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From imatiach-msft <...@git.apache.org>
Subject [GitHub] spark pull request #19439: [SPARK-21866][ML][PySpark] Adding spark image rea...
Date Mon, 16 Oct 2017 02:03:24 GMT
Github user imatiach-msft commented on a diff in the pull request:

    https://github.com/apache/spark/pull/19439#discussion_r144742476
  
    --- Diff: mllib/src/test/scala/org/apache/spark/ml/image/ImageSchemaSuite.scala ---
    @@ -0,0 +1,124 @@
    +/*
    + * 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.spark.ml.image
    +
    +import java.nio.file.Paths
    +
    +import org.apache.spark.SparkFunSuite
    +import org.apache.spark.ml.image.ImageSchema._
    +import org.apache.spark.mllib.util.MLlibTestSparkContext
    +import org.apache.spark.sql.Row
    +import org.apache.spark.sql.types._
    +
    +class ImageSchemaSuite extends SparkFunSuite with MLlibTestSparkContext {
    +  // Single column of images named "image"
    +  private val imageDFSchema =
    +    StructType(StructField("image", ImageSchema.columnSchema, true) :: Nil)
    +  private lazy val imagePath =
    +    Thread.currentThread().getContextClassLoader.getResource("test-data/images").getPath
    +
    +  test("Smoke test: create basic ImageSchema dataframe") {
    +    val origin = "path"
    +    val width = 1
    +    val height = 1
    +    val nChannels = 3
    +    val data = Array[Byte](0, 0, 0)
    +    val mode = "CV_8UC3"
    +
    +    // Internal Row corresponds to image StructType
    +    val rows = Seq(Row(Row(origin, height, width, nChannels, mode, data)),
    +      Row(Row(null, height, width, nChannels, mode, data)))
    +    val rdd = sc.makeRDD(rows)
    +    val df = spark.createDataFrame(rdd, imageDFSchema)
    +
    +    assert(df.count == 2, "incorrect image count")
    +    assert(ImageSchema.isImageColumn(df, "image"), "data do not fit ImageSchema")
    +  }
    +
    +  test("readImages count test") {
    +    var df = readImages(imagePath, recursive = false)
    +    assert(df.count == 0)
    +
    +    df = readImages(imagePath, recursive = true, dropImageFailures = false)
    +    assert(df.count == 8)
    +
    +    df = readImages(imagePath, recursive = true, dropImageFailures = true)
    +    val count100 = df.count
    +    assert(count100 == 7)
    +
    +    df = readImages(imagePath, recursive = true, sampleRatio = 0.5, dropImageFailures
= true)
    +    // Random number about half of the size of the original dataset
    +    val count50 = df.count
    +    assert(count50 > 0.2 * count100 && count50 < 0.8 * count100)
    +  }
    +
    +  test("readImages partition test") {
    +    val df = readImages(imagePath, recursive = true, dropImageFailures = true, numPartitions
= 3)
    +    assert(df.rdd.getNumPartitions == 3)
    +  }
    +
    +  // Images with the different number of channels
    +  test("readImages pixel values test") {
    +
    +    val images = readImages(imagePath + "/multi-channel/", recursive = false).collect
    +
    +    images.foreach{
    --- End diff --
    
    done


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