apache · lanking520 · Jan 31, 2019 · Jan 5, 2019 · Jan 8, 2019 · Jan 8, 2019
@@ -138,12 +138,6 @@
  <version>INTERNAL</version>
  <scope>provided</scope>
  </dependency>
- <dependency>
- <groupId>junit</groupId>
- <artifactId>junit</artifactId>
- <version>4.11</version>
- <scope>test</scope>
- </dependency>
  <dependency>
  <groupId>commons-io</groupId>
  <artifactId>commons-io</artifactId>

@@ -37,7 +37,7 @@ object Image {
  * @param flag Convert decoded image to grayscale (0) or color (1).
  * @param to_rgb Whether to convert decoded image
  * to mxnet's default RGB format (instead of opencv's default BGR).
- * @return NDArray in HWC format
+ * @return NDArray in HWC format with DType [[DType.UInt8]]
  */
  def imDecode(buf: Array[Byte], flag: Int,
  to_rgb: Boolean,
@@ -56,7 +56,7 @@ object Image {
  /**
  * Same imageDecode with InputStream
  * @param inputStream the inputStream of the image
- * @return NDArray in HWC format
+ * @return NDArray in HWC format with DType [[DType.UInt8]]
  */
  def imDecode(inputStream: InputStream, flag: Int = 1,
  to_rgb: Boolean = true,
@@ -78,7 +78,7 @@ object Image {
  * @param flag Convert decoded image to grayscale (0) or color (1).
  * @param to_rgb Whether to convert decoded image to mxnet's default RGB format
  * (instead of opencv's default BGR).
- * @return org.apache.mxnet.NDArray in HWC format
+ * @return org.apache.mxnet.NDArray in HWC format with DType [[DType.UInt8]]
  */
  def imRead(filename: String, flag: Option[Int] = None,
  to_rgb: Option[Boolean] = None,

@@ -97,9 +97,11 @@ object NDArray extends NDArrayBase {
  case ndArr: Seq[NDArray @unchecked] =>
  if (ndArr.head.isInstanceOf[NDArray]) (ndArr.toArray, ndArr.toArray.map(_.handle))
  else throw new IllegalArgumentException(
- "Unsupported out var type, should be NDArray or subclass of Seq[NDArray]")
+ s"""Unsupported out ${output.getClass} type,
+ | should be NDArray or subclass of Seq[NDArray]""".stripMargin)
  case _ => throw new IllegalArgumentException(
- "Unsupported out var type, should be NDArray or subclass of Seq[NDArray]")
+ s"""Unsupported out ${output.getClass} type,
+ | should be NDArray or subclass of Seq[NDArray]""".stripMargin)
  }
  } else {
  (null, null)

@@ -0,0 +1,114 @@
+/*
+ * 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.mxnet.javaapi
+// scalastyle:off
+import java.awt.image.BufferedImage
+// scalastyle:on
+import java.io.InputStream
+
+object Image {
+ /**
+ * Decode image with OpenCV.
+ * Note: return image in RGB by default, instead of OpenCV's default BGR.
+ * @param buf Buffer containing binary encoded image
+ * @param flag Convert decoded image to grayscale (0) or color (1).
+ * @param toRGB Whether to convert decoded image
+ * to mxnet's default RGB format (instead of opencv's default BGR).
+ * @return NDArray in HWC format with DType [[DType.UInt8]]
+ */
+ def imDecode(buf: Array[Byte], flag: Int, toRGB: Boolean): NDArray = {
+ org.apache.mxnet.Image.imDecode(buf, flag, toRGB, None)
+ }
+
+ def imDecode(buf: Array[Byte]): NDArray = {
+ imDecode(buf, 1, true)
+ }
+
+ /**
+ * Same imageDecode with InputStream
+ *
+ * @param inputStream the inputStream of the image
+ * @param flag Convert decoded image to grayscale (0) or color (1).
+ * @param toRGB Whether to convert decoded image
+ * @return NDArray in HWC format with DType [[DType.UInt8]]
+ */
+ def imDecode(inputStream: InputStream, flag: Int, toRGB: Boolean): NDArray = {
+ org.apache.mxnet.Image.imDecode(inputStream, flag, toRGB, None)
+ }
+
+ def imDecode(inputStream: InputStream): NDArray = {
+ imDecode(inputStream, 1, true)
+ }
+
+ /**
+ * Read and decode image with OpenCV.
+ * Note: return image in RGB by default, instead of OpenCV's default BGR.
+ * @param filename Name of the image file to be loaded.
+ * @param flag Convert decoded image to grayscale (0) or color (1).
+ * @param toRGB Whether to convert decoded image to mxnet's default RGB format
+ * (instead of opencv's default BGR).
+ * @return org.apache.mxnet.NDArray in HWC format with DType [[DType.UInt8]]
+ */
+ def imRead(filename: String, flag: Int, toRGB: Boolean): NDArray = {
+ org.apache.mxnet.Image.imRead(filename, Some(flag), Some(toRGB), None)
+ }
+
+ def imRead(filename: String): NDArray = {
+ imRead(filename, 1, true)
+ }
+
+ /**
+ * Resize image with OpenCV.
+ * @param src source image in NDArray
+ * @param w Width of resized image.
+ * @param h Height of resized image.
+ * @param interp Interpolation method (default=cv2.INTER_LINEAR).
+ * @return org.apache.mxnet.NDArray
+ */
+ def imResize(src: NDArray, w: Int, h: Int, interp: Integer): NDArray = {
+ val interpVal = if (interp == null) None else Some(interp.intValue())
+ org.apache.mxnet.Image.imResize(src, w, h, interpVal, None)
+ }
+
+ def imResize(src: NDArray, w: Int, h: Int): NDArray = {
+ imResize(src, w, h, null)
+ }
+
+ /**
+ * Do a fixed crop on the image
+ * @param src Src image in NDArray
+ * @param x0 starting x point
+ * @param y0 starting y point
+ * @param w width of the image
+ * @param h height of the image
+ * @return cropped NDArray
+ */
+ def fixedCrop(src: NDArray, x0: Int, y0: Int, w: Int, h: Int): NDArray = {
+ org.apache.mxnet.Image.fixedCrop(src, x0, y0, w, h)
+ }
+
+ /**
+ * Convert a NDArray image to a real image
+ * The time cost will increase if the image resolution is big
+ * @param src Source image file in RGB
+ * @return Buffered Image
+ */
+ def toImage(src: NDArray): BufferedImage = {
+ org.apache.mxnet.Image.toImage(src)
+ }
+}
@@ -0,0 +1,67 @@
+/*
+ * 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.mxnet.javaapi;
+
+import org.apache.commons.io.FileUtils;
+import org.junit.BeforeClass;
+import org.junit.Test;
+import java.io.File;
+import java.net.URL;
+
+import static org.junit.Assert.assertArrayEquals;
+
+public class ImageTest {
+
+ private static String imLocation;
+
+ private static void downloadUrl(String url, String filePath, int maxRetry) throws Exception{
+ File tmpFile = new File(filePath);
+ Boolean success = false;
+ if (!tmpFile.exists()) {
+ while (maxRetry > 0 && !success) {
+ try {
+ FileUtils.copyURLToFile(new URL(url), tmpFile);
+ success = true;
+ } catch(Exception e){
+ maxRetry -= 1;
+ }
+ }
+ } else {
+ success = true;
+ }
+ if (!success) throw new Exception("$url Download failed!");
+ }
+
+ @BeforeClass
+ public static void downloadFile() throws Exception {
+ String tempDirPath = System.getProperty("java.io.tmpdir");
+ imLocation = tempDirPath + "/inputImages/Pug-Cookie.jpg";
+ downloadUrl("https://s3.amazonaws.com/model-server/inputs/Pug-Cookie.jpg",
+ imLocation, 3);
+ }
+
+ @Test
+ public void testImageProcess() {
+ NDArray nd = Image.imRead(imLocation, 1, true);
+ assertArrayEquals(nd.shape().toArray(), new int[]{576, 1024, 3});
+ NDArray nd2 = Image.imResize(nd, 224, 224, null);
+ assertArrayEquals(nd2.shape().toArray(), new int[]{224, 224, 3});
+ NDArray cropped = Image.fixedCrop(nd, 0, 0, 224, 224);
+ Image.toImage(cropped);
+ }
+}
@@ -15,6 +15,7 @@
 
  <properties>
  <skipTests>true</skipTests>
+ <skipJavaTests>${skipTests}</skipJavaTests>
  </properties>
 
  <build>

@@ -24,8 +24,6 @@
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
-import javax.imageio.ImageIO;
-import java.awt.Graphics2D;
 import java.awt.image.BufferedImage;
 import java.io.BufferedReader;
 import java.io.File;
@@ -47,76 +45,7 @@ public class PredictorExample {
  private String inputImagePath = "/images/dog.jpg";
 
  final static Logger logger = LoggerFactory.getLogger(PredictorExample.class);
-
- /**
- * Load the image from file to buffered image
- * It can be replaced by loadImageFromFile from ObjectDetector
- * @param inputImagePath input image Path in String
- * @return Buffered image
- */
- private static BufferedImage loadIamgeFromFile(String inputImagePath) {
- BufferedImage buf = null;
- try {
- buf = ImageIO.read(new File(inputImagePath));
- } catch (IOException e) {
- System.err.println(e);
- }
- return buf;
- }
-
- /**
- * Reshape the current image using ImageIO and Graph2D
- * It can be replaced by reshapeImage from ObjectDetector
- * @param buf Buffered image
- * @param newWidth desired width
- * @param newHeight desired height
- * @return a reshaped bufferedImage
- */
- private static BufferedImage reshapeImage(BufferedImage buf, int newWidth, int newHeight) {
- BufferedImage resizedImage = new BufferedImage(newWidth, newHeight, BufferedImage.TYPE_INT_RGB);
- Graphics2D g = resizedImage.createGraphics();
- g.drawImage(buf, 0, 0, newWidth, newHeight, null);
- g.dispose();
- return resizedImage;
- }
-
- /**
- * Convert an image from a buffered image into pixels float array
- * It can be replaced by bufferedImageToPixels from ObjectDetector
- * @param buf buffered image
- * @return Float array
- */
- private static float[] imagePreprocess(BufferedImage buf) {
- // Get height and width of the image
- int w = buf.getWidth();
- int h = buf.getHeight();
-
- // get an array of integer pixels in the default RGB color mode
- int[] pixels = buf.getRGB(0, 0, w, h, null, 0, w);
-
- // 3 times height and width for R,G,B channels
- float[] result = new float[3 * h * w];
-
- int row = 0;
- // copy pixels to array vertically
- while (row < h) {
- int col = 0;
- // copy pixels to array horizontally
- while (col < w) {
- int rgb = pixels[row * w + col];
- // getting red color
- result[0 * h * w + row * w + col] = (rgb >> 16) & 0xFF;
- // getting green color
- result[1 * h * w + row * w + col] = (rgb >> 8) & 0xFF;
- // getting blue color
- result[2 * h * w + row * w + col] = rgb & 0xFF;
- col += 1;
- }
- row += 1;
- }
- buf.flush();
- return result;
- }
+ private static NDArray$ NDArray = NDArray$.MODULE$;
 
  /**
  * Helper class to print the maximum prediction result
@@ -170,22 +99,21 @@ public static void main(String[] args) {
  inputDesc.add(new DataDesc("data", inputShape, DType.Float32(), "NCHW"));
  Predictor predictor = new Predictor(inst.modelPathPrefix, inputDesc, context,0);
  // Prepare data
- BufferedImage img = loadIamgeFromFile(inst.inputImagePath);
-
- img = reshapeImage(img, 224, 224);
+ NDArray img = Image.imRead(inst.inputImagePath, 1, true);
+ img = Image.imResize(img, 224, 224, null);
  // predict
- float[][] result = predictor.predict(new float[][]{imagePreprocess(img)});
+ float[][] result = predictor.predict(new float[][]{img.toArray()});
  try {
  System.out.println("Predict with Float input");
  System.out.println(printMaximumClass(result[0], inst.modelPathPrefix));
  } catch (IOException e) {
  System.err.println(e);
  }
  // predict with NDArray
- NDArray nd = new NDArray(
-  imagePreprocess(img),
-  new Shape(new int[]{1, 3, 224, 224}),
-  Context.cpu());
+ NDArray nd = img;
+ nd = NDArray.transpose(nd, new Shape(new int[]{2, 0, 1}), null)[0];
+ nd = NDArray.expand_dims(nd, 0, null)[0];
+ nd = nd.asType(DType.Float32());
  List<NDArray> ndList = new ArrayList<>();
  ndList.add(nd);
  List<NDArray> ndResult = predictor.predictWithNDArray(ndList);

@@ -24,9 +24,9 @@ import org.apache.commons.io.FileUtils
 
 object Util {
 
- def downloadUrl(url: String, filePath: String, maxRetry: Option[Int] = None) : Unit = {
+ def downloadUrl(url: String, filePath: String, maxRetry: Int = 3) : Unit = {
  val tmpFile = new File(filePath)
- var retry = maxRetry.getOrElse(3)
+ var retry = maxRetry
  var success = false
  if (!tmpFile.exists()) {
  while (retry > 0 && !success) {