lint

Author: samfreund

photon-client/src/components/settings/ObjectDetectionCard.vue

@@ -320,8 +320,8 @@ const handleBulkImport = () => {
               <v-card-text>
                 <span v-if="useSettingsStore().general.supportedBackends?.includes('RKNN')"
                   >Upload a new object detection model to this device that can be used in a pipeline. Note that ONLY
-                  640x640 YOLOv5, YOLOv8, YOLOv11, and YOLOv11 OBB models trained and converted to `.rknn` format for RK3588 SOCs are
-                  currently supported!</span
+                  640x640 YOLOv5, YOLOv8, YOLOv11, and YOLOv11 OBB models trained and converted to `.rknn` format for
+                  RK3588 SOCs are currently supported!</span
                 >
                 <span v-else-if="useSettingsStore().general.supportedBackends?.includes('RUBIK')"
                   >Upload a new object detection model to this device that can be used in a pipeline. Note that ONLY

photon-core/src/main/java/org/photonvision/vision/objects/Letterbox.java

@@ -22,7 +22,6 @@
 import org.opencv.core.Core;
 import org.opencv.core.Mat;
 import org.opencv.core.Point;
-import org.opencv.core.Rect2d;
 import org.opencv.core.RotatedRect;
 import org.opencv.core.Scalar;
 import org.opencv.core.Size;

photon-core/src/main/java/org/photonvision/vision/objects/RknnModel.java

@@ -55,7 +55,8 @@ public RknnModel(ModelProperties properties) throws IllegalArgumentException {
                 && properties.version() != Version.YOLOV8
                 && properties.version() != Version.YOLOV11
                 && properties.version() != Version.YOLOV11OBB) {
-            throw new IllegalArgumentException("Model version must be YOLOV5, YOLOV8, YOLOV11, or YOLOV11OBB");
+            throw new IllegalArgumentException(
+                    "Model version must be YOLOV5, YOLOV8, YOLOV11, or YOLOV11OBB");
         }
 
         this.properties = properties;

photon-core/src/main/java/org/photonvision/vision/pipe/impl/FilterObjectDetectionsPipe.java

@@ -43,16 +43,15 @@ protected List<NeuralNetworkPipeResult> process(List<NeuralNetworkPipeResult> in
 
     private void filterContour(NeuralNetworkPipeResult contour) {
         var boc = contour.bbox();
-        
+
         // Area filtering
         double areaPercentage = boc.size.area() / params.frameStaticProperties().imageArea * 100.0;
         double minAreaPercentage = params.area().getFirst();
         double maxAreaPercentage = params.area().getSecond();
         if (areaPercentage < minAreaPercentage || areaPercentage > maxAreaPercentage) return;
 
         // Aspect Ratio Filtering.
-        double aspectRatio =
-                TargetCalculations.getAspectRatio(boc, params.isLandscape());
+        double aspectRatio = TargetCalculations.getAspectRatio(boc, params.isLandscape());
         if (aspectRatio < params.ratio().getFirst() || aspectRatio > params.ratio().getSecond()) return;
 
         m_filteredContours.add(contour);

photon-core/src/main/java/org/photonvision/vision/pipe/impl/NeuralNetworkPipeResult.java

@@ -23,16 +23,14 @@
 import org.opencv.core.Size;
 
 public record NeuralNetworkPipeResult(RotatedRect bbox, int classIdx, double confidence) {
-    public NeuralNetworkPipeResult(Rect2d rect, int classIdx, double confidence) {        
+    public NeuralNetworkPipeResult(Rect2d rect, int classIdx, double confidence) {
         // turn the axis-aligned rect into a RotatedRect with angle 0 degrees
         this(
-            new RotatedRect(
-                new Point(rect.x + (rect.width) / 2, rect.y + (rect.height) / 2), 
-                new Size(rect.width, rect.height), 
-                0.0
-            ),
-            classIdx,
-            confidence
-        );
+                new RotatedRect(
+                        new Point(rect.x + (rect.width) / 2, rect.y + (rect.height) / 2),
+                        new Size(rect.width, rect.height),
+                        0.0),
+                classIdx,
+                confidence);
     }
 }