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Add RKNN / Object Detection Pipeline (#1144)

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Tested on Orange Pi 5 and Cool Pi 4B. Merge with parts of the OpenCV DNN PR. 

Adds support for YOLOv5s models for Rockchip CPUs with a NPU. Right now hard coded to a note model from alex_idk. Very much still incubating and largely untested.
This commit is contained in:
Mohammad Durrani
2024-01-15 22:28:34 -05:00
committed by GitHub
parent e1f550a751
commit 7b67f6bebf
42 changed files with 830 additions and 63 deletions
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17
photon-server/src/main/java/org/photonvision/Main.java
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@@ -27,6 +27,7 @@ import java.util.stream.Collectors;
import org.apache.commons.cli.*;
import org.photonvision.common.configuration.CameraConfiguration;
import org.photonvision.common.configuration.ConfigManager;
import org.photonvision.common.configuration.NeuralNetworkModelManager;
import org.photonvision.common.dataflow.networktables.NetworkTablesManager;
import org.photonvision.common.hardware.HardwareManager;
import org.photonvision.common.hardware.PiVersion;
@@ -37,6 +38,7 @@ import org.photonvision.common.logging.Logger;
import org.photonvision.common.networking.NetworkManager;
import org.photonvision.common.util.TestUtils;
import org.photonvision.common.util.numbers.IntegerCouple;
import org.photonvision.jni.RknnDetectorJNI;
import org.photonvision.mrcal.MrCalJNILoader;
import org.photonvision.raspi.LibCameraJNILoader;
import org.photonvision.server.Server;
@@ -348,7 +350,15 @@ public class Main {
} catch (IOException e) {
logger.error("Failed to load libcamera-JNI!", e);
}
try {
if (Platform.isRK3588()) {
RknnDetectorJNI.forceLoad();
} else {
logger.error("Platform does not support RKNN based machine learning!");
}
} catch (IOException e) {
logger.error("Failed to load rknn-JNI!", e);
}
try {
MrCalJNILoader.forceLoad();
} catch (IOException e) {
@@ -364,7 +374,6 @@ public class Main {
} catch (ParseException e) {
logger.error("Failed to parse command-line options!", e);
}
CVMat.enablePrint(false);
PipelineProfiler.enablePrint(false);
@@ -399,6 +408,10 @@ public class Main {
NetworkTablesManager.getInstance()
.setConfig(ConfigManager.getInstance().getConfig().getNetworkConfig());
logger.info("Loading ML models");
NeuralNetworkModelManager.getInstance()
.initialize(ConfigManager.getInstance().getModelsDirectory());
if (!isTestMode) {
logger.debug("Loading VisionSourceManager...");
VisionSourceManager.getInstance()