diff --git "a/models/MiDaS_small.xml" "b/models/MiDaS_small.xml"
new file mode 100644--- /dev/null
+++ "b/models/MiDaS_small.xml"
@@ -0,0 +1,10464 @@
+<?xml version="1.0" ?>
+<net name="MiDaS_small" version="10">
+	<layers>
+		<layer id="0" name="input.1" type="Parameter" version="opset1">
+			<data shape="1,3,256,256" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16" names="input.1">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="data_mul_15300_const" type="Const" version="opset1">
+			<data offset="0" size="6" shape="1,3,1,1" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="2" name="input.1/scale/Fused_Mul_" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="3" name="data_add_15302_const" type="Const" version="opset1">
+			<data offset="6" size="6" shape="1,3,1,1" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="input.1/mean/Fused_Add_" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="5" name="1351/Output_0/Data__const" type="Const" version="opset1">
+			<data offset="12" size="1728" shape="32,3,3,3" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16" names="1351">
+					<dim>32</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" name="Conv_80/WithoutBiases" type="Convolution" version="opset1">
+			<data auto_pad="explicit" strides="2,2" dilations="1,1" pads_begin="0,0" pads_end="1,1"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1">
+					<dim>32</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="7" name="Conv_80/Dims977615600/EltwiseUnsqueeze15899_const" type="Const" version="opset1">
+			<data offset="1740" size="64" shape="1,32,1,1" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="8" name="Conv_80" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16" names="1350">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="9" name="Clip_83" type="Clamp" version="opset1">
+			<data max="6.0" min="0.0"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP16" names="584">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="10" name="2792027923_const" type="Const" version="opset1">
+			<data offset="1804" size="576" shape="32,1,1,3,3" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16" names="1354">
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="11" name="Conv_84/WithoutBiases" type="GroupConvolution" version="opset1">
+			<data auto_pad="explicit" strides="1,1" dilations="1,1" pads_begin="1,1" pads_end="1,1"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1">
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="12" name="Conv_84/Dims944015544/EltwiseUnsqueeze15675_const" type="Const" version="opset1">
+			<data offset="2380" size="64" shape="1,32,1,1" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="13" name="Conv_84" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16" names="1353">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="14" name="Clip_87" type="Clamp" version="opset1">
+			<data max="6.0" min="0.0"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP16" names="589">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="15" name="1357/Output_0/Data__const" type="Const" version="opset1">
+			<data offset="2444" size="1536" shape="24,32,1,1" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16" names="1357">
+					<dim>24</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="16" name="Conv_88/WithoutBiases" type="Convolution" version="opset1">
+			<data auto_pad="explicit" strides="1,1" dilations="1,1" pads_begin="0,0" pads_end="0,0"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1">
+					<dim>24</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>1</dim>
+					<dim>24</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="17" name="Conv_88/Dims938615535/EltwiseUnsqueeze15639_const" type="Const" version="opset1">
+			<data offset="3980" size="48" shape="1,24,1,1" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>24</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="18" name="Conv_88" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>24</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1">
+					<dim>1</dim>
+					<dim>24</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16" names="1356">
+					<dim>1</dim>
+					<dim>24</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="19" name="1360/Output_0/Data__const" type="Const" version="opset1">
+			<data offset="4028" size="6912" shape="144,24,1,1" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16" names="1360">
+					<dim>144</dim>
+					<dim>24</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="20" name="Conv_89/WithoutBiases" type="Convolution" version="opset1">
+			<data auto_pad="explicit" strides="1,1" dilations="1,1" pads_begin="0,0" pads_end="0,0"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>24</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1">
+					<dim>144</dim>
+					<dim>24</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="21" name="Conv_89/Dims968015584/EltwiseUnsqueeze15835_const" type="Const" version="opset1">
+			<data offset="10940" size="288" shape="1,144,1,1" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="22" name="Conv_89" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16" names="1359">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="23" name="Clip_92" type="Clamp" version="opset1">
+			<data max="6.0" min="0.0"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP16" names="596">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="24" name="2796027963_const" type="Const" version="opset1">
+			<data offset="11228" size="2592" shape="144,1,1,3,3" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16" names="1363">
+					<dim>144</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="25" name="Conv_173/WithoutBiases" type="GroupConvolution" version="opset1">
+			<data auto_pad="explicit" strides="2,2" dilations="1,1" pads_begin="0,0" pads_end="1,1"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1">
+					<dim>144</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="26" name="Conv_173/Dims951815557/EltwiseUnsqueeze15727_const" type="Const" version="opset1">
+			<data offset="13820" size="288" shape="1,144,1,1" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="27" name="Conv_173" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16" names="1362">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="28" name="Clip_176" type="Clamp" version="opset1">
+			<data max="6.0" min="0.0"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP16" names="698">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="29" name="1366/Output_0/Data__const" type="Const" version="opset1">
+			<data offset="14108" size="9216" shape="32,144,1,1" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16" names="1366">
+					<dim>32</dim>
+					<dim>144</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="30" name="Conv_177/WithoutBiases" type="Convolution" version="opset1">
+			<data auto_pad="explicit" strides="1,1" dilations="1,1" pads_begin="0,0" pads_end="0,0"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>144</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1">
+					<dim>32</dim>
+					<dim>144</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="31" name="Conv_177/Dims960815572/EltwiseUnsqueeze15787_const" type="Const" version="opset1">
+			<data offset="23324" size="64" shape="1,32,1,1" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="32" name="Conv_177" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16" names="1365">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="33" name="1369/Output_0/Data__const" type="Const" version="opset1">
+			<data offset="23388" size="12288" shape="192,32,1,1" element_type="f16"/>
+			<output>
+				<port id="0" precision="FP16" names="1369">
+					<dim>192</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="34" name="Conv_178/WithoutBiases" type="Convolution" version="opset1">
+			<data auto_pad="explicit" strides="1,1" dilations="1,1" pads_begin="0,0" pads_end="0,0"/>
+			<input>
+				<port id="0">
+					<dim>1</dim>
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+		<edge from-layer="532" from-port="1" to-layer="533" to-port="0"/>
+		<edge from-layer="533" from-port="1" to-layer="537" to-port="0"/>
+		<edge from-layer="534" from-port="0" to-layer="537" to-port="1"/>
+		<edge from-layer="535" from-port="0" to-layer="537" to-port="2"/>
+		<edge from-layer="536" from-port="0" to-layer="537" to-port="3"/>
+		<edge from-layer="525" from-port="2" to-layer="540" to-port="0"/>
+		<edge from-layer="537" from-port="4" to-layer="540" to-port="1"/>
+		<edge from-layer="538" from-port="0" to-layer="540" to-port="2"/>
+		<edge from-layer="539" from-port="0" to-layer="540" to-port="3"/>
+		<edge from-layer="540" from-port="4" to-layer="542" to-port="0"/>
+		<edge from-layer="541" from-port="0" to-layer="542" to-port="1"/>
+		<edge from-layer="542" from-port="2" to-layer="544" to-port="0"/>
+		<edge from-layer="543" from-port="0" to-layer="544" to-port="1"/>
+		<edge from-layer="544" from-port="2" to-layer="545" to-port="0"/>
+		<edge from-layer="545" from-port="1" to-layer="547" to-port="0"/>
+		<edge from-layer="546" from-port="0" to-layer="547" to-port="1"/>
+		<edge from-layer="547" from-port="2" to-layer="549" to-port="0"/>
+		<edge from-layer="548" from-port="0" to-layer="549" to-port="1"/>
+		<edge from-layer="549" from-port="2" to-layer="550" to-port="0"/>
+		<edge from-layer="550" from-port="1" to-layer="552" to-port="0"/>
+		<edge from-layer="551" from-port="0" to-layer="552" to-port="1"/>
+		<edge from-layer="552" from-port="2" to-layer="553" to-port="0"/>
+	</edges>
+	<meta_data>
+		<MO_version value="unknown version"/>
+		<cli_parameters>
+			<data_type value="FP16"/>
+			<disable_resnet_optimization value="False"/>
+			<disable_weights_compression value="False"/>
+			<enable_concat_optimization value="False"/>
+			<extensions value="DIR"/>
+			<framework value="onnx"/>
+			<freeze_placeholder_with_value value="{}"/>
+			<generate_deprecated_IR_V7 value="False"/>
+			<input_model value="DIR/MiDaS_small.onnx"/>
+			<keep_shape_ops value="True"/>
+			<log_level value="ERROR"/>
+			<mean_scale_values value="[(array([123.675, 116.28 , 103.53 ]), array([58.395, 57.12 , 57.375]))]"/>
+			<mean_values value="[123.675, 116.28, 103.53]"/>
+			<model_name value="MiDaS_small"/>
+			<move_to_preprocess value="True"/>
+			<output_dir value="DIR"/>
+			<placeholder_data_types value="{}"/>
+			<progress value="False"/>
+			<reverse_input_channels value="False"/>
+			<scale_values value="[58.395, 57.120000000000005, 57.375]"/>
+			<silent value="False"/>
+			<static_shape value="False"/>
+			<stream_output value="False"/>
+			<unset unset_cli_parameters="batch, disable_fusing, disable_gfusing, finegrain_fusing, input, input_shape, output, placeholder_shapes, scale, transformations_config"/>
+		</cli_parameters>
+	</meta_data>
+</net>
\ No newline at end of file