minor formatting

apache · Apr 4, 2018 · 43b5e00 · 43b5e00
1 parent 91ac8a6
commit 43b5e00
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Showing 3 changed files with 12 additions and 12 deletions.
diff --git a/scala-package/infer/src/main/scala/ml/dmlc/mxnet/infer/Classifier.scala b/scala-package/infer/src/main/scala/ml/dmlc/mxnet/infer/Classifier.scala
@@ -31,7 +31,7 @@ trait ClassifierBase {
     * Takes an array of floats and returns corresponding (Label, Score) tuples
     * @param input            Indexed sequence one-dimensional array of floats
     * @param topK             (Optional) How many result (sorting based on the last axis)
-    *                         elements to return. Default returns unsorted output
+    *                         elements to return. Default returns unsorted output.
     * @return                 Indexed sequence of (Label, Score) tuples
     */
   def classify(input: IndexedSeq[Array[Float]],
@@ -41,7 +41,7 @@ trait ClassifierBase {
     * Takes a sequence of NDArrays and returns (Label, Score) tuples
     * @param input            Indexed sequence of NDArrays
     * @param topK             (Optional) How many result (sorting based on the last axis)
-    *                         elements to return. Default returns unsorted output
+    *                         elements to return. Default returns unsorted output.
     * @return                 Traversable sequence of (Label, Score) tuple
     */
   def classifyWithNDArray(input: IndexedSeq[NDArray],
@@ -78,8 +78,8 @@ class Classifier(modelPathPrefix: String,
   /**
     * Takes flat arrays as input and returns (Label, Score) tuples.
     * @param input            Indexed sequence one-dimensional array of floats
-    * @param topK:            (Optional) How many result (sorting based on the last axis) 
-    *                         elements to return. Default returns unsorted output
+    * @param topK             (Optional) How many result (sorting based on the last axis)
+    *                         elements to return. Default returns unsorted output.
     * @return                 Indexed sequence of (Label, Score) tuples
     */
   override def classify(input: IndexedSeq[Array[Float]],
@@ -103,7 +103,7 @@ class Classifier(modelPathPrefix: String,
     * Also works with batched input.
     * @param input            Indexed sequence of NDArrays
     * @param topK             (Optional) How many result (sorting based on the last axis)
-    *                         elements to return. Default returns unsorted output
+    *                         elements to return. Default returns unsorted output.
     * @return                 Traversable sequence of (Label, Score) tuples
     */
   override def classifyWithNDArray(input: IndexedSeq[NDArray], topK: Option[Int] = None)

diff --git a/scala-package/infer/src/main/scala/ml/dmlc/mxnet/infer/ImageClassifier.scala b/scala-package/infer/src/main/scala/ml/dmlc/mxnet/infer/ImageClassifier.scala
@@ -33,7 +33,7 @@ import javax.imageio.ImageIO
   * Contains helper methods.
   *
   * @param modelPathPrefix    Path prefix from where to load the model artifacts.
-  *                           These include the symbol, parameters, and synset.txt
+  *                           These include the symbol, parameters, and synset.txt. 
   *                           Example: file://model-dir/resnet-152 (containing
   *                           resnet-152-symbol.json, resnet-152-0000.params, and synset.txt).
   * @param inputDescriptors   Descriptors defining the input node names, shape,

diff --git a/scala-package/infer/src/main/scala/ml/dmlc/mxnet/infer/ObjectDetector.scala b/scala-package/infer/src/main/scala/ml/dmlc/mxnet/infer/ObjectDetector.scala
@@ -57,11 +57,11 @@ class ObjectDetector(modelPathPrefix: String,
   protected[infer] val width = imgClassifier.width
 
   /**
-    * Detects objects and returns bounding boxes with corresponding labels
+    * Detects objects and returns bounding boxes with corresponding class/label
     *
-    * @param inputImage       PathPrefix of the input image
-    * @param topK             Get top k elements with maximum probability
-    * @return                 List of List of tuples of
+    * @param inputImage       Path prefix of the input image
+    * @param topK             Number of result elements to return, sorted by probability
+    * @return                 List of list of tuples of
     *                         (class, [probability, xmin, ymin, xmax, ymax])
     */
   def imageObjectDetect(inputImage: BufferedImage,
@@ -77,7 +77,7 @@ class ObjectDetector(modelPathPrefix: String,
 
   /**
     * Takes input images as NDArrays. Useful when you want to perform multiple operations on
-    * the input Array, or when you want to pass a batch of input images.
+    * the input array, or when you want to pass a batch of input images.
     *
     * @param input            Indexed Sequence of NDArrays
     * @param topK             (Optional) How many top_k (sorting will be based on the last axis)
@@ -139,7 +139,7 @@ class ObjectDetector(modelPathPrefix: String,
     *
     * @param inputBatch       Input array of buffered images
     * @param topK             Number of result elements to return, sorted by probability
-    * @return                 List of list of tuples of (Label, Probability)
+    * @return                 List of list of tuples of (class, probability)
     */
   def imageBatchObjectDetect(inputBatch: Traversable[BufferedImage], topK: Option[Int] = None):
   IndexedSeq[IndexedSeq[(String, Array[Float])]] = {