Github user dakirsa commented on a diff in the pull request:
https://github.com/apache/spark/pull/19439#discussion_r143894101
--- Diff: mllib/src/main/scala/org/apache/spark/ml/image/ImageSchema.scala
---
@@ -0,0 +1,229 @@
+/*
+ * 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.awt.Color
+import java.awt.color.ColorSpace
+import java.io.ByteArrayInputStream
+import javax.imageio.ImageIO
+
+import org.apache.spark.annotation.{Experimental, Since}
+import org.apache.spark.sql.{DataFrame, Row, SparkSession}
+import org.apache.spark.sql.types._
+
+@Experimental
+@Since("2.3.0")
+object ImageSchema {
+
+ val undefinedImageType = "Undefined"
+
+ val ocvTypes = Map(
+ undefinedImageType -> -1,
+ "CV_8U" -> 0, "CV_8UC1" -> 0, "CV_8UC2" -> 8, "CV_8UC3" -> 16,
"CV_8UC4" -> 24,
+ "CV_8S" -> 1, "CV_8SC1" -> 1, "CV_8SC2" -> 9, "CV_8SC3" -> 17,
"CV_8SC4" -> 25,
+ "CV_16U" -> 2, "CV_16UC1" -> 2, "CV_16UC2" -> 10, "CV_16UC3" -> 18,
"CV_16UC4" -> 26,
+ "CV_16S" -> 3, "CV_16SC1" -> 3, "CV_16SC2" -> 11, "CV_16SC3" -> 19,
"CV_16SC4" -> 27,
+ "CV_32S" -> 4, "CV_32SC1" -> 4, "CV_32SC2" -> 12, "CV_32SC3" -> 20,
"CV_32SC4" -> 28,
+ "CV_32F" -> 5, "CV_32FC1" -> 5, "CV_32FC2" -> 13, "CV_32FC3" -> 21,
"CV_32FC4" -> 29,
+ "CV_64F" -> 6, "CV_64FC1" -> 6, "CV_64FC2" -> 14, "CV_64FC3" -> 22,
"CV_64FC4" -> 30
+ )
+
+ /**
+ * Schema for the image column: Row(String, Int, Int, Int, Array[Byte])
+ */
+ val columnSchema = StructType(
+ StructField("origin", StringType, true) ::
+ StructField("height", IntegerType, false) ::
+ StructField("width", IntegerType, false) ::
+ StructField("nChannels", IntegerType, false) ::
+ // OpenCV-compatible type: CV_8UC3 in most cases
+ StructField("mode", StringType, false) ::
--- End diff --
Technically, we could use either int or string (in fact, we are using Int
in mmlspark implementation) -- but after discussion with Databricks we agreed
to use strings for readability. The map is used to emphasize OpenCV
compatibility, list all the potential use cases we are planning to cover, and
to make a correct translation when actual OpenCV libraries are used to read the
binaries.
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