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scala-package/infer/src/main/scala/ml/dmlc/mxnet/infer/Classifier.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. | ||
| */ | ||
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| package ml.dmlc.mxnet.infer | ||
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| import ml.dmlc.mxnet.{DataDesc, NDArray} | ||
| import java.io.File | ||
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| import scala.io | ||
| import scala.collection.mutable.ListBuffer | ||
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| trait ClassifierBase { | ||
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| /** | ||
| * Takes an Array of Floats and returns corresponding labels, score tuples. | ||
| * @param input: IndexedSequence one-dimensional array of Floats. | ||
| * @param topK: (Optional) How many top_k(sorting will be based on the last axis) | ||
| * elements to return, if not passed returns unsorted output. | ||
| * @return IndexedSequence of (Label, Score) tuples. | ||
| */ | ||
| def classify(input: IndexedSeq[Array[Float]], | ||
| topK: Option[Int] = None): List[(String, Float)] | ||
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| /** | ||
| * Takes a Sequence of NDArrays and returns Label, Score tuples. | ||
| * @param input: Indexed Sequence of NDArrays | ||
| * @param topK: (Optional) How many top_k(sorting will be based on the last axis) | ||
| * elements to return, if not passed returns unsorted output. | ||
| * @return Traversable Sequence of (Label, Score) tuple, Score will be in the form of NDArray | ||
| */ | ||
| def classifyWithNDArray(input: IndexedSeq[NDArray], | ||
| topK: Option[Int] = None): IndexedSeq[List[(String, Float)]] | ||
| } | ||
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| /** | ||
| * A class for classifier tasks | ||
| * @param modelPathPrefix PathPrefix from where to load the symbol, parameters and synset.txt | ||
| * Example: file://model-dir/resnet-152(containing resnet-152-symbol.json | ||
| * file://model-dir/synset.txt | ||
| * @param inputDescriptors Descriptors defining the input node names, shape, | ||
| * layout and Type parameters | ||
| * @param outputDescriptor Output Descriptor defining the output node name, shape, | ||
| * layout and Type parameter | ||
| */ | ||
| class Classifier(modelPathPrefix: String, | ||
| protected val inputDescriptors: IndexedSeq[DataDesc], | ||
| protected var outputDescriptor: | ||
| Option[DataDesc] = None) extends ClassifierBase { | ||
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| val synsetFilePath = getSynsetFilePath | ||
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| if (outputDescriptor.isDefined) { | ||
| require(outputDescriptor.size == 1, "expected single output") | ||
| } | ||
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| val outDescriptor : Option[IndexedSeq[DataDesc]] = if (!outputDescriptor.isDefined) None | ||
| else Some(IndexedSeq(outputDescriptor.get)) | ||
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| val predictor: PredictBase = new Predictor(modelPathPrefix, inputDescriptors, outDescriptor) | ||
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| val synset = readSynsetFile(synsetFilePath) | ||
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| val handler = MXNetHandler() | ||
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| /** | ||
| * Takes a flat arrays as input and returns a List of (Label, tuple) | ||
| * @param input: IndexedSequence one-dimensional array of Floats. | ||
| * @param topK: (Optional) How many top_k(sorting will be based on the last axis) | ||
| * elements to return, if not passed returns unsorted output. | ||
| * @return IndexedSequence of (Label, Score) tuples. | ||
| */ | ||
| override def classify(input: IndexedSeq[Array[Float]], | ||
| topK: Option[Int] = None): List[(String, Float)] = { | ||
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| // considering only the first output | ||
| val predictResult = predictor.predict(input)(0) | ||
| var result: List[(String, Float)] = List.empty | ||
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| if (topK.isDefined) { | ||
| val sortedIndex = predictResult.zipWithIndex.sortBy(_._1).map(_._2).take(topK.get) | ||
| result = sortedIndex.map(i => (synset(i), predictResult(i))).toList | ||
| } else { | ||
| result = synset.zip(predictResult).toList | ||
| } | ||
| result | ||
| } | ||
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| /** | ||
| * Takes input as NDArrays, useful when | ||
| * @param input: Indexed Sequence of NDArrays | ||
| * @param topK: (Optional) How many top_k(sorting will be based on the last axis) | ||
| * elements to return, if not passed returns unsorted output. | ||
| * @return Traversable Sequence of (Label, Score) tuple, Score will be in the form of NDArray | ||
| */ | ||
| override def classifyWithNDArray(input: IndexedSeq[NDArray], topK: Option[Int] = None) | ||
| : IndexedSeq[List[(String, Float)]] = { | ||
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| val predictResultND = predictor.predictWithNDArray(input) | ||
| val predictResult = predictResultND.map(_.toArray) | ||
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| var result: ListBuffer[List[(String, Float)]] = ListBuffer.empty[List[(String, Float)]] | ||
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| if (topK.isDefined) { | ||
| val sortedIndices = predictResult.map(r => | ||
| r.zipWithIndex.sortBy(_._1).map(_._2).take(topK.get) | ||
| ) | ||
| for (i <- sortedIndices.indices) { | ||
| result += sortedIndices(i).map(sIndx => (synset(sIndx), predictResult(i)(sIndx))).toList | ||
| } | ||
| } else { | ||
| for (i <- predictResult.indices) { | ||
| result += synset.zip(predictResult(i)) | ||
| } | ||
| } | ||
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| handler.execute(predictResultND.foreach(_.dispose())) | ||
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| result.toIndexedSeq | ||
| } | ||
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| def getSynsetFilePath: String = { | ||
| val dirPath = modelPathPrefix.substring(0, 1 + modelPathPrefix.lastIndexOf(File.pathSeparator)) | ||
| val d = new File(dirPath) | ||
| require(d.exists && d.isDirectory, "directory: %s not found".format(dirPath)) | ||
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| val s = new File(dirPath + File.pathSeparator + "synset.txt") | ||
| require(s.exists() && s.isFile, "File synset.txt should exist inside modelPath: %s".format | ||
| (dirPath + File.pathSeparator + "synset.txt")) | ||
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| s.getCanonicalPath | ||
| } | ||
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| protected def readSynsetFile(synsetFilePath: String): List[String] = { | ||
| val f = io.Source.fromFile(synsetFilePath) | ||
| val lines = for ( line <- f.getLines()) yield line | ||
| f.close | ||
| lines.toList | ||
| } | ||
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| } |
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scala-package/infer/src/main/test/scala/ml/dmlc/mxnet/infer/PredictorSuite.scala
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