183 lines
7.2 KiB
Java
183 lines
7.2 KiB
Java
/* Copyright (c) 2019 FIRST. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without modification,
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* are permitted (subject to the limitations in the disclaimer below) provided that
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* the following conditions are met:
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*
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* Redistributions of source code must retain the above copyright notice, this list
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* of conditions and the following disclaimer.
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*
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* Redistributions in binary form must reproduce the above copyright notice, this
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* list of conditions and the following disclaimer in the documentation and/or
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* other materials provided with the distribution.
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*
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* Neither the name of FIRST nor the names of its contributors may be used to endorse or
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* promote products derived from this software without specific prior written permission.
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*
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* NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS
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* LICENSE. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
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* THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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package org.firstinspires.ftc.robotcontroller.external.samples;
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import com.qualcomm.robotcore.eventloop.opmode.Disabled;
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import com.qualcomm.robotcore.eventloop.opmode.LinearOpMode;
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import com.qualcomm.robotcore.eventloop.opmode.TeleOp;
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import org.firstinspires.ftc.robotcore.external.hardware.camera.BuiltinCameraDirection;
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import org.firstinspires.ftc.robotcore.external.hardware.camera.WebcamName;
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import org.firstinspires.ftc.robotcore.external.tfod.Recognition;
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import org.firstinspires.ftc.vision.VisionPortal;
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import org.firstinspires.ftc.vision.tfod.TfodProcessor;
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import java.util.List;
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/*
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* This OpMode illustrates the basics of TensorFlow Object Detection,
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* including Java Builder structures for specifying Vision parameters.
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*
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* Use Android Studio to Copy this Class, and Paste it into your team's code folder with a new name.
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* Remove or comment out the @Disabled line to add this OpMode to the Driver Station OpMode list.
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*/
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@TeleOp(name = "Concept: TensorFlow Object Detection", group = "Concept")
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@Disabled
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public class ConceptTensorFlowObjectDetection extends LinearOpMode {
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private static final boolean USE_WEBCAM = true; // true for webcam, false for phone camera
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/**
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* The variable to store our instance of the TensorFlow Object Detection processor.
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*/
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private TfodProcessor tfod;
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/**
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* The variable to store our instance of the vision portal.
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*/
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private VisionPortal visionPortal;
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@Override
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public void runOpMode() {
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initTfod();
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// Wait for the DS start button to be touched.
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telemetry.addData("DS preview on/off", "3 dots, Camera Stream");
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telemetry.addData(">", "Touch Play to start OpMode");
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telemetry.update();
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waitForStart();
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if (opModeIsActive()) {
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while (opModeIsActive()) {
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telemetryTfod();
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// Push telemetry to the Driver Station.
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telemetry.update();
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// Save CPU resources; can resume streaming when needed.
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if (gamepad1.dpad_down) {
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visionPortal.stopStreaming();
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} else if (gamepad1.dpad_up) {
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visionPortal.resumeStreaming();
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}
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// Share the CPU.
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sleep(20);
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}
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}
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// Save more CPU resources when camera is no longer needed.
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visionPortal.close();
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} // end runOpMode()
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/**
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* Initialize the TensorFlow Object Detection processor.
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*/
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private void initTfod() {
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// Create the TensorFlow processor by using a builder.
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tfod = new TfodProcessor.Builder()
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// Use setModelAssetName() if the TF Model is built in as an asset.
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// Use setModelFileName() if you have downloaded a custom team model to the Robot Controller.
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//.setModelAssetName(TFOD_MODEL_ASSET)
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//.setModelFileName(TFOD_MODEL_FILE)
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//.setModelLabels(LABELS)
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//.setIsModelTensorFlow2(true)
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//.setIsModelQuantized(true)
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//.setModelInputSize(300)
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//.setModelAspectRatio(16.0 / 9.0)
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.build();
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// Create the vision portal by using a builder.
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VisionPortal.Builder builder = new VisionPortal.Builder();
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// Set the camera (webcam vs. built-in RC phone camera).
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if (USE_WEBCAM) {
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builder.setCamera(hardwareMap.get(WebcamName.class, "Webcam 1"));
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} else {
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builder.setCamera(BuiltinCameraDirection.BACK);
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}
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// Choose a camera resolution. Not all cameras support all resolutions.
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//builder.setCameraResolution(new Size(640, 480));
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// Enable the RC preview (LiveView). Set "false" to omit camera monitoring.
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//builder.enableCameraMonitoring(true);
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// Set the stream format; MJPEG uses less bandwidth than default YUY2.
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//builder.setStreamFormat(VisionPortal.StreamFormat.YUY2);
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// Choose whether or not LiveView stops if no processors are enabled.
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// If set "true", monitor shows solid orange screen if no processors enabled.
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// If set "false", monitor shows camera view without annotations.
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//builder.setAutoStopLiveView(false);
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// Set and enable the processor.
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builder.addProcessor(tfod);
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// Build the Vision Portal, using the above settings.
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visionPortal = builder.build();
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// Set confidence threshold for TFOD recognitions, at any time.
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//tfod.setMinResultConfidence(0.75f);
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// Disable or re-enable the TFOD processor at any time.
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//visionPortal.setProcessorEnabled(tfod, true);
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} // end method initTfod()
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/**
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* Add telemetry about TensorFlow Object Detection (TFOD) recognitions.
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*/
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private void telemetryTfod() {
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List<Recognition> currentRecognitions = tfod.getRecognitions();
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telemetry.addData("# Objects Detected", currentRecognitions.size());
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// Step through the list of recognitions and display info for each one.
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for (Recognition recognition : currentRecognitions) {
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double x = (recognition.getLeft() + recognition.getRight()) / 2 ;
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double y = (recognition.getTop() + recognition.getBottom()) / 2 ;
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telemetry.addData(""," ");
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telemetry.addData("Image", "%s (%.0f %% Conf.)", recognition.getLabel(), recognition.getConfidence() * 100);
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telemetry.addData("- Position", "%.0f / %.0f", x, y);
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telemetry.addData("- Size", "%.0f x %.0f", recognition.getWidth(), recognition.getHeight());
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} // end for() loop
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} // end method telemetryTfod()
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} // end class
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