Used TFOD sample to detect the white pixel

TeamCode/src/main/java/org/firstinspires/ftc/teamcode/utility/WhitePixelSpikeDetection.java

@@ -0,0 +1,154 @@
+package org.firstinspires.ftc.teamcode.utility;
+
+import com.qualcomm.robotcore.eventloop.opmode.Autonomous;
+import com.qualcomm.robotcore.eventloop.opmode.Disabled;
+import com.qualcomm.robotcore.eventloop.opmode.LinearOpMode;
+import com.qualcomm.robotcore.eventloop.opmode.TeleOp;
+import org.firstinspires.ftc.robotcore.external.hardware.camera.BuiltinCameraDirection;
+import org.firstinspires.ftc.robotcore.external.hardware.camera.WebcamName;
+import org.firstinspires.ftc.robotcore.external.tfod.Recognition;
+import org.firstinspires.ftc.vision.VisionPortal;
+import org.firstinspires.ftc.vision.tfod.TfodProcessor;
+
+import java.util.List;
+@Autonomous
+public class WhitePixelSpikeDetection extends LinearOpMode {
+
+    private static final boolean USE_WEBCAM = true;  // true for webcam, false for phone camera
+
+    // TFOD_MODEL_FILE points to a model file stored onboard the Robot Controller's storage,
+    // this is used when uploading models directly to the RC using the model upload interface.
+    private static final String TFOD_MODEL_ASSET = "whitePixel.tflite";
+    // Define the labels recognized in the model for TFOD (must be in training order!)
+    private static final String[] LABELS = {
+            "WhitePixel",
+    };
+
+    /**
+     * The variable to store our instance of the TensorFlow Object Detection processor.
+     */
+    private TfodProcessor tfod;
+    private VisionPortal visionPortal;
+
+    @Override
+    public void runOpMode() {
+
+        initTfod();
+
+        // Wait for the DS start button to be touched.
+        telemetry.addData("DS preview on/off", "3 dots, Camera Stream");
+        telemetry.addData(">", "Touch Play to start OpMode");
+        telemetry.update();
+        waitForStart();
+
+        if (opModeIsActive()) {
+            while (opModeIsActive()) {
+
+                telemetryTfod();
+
+                // Push telemetry to the Driver Station.
+                telemetry.update();
+
+                // Save CPU resources; can resume streaming when needed.
+                if (gamepad1.dpad_down) {
+                    visionPortal.stopStreaming();
+                } else if (gamepad1.dpad_up) {
+                    visionPortal.resumeStreaming();
+                }
+
+                // Share the CPU.
+                sleep(20);
+            }
+        }
+
+        // Save more CPU resources when camera is no longer needed.
+        visionPortal.close();
+
+    }   // end runOpMode()
+
+    /**
+     * Initialize the TensorFlow Object Detection processor.
+     */
+    private void initTfod() {
+
+        // Create the TensorFlow processor by using a builder.
+        tfod = new TfodProcessor.Builder()
+
+                // With the following lines commented out, the default TfodProcessor Builder
+                // will load the default model for the season. To define a custom model to load,
+                // choose one of the following:
+                //   Use setModelAssetName() if the custom TF Model is built in as an asset (AS only).
+                //   Use setModelFileName() if you have downloaded a custom team model to the Robot Controller.
+                .setModelAssetName(TFOD_MODEL_ASSET)
+                //.setModelFileName(TFOD_MODEL_FILE)
+
+                // The following default settings are available to un-comment and edit as needed to
+                // set parameters for custom models.
+                .setModelLabels(LABELS)
+                //.setIsModelTensorFlow2(true)
+                //.setIsModelQuantized(true)
+                //.setModelInputSize(300)
+                //.setModelAspectRatio(16.0 / 9.0)
+
+                .build();
+
+        // Create the vision portal by using a builder.
+        VisionPortal.Builder builder = new VisionPortal.Builder();
+
+        // Set the camera (webcam vs. built-in RC phone camera).
+        if (USE_WEBCAM) {
+            builder.setCamera(hardwareMap.get(WebcamName.class, "Webcam 1"));
+        } else {
+            builder.setCamera(BuiltinCameraDirection.BACK);
+        }
+
+        // Choose a camera resolution. Not all cameras support all resolutions.
+        //builder.setCameraResolution(new Size(640, 480));
+
+        // Enable the RC preview (LiveView).  Set "false" to omit camera monitoring.
+        //builder.enableLiveView(true);
+
+        // Set the stream format; MJPEG uses less bandwidth than default YUY2.
+        //builder.setStreamFormat(VisionPortal.StreamFormat.YUY2);
+
+        // Choose whether or not LiveView stops if no processors are enabled.
+        // If set "true", monitor shows solid orange screen if no processors enabled.
+        // If set "false", monitor shows camera view without annotations.
+        //builder.setAutoStopLiveView(false);
+
+        // Set and enable the processor.
+        builder.addProcessor(tfod);
+
+        // Build the Vision Portal, using the above settings.
+        visionPortal = builder.build();
+
+        // Set confidence threshold for TFOD recognitions, at any time.
+        //tfod.setMinResultConfidence(0.75f);
+
+        // Disable or re-enable the TFOD processor at any time.
+        //visionPortal.setProcessorEnabled(tfod, true);
+
+    }   // end method initTfod()
+
+    /**
+     * Add telemetry about TensorFlow Object Detection (TFOD) recognitions.
+     */
+    private void telemetryTfod() {
+
+        List<Recognition> currentRecognitions = tfod.getRecognitions();
+        telemetry.addData("# Objects Detected", currentRecognitions.size());
+
+        // Step through the list of recognitions and display info for each one.
+        for (Recognition recognition : currentRecognitions) {
+            double x = (recognition.getLeft() + recognition.getRight()) / 2 ;
+            double y = (recognition.getTop()  + recognition.getBottom()) / 2 ;
+
+            telemetry.addData(""," ");
+            telemetry.addData("Image", "%s (%.0f %% Conf.)", recognition.getLabel(), recognition.getConfidence() * 100);
+            telemetry.addData("- Position", "%.0f,%.0f", x, y);
+            telemetry.addData("- Size", "%.0f x %.0f", recognition.getWidth(), recognition.getHeight());
+        }   // end for() loop
+
+    }   // end method telemetryTfod()
+
+}   // end class