add test and change PredictorExample

scala-package/core/src/test/java/org/apache/mxnet/javaapi/ImageTest.java

@@ -0,0 +1,50 @@
+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;
+
+public class ImageTest {
+
+    private String imLocation;
+
+    private 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 void downloadFile() throws Exception {
+        String tempDirPath = System.getProperty("java.io.tmpdir");
+        imLocation = tempDirPath + "/inputImages/Pug-Cookie.jpg";
+        try {
+            downloadUrl("https://s3.amazonaws.com/model-server/inputs/Pug-Cookie.jpg",
+                    imLocation, 3);
+        } catch (Exception e) {
+            throw e;
+        }
+    }
+
+    @Test
+    public void testImageProcess() {
+        NDArray nd = Image.imRead(imLocation, 1, true, null);
+        NDArray nd2 = Image.imResize(nd, 224, 224, null, null);
+        NDArray cropped = Image.fixedCrop(nd, 0, 0, 224, 224);
+        Image.toImage(cropped);
+    }
+}

scala-package/examples/src/main/java/org/apache/mxnetexamples/javaapi/infer/predictor/PredictorExample.java

@@ -101,18 +101,15 @@ public static void main(String[] args) {
         NDArray img = Image.imRead(inst.inputImagePath, 1, true, null);
         img = Image.imResize(img, 224, 224, null, 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;
         List<NDArray> ndList = new ArrayList<>();
         ndList.add(nd);
         List<NDArray> ndResult = predictor.predictWithNDArray(ndList);