freesight/FtcRobotController/src/main/java/org/firstinspires/ftc/robotcontroller/external/samples/ConceptTensorFlowObjectDetectionEasy.java
2023-07-07 15:15:11 -07:00

142 lines
5.6 KiB
Java

/* Copyright (c) 2019 FIRST. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without modification,
* are permitted (subject to the limitations in the disclaimer below) provided that
* the following conditions are met:
*
* Redistributions of source code must retain the above copyright notice, this list
* of conditions and the following disclaimer.
*
* Redistributions in binary form must reproduce the above copyright notice, this
* list of conditions and the following disclaimer in the documentation and/or
* other materials provided with the distribution.
*
* Neither the name of FIRST nor the names of its contributors may be used to endorse or
* promote products derived from this software without specific prior written permission.
*
* NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS
* LICENSE. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
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package org.firstinspires.ftc.robotcontroller.external.samples;
import com.qualcomm.robotcore.eventloop.opmode.Disabled;
import com.qualcomm.robotcore.eventloop.opmode.LinearOpMode;
import com.qualcomm.robotcore.eventloop.opmode.TeleOp;
import java.util.List;
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;
/**
* This 2023-2024 OpMode illustrates the basics of TensorFlow Object Detection, using
* the easiest way.
*
* Use Android Studio to Copy this Class, and Paste it into your team's code folder with a new name.
* Remove or comment out the @Disabled line to add this OpMode to the Driver Station OpMode list.
*/
@TeleOp(name = "Concept: TensorFlow Object Detection Easy", group = "Concept")
@Disabled
public class ConceptTensorFlowObjectDetectionEasy extends LinearOpMode {
private static final boolean USE_WEBCAM = true; // true for webcam, false for phone camera
/**
* {@link #tfod} is the variable to store our instance of the TensorFlow Object Detection processor.
*/
private TfodProcessor tfod;
/**
* {@link #visionPortal} is the variable to store our instance of the vision portal.
*/
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 the easy way.
tfod = TfodProcessor.easyCreateWithDefaults();
// Create the vision portal the easy way.
if (USE_WEBCAM) {
visionPortal = VisionPortal.easyCreateWithDefaults(
hardwareMap.get(WebcamName.class, "Webcam 1"), tfod);
} else {
visionPortal = VisionPortal.easyCreateWithDefaults(
BuiltinCameraDirection.BACK, tfod);
}
} // end method initTfod()
/**
* Function to 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