Add RKNN object detection docs

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

@@ -0,0 +1,37 @@
+About Object Detection
+======================
+
+.. image:: images/notes-ui.png
+
+How does it work?
+^^^^^^^^^^^^^^^^^^^
+
+PhotonVision supports object detection using neural network accelerator hardware built into Orange Pi 5/5+ coprocessors. The Neural Processing Unit, or NPU, is `used by Photon <https://github.com/PhotonVision/rknn_jni/tree/main>`_ to massively accelerate certain math operations like those needed for running ML-based object detection.
+
+For the 2024 season, Photon ships with a **pre-trained NOTE detector** (shown above), as well as a mechanism for swapping in custom models. Future development will focus on enabling lower friction management of multiple custom models.
+
+Tuning and Filtering
+^^^^^^^^^^^^^^^^^^^^
+
+Compared to other pipelines, object detection exposes very few tuning handles. The Confidence slider changes the minimum confidence that the model needs to have in a given detection to consider it valid, as a number between 0 and 1 (with 0 meaning completely uncertain and 1 meaning maximally certain).
+
+.. raw:: html
+
+        <video width="85%" controls>
+            <source src="../../_static/assets/objdetectFiltering.mp4" type="video/mp4">
+            Your browser does not support the video tag.
+        </video>
+
+The same area, aspect ratio, and target orientation/sort parameters from :ref:`reflective pipelines <docs/reflectiveAndShape/contour-filtering:Reflective>` are also exposed in the object detection hard.
+
+Training Custom Models
+^^^^^^^^^^^^^^^^^^^^^^
+
+Coming soon!
+
+Uploading Custom Models
+^^^^^^^^^^^^^^^^^^^^^^^
+
+Our `pre-trained NOTE model <https://github.com/PhotonVision/photonvision/blob/master/photon-server/src/main/resources/models/note-640-640-yolov5s.rknn>`_ is automatically extracted from the JAR when PhotonVision starts, only if a file named “note-640-640-yolov5s.rknn” and "labels.txt" does not exist in the folder ``photonvision_config/models/``. This technically allows power users to replace the model and label files with new ones without rebuilding Photon from source and uploading a new JAR.
+
+Use a program like WinSCP or FileZilla to access your coprocessor's filesystem, and copy the new ``.rknn`` model file into /home/pi. Next, SSH into the coprocessor and ``sudo mv /path/to/new/model.rknn /opt/photonvision/photonvision_config/models/note-640-640-yolov5s.rknn``. Repeat this process with the labels file, which should contain one line per label the model outputs with no training newline. Next, restart PhotonVision via the web UI.

source/docs/objectDetection/index.rst

@@ -0,0 +1,8 @@
+Object Detection
+================
+
+.. toctree::
+   :maxdepth: 0
+   :titlesonly:
+
+   about-object-detection

source/docs/reflectiveAndShape/index.rst

@@ -1,5 +1,5 @@
-Colored Shape Detection
-=======================
+Colored Shape & Reflective
+==========================
 
 .. toctree::
    :maxdepth: 0

source/docs/reflectiveAndShape/thresholding.rst

@@ -8,7 +8,7 @@ In PhotonVision, HSV thresholds is available in the "Threshold" tab.
 .. raw:: html
 
         <video width="85%" controls>
-            <source src="../../../../_static/assets/tuningHueSatVal.mp4" type="video/mp4">
+            <source src="../../_static/assets/tuningHueSatVal.mp4" type="video/mp4">
             Your browser does not support the video tag.
         </video>
 
@@ -20,7 +20,7 @@ The color picker can be used to quickly adjust HSV values. "Set to average" will
 .. raw:: html
 
         <video width="85%" controls>
-            <source src="../../../../_static/assets/colorPicker.mp4" type="video/mp4">
+            <source src="../../_static/assets/colorPicker.mp4" type="video/mp4">
             Your browser does not support the video tag.
         </video>
 

source/index.rst

@@ -87,6 +87,7 @@ PhotonVision is licensed under the `GNU GPL v3 <https://www.gnu.org/licenses/gpl
    docs/pipelines/index
    docs/apriltag-pipelines/index
    docs/reflectiveAndShape/index
+   docs/objectDetection/index
    docs/calibration/calibration
 
 .. toctree::