[GitHub] piyushghai commented on a change in pull request #13330: [MXNET-1222][WIP] Scala Inference "Pandora Box"

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piyushghai commented on a change in pull request #13330: [MXNET-1222][WIP] Scala Inference "Pandora Box"
URL: https://github.com/apache/incubator-mxnet/pull/13330#discussion_r235132268
 
 

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 File path: scala-package/examples/src/main/scala/org/apache/mxnetexamples/infer/predictor/PredictorExample.scala
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+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.mxnetexamples.infer.predictor
+
+import java.io.File
+
+import scala.io
+import org.apache.mxnet._
+import org.apache.mxnet.infer.Predictor
+import org.apache.mxnetexamples.benchmark.CLIParserBase
+import org.kohsuke.args4j.{CmdLineParser, Option}
+
+import scala.collection.JavaConverters._
+
+object PredictorExample {
+
+  def loadModel(modelPathPrefix : String, inputDesc : IndexedSeq[DataDesc],
+                context : Context, epoch : Int): Predictor = {
+    new Predictor(modelPathPrefix, inputDesc, context, Some(epoch))
+  }
+
+  def doInference(predictor : Predictor, imageND : NDArray): IndexedSeq[NDArray] = {
+    predictor.predictWithNDArray(IndexedSeq(imageND))
+  }
+
+  def preProcess(imagePath: String, h: Int, w: Int) : NDArray = {
+    var img = Image.imRead(imagePath)
+    img = Image.imResize(img, h, w)
+    // HWC -> CHW
+    img = NDArray.api.transpose(img, Some(Shape(2, 0, 1)))
+    img = NDArray.api.expand_dims(img, 0)
+    img.asType(DType.Float32)
+  }
+
+  def postProcess(modelPathPrefix : String, result : Array[Float]) : String = {
+    val dirPath = modelPathPrefix.substring(0, 1 + modelPathPrefix.lastIndexOf(File.separator))
+    val d = new File(dirPath)
+    require(d.exists && d.isDirectory, s"directory: $dirPath not found")
+    val f = io.Source.fromFile(dirPath + "synset.txt")
+    val s = f.getLines().toIndexedSeq
+    val maxIdx = result.zipWithIndex.maxBy(_._1)._2
+    printf(s"Predict Result ${s(maxIdx)} with prob ${result(maxIdx)}\n")
+    s(maxIdx)
+  }
+
+  def main(args : Array[String]): Unit = {
+    val inst = new CLIParser
+    val parser: CmdLineParser = new CmdLineParser(inst)
+
+    parser.parseArgument(args.toList.asJava)
+
+    var context = Context.cpu()
+    if (System.getenv().containsKey("SCALA_TEST_ON_GPU") &&
+      System.getenv("SCALA_TEST_ON_GPU").toInt == 1) {
+      context = Context.gpu()
+    }
+
+    val inputDesc = IndexedSeq(new DataDesc("data", Shape(1, 3, 224, 224),
 
 Review comment:
   Can we define 224, 224 as two variables : imgHeight and imgWidth and then use them ? 
   It makes it a lot more cleaner and easier to understand the example. 

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