187 lines
8.5 KiB
Java
187 lines
8.5 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 java.util.List;
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import org.firstinspires.ftc.robotcore.external.ClassFactory;
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import org.firstinspires.ftc.robotcore.external.navigation.VuforiaLocalizer;
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import org.firstinspires.ftc.robotcore.external.navigation.VuforiaLocalizer.CameraDirection;
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import org.firstinspires.ftc.robotcore.external.tfod.TFObjectDetector;
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import org.firstinspires.ftc.robotcore.external.tfod.Recognition;
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/**
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* This 2020-2021 OpMode illustrates the basics of using the TensorFlow Object Detection API to
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* determine the position of the Freight Frenzy game elements.
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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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* IMPORTANT: In order to use this OpMode, you need to obtain your own Vuforia license key as
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* is explained below.
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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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/* Note: This sample uses the all-objects Tensor Flow model (FreightFrenzy_BCDM.tflite), which contains
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* the following 4 detectable objects
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* 0: Ball,
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* 1: Cube,
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* 2: Duck,
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* 3: Marker (duck location tape marker)
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*
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* Two additional model assets are available which only contain a subset of the objects:
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* FreightFrenzy_BC.tflite 0: Ball, 1: Cube
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* FreightFrenzy_DM.tflite 0: Duck, 1: Marker
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*/
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private static final String TFOD_MODEL_ASSET = "FreightFrenzy_BCDM.tflite";
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private static final String[] LABELS = {
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"Ball",
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"Cube",
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"Duck",
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"Marker"
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};
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/*
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* IMPORTANT: You need to obtain your own license key to use Vuforia. The string below with which
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* 'parameters.vuforiaLicenseKey' is initialized is for illustration only, and will not function.
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* A Vuforia 'Development' license key, can be obtained free of charge from the Vuforia developer
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* web site at https://developer.vuforia.com/license-manager.
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*
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* Vuforia license keys are always 380 characters long, and look as if they contain mostly
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* random data. As an example, here is a example of a fragment of a valid key:
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* ... yIgIzTqZ4mWjk9wd3cZO9T1axEqzuhxoGlfOOI2dRzKS4T0hQ8kT ...
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* Once you've obtained a license key, copy the string from the Vuforia web site
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* and paste it in to your code on the next line, between the double quotes.
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*/
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private static final String VUFORIA_KEY =
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" -- YOUR NEW VUFORIA KEY GOES HERE --- ";
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/**
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* {@link #vuforia} is the variable we will use to store our instance of the Vuforia
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* localization engine.
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*/
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private VuforiaLocalizer vuforia;
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/**
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* {@link #tfod} is the variable we will use to store our instance of the TensorFlow Object
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* Detection engine.
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*/
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private TFObjectDetector tfod;
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@Override
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public void runOpMode() {
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// The TFObjectDetector uses the camera frames from the VuforiaLocalizer, so we create that
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// first.
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initVuforia();
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initTfod();
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/**
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* Activate TensorFlow Object Detection before we wait for the start command.
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* Do it here so that the Camera Stream window will have the TensorFlow annotations visible.
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**/
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if (tfod != null) {
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tfod.activate();
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// The TensorFlow software will scale the input images from the camera to a lower resolution.
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// This can result in lower detection accuracy at longer distances (> 55cm or 22").
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// If your target is at distance greater than 50 cm (20") you can adjust the magnification value
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// to artificially zoom in to the center of image. For best results, the "aspectRatio" argument
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// should be set to the value of the images used to create the TensorFlow Object Detection model
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// (typically 16/9).
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tfod.setZoom(2.5, 16.0/9.0);
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}
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/** Wait for the game to begin */
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telemetry.addData(">", "Press Play to start op mode");
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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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if (tfod != null) {
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// getUpdatedRecognitions() will return null if no new information is available since
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// the last time that call was made.
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List<Recognition> updatedRecognitions = tfod.getUpdatedRecognitions();
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if (updatedRecognitions != null) {
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telemetry.addData("# Object Detected", updatedRecognitions.size());
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// step through the list of recognitions and display boundary info.
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int i = 0;
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for (Recognition recognition : updatedRecognitions) {
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telemetry.addData(String.format("label (%d)", i), recognition.getLabel());
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telemetry.addData(String.format(" left,top (%d)", i), "%.03f , %.03f",
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recognition.getLeft(), recognition.getTop());
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telemetry.addData(String.format(" right,bottom (%d)", i), "%.03f , %.03f",
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recognition.getRight(), recognition.getBottom());
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i++;
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}
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telemetry.update();
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}
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}
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}
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}
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}
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/**
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* Initialize the Vuforia localization engine.
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*/
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private void initVuforia() {
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/*
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* Configure Vuforia by creating a Parameter object, and passing it to the Vuforia engine.
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*/
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VuforiaLocalizer.Parameters parameters = new VuforiaLocalizer.Parameters();
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parameters.vuforiaLicenseKey = VUFORIA_KEY;
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parameters.cameraDirection = CameraDirection.BACK;
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// Instantiate the Vuforia engine
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vuforia = ClassFactory.getInstance().createVuforia(parameters);
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// Loading trackables is not necessary for the TensorFlow Object Detection engine.
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}
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/**
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* Initialize the TensorFlow Object Detection engine.
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*/
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private void initTfod() {
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int tfodMonitorViewId = hardwareMap.appContext.getResources().getIdentifier(
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"tfodMonitorViewId", "id", hardwareMap.appContext.getPackageName());
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TFObjectDetector.Parameters tfodParameters = new TFObjectDetector.Parameters(tfodMonitorViewId);
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tfodParameters.minResultConfidence = 0.8f;
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tfodParameters.isModelTensorFlow2 = true;
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tfodParameters.inputSize = 320;
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tfod = ClassFactory.getInstance().createTFObjectDetector(tfodParameters, vuforia);
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tfod.loadModelFromAsset(TFOD_MODEL_ASSET, LABELS);
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}
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}
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