Add FRC 2026 game piece detection models

docs/source/docs/objectDetection/about-object-detection.md

@@ -4,7 +4,7 @@
 
 PhotonVision supports object detection using neural network accelerator hardware, commonly known as an NPU. The two coprocessors currently supported are the {ref}`Orange Pi 5 <docs/objectDetection/opi:Orange Pi 5 (and variants) Object Detection>` and the {ref}`Rubik Pi 3 <docs/objectDetection/rubik:Rubik Pi 3 Object Detection>`.
 
-PhotonVision currently ships with a model trained on the [COCO dataset](https://cocodataset.org/) by [Ultralytics](https://github.com/ultralytics/ultralytics) (this model is licensed under [AGPLv3](https://www.gnu.org/licenses/agpl-3.0.en.html)). This model is meant to be used for testing and other miscellaneous purposes. It is not meant to be used in competition. For the 2025 post-season, PhotonVision also ships with a pretrained ALGAE model. A model to detect coral is available in the PhotonVision discord, but will not be distributed with PhotonVision.
+PhotonVision currently ships with a model trained on the [COCO dataset](https://cocodataset.org/) by [Ultralytics](https://github.com/ultralytics/ultralytics) (this model is licensed under [AGPLv3](https://www.gnu.org/licenses/agpl-3.0.en.html)). This model is meant to be used for testing and other miscellaneous purposes. It is not meant to be used in competition. For the 2026 season, PhotonVision ships with a model to detect FUEL, this is also licensed under AGPL.
 
 ## Tracking Objects
 

photon-core/src/main/java/org/photonvision/common/configuration/NeuralNetworkModelManager.java

@@ -149,16 +149,6 @@ private NeuralNetworkPropertyManager getShippedProperties(File modelsDirectory)
                                 "hair drier", // Typo in official COCO documentation
                                 "toothbrush"));
 
-        nnProps.addModelProperties(
-                new ModelProperties(
-                        Path.of(modelsDirectory.getAbsolutePath(), "algaeV1-640-640-yolov8n.rknn"),
-                        "Algae v8n",
-                        new LinkedList<String>(List.of("Algae")),
-                        640,
-                        480,
-                        Family.RKNN,
-                        Version.YOLOV8));
-
         nnProps.addModelProperties(
                 new ModelProperties(
                         Path.of(modelsDirectory.getAbsolutePath(), "yolov8nCOCO.rknn"),
@@ -171,13 +161,13 @@ private NeuralNetworkPropertyManager getShippedProperties(File modelsDirectory)
 
         nnProps.addModelProperties(
                 new ModelProperties(
-                        Path.of(modelsDirectory.getAbsolutePath(), "algae-coral-yolov8s.tflite"),
-                        "Algae Coral v8s",
-                        new LinkedList<String>(List.of("Algae", "Coral")),
+                        Path.of(modelsDirectory.getAbsolutePath(), "fuelV1-yolo11n.rknn"),
+                        "Fuel v11n",
+                        new LinkedList<String>(List.of("Fuel")),
                         640,
                         640,
-                        Family.RUBIK,
-                        Version.YOLOV8));
+                        Family.RKNN,
+                        Version.YOLOV11));
 
         nnProps.addModelProperties(
                 new ModelProperties(
@@ -189,6 +179,16 @@ private NeuralNetworkPropertyManager getShippedProperties(File modelsDirectory)
                         Family.RUBIK,
                         Version.YOLOV8));
 
+        nnProps.addModelProperties(
+                new ModelProperties(
+                        Path.of(modelsDirectory.getAbsolutePath(), "fuelV1-yolo11n.tflite"),
+                        "Fuel v11n",
+                        new LinkedList<String>(List.of("Fuel")),
+                        640,
+                        640,
+                        Family.RUBIK,
+                        Version.YOLOV11));
+
         return nnProps;
     }