Added grayscale support; fixed partitioning

This commit is contained in:
dakirsa 2017-10-04 09:16:52 -04:00
Родитель 822234599d
Коммит e5698c08a7
2 изменённых файлов: 34 добавлений и 16 удалений

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@ -9,6 +9,7 @@ import java.awt.image.BufferedImage
import java.awt.{Color, Image}
import java.io.ByteArrayInputStream
import javax.imageio.ImageIO
import java.awt.color.ColorSpace
object ImageSchema{
@ -74,27 +75,45 @@ object ImageSchema{
None
} else {
val is_gray = img.getColorModel.getColorSpace.getType == ColorSpace.TYPE_GRAY
val has_alpha = img.getColorModel.hasAlpha
val height = img.getHeight
val width = img.getWidth
val (nChannels, mode) = if(img.getColorModel().hasAlpha()) (4, "CV_8UC4") else (3, "CV_8UC3") //TODO: grayscale
val (nChannels, mode) = if(is_gray) (1, "CV_8UC1")
else if(has_alpha) (4, "CV_8UC4")
else (3, "CV_8UC3")
assert(height*width*nChannels < 1e9, "image is too large")
val decoded = Array.ofDim[Byte](height*width*nChannels)
var offset = 0
for(h <- 0 until height) {
for (w <- 0 until width) {
val color = new Color(img.getRGB(w, h))
decoded(offset) = color.getBlue.toByte
decoded(offset+1) = color.getGreen.toByte
decoded(offset+2) = color.getRed.toByte
if(nChannels == 4){
decoded(offset+3) = color.getAlpha.toByte
// grayscale images in Java require special handling to get the correct intensity
if(is_gray){
var offset = 0
val raster = img.getRaster
for(h <- 0 until height) {
for (w <- 0 until width) {
decoded(offset) = raster.getSample(w, h, 0).toByte
offset += 1
}
offset += nChannels
}
}
else{
var offset = 0
for (h <- 0 until height) {
for (w <- 0 until width) {
val color = new Color(img.getRGB(w, h))
decoded(offset) = color.getBlue.toByte
decoded(offset + 1) = color.getGreen.toByte
decoded(offset + 2) = color.getRed.toByte
if (nChannels == 4) {
decoded(offset + 3) = color.getAlpha.toByte
}
offset += nChannels
}
}
}
// the internal "Row" is needed, because the image is a single dataframe column
Some(Row(Row(origin, height, width, nChannels, mode, decoded)))
@ -132,6 +151,7 @@ object ImageSchema{
var result: DataFrame = null
try {
val streams = session.sparkContext.binaryFiles(path, partitions)
.repartition(partitions)
val images = if(dropImageFailures){
streams.flatMap{

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@ -53,8 +53,7 @@ class TestImageSchemaSuite extends FunSuite with TestSparkContext {
assert(count50 > 0.2 * count100 && count50 < 0.8 * count100)
}
// TODO: fix the partition test
ignore("readImages partition test") {
test("readImages partition test") {
val df = readImages(imagePath, recursive = true, dropImageFailures = true, numPartitions = 3)
assert(df.rdd.getNumPartitions == 3)
}
@ -88,12 +87,11 @@ class TestImageSchemaSuite extends FunSuite with TestSparkContext {
}
}
// TODO: fix grayscale test
// number of channels and first 20 bytes of OpenCV representation
// - default representation for 3-channel RGB images is BGR row-wise: (B00, G00, R00, B10, G10, R10, ...)
// - default representation for 4-channel RGB images is BGRA row-wise: (B00, G00, R00, A00, B10, G10, R10, A00, ...)
private val firstBytes20 = Map(
//"grayscale.png" -> (("CV_8UC1", Array[Byte](0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 3, 5, 2, 1))),
"grayscale.png" -> (("CV_8UC1", Array[Byte](0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 3, 5, 2, 1))),
"RGB.png" -> (("CV_8UC3", Array[Byte](-34, -66, -98, -38, -69, -98, -62, -90, -117, -70, -98, -124, -34, -63, -90, -20, -48, -74, -18, -45))),
"RGBA.png" -> (("CV_8UC4", Array[Byte](-128, -128, -8, -1, -128, -128, -8, -1, -128, -128, -8, -1, 127, 127, -9, -1, 127, 127, -9, -1)))
)