mirror of
https://github.com/PhotonVision/photonvision
synced 2026-06-21 01:01:41 +00:00
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1 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
3a784c7252 |
@@ -11,16 +11,6 @@ const currentPipelineSettings = computed<ActivePipelineSettings>(
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() => useCameraSettingsStore().currentPipelineSettings
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);
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// TODO fix pv-range-slider so that store access doesn't need to be deferred
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const contourArea = computed<[number, number]>({
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get: () => Object.values(useCameraSettingsStore().currentPipelineSettings.contourArea) as [number, number],
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set: (v) => (useCameraSettingsStore().currentPipelineSettings.contourArea = v)
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});
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const contourRatio = computed<[number, number]>({
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get: () => Object.values(useCameraSettingsStore().currentPipelineSettings.contourRatio) as [number, number],
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set: (v) => (useCameraSettingsStore().currentPipelineSettings.contourRatio = v)
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});
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const interactiveCols = computed(() =>
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(getCurrentInstance()?.proxy.$vuetify.breakpoint.mdAndDown || false) &&
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(!useStateStore().sidebarFolded || useCameraSettingsStore().isDriverMode)
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@@ -42,42 +32,5 @@ const interactiveCols = computed(() =>
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:step="0.01"
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@input="(value) => useCameraSettingsStore().changeCurrentPipelineSetting({ confidence: value }, false)"
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/>
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<pv-range-slider
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v-model="contourArea"
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label="Area"
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:min="0"
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:max="100"
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:slider-cols="interactiveCols"
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:step="0.01"
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@input="(value) => useCameraSettingsStore().changeCurrentPipelineSetting({ contourArea: value }, false)"
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/>
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<pv-range-slider
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v-model="contourRatio"
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label="Ratio (W/H)"
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tooltip="Min and max ratio between the width and height of a contour's bounding rectangle"
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:min="0"
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:max="100"
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:slider-cols="interactiveCols"
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:step="0.01"
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@input="(value) => useCameraSettingsStore().changeCurrentPipelineSetting({ contourRatio: value }, false)"
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/>
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<pv-select
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v-model="useCameraSettingsStore().currentPipelineSettings.contourTargetOrientation"
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label="Target Orientation"
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tooltip="Used to determine how to calculate target landmarks, as well as aspect ratio"
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:items="['Portrait', 'Landscape']"
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:select-cols="interactiveCols"
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@input="
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(value) => useCameraSettingsStore().changeCurrentPipelineSetting({ contourTargetOrientation: value }, false)
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"
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/>
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<pv-select
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v-model="currentPipelineSettings.contourSortMode"
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label="Target Sort"
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tooltip="Chooses the sorting mode used to determine the 'best' targets to provide to user code"
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:select-cols="interactiveCols"
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:items="['Largest', 'Smallest', 'Highest', 'Lowest', 'Rightmost', 'Leftmost', 'Centermost']"
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@input="(value) => useCameraSettingsStore().changeCurrentPipelineSetting({ contourSortMode: value }, false)"
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/>
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</div>
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</template>
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@@ -47,16 +47,6 @@ public class Contour implements Releasable {
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this.mat = mat;
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}
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public Contour(Rect2d box) {
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// no easy way to convert a Rect2d to Mat, diy it. Order is tl tr br bl
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this.mat =
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new MatOfPoint(
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box.tl(),
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new Point(box.x + box.width, box.y),
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box.br(),
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new Point(box.x, box.y + box.height));
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}
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public MatOfPoint2f getMat2f() {
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if (mat2f == null) {
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mat2f = new MatOfPoint2f(mat.toArray());
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@@ -25,15 +25,15 @@ public enum ContourSortMode {
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Comparator.comparingDouble(PotentialTarget::getArea)
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.reversed()), // reversed so that zero index has the largest size
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Smallest(Largest.getComparator().reversed()),
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Highest(Comparator.comparingDouble(tgt -> tgt.getMinAreaRect().center.y)),
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Highest(Comparator.comparingDouble(rect -> rect.getMinAreaRect().center.y)),
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Lowest(Highest.getComparator().reversed()),
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Leftmost(Comparator.comparingDouble(tgt -> tgt.getMinAreaRect().center.x * -1)),
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Leftmost(Comparator.comparingDouble(target -> target.getMinAreaRect().center.x * -1)),
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Rightmost(Leftmost.getComparator().reversed()),
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Centermost(
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Comparator.comparingDouble(
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tgt ->
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(Math.pow(tgt.getMinAreaRect().center.y, 2)
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+ Math.pow(tgt.getMinAreaRect().center.x, 2))));
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rect ->
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(Math.pow(rect.getMinAreaRect().center.y, 2)
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+ Math.pow(rect.getMinAreaRect().center.x, 2))));
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private final Comparator<PotentialTarget> m_comparator;
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@@ -1,89 +0,0 @@
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/*
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* Copyright (C) Photon Vision.
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*
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* This program is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program. If not, see <https://www.gnu.org/licenses/>.
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*/
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package org.photonvision.vision.pipe.impl;
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import java.util.ArrayList;
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import java.util.List;
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import org.photonvision.common.util.numbers.DoubleCouple;
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import org.photonvision.vision.frame.FrameStaticProperties;
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import org.photonvision.vision.pipe.CVPipe;
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public class FilterObjectDetectionsPipe
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extends CVPipe<
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List<NeuralNetworkPipeResult>,
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List<NeuralNetworkPipeResult>,
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FilterObjectDetectionsPipe.FilterContoursParams> {
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List<NeuralNetworkPipeResult> m_filteredContours = new ArrayList<>();
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@Override
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protected List<NeuralNetworkPipeResult> process(List<NeuralNetworkPipeResult> in) {
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m_filteredContours.clear();
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for (var contour : in) {
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filterContour(contour);
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}
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return m_filteredContours;
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}
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private void filterContour(NeuralNetworkPipeResult contour) {
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var boc = contour.box;
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// Area filtering
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double areaPercentage = boc.area() / params.getFrameStaticProperties().imageArea * 100.0;
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double minAreaPercentage = params.getArea().getFirst();
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double maxAreaPercentage = params.getArea().getSecond();
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if (areaPercentage < minAreaPercentage || areaPercentage > maxAreaPercentage) return;
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// Aspect ratio filtering; much simpler since always axis-aligned
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double aspectRatio = boc.width / boc.height;
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if (aspectRatio < params.getRatio().getFirst() || aspectRatio > params.getRatio().getSecond())
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return;
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m_filteredContours.add(contour);
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}
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public static class FilterContoursParams {
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private final DoubleCouple m_area;
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private final DoubleCouple m_ratio;
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private final FrameStaticProperties m_frameStaticProperties;
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public final boolean isLandscape;
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public FilterContoursParams(
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DoubleCouple area,
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DoubleCouple ratio,
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FrameStaticProperties camProperties,
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boolean isLandscape) {
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this.m_area = area;
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this.m_ratio = ratio;
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this.m_frameStaticProperties = camProperties;
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this.isLandscape = isLandscape;
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}
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public DoubleCouple getArea() {
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return m_area;
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}
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public DoubleCouple getRatio() {
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return m_ratio;
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}
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public FrameStaticProperties getFrameStaticProperties() {
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return m_frameStaticProperties;
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}
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}
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}
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@@ -42,7 +42,6 @@ public class SortContoursPipe
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if (params.getSortMode() != ContourSortMode.Centermost) {
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m_sortedContours.sort(params.getSortMode().getComparator());
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} else {
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// we need knowledge of camera properties to calculate this distance -- do it ourselves
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m_sortedContours.sort(Comparator.comparingDouble(this::calcSquareCenterDistance));
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}
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}
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@@ -51,10 +50,10 @@ public class SortContoursPipe
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m_sortedContours.subList(0, Math.min(in.size(), params.getMaxTargets())));
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}
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private double calcSquareCenterDistance(PotentialTarget tgt) {
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private double calcSquareCenterDistance(PotentialTarget rect) {
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return Math.sqrt(
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Math.pow(params.getCamProperties().centerX - tgt.getMinAreaRect().center.x, 2)
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+ Math.pow(params.getCamProperties().centerY - tgt.getMinAreaRect().center.y, 2));
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Math.pow(params.getCamProperties().centerX - rect.getMinAreaRect().center.x, 2)
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+ Math.pow(params.getCamProperties().centerY - rect.getMinAreaRect().center.y, 2));
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}
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public static class SortContoursParams {
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@@ -26,8 +26,6 @@ import org.photonvision.vision.pipeline.result.CVPipelineResult;
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public abstract class CVPipeline<R extends CVPipelineResult, S extends CVPipelineSettings>
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implements Releasable {
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static final int MAX_MULTI_TARGET_RESULTS = 10;
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protected S settings;
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protected FrameStaticProperties frameStaticProperties;
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protected QuirkyCamera cameraQuirks;
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@@ -109,7 +109,7 @@ public class ColoredShapePipeline
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SortContoursPipe.SortContoursParams sortContoursParams =
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new SortContoursPipe.SortContoursParams(
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settings.contourSortMode,
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settings.outputShowMultipleTargets ? MAX_MULTI_TARGET_RESULTS : 1,
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settings.outputShowMultipleTargets ? 5 : 1,
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frameStaticProperties); // TODO don't hardcode?
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sortContoursPipe.setParams(sortContoursParams);
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@@ -17,26 +17,21 @@
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package org.photonvision.vision.pipeline;
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import java.util.ArrayList;
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import java.util.List;
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import java.util.stream.Collectors;
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import org.photonvision.vision.frame.Frame;
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import org.photonvision.vision.frame.FrameThresholdType;
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import org.photonvision.vision.opencv.DualOffsetValues;
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import org.photonvision.vision.pipe.CVPipe.CVPipeResult;
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import org.photonvision.vision.pipe.impl.*;
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import org.photonvision.vision.pipe.impl.RknnDetectionPipe.RknnDetectionPipeParams;
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import org.photonvision.vision.pipeline.result.CVPipelineResult;
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import org.photonvision.vision.target.PotentialTarget;
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import org.photonvision.vision.target.TargetOrientation;
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import org.photonvision.vision.target.TrackedTarget;
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import org.photonvision.vision.target.TrackedTarget.TargetCalculationParameters;
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public class ObjectDetectionPipeline
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extends CVPipeline<CVPipelineResult, ObjectDetectionPipelineSettings> {
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private final CalculateFPSPipe calculateFPSPipe = new CalculateFPSPipe();
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private final RknnDetectionPipe rknnPipe = new RknnDetectionPipe();
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private final SortContoursPipe sortContoursPipe = new SortContoursPipe();
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private final Collect2dTargetsPipe collect2dTargetsPipe = new Collect2dTargetsPipe();
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private final FilterObjectDetectionsPipe filterContoursPipe = new FilterObjectDetectionsPipe();
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private static final FrameThresholdType PROCESSING_TYPE = FrameThresholdType.NONE;
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@@ -57,38 +52,6 @@ public class ObjectDetectionPipeline
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params.confidence = settings.confidence;
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params.nms = settings.nms;
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rknnPipe.setParams(params);
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DualOffsetValues dualOffsetValues =
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new DualOffsetValues(
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settings.offsetDualPointA,
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settings.offsetDualPointAArea,
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settings.offsetDualPointB,
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settings.offsetDualPointBArea);
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SortContoursPipe.SortContoursParams sortContoursParams =
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new SortContoursPipe.SortContoursParams(
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settings.contourSortMode,
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settings.outputShowMultipleTargets ? MAX_MULTI_TARGET_RESULTS : 1,
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frameStaticProperties);
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sortContoursPipe.setParams(sortContoursParams);
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var filterContoursParams =
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new FilterObjectDetectionsPipe.FilterContoursParams(
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settings.contourArea,
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settings.contourRatio,
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frameStaticProperties,
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settings.contourTargetOrientation == TargetOrientation.Landscape);
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filterContoursPipe.setParams(filterContoursParams);
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Collect2dTargetsPipe.Collect2dTargetsParams collect2dTargetsParams =
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new Collect2dTargetsPipe.Collect2dTargetsParams(
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settings.offsetRobotOffsetMode,
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settings.offsetSinglePoint,
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dualOffsetValues,
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settings.contourTargetOffsetPointEdge,
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settings.contourTargetOrientation,
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frameStaticProperties);
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collect2dTargetsPipe.setParams(collect2dTargetsParams);
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}
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@Override
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@@ -97,35 +60,31 @@ public class ObjectDetectionPipeline
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// ***************** change based on backend ***********************
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CVPipeResult<List<NeuralNetworkPipeResult>> rknnResult = rknnPipe.run(input_frame.colorImage);
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sumPipeNanosElapsed += rknnResult.nanosElapsed;
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CVPipeResult<List<NeuralNetworkPipeResult>> ret = rknnPipe.run(input_frame.colorImage);
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sumPipeNanosElapsed += ret.nanosElapsed;
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List<NeuralNetworkPipeResult> targetList;
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targetList = ret.output;
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var names = rknnPipe.getClassNames();
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input_frame.colorImage.getMat().copyTo(input_frame.processedImage.getMat());
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// ***************** change based on backend ***********************
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var filterContoursResult = filterContoursPipe.run(rknnResult.output);
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sumPipeNanosElapsed += filterContoursResult.nanosElapsed;
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List<TrackedTarget> targets = new ArrayList<>();
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CVPipeResult<List<PotentialTarget>> sortContoursResult =
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sortContoursPipe.run(
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filterContoursResult.output.stream()
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.map(shape -> new PotentialTarget(shape))
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.collect(Collectors.toList()));
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sumPipeNanosElapsed += sortContoursResult.nanosElapsed;
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CVPipeResult<List<TrackedTarget>> collect2dTargetsResult =
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collect2dTargetsPipe.run(sortContoursResult.output);
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sumPipeNanosElapsed += collect2dTargetsResult.nanosElapsed;
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for (var t : targetList) {
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targets.add(
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new TrackedTarget(
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t,
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new TargetCalculationParameters(
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false, null, null, null, null, frameStaticProperties)));
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}
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var fpsResult = calculateFPSPipe.run(null);
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var fps = fpsResult.output;
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return new CVPipelineResult(
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sumPipeNanosElapsed, fps, collect2dTargetsResult.output, input_frame, names);
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return new CVPipelineResult(sumPipeNanosElapsed, fps, targets, input_frame, names);
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}
|
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@Override
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@@ -64,6 +64,29 @@ public class ReflectivePipeline extends CVPipeline<CVPipelineResult, ReflectiveP
|
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settings.offsetDualPointB,
|
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settings.offsetDualPointBArea);
|
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|
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// var rotateImageParams = new
|
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// RotateImagePipe.RotateImageParams(settings.inputImageRotationMode);
|
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// rotateImagePipe.setParams(rotateImageParams);
|
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|
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// if (cameraQuirks.hasQuirk(CameraQuirk.PiCam) && LibCameraJNI.isSupported()) {
|
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// LibCameraJNI.setThresholds(
|
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// settings.hsvHue.getFirst() / 180d,
|
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// settings.hsvSaturation.getFirst() / 255d,
|
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// settings.hsvValue.getFirst() / 255d,
|
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// settings.hsvHue.getSecond() / 180d,
|
||||
// settings.hsvSaturation.getSecond() / 255d,
|
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// settings.hsvValue.getSecond() / 255d);
|
||||
// // LibCameraJNI.setInvertHue(settings.hueInverted);
|
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// LibCameraJNI.setRotation(settings.inputImageRotationMode.value);
|
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// // LibCameraJNI.setShouldCopyColor(settings.inputShouldShow);
|
||||
// } else {
|
||||
// var hsvParams =
|
||||
// new HSVPipe.HSVParams(
|
||||
// settings.hsvHue, settings.hsvSaturation, settings.hsvValue,
|
||||
// settings.hueInverted);
|
||||
// hsvPipe.setParams(hsvParams);
|
||||
// }
|
||||
|
||||
var findContoursParams = new FindContoursPipe.FindContoursParams();
|
||||
findContoursPipe.setParams(findContoursParams);
|
||||
|
||||
@@ -90,7 +113,7 @@ public class ReflectivePipeline extends CVPipeline<CVPipelineResult, ReflectiveP
|
||||
var sortContoursParams =
|
||||
new SortContoursPipe.SortContoursParams(
|
||||
settings.contourSortMode,
|
||||
settings.outputShowMultipleTargets ? MAX_MULTI_TARGET_RESULTS : 1,
|
||||
settings.outputShowMultipleTargets ? 8 : 1, // TODO don't hardcode?
|
||||
frameStaticProperties);
|
||||
sortContoursPipe.setParams(sortContoursParams);
|
||||
|
||||
|
||||
@@ -98,7 +98,8 @@ public class VisionRunner {
|
||||
var pipelineResult = pipeline.run(frame, cameraQuirks);
|
||||
pipelineResultConsumer.accept(pipelineResult);
|
||||
} catch (Exception ex) {
|
||||
logger.error("Exception on loop " + loopCount, ex);
|
||||
logger.error("Exception on loop " + loopCount);
|
||||
ex.printStackTrace();
|
||||
}
|
||||
|
||||
loopCount++;
|
||||
|
||||
@@ -21,9 +21,7 @@ import java.util.List;
|
||||
import org.opencv.core.RotatedRect;
|
||||
import org.photonvision.vision.opencv.CVShape;
|
||||
import org.photonvision.vision.opencv.Contour;
|
||||
import org.photonvision.vision.opencv.ContourShape;
|
||||
import org.photonvision.vision.opencv.Releasable;
|
||||
import org.photonvision.vision.pipe.impl.NeuralNetworkPipeResult;
|
||||
|
||||
public class PotentialTarget implements Releasable {
|
||||
|
||||
@@ -31,10 +29,6 @@ public class PotentialTarget implements Releasable {
|
||||
public final List<Contour> m_subContours;
|
||||
public final CVShape shape;
|
||||
|
||||
// additional metadata about object detections we need to keep around
|
||||
public final double confidence;
|
||||
public final int clsId;
|
||||
|
||||
public PotentialTarget(Contour inputContour) {
|
||||
this(inputContour, List.of());
|
||||
}
|
||||
@@ -47,26 +41,12 @@ public class PotentialTarget implements Releasable {
|
||||
m_mainContour = inputContour;
|
||||
m_subContours = new ArrayList<>(subContours);
|
||||
this.shape = shape;
|
||||
this.clsId = -1;
|
||||
this.confidence = -1;
|
||||
}
|
||||
|
||||
public PotentialTarget(Contour inputContour, CVShape shape) {
|
||||
this(inputContour, List.of(), shape);
|
||||
}
|
||||
|
||||
public PotentialTarget(NeuralNetworkPipeResult det) {
|
||||
this.shape = new CVShape(new Contour(det.box), ContourShape.Quadrilateral);
|
||||
this.m_mainContour = this.shape.getContour();
|
||||
m_subContours = List.of();
|
||||
this.clsId = det.classIdx;
|
||||
this.confidence = det.confidence;
|
||||
}
|
||||
|
||||
public PotentialTarget(CVShape cvShape) {
|
||||
this(cvShape.getContour(), cvShape);
|
||||
}
|
||||
|
||||
public RotatedRect getMinAreaRect() {
|
||||
return m_mainContour.getMinAreaRect();
|
||||
}
|
||||
@@ -81,7 +61,7 @@ public class PotentialTarget implements Releasable {
|
||||
for (var sc : m_subContours) {
|
||||
sc.release();
|
||||
}
|
||||
if (!m_subContours.isEmpty()) m_subContours.clear();
|
||||
m_subContours.clear();
|
||||
if (shape != null) shape.release();
|
||||
}
|
||||
}
|
||||
|
||||
@@ -27,6 +27,7 @@ import org.opencv.core.Mat;
|
||||
import org.opencv.core.MatOfPoint;
|
||||
import org.opencv.core.MatOfPoint2f;
|
||||
import org.opencv.core.Point;
|
||||
import org.opencv.core.Rect2d;
|
||||
import org.opencv.core.RotatedRect;
|
||||
import org.photonvision.common.util.SerializationUtils;
|
||||
import org.photonvision.common.util.math.MathUtils;
|
||||
@@ -38,6 +39,7 @@ import org.photonvision.vision.opencv.CVShape;
|
||||
import org.photonvision.vision.opencv.Contour;
|
||||
import org.photonvision.vision.opencv.DualOffsetValues;
|
||||
import org.photonvision.vision.opencv.Releasable;
|
||||
import org.photonvision.vision.pipe.impl.NeuralNetworkPipeResult;
|
||||
|
||||
public class TrackedTarget implements Releasable {
|
||||
public final Contour m_mainContour;
|
||||
@@ -74,9 +76,6 @@ public class TrackedTarget implements Releasable {
|
||||
this.m_subContours = origTarget.m_subContours;
|
||||
this.m_shape = shape;
|
||||
calculateValues(params);
|
||||
|
||||
this.m_classId = origTarget.clsId;
|
||||
this.m_confidence = origTarget.confidence;
|
||||
}
|
||||
|
||||
public TrackedTarget(
|
||||
@@ -160,6 +159,47 @@ public class TrackedTarget implements Releasable {
|
||||
m_robotOffsetPoint = new Point();
|
||||
}
|
||||
|
||||
public TrackedTarget(
|
||||
Rect2d box, int class_id, double confidence, TargetCalculationParameters params) {
|
||||
m_targetOffsetPoint = new Point(box.x + box.width / 2.0, box.y + box.height / 2.0);
|
||||
m_robotOffsetPoint = new Point();
|
||||
|
||||
var yawPitch =
|
||||
TargetCalculations.calculateYawPitch(
|
||||
params.cameraCenterPoint.x,
|
||||
box.x + box.width / 2.0,
|
||||
params.horizontalFocalLength,
|
||||
params.cameraCenterPoint.y,
|
||||
box.y + box.height / 2.0,
|
||||
params.verticalFocalLength);
|
||||
m_yaw = yawPitch.getFirst();
|
||||
m_pitch = yawPitch.getSecond();
|
||||
|
||||
Point[] cornerPoints =
|
||||
new Point[] {
|
||||
// Box.x/y is the top-left corner, not the center
|
||||
new Point(box.x, box.y), // tl
|
||||
new Point(box.x + box.width, box.y), // tr
|
||||
new Point(box.x + box.width, box.y + box.height), // br
|
||||
new Point(box.x, box.y + box.height), // bl
|
||||
};
|
||||
|
||||
m_targetCorners = List.of(cornerPoints);
|
||||
MatOfPoint contourMat = new MatOfPoint(cornerPoints);
|
||||
m_approximateBoundingPolygon = new MatOfPoint2f(cornerPoints);
|
||||
|
||||
m_mainContour = new Contour(contourMat);
|
||||
m_area = m_mainContour.getArea() / params.imageArea * 100;
|
||||
|
||||
m_classId = class_id;
|
||||
m_confidence = confidence;
|
||||
}
|
||||
|
||||
public TrackedTarget(
|
||||
NeuralNetworkPipeResult t, TargetCalculationParameters targetCalculationParameters) {
|
||||
this(t.box, t.classIdx, t.confidence, targetCalculationParameters);
|
||||
}
|
||||
|
||||
/**
|
||||
* @return Returns the confidence of the detection ranging from 0 - 1.
|
||||
*/
|
||||
|
||||
@@ -435,7 +435,7 @@ class PhotonCameraSim {
|
||||
double minTargetAreaPercent;
|
||||
|
||||
frc::AprilTagFieldLayout tagLayout{
|
||||
frc::LoadAprilTagLayoutField(frc::AprilTagField::k2024Crescendo)};
|
||||
frc::LoadAprilTagLayoutField(frc::AprilTagField::k2023ChargedUp)};
|
||||
|
||||
cs::CvSource videoSimRaw;
|
||||
cv::Mat videoSimFrameRaw{};
|
||||
|
||||
@@ -138,6 +138,7 @@ public class Server {
|
||||
app.post("/api/calibration/importFromData", RequestHandler::onDataCalibrationImportRequest);
|
||||
|
||||
app.start(port);
|
||||
System.out.println("hi");
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
@@ -35,48 +35,48 @@
|
||||
|
||||
namespace constants {
|
||||
namespace Vision {
|
||||
inline constexpr std::string_view kCameraName{"YOUR CAMERA NAME"};
|
||||
inline const frc::Transform3d kRobotToCam{
|
||||
static constexpr std::string_view kCameraName{"YOUR CAMERA NAME"};
|
||||
static const frc::Transform3d kRobotToCam{
|
||||
frc::Translation3d{0.5_m, 0.0_m, 0.5_m},
|
||||
frc::Rotation3d{0_rad, 0_rad, 0_rad}};
|
||||
inline const frc::AprilTagFieldLayout kTagLayout{
|
||||
frc::LoadAprilTagLayoutField(frc::AprilTagField::k2024Crescendo)};
|
||||
static const frc::AprilTagFieldLayout kTagLayout{
|
||||
frc::LoadAprilTagLayoutField(frc::AprilTagField::k2023ChargedUp)};
|
||||
|
||||
inline const Eigen::Matrix<double, 3, 1> kSingleTagStdDevs{4, 4, 8};
|
||||
inline const Eigen::Matrix<double, 3, 1> kMultiTagStdDevs{0.5, 0.5, 1};
|
||||
static const Eigen::Matrix<double, 3, 1> kSingleTagStdDevs{4, 4, 8};
|
||||
static const Eigen::Matrix<double, 3, 1> kMultiTagStdDevs{0.5, 0.5, 1};
|
||||
} // namespace Vision
|
||||
namespace Swerve {
|
||||
|
||||
inline constexpr units::meter_t kTrackWidth{18.5_in};
|
||||
inline constexpr units::meter_t kTrackLength{18.5_in};
|
||||
inline constexpr units::meter_t kRobotWidth{25_in + 3.25_in * 2};
|
||||
inline constexpr units::meter_t kRobotLength{25_in + 3.25_in * 2};
|
||||
inline constexpr units::meters_per_second_t kMaxLinearSpeed{15.5_fps};
|
||||
inline constexpr units::radians_per_second_t kMaxAngularSpeed{720_deg_per_s};
|
||||
inline constexpr units::meter_t kWheelDiameter{4_in};
|
||||
inline constexpr units::meter_t kWheelCircumference{kWheelDiameter *
|
||||
static constexpr units::meter_t kTrackWidth{18.5_in};
|
||||
static constexpr units::meter_t kTrackLength{18.5_in};
|
||||
static constexpr units::meter_t kRobotWidth{25_in + 3.25_in * 2};
|
||||
static constexpr units::meter_t kRobotLength{25_in + 3.25_in * 2};
|
||||
static constexpr units::meters_per_second_t kMaxLinearSpeed{15.5_fps};
|
||||
static constexpr units::radians_per_second_t kMaxAngularSpeed{720_deg_per_s};
|
||||
static constexpr units::meter_t kWheelDiameter{4_in};
|
||||
static constexpr units::meter_t kWheelCircumference{kWheelDiameter *
|
||||
std::numbers::pi};
|
||||
|
||||
inline constexpr double kDriveGearRatio = 6.75;
|
||||
inline constexpr double kSteerGearRatio = 12.8;
|
||||
static constexpr double kDriveGearRatio = 6.75;
|
||||
static constexpr double kSteerGearRatio = 12.8;
|
||||
|
||||
inline constexpr units::meter_t kDriveDistPerPulse =
|
||||
static constexpr units::meter_t kDriveDistPerPulse =
|
||||
kWheelCircumference / 1024.0 / kDriveGearRatio;
|
||||
inline constexpr units::radian_t kSteerRadPerPulse =
|
||||
static constexpr units::radian_t kSteerRadPerPulse =
|
||||
units::radian_t{2 * std::numbers::pi} / 1024.0;
|
||||
|
||||
inline constexpr double kDriveKP = 1.0;
|
||||
inline constexpr double kDriveKI = 0.0;
|
||||
inline constexpr double kDriveKD = 0.0;
|
||||
static constexpr double kDriveKP = 1.0;
|
||||
static constexpr double kDriveKI = 0.0;
|
||||
static constexpr double kDriveKD = 0.0;
|
||||
|
||||
inline constexpr double kSteerKP = 20.0;
|
||||
inline constexpr double kSteerKI = 0.0;
|
||||
inline constexpr double kSteerKD = 0.25;
|
||||
static constexpr double kSteerKP = 20.0;
|
||||
static constexpr double kSteerKI = 0.0;
|
||||
static constexpr double kSteerKD = 0.25;
|
||||
|
||||
inline const frc::SimpleMotorFeedforward<units::meters> kDriveFF{
|
||||
static const frc::SimpleMotorFeedforward<units::meters> kDriveFF{
|
||||
0.25_V, 2.5_V / 1_mps, 0.3_V / 1_mps_sq};
|
||||
|
||||
inline const frc::SimpleMotorFeedforward<units::radians> kSteerFF{
|
||||
static const frc::SimpleMotorFeedforward<units::radians> kSteerFF{
|
||||
0.5_V, 0.25_V / 1_rad_per_s, 0.01_V / 1_rad_per_s_sq};
|
||||
|
||||
struct ModuleConstants {
|
||||
@@ -106,13 +106,13 @@ struct ModuleConstants {
|
||||
centerOffset(frc::Translation2d{xOffset, yOffset}) {}
|
||||
};
|
||||
|
||||
inline const ModuleConstants FL_CONSTANTS{
|
||||
static const ModuleConstants FL_CONSTANTS{
|
||||
1, 0, 0, 1, 1, 2, 3, 0, kTrackLength / 2, kTrackWidth / 2};
|
||||
inline const ModuleConstants FR_CONSTANTS{
|
||||
static const ModuleConstants FR_CONSTANTS{
|
||||
2, 2, 4, 5, 3, 6, 7, 0, kTrackLength / 2, -kTrackWidth / 2};
|
||||
inline const ModuleConstants BL_CONSTANTS{
|
||||
static const ModuleConstants BL_CONSTANTS{
|
||||
3, 4, 8, 9, 5, 10, 11, 0, -kTrackLength / 2, kTrackWidth / 2};
|
||||
inline const ModuleConstants BR_CONSTANTS{
|
||||
static const ModuleConstants BR_CONSTANTS{
|
||||
4, 6, 12, 13, 7, 14, 15, 0, -kTrackLength / 2, -kTrackWidth / 2};
|
||||
} // namespace Swerve
|
||||
} // namespace constants
|
||||
|
||||
@@ -61,7 +61,7 @@ class Vision {
|
||||
cameraSim = std::make_shared<photon::PhotonCameraSim>(camera.get(),
|
||||
*cameraProp.get());
|
||||
|
||||
visionSim->AddCamera(cameraSim.get(), constants::Vision::kRobotToCam);
|
||||
visionSim->AddCamera(cameraSim.get(), robotToCam);
|
||||
cameraSim->EnableDrawWireframe(true);
|
||||
}
|
||||
}
|
||||
@@ -138,10 +138,12 @@ class Vision {
|
||||
frc::Field2d& GetSimDebugField() { return visionSim->GetDebugField(); }
|
||||
|
||||
private:
|
||||
frc::Transform3d robotToCam{frc::Translation3d{0.5_m, 0.5_m, 0.5_m},
|
||||
frc::Rotation3d{}};
|
||||
photon::PhotonPoseEstimator photonEstimator{
|
||||
constants::Vision::kTagLayout,
|
||||
LoadAprilTagLayoutField(frc::AprilTagField::k2023ChargedUp),
|
||||
photon::PoseStrategy::MULTI_TAG_PNP_ON_COPROCESSOR,
|
||||
photon::PhotonCamera{"photonvision"}, constants::Vision::kRobotToCam};
|
||||
photon::PhotonCamera{"photonvision"}, robotToCam};
|
||||
std::shared_ptr<photon::PhotonCamera> camera{photonEstimator.GetCamera()};
|
||||
std::unique_ptr<photon::VisionSystemSim> visionSim;
|
||||
std::unique_ptr<photon::SimCameraProperties> cameraProp;
|
||||
|
||||
Reference in New Issue
Block a user