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data-clipboard-text='NetModel["Dilated ResNet-22 Trained on Cityscapes Data"]' > <h1> Dilated ResNet-22 <span class="action">Trained on</span> <span class="data">Cityscapes Data</span> </h1> </div> </div> <p class="lead">Segment an image of a driving scenario into semantic component classes</p> <div class="details"> <p>Released in 2017, this architecure combines the technique of dilated convolutions with the paradigm of residual networks, outperforming their nonrelated counterparts in image classification and semantic segmentation.</p> </div> <p class="netsize"> Number of layers: 86 | Parameter count: 15,994,691 | Trained size: 64 MB | </p> <h2 id="training-set-info">Training Set Information</h2> <ul> <li> <a href="https://www.cityscapes-dataset.com/">Cityscapes</a>, a collection of 25,000 annotated images for semantic understanding of urban street scenes. </li> </ul> <h2 id="training-set-info">Performance</h2> <ul> <li><p>This model achieves 68% mean IoU accuracy on the <a href="https://www.cityscapes-dataset.com/" target="_blank">Cityscapes</a> dataset.</p></li> </ul> <div class="col main"> <h2 id="Examples">Examples</h2> <div id="notebookButtons" class="example"> <p> <a href="https://www.wolframcloud.com/download/ad17cde9-adad-4b83-bd49-d7ad08e338f4?extension=always&filename=Dilated-ResNet-22-Trained-on-Cityscapes-Data-1-2-0-examples" target="notebookButton" data-toggle="tooltip" data-placement="bottom" title="Download Example Notebook" > <svg xmlns="http://www.w3.org/2000/svg" class="notebook-download" width="26" height="32" viewBox="0 0 26 32" role="presentation" > <path class="fill" fill="#598527" d="M3.5 0C2.3 0 1.27.86 1.04 2H0v3h1v1H0v3h1v1H0v3h1v1H0v3h1v1H0v3h1v1H0v3h1v1H0v3h1v.5C1 30.9 2.12 32 3.5 32h20c1.4 0 2.5-1.1 2.5-2.5v-27C26 1.1 24.88 0 23.5 0h-20zm0 .98h20c.85 0 1.52.67 1.52 1.5v26.03c0 .85-.67 1.52-1.5 1.52H3.48c-.85 0-1.52-.67-1.52-1.5V2.48c0-.85.67-1.52 1.5-1.52zM19.54 15.15L22 12.4l-3.6-.77.36-3.64-3.4 1.46L13.5 6.3l-1.87 3.16L8.25 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href="https://www.wolframcloud.com/env/ad17cde9-adad-4b83-bd49-d7ad08e338f4?src=CloudBasicCopiedContent#sidebar=basic-notebook-links" target="notebookButton" data-toggle="tooltip" data-placement="bottom" title="Open in Wolfram Cloud" > <svg xmlns="http://www.w3.org/2000/svg" class="cloud-open example" width="41" height="32" viewBox="0 0 64 50" role="presentation" > <path class="stroke" fill="none" stroke="#598527" stroke-width="2" stroke-linecap="round" d="M22 42h30c6.08 0 11-4.92 11-11 0-3.85-2.03-7.42-5.33-9.4.22-.7.33-1.4.33-2.1 0-3.87-3.13-7-7-7-.43 0-.86.04-1.3.12C48.35 5.86 42.4 1 35.5 1c-4.74 0-9.18 2.32-11.9 6.2-1.3-.45-2.7-.7-4.1-.7C12.6 6.5 7 12.1 7 19c0 .87.1 1.73.28 2.57C3.45 23.4 1 27.27 1 31.5c0 3.92 2.1 7.54 5.5 9.5" /> <path class="fill" fill="#598527" d="M22.5 19.1L45 20 28.3 35l1-5.5c-5.24 2.27-13.42 9.74-16.1 19.8l-.6-.1c0-12.6 7.6-20.76 14.5-26.3z" /> </svg> <span class="text" ><span class="line">Open in </span ><span class="line">Wolfram Cloud</span></span > </a> </p> </div> <!-- RS_SHINGLE_EXAMPLE_SECTION_START --><div class="example-notebook"><div class="subsection cell-group"><h3>Resource retrieval</h3><p class="example-text">Get the pre-trained net:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[1]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/0638b670834a04d2.png" alt="NetModel["Dilated ResNet-22 Trained on Cityscapes Data"]" width="371" height="19" style="width: 23.1875em; height: 1.1875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[1]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/38dd3ac17f86b4e1.png" width="938" height="153" style="width: 58.6250em; height: 9.5625em;"/></div></td></tr></table></div></div><div class="subsection cell-group"><h3>Evaluation function</h3><p class="example-text">Write an evaluation function to handle net reshaping and resampling of input and output:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[2]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/1e019412ebba0847.png" alt="netevaluate[img_, device_ : "CPU"] := Block[ {net, encData, dec, mean, var, prob}, net = NetModel["Dilated ResNet-22 Trained on Cityscapes Data"]; encData = Normal@NetExtract[net, "input_0"]; dec = NetExtract[net, "Output"]; {mean, var} = Lookup[encData, {"MeanImage", "VarianceImage"}]; NetReplacePart[net, {"input_0" -> NetEncoder[{"Image", ImageDimensions@img, "MeanImage" -> mean, "VarianceImage" -> var}], "Output" -> dec} ][img, TargetDevice -> device] ]" width="579" height="254" style="width: 36.1875em; height: 15.8750em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out"></td></tr></table></div></div><div class="subsection cell-group"><h3>Label list</h3><p class="example-text">Define the label list for this model. Integers in the model’s output correspond to elements in the label list:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[3]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/1ae4f14b58f611b6.png" alt="labels = {"road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle"};" width="529" height="66" style="width: 33.0625em; height: 4.1250em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out"></td></tr></table></div></div><div class="subsection cell-group"><h3>Basic usage</h3><p class="example-text">Obtain a segmentation mask for a given image:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[4]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/7dfcf213899fba36.png" alt="(* Evaluate this cell to get the example input *) CloudGet["https://www.wolframcloud.com/obj/90161845-03f3-4235-adfc-5b9de58bec2b"] " width="437" height="227" style="width: 27.3125em; height: 14.1875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out"></td></tr></table></div><p class="example-text">Inspect which classes are detected:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[5]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/5eaa57b1a47614fb.png" alt="detected = DeleteDuplicates@Flatten@mask" width="284" height="19" style="width: 17.7500em; height: 1.1875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[5]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/5a161d2306d602eb.png" width="210" height="17" style="width: 13.1250em; height: 1.0625em;"/></div></td></tr></table></div><div class="example-frame"><table class="example input"><tr><td class="in-out">In[6]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/7677956c0aa24fc4.png" alt="labels[[detected]]" width="111" height="19" style="width: 6.9375em; height: 1.1875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[6]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/3cd283ea74d10807.png" width="559" height="17" style="width: 34.9375em; height: 1.0625em;"/></div></td></tr></table></div><p class="example-text">Visualize the mask:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[7]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/66b4c55a3933a176.png" alt="Colorize[mask]" width="94" height="19" style="width: 5.8750em; height: 1.1875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[7]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/43eec264c9cf7460.png" width="575" height="432" style="width: 35.9375em; height: 27.0000em;"/></div></td></tr></table></div></div><div class="subsection cell-group"><h3>Advanced visualization</h3><p class="example-text">Associate classes to colors using the standard Cityscapes palette:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[8]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/42aff53bcae8af9f.png" alt="colors = Apply[ RGBColor, {{128, 64, 128}, {244, 35, 232}, {70, 70, 70}, {102, 102, 156}, {190, 153, 153}, {153, 153, 153}, {250, 170, 30}, {220, 220, 0}, {107, 142, 35}, {152, 251, 152}, {70, 130, 180}, {220, 20, 60}, {255, 0, 0}, {0, 0, 142}, {0, 0, 70}, {0, 60, 100}, {0, 80, 100}, {0, 0, 230}, {119, 11, 32}}/255., {1}]" width="522" height="137" style="width: 32.6250em; height: 8.5625em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[8]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/30ce1e494ce4bb30.png" width="325" height="17" style="width: 20.3125em; height: 1.0625em;"/></div></td></tr></table></div><div class="example-frame"><table class="example input"><tr><td class="in-out">In[9]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/17b525b97a233f35.png" alt="indexToColor = Thread[Range[19] -> colors];" width="274" height="19" style="width: 17.1250em; height: 1.1875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out"></td></tr></table></div><p class="example-text">Write a function to overlap the image and the mask with a legend:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[10]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/21ed88b928125bc7.png" alt="result[img_, device_ : "CPU"] := Block[ {mask, classes, maskPlot, composition}, mask = netevaluate[img, device]; classes = DeleteDuplicates[Flatten@mask]; maskPlot = Colorize[mask, ColorRules -> indexToColor]; composition = ImageCompose[img, {maskPlot, 0.5}]; Legended[ Row[Image[#, ImageSize -> Large] & /@ {maskPlot, composition}], SwatchLegend[indexToColor[[classes, 2]], labels[[classes]]]] ]" width="506" height="207" style="width: 31.6250em; height: 12.9375em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out"></td></tr></table></div><p class="example-text">Inspect the results:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[11]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/3aa892612115ad9e.png" alt="(* Evaluate this cell to get the example input *) CloudGet["https://www.wolframcloud.com/obj/9e30aff4-8c11-459e-81c7-4d34b6f982f5"] " width="441" height="264" style="width: 27.5625em; height: 16.5000em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[11]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/27462bae653fd4ef.png" width="797" height="803" style="width: 49.8125em; height: 50.1875em;"/></div></td></tr></table></div><div class="example-frame"><table class="example input"><tr><td class="in-out">In[12]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/5d4719d64fc32b86.png" alt="(* Evaluate this cell to get the example input *) CloudGet["https://www.wolframcloud.com/obj/d080db18-e42f-47ec-b9d4-8e14a2d67314"] " width="427" height="241" style="width: 26.6875em; height: 15.0625em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[12]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/4a2a76d5910af388.png" width="795" height="764" style="width: 49.6875em; height: 47.7500em;"/></div></td></tr></table></div><div class="example-frame"><table class="example input"><tr><td class="in-out">In[13]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/732d3d83ad041c3d.png" alt="(* Evaluate this cell to get the example input *) CloudGet["https://www.wolframcloud.com/obj/3bfec9cc-4f18-438a-8040-41fb5ad2c207"] " width="310" height="199" style="width: 19.3750em; height: 12.4375em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[13]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/23716a8f1fb8269c.png" width="797" height="899" style="width: 49.8125em; height: 56.1875em;"/></div></td></tr></table></div></div><div class="subsection cell-group"><h3>Net information</h3><p class="example-text">Inspect the number of parameters of all arrays in the net:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[14]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/1b5504dcd248a928.png" alt="NetInformation[ NetModel["Dilated ResNet-22 Trained on Cityscapes Data"], \ "ArraysElementCounts"]" width="477" height="43" style="width: 29.8125em; height: 2.6875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[14]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/0c4522e96c4a8be4.png" width="639" height="134" style="width: 39.9375em; height: 8.3750em;"/></div></td></tr></table></div><p class="example-text">Obtain the total number of parameters:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[15]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/57ca66eade804d19.png" alt="NetInformation[ NetModel["Dilated ResNet-22 Trained on Cityscapes Data"], \ "ArraysTotalElementCount"]" width="477" height="43" style="width: 29.8125em; height: 2.6875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[15]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/0ec3d5f5482b0039.png" width="55" height="17" style="width: 3.4375em; height: 1.0625em;"/></div></td></tr></table></div><p class="example-text">Obtain the layer type counts:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[16]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/42f7c5540865d9ab.png" alt="NetInformation[ NetModel["Dilated ResNet-22 Trained on Cityscapes Data"], \ "LayerTypeCounts"]" width="477" height="43" style="width: 29.8125em; height: 2.6875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[16]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/4e1149c027f13fe7.png" width="618" height="39" style="width: 38.6250em; height: 2.4375em;"/></div></td></tr></table></div><p class="example-text">Display the summary graphic:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[17]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/54c9203058b7f833.png" alt="NetInformation[ NetModel["Dilated ResNet-22 Trained on Cityscapes Data"], \ "SummaryGraphic"]" width="477" height="43" style="width: 29.8125em; height: 2.6875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[17]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/128d72c59fb41f04.png" width="2751" height="89" style="width: 171.9380em; height: 5.5625em;"/></div></td></tr></table></div></div><div class="subsection cell-group"><h3>Export to MXNet</h3><p class="example-text"><span class="inline-formula"><a class="reflink" href="https://reference.wolfram.com/language/ref/Export">Export</a></span> the net into a format that can be opened in MXNet:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[18]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/7943310fc62b461f.png" alt="jsonPath = Export[FileNameJoin[{$TemporaryDirectory, "net.json"}], NetModel["Dilated ResNet-22 Trained on Cityscapes Data"], "MXNet"]" width="463" height="43" style="width: 28.9375em; height: 2.6875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[18]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/4fb59c83f2a8c3b8.png" width="369" height="17" style="width: 23.0625em; height: 1.0625em;"/></div></td></tr></table></div><p class="example-text"><span class="inline-formula"><a class="reflink" href="https://reference.wolfram.com/language/ref/Export">Export</a></span> also creates a <i>net.params </i>file containing parameters:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[19]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/2743efac7a6ae332.png" alt="paramPath = FileNameJoin[{DirectoryName[jsonPath], "net.params"}]" width="443" height="19" style="width: 27.6875em; height: 1.1875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[19]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/418a35cbf4329bd9.png" width="387" height="17" style="width: 24.1875em; height: 1.0625em;"/></div></td></tr></table></div><p class="example-text">Get the size of the parameter file:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[20]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/6a0d25127d19098d.png" alt="FileByteCount[paramPath]" width="168" height="19" style="width: 10.5000em; height: 1.1875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[20]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/74e50289d7efb943.png" width="55" height="17" style="width: 3.4375em; height: 1.0625em;"/></div></td></tr></table></div><p class="example-text">The size is similar to the byte count of the resource object:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[21]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/35bb5f2ac34ed95f.png" alt="ResourceObject[ "Dilated ResNet-22 Trained on Cityscapes Data"]["ByteCount"]" width="498" height="19" style="width: 31.1250em; height: 1.1875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[21]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/0ccdee1a11d78bf7.png" width="55" height="17" style="width: 3.4375em; height: 1.0625em;"/></div></td></tr></table></div><p class="example-text">Represent the MXNet net as a graph:</p><div class="example-frame"><table class="example input"><tr><td class="in-out">In[22]:=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/53e977a65e16b2f3.png" alt="Import[jsonPath, {"MXNet", "NodeGraphPlot"}]" width="300" height="19" style="width: 18.7500em; height: 1.1875em;"/></div></td></tr></table><table class="example output"><tr><td class="in-out">Out[22]=</td><td><div class="img-frame"><img src="https://www.wolframcloud.com/obj/resourcesystem/images/3e8/3e883192-f67d-4da9-923a-f9fddc4dc7ab/3f5f794bd67ef829.png" width="1203" height="627" style="width: 75.1875em; height: 39.1875em;"/></div></td></tr></table></div></div></div><!-- RS_SHINGLE_EXAMPLE_SECTION_END --> <div id="notebookButtons" class="construction"> <h2 id="Construction-notebook">Construction Notebook</h2> <p> <a href="https://www.wolframcloud.com/download/949c4a0e-7c06-412e-927c-57857c71d0f5?extension=always&filename=Dilated-ResNet-22-Trained-on-Cityscapes-Data" target="notebookButton" data-toggle="tooltip" data-placement="bottom" title="Download Construction Notebook" > <svg id="iconGroup" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 28 34" class="notebook-download" width="26" height="32" role="presentation" > <path class="fill" fill="#598527" d="M16.67276,8.65568A1.26126,1.26126,0,1,1,15.4115,7.39442,1.26126,1.26126,0,0,1,16.67276,8.65568ZM15.4115,12.655a1.26126,1.26126,0,1,0,1.26126,1.26126A1.26126,1.26126,0,0,0,15.4115,12.655Zm0,4.99574A1.26126,1.26126,0,1,0,16.67276,18.912,1.26126,1.26126,0,0,0,15.4115,17.65072Zm0,4.99574a1.26126,1.26126,0,1,0,1.26126,1.26126A1.26126,1.26126,0,0,0,15.4115,22.64646Zm7.24962-10.2563a1.26126,1.26126,0,1,0,1.26126,1.26126A1.26126,1.26126,0,0,0,22.66112,12.39016Zm0,5.52537a1.26126,1.26126,0,1,0,1.26126,1.26126A1.26126,1.26126,0,0,0,22.66112,17.91553ZM6.83888,9.89229a1.26126,1.26126,0,1,0,1.26126,1.26126A1.26126,1.26126,0,0,0,6.83888,9.89229Zm0,5.26055a1.26126,1.26126,0,1,0,1.26126,1.26126A1.26126,1.26126,0,0,0,6.83888,15.15285Zm0,5.26055a1.26126,1.26126,0,1,0,1.26126,1.26126A1.26126,1.26126,0,0,0,6.83888,20.4134ZM24.5,1A2.48819,2.48819,0,0,1,27,3.5v27A2.47572,2.47572,0,0,1,24.5,33H4.5A2.48819,2.48819,0,0,1,2,30.5V30H1V27H2V26H1V23H2V22H1V19H2V18H1V15H2V14H1V11H2V10H1V7H2V6H1V3H2.04A2.51946,2.51946,0,0,1,4.5,1ZM4.46,1.96a1.50243,1.50243,0,0,0-1.5,1.52V29.53a1.50243,1.50243,0,0,0,1.52,1.5H24.52a1.50243,1.50243,0,0,0,1.5-1.52V3.48a1.50243,1.50243,0,0,0-1.52-1.5H4.5Z" /> <path class="stroke" fill="none" stroke="#598527" stroke-miterlimit="10" stroke-width="0.25px" d="M7.0766,11.391l8.3349-2.51153M7.0766,16.41411l8.3349-2.51153M7.0766,21.43717l8.3349-2.51153m0,5.02306,7.0119-5.02306M15.4115,8.87952l7.0119,5.02306M7.0766,11.391l8.3349,2.51153m0,5.02306L7.0766,11.391m0,0L15.4115,23.9487M7.0766,16.41411l8.3349-7.53459M7.0766,21.43717,15.4115,8.87952M7.0766,16.41411l8.3349,2.51153m0-5.02306L7.0766,21.43717m0-5.02306,8.3349,7.53459m0-5.02306,7.0119-5.02306m-7.0119,0h7.0119m-7.0119,5.02306h7.0119M15.4115,23.9487l7.0119-10.04612M15.4115,8.87952l7.0119,10.04612m-7.0119-5.02306,7.0119,5.02306M7.0766,21.43717l8.3349,2.51153" /> </svg> <span class="text" ><span class="line">Download Construction </span ><span class="line">Notebook</span></span > </a> </p> <p> <a href="https://www.wolframcloud.com/env/949c4a0e-7c06-412e-927c-57857c71d0f5?src=CloudBasicCopiedContent#sidebar=basic-notebook-links" target="notebookButton" data-toggle="tooltip" data-placement="bottom" title="Open in Wolfram Cloud" > <svg xmlns="http://www.w3.org/2000/svg" class="cloud-open construction" width="41" height="32" viewBox="0 0 64 50" role="presentation" > <path class="stroke" fill="none" stroke="#598527" stroke-width="2" stroke-linecap="round" d="M22 42h30c6.08 0 11-4.92 11-11 0-3.85-2.03-7.42-5.33-9.4.22-.7.33-1.4.33-2.1 0-3.87-3.13-7-7-7-.43 0-.86.04-1.3.12C48.35 5.86 42.4 1 35.5 1c-4.74 0-9.18 2.32-11.9 6.2-1.3-.45-2.7-.7-4.1-.7C12.6 6.5 7 12.1 7 19c0 .87.1 1.73.28 2.57C3.45 23.4 1 27.27 1 31.5c0 3.92 2.1 7.54 5.5 9.5" /> <path class="fill" fill="#598527" d="M22.5 19.1L45 20 28.3 35l1-5.5c-5.24 2.27-13.42 9.74-16.1 19.8l-.6-.1c0-12.6 7.6-20.76 14.5-26.3z" /> </svg> <span class="text" ><span class="line">Open in </span ><span class="line">Wolfram Cloud</span></span > </a> </p> </div> <h2 id="WLVersion">Requirements</h2> <p> <a href="http://reference.wolfram.com/language/guide/SummaryOfNewFeaturesIn113.html"> Wolfram Language 11.3 </a> (March 2018) or above </p> <h2 id="Resource-History">Resource History</h2> <ul class="source-metadata"> <li> Date Created: <span class="property">22 March 2018</span> </li> <li> Latest Update: <span class="property">21 June 2018</span> </li> </ul> <h2 id="Reference">Reference</h2> <ul class="reference"> <li> <span> F. Yu, V. Koltun, T. Funkhouser, "Dilated Residual Networks," arXiv:1705.09914 (2017) </span> </li> </span></li> <li><span>Available from: <a href="https://github.com/fyu/drn" target="_blank">https://github.com/fyu/drn</a></span></li> <li> <span>Rights: <a href="https://opensource.org/licenses/BSD-3-Clause" target="_blank">BSD 3-Clause License</a> </span> </li> </ul> <footer id="bottom"> <ul> <li> <a href="https://resources.wolframcloud.com/NeuralNetRepository/contact-us" class="contact"> <svg viewBox="0 0 44 32"> <path d="M19 .5A6.5 6.5 0 0 0 12.5 7v4.5H.46l12.04 8.75V25a6.5 6.5 0 0 0 6.5 6.5h18a6.5 6.5 0 0 0 6.5-6.5V7A6.5 6.5 0 0 0 37 .5zm0 1h18A5.5 5.5 0 0 1 42.5 7v18a5.5 5.5 0 0 1-5.5 5.5H19a5.5 5.5 0 0 1-5.5-5.5v-5.25L3.54 12.5h9.96V7A5.5 5.5 0 0 1 19 1.5z" /> <path d="M18 6h20v4H18zM18 14h20v4H18zM18 22h10v4H18z" /></svg ><span class="text">Give Feedback</span> </a> </li> <li> <a href="#top" class="top"> <svg viewBox="0 0 16 16"> <path d="M4 0C1.784 0 0 1.784 0 4v8c0 2.216 1.784 4 4 4h8c2.216 0 4-1.784 4-4V4c0-2.216-1.784-4-4-4H4zm4 3l4 4-1 1-3-3-3 3-1-1 4-4zm0 5l4 4-1 1-3-3-3 3-1-1 4-4z" /></svg ><span class="text">Top</span> </a> </li> </ul> </footer> </div> </div> </main> <footer id="gws-footer"> <div class="wrap"> <p> © 2025 <a href="https://www.wolfram.com/" target="gws-footer">Wolfram</a>. 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