision="FP32" type="Convolution">
<data auto_pad="same_upper" dilations="1,1" group="1" kernel="3,3" output="512" pads_begin="1,1" pads_end="1,1" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>256</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="3">
<dim>1</dim>
<dim>512</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
<blobs>
<weights offset="30152828" size="4718592"/>
<biases offset="34871420" size="2048"/>
</blobs>
</layer>
<layer id="32" name="LeakyReLU_" precision="FP32" type="ReLU">
<data negative_slope="0.10000000149011612"/>
<input>
<port id="0">
<dim>1</dim>
<dim>512</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>512</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
</layer>
<layer id="33" name="detector/yolo-v3-tiny/Conv_9/Conv2D" precision="FP32" type="Convolution">
<data auto_pad="same_upper" dilations="1,1" group="1" kernel="1,1" output="255" pads_begin="0,0" pads_end="0,0" strides="1,1"/>
<input>
<port id="0">
<dim>1</dim>
<dim>512</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="3">
<dim>1</dim>
<dim>255</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
<blobs>
<weights offset="34873468" size="522240"/>
<biases offset="35395708" size="1020"/>
</blobs>
</layer>
<layer id="34" name="detector/yolo-v3-tiny/Conv_9/BiasAdd/YoloRegion" precision="FP32" type="RegionYolo">
<data anchors="10,14,23,27,37,58,81,82,135,169,344,319" axis="1" classes="80" coords="4" do_softmax="0" end_axis="3" mask="0,1,2" num="6"/>
<input>
<port id="0">
<dim>1</dim>
<dim>255</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="1">
<dim>1</dim>
<dim>255</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="1" to-port="0"/>
<edge from-layer="1" from-port="3" to-layer="2" to-port="0"/>
<edge from-layer="2" from-port="1" to-layer="3" to-port="0"/>
<edge from-layer="3" from-port="1" to-layer="4" to-port="0"/>
<edge from-layer="4" from-port="3" to-layer="5" to-port="0"/>
<edge from-layer="5" from-port="1" to-layer="6" to-port="0"/>
<edge from-layer="6" from-port="1" to-layer="7" to-port="0"/>
<edge from-layer="7" from-port="3" to-layer="8" to-port="0"/>
<edge from-layer="8" from-port="1" to-layer="9" to-port="0"/>
<edge from-layer="9" from-port="1" to-layer="10" to-port="0"/>
<edge from-layer="10" from-port="3" to-layer="11" to-port="0"/>
<edge from-layer="11" from-port="1" to-layer="12" to-port="0"/>
<edge from-layer="12" from-port="1" to-layer="13" to-port="0"/>
<edge from-layer="13" from-port="3" to-layer="14" to-port="0"/>
<edge from-layer="14" from-port="1" to-layer="15" to-port="0"/>
<edge from-layer="15" from-port="1" to-layer="16" to-port="0"/>
<edge from-layer="16" from-port="3" to-layer="17" to-port="0"/>
<edge from-layer="17" from-port="1" to-layer="18" to-port="0"/>
<edge from-layer="18" from-port="1" to-layer="19" to-port="0"/>
<edge from-layer="19" from-port="3" to-layer="20" to-port="0"/>
<edge from-layer="20" from-port="1" to-layer="21" to-port="0"/>
<edge from-layer="21" from-port="3" to-layer="22" to-port="0"/>
<edge from-layer="22" from-port="1" to-layer="23" to-port="0"/>
<edge from-layer="23" from-port="3" to-layer="24" to-port="0"/>
<edge from-layer="24" from-port="1" to-layer="25" to-port="0"/>
<edge from-layer="25" from-port="1" to-layer="26" to-port="0"/>
<edge from-layer="14" from-port="1" to-layer="26" to-port="1"/>
<edge from-layer="26" from-port="2" to-layer="27" to-port="0"/>
<edge from-layer="27" from-port="3" to-layer="28" to-port="0"/>
<edge from-layer="28" from-port="1" to-layer="29" to-port="0"/>
<edge from-layer="29" from-port="3" to-layer="30" to-port="0"/>
<edge from-layer="22" from-port="1" to-layer="31" to-port="0"/>
<edge from-layer="31" from-port="3" to-layer="32" to-port="0"/>
<edge from-layer="32" from-port="1" to-layer="33" to-port="0"/>
<edge from-layer="33" from-port="3" to-layer="34" to-port="0"/>
</edges>
<meta_data>
<MO_version value="1.5.12.49d067a0"/>
<cli_parameters>
<batch value="1"/>
<data_type value="FP32"/>
<disable_fusing value="False"/>
<disable_gfusing value="False"/>
<disable_nhwc_to_nchw value="False"/>
<disable_resnet_optimization value="False"/>
<extensions value="DIR"/>
<framework value="tf"/>
<generate_deprecated_IR_V2 value="False"/>
<input_model value="DIR/frozen_tiny_yolo_v3.pb"/>
<input_model_is_text value="False"/>
<log_level value="ERROR"/>
<mean_values value="()"/>
<move_to_preprocess value="False"/>
<offload_unsupported_operations_to_tf value="False"/>
<output_dir value="DIR"/>
<reverse_input_channels value="False"/>
<scale_values value="()"/>
<silent value="False"/>
<tensorflow_use_custom_operations_config value="DIR/yolo_v3_tiny_changed.json"/>
<version value="False"/>
<unset unset_cli_parameters="finegrain_fusing, freeze_placeholder_with_value, input, input_checkpoint, input_meta_graph, input_shape, model_name, output, saved_model_dir, saved_model_tags, scale, tensorboard_logdir, tensorflow_custom_layer_libraries, tensorflow_custom_operations_config_update, tensorflow_object_detection_api_pipeline_config, tensorflow_operation_patterns, tensorflow_subgraph_patterns"/>
</cli_parameters>
</meta_data>
</net>
Reference in New Issue View Git Blame Copy Permalink