[api] Adds center fit image operation for Yolo

api/src/main/java/ai/djl/modality/cv/transform/CenterFit.java

@@ -0,0 +1,59 @@
+/*
+ * Copyright 2024 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance
+ * with the License. A copy of the License is located at
+ *
+ * http://aws.amazon.com/apache2.0/
+ *
+ * or in the "license" file accompanying this file. This file 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 ai.djl.modality.cv.transform;
+
+import ai.djl.modality.cv.util.NDImageUtils;
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.types.Shape;
+import ai.djl.translate.Transform;
+
+/** A {@link Transform} that fit the size of an image. */
+public class CenterFit implements Transform {
+
+    private int width;
+    private int height;
+
+    /**
+     * Creates a {@code CenterFit} {@link Transform} that fit to the given width and height with
+     * given interpolation.
+     *
+     * @param width the desired width
+     * @param height the desired height
+     */
+    public CenterFit(int width, int height) {
+        this.width = width;
+        this.height = height;
+    }
+
+    /** {@inheritDoc} */
+    @Override
+    public NDArray transform(NDArray array) {
+        Shape shape = array.getShape();
+        int w = (int) shape.get(1);
+        int h = (int) shape.get(0);
+        if (w > width || h > height) {
+            array = NDImageUtils.centerCrop(array, Math.min(w, width), Math.min(h, height));
+        }
+        int padW = width - w;
+        int padH = height - h;
+        if (padW > 0 || padH > 0) {
+            padW = Math.max(0, padW);
+            padH = Math.max(0, padH);
+            int padW1 = padW / 2;
+            int padH1 = padH / 2;
+            Shape padding = new Shape(0, 0, padW1, padW - padW1, padH1, padH - padH1);
+            array = array.pad(padding, 0);
+        }
+        return array;
+    }
+}

api/src/main/java/ai/djl/modality/cv/translator/BaseImageTranslator.java

@@ -15,6 +15,7 @@
 import ai.djl.Model;
 import ai.djl.modality.cv.Image;
 import ai.djl.modality.cv.transform.CenterCrop;
+import ai.djl.modality.cv.transform.CenterFit;
 import ai.djl.modality.cv.transform.Normalize;
 import ai.djl.modality.cv.transform.Resize;
 import ai.djl.modality.cv.transform.ToTensor;
@@ -50,6 +51,8 @@ public abstract class BaseImageTranslator<T> implements Translator<Image, T> {
 
     private Image.Flag flag;
     private Batchifier batchifier;
+    protected int width;
+    protected int height;
 
     /**
      * Constructs an ImageTranslator with the provided builder.
@@ -60,6 +63,8 @@ public BaseImageTranslator(BaseBuilder<?> builder) {
         flag = builder.flag;
         pipeline = builder.pipeline;
         batchifier = builder.batchifier;
+        width = builder.width;
+        height = builder.height;
     }
 
     /** {@inheritDoc} */
@@ -72,6 +77,8 @@ public Batchifier getBatchifier() {
     @Override
     public NDList processInput(TranslatorContext ctx, Image input) {
         NDArray array = input.toNDArray(ctx.getNDManager(), flag);
+        ctx.setAttachment("width", input.getWidth());
+        ctx.setAttachment("height", input.getHeight());
         return pipeline.transform(new NDList(array));
     }
 
@@ -171,6 +178,10 @@ protected void configPreProcess(Map<String, ?> arguments) {
             if (ArgumentsUtil.booleanValue(arguments, "centerCrop", false)) {
                 addTransform(new CenterCrop(width, height));
             }
+            String centerFit = ArgumentsUtil.stringValue(arguments, "centerFit", "false");
+            if ("true".equals(centerFit)) {
+                addTransform(new CenterFit(width, height));
+            }
             if (ArgumentsUtil.booleanValue(arguments, "toTensor", true)) {
                 addTransform(new ToTensor());
             }

api/src/main/java/ai/djl/modality/cv/translator/ObjectDetectionTranslator.java

@@ -29,9 +29,8 @@ public abstract class ObjectDetectionTranslator extends BaseImageTranslator<Dete
     protected float threshold;
     private SynsetLoader synsetLoader;
     protected List<String> classes;
-    protected double imageWidth;
-    protected double imageHeight;
     protected boolean applyRatio;
+    protected boolean removePadding;
 
     /**
      * Creates the {@link ObjectDetectionTranslator} from the given builder.
@@ -42,9 +41,8 @@ protected ObjectDetectionTranslator(ObjectDetectionBuilder<?> builder) {
         super(builder);
         this.threshold = builder.threshold;
         this.synsetLoader = builder.synsetLoader;
-        this.imageWidth = builder.imageWidth;
-        this.imageHeight = builder.imageHeight;
         this.applyRatio = builder.applyRatio;
+        this.removePadding = builder.removePadding;
     }
 
     /** {@inheritDoc} */
@@ -61,9 +59,8 @@ public abstract static class ObjectDetectionBuilder<T extends ObjectDetectionBui
             extends ClassificationBuilder<T> {
 
         protected float threshold = 0.2f;
-        protected double imageWidth;
-        protected double imageHeight;
         protected boolean applyRatio;
+        protected boolean removePadding;
 
         /**
          * Sets the threshold for prediction accuracy.
@@ -78,19 +75,6 @@ public T optThreshold(float threshold) {
             return self();
         }
 
-        /**
-         * Sets the optional rescale size.
-         *
-         * @param imageWidth the width to rescale images to
-         * @param imageHeight the height to rescale images to
-         * @return this builder
-         */
-        public T optRescaleSize(double imageWidth, double imageHeight) {
-            this.imageWidth = imageWidth;
-            this.imageHeight = imageHeight;
-            return self();
-        }
-
         /**
          * Determine Whether to divide output object width/height on the inference result. Default
          * false.
@@ -108,37 +92,17 @@ public T optApplyRatio(boolean value) {
             return self();
         }
 
-        /**
-         * Get resized image width.
-         *
-         * @return image width
-         */
-        public double getImageWidth() {
-            return imageWidth;
-        }
-
-        /**
-         * Get resized image height.
-         *
-         * @return image height
-         */
-        public double getImageHeight() {
-            return imageHeight;
-        }
-
         /** {@inheritDoc} */
         @Override
         protected void configPostProcess(Map<String, ?> arguments) {
             super.configPostProcess(arguments);
-            if (ArgumentsUtil.booleanValue(arguments, "rescale")) {
-                optRescaleSize(width, height);
-            }
             if (ArgumentsUtil.booleanValue(arguments, "optApplyRatio")
                     || ArgumentsUtil.booleanValue(arguments, "applyRatio")) {
                 optApplyRatio(true);
-                optRescaleSize(width, height);
             }
             threshold = ArgumentsUtil.floatValue(arguments, "threshold", 0.2f);
+            String centerFit = ArgumentsUtil.stringValue(arguments, "centerFit", "false");
+            removePadding = "true".equals(centerFit);
         }
     }
 }

api/src/main/java/ai/djl/modality/cv/translator/SingleShotDetectionTranslator.java

@@ -59,19 +59,14 @@ public DetectedObjects processOutput(TranslatorContext ctx, NDList list) {
                 }
                 String className = classes.get(classId);
                 float[] box = boundingBoxes.get(i).toFloatArray();
-                // rescale box coordinates by imageWidth and imageHeight
-                double x = imageWidth > 0 ? box[0] / imageWidth : box[0];
-                double y = imageHeight > 0 ? box[1] / imageHeight : box[1];
-                double w = imageWidth > 0 ? box[2] / imageWidth - x : box[2] - x;
-                double h = imageHeight > 0 ? box[3] / imageHeight - y : box[3] - y;
+                // rescale box coordinates by width and height
+                double x = width > 0 ? box[0] / width : box[0];
+                double y = height > 0 ? box[1] / height : box[1];
+                double w = width > 0 ? box[2] / width - x : box[2] - x;
+                double h = height > 0 ? box[3] / height - y : box[3] - y;
                 Rectangle rect;
                 if (applyRatio) {
-                    rect =
-                            new Rectangle(
-                                    x / imageWidth,
-                                    y / imageHeight,
-                                    w / imageWidth,
-                                    h / imageHeight);
+                    rect = new Rectangle(x / width, y / height, w / width, h / height);
                 } else {
                     rect = new Rectangle(x, y, w, h);
                 }

api/src/main/java/ai/djl/modality/cv/translator/YoloPoseTranslator.java

@@ -29,8 +29,6 @@ public class YoloPoseTranslator extends BaseImageTranslator<Joints[]> {
 
     private static final int MAX_DETECTION = 300;
 
-    private int width;
-    private int height;
     private float threshold;
     private float nmsThreshold;
 
@@ -41,8 +39,6 @@ public class YoloPoseTranslator extends BaseImageTranslator<Joints[]> {
      */
     public YoloPoseTranslator(Builder builder) {
         super(builder);
-        this.width = builder.width;
-        this.height = builder.height;
         this.threshold = builder.threshold;
         this.nmsThreshold = builder.nmsThreshold;
     }

api/src/main/java/ai/djl/modality/cv/translator/YoloSegmentationTranslator.java

@@ -33,8 +33,6 @@ public class YoloSegmentationTranslator extends YoloV5Translator {
 
     private float threshold;
     private float nmsThreshold;
-    private int width;
-    private int height;
 
     /**
      * Creates the instance segmentation translator from the given builder.
@@ -45,8 +43,6 @@ public YoloSegmentationTranslator(Builder builder) {
         super(builder);
         this.threshold = builder.threshold;
         this.nmsThreshold = builder.nmsThreshold;
-        this.width = builder.width;
-        this.height = builder.height;
     }
 
     /** {@inheritDoc} */

api/src/main/java/ai/djl/modality/cv/translator/YoloTranslator.java

@@ -44,10 +44,10 @@ public DetectedObjects processOutput(TranslatorContext ctx, NDList list) {
         NDArray boundingBoxes = list.get(2);
         int detected = Math.toIntExact(probs.length);
 
-        NDArray xMin = boundingBoxes.get(":, 0").clip(0, imageWidth).div(imageWidth);
-        NDArray yMin = boundingBoxes.get(":, 1").clip(0, imageHeight).div(imageHeight);
-        NDArray xMax = boundingBoxes.get(":, 2").clip(0, imageWidth).div(imageWidth);
-        NDArray yMax = boundingBoxes.get(":, 3").clip(0, imageHeight).div(imageHeight);
+        NDArray xMin = boundingBoxes.get(":, 0").clip(0, width).div(width);
+        NDArray yMin = boundingBoxes.get(":, 1").clip(0, height).div(height);
+        NDArray xMax = boundingBoxes.get(":, 2").clip(0, width).div(width);
+        NDArray yMax = boundingBoxes.get(":, 3").clip(0, height).div(height);
 
         float[] boxX = xMin.toFloatArray();
         float[] boxY = yMin.toFloatArray();
@@ -67,10 +67,10 @@ public DetectedObjects processOutput(TranslatorContext ctx, NDList list) {
             if (applyRatio) {
                 rect =
                         new Rectangle(
-                                boxX[i] / imageWidth,
-                                boxY[i] / imageHeight,
-                                boxWidth[i] / imageWidth,
-                                boxHeight[i] / imageHeight);
+                                boxX[i] / width,
+                                boxY[i] / height,
+                                boxWidth[i] / width,
+                                boxHeight[i] / height);
             } else {
                 rect = new Rectangle(boxX[i], boxY[i], boxWidth[i], boxHeight[i]);
             }

api/src/main/java/ai/djl/modality/cv/translator/YoloV5Translator.java

@@ -27,7 +27,7 @@
 
 /**
  * A translator for YoloV5 models. This was tested with ONNX exported Yolo models. For details check
- * here: https://github.com/ultralytics/yolov5
+ * <a href="https://github.com/ultralytics/yolov5">here</a>
  */
 public class YoloV5Translator extends ObjectDetectionTranslator {
 
@@ -68,7 +68,11 @@ public static YoloV5Translator.Builder builder(Map<String, ?> arguments) {
     }
 
     protected DetectedObjects nms(
-            List<Rectangle> boxes, List<Integer> classIds, List<Float> scores) {
+            int imageWidth,
+            int imageHeight,
+            List<Rectangle> boxes,
+            List<Integer> classIds,
+            List<Float> scores) {
         List<String> retClasses = new ArrayList<>();
         List<Double> retProbs = new ArrayList<>();
         List<BoundingBox> retBB = new ArrayList<>();
@@ -94,22 +98,30 @@ protected DetectedObjects nms(
                 retClasses.add(classes.get(id));
                 retProbs.add(scores.get(pos).doubleValue());
                 Rectangle rect = boxes.get(pos);
-                if (applyRatio) {
-                    retBB.add(
+                if (removePadding) {
+                    int padW = (width - imageWidth) / 2;
+                    int padH = (height - imageHeight) / 2;
+                    rect =
                             new Rectangle(
-                                    rect.getX() / imageWidth,
-                                    rect.getY() / imageHeight,
+                                    (rect.getX() - padW) / imageWidth,
+                                    (rect.getY() - padH) / imageHeight,
                                     rect.getWidth() / imageWidth,
-                                    rect.getHeight() / imageHeight));
-                } else {
-                    retBB.add(rect);
+                                    rect.getHeight() / imageHeight);
+                } else if (applyRatio) {
+                    rect =
+                            new Rectangle(
+                                    rect.getX() / width,
+                                    rect.getY() / height,
+                                    rect.getWidth() / width,
+                                    rect.getHeight() / height);
                 }
+                retBB.add(rect);
             }
         }
         return new DetectedObjects(retClasses, retProbs, retBB);
     }
 
-    protected DetectedObjects processFromBoxOutput(NDList list) {
+    protected DetectedObjects processFromBoxOutput(int imageWidth, int imageHeight, NDList list) {
         float[] flattened = list.get(0).toFloatArray();
         int sizeClasses = classes.size();
         int stride = 5 + sizeClasses;
@@ -142,7 +154,7 @@ protected DetectedObjects processFromBoxOutput(NDList list) {
                 classIds.add(maxIndex);
             }
         }
-        return nms(boxes, classIds, scores);
+        return nms(imageWidth, imageHeight, boxes, classIds, scores);
     }
 
     private DetectedObjects processFromDetectOutput() {
@@ -153,18 +165,20 @@ private DetectedObjects processFromDetectOutput() {
     /** {@inheritDoc} */
     @Override
     public DetectedObjects processOutput(TranslatorContext ctx, NDList list) {
+        int imageWidth = (Integer) ctx.getAttachment("width");
+        int imageHeight = (Integer) ctx.getAttachment("height");
         switch (yoloOutputLayerType) {
             case DETECT:
                 return processFromDetectOutput();
             case AUTO:
                 if (list.get(0).getShape().dimension() > 2) {
                     return processFromDetectOutput();
                 } else {
-                    return processFromBoxOutput(list);
+                    return processFromBoxOutput(imageWidth, imageHeight, list);
                 }
             case BOX:
             default:
-                return processFromBoxOutput(list);
+                return processFromBoxOutput(imageWidth, imageHeight, list);
         }
     }