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Merge pull request #6 from smartbank-inc/develop
Release 2021-10-21 01:05:09 +0900
2 parents b2ab5c1 + a1535e6 commit 9accbf3

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‎.git-pr-release‎

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[pr-release]
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template = ./.git-pr-release-template
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[pr-release "branch"]
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production = main
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staging = develop

‎.git-pr-release-template‎

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Release <%= Time.now.getlocal("+09:00") %>
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## Changes
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<% pull_requests.each do |pr| -%>
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<%= pr.to_checklist_item %>
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<% end -%>

‎.github/workflows/create-release-pr.yml‎

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name: Create Release Pull Request
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on: workflow_dispatch
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jobs:
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job:
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runs-on: ubuntu-18.04
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steps:
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- uses: actions/checkout@v2.3.4
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with:
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fetch-depth: 0
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- name: Set up Ruby
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uses: actions/setup-ruby@v1.1.2
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with:
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ruby-version: 2.7.x
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- name: Create a release pull request
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env:
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GIT_PR_RELEASE_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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run: |
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gem install -N git-pr-release
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git-pr-release

‎build.gradle‎

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@@ -3,8 +3,8 @@ buildscript {
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compile_sdk_version = 31
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min_sdk_version = 26
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target_sdk_version = 31
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version_name = "0.1.0"
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version_code = 1
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version_name = "0.2.0"
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version_code = 2
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compose_version = '1.1.0-alpha06'
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junit_version = '4.13.2'
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}
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}
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dependencies {
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classpath 'com.android.tools.build:gradle:7.0.3'
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classpath 'org.jetbrains.kotlin:kotlin-gradle-plugin:1.5.31'
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classpath 'com.github.kezong:fat-aar:1.3.6'
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classpath 'org.jetbrains.dokka:dokka-gradle-plugin:1.5.30'
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classpath 'org.jetbrains.kotlin:kotlin-gradle-plugin:1.5.31'
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}
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}
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‎library/build.gradle‎

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id 'com.kezong.fat-aar'
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id 'kotlin-android'
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id 'maven-publish'
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id 'org.jetbrains.dokka'
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}
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group = 'com.github.smartbank-inc'
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}
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afterEvaluate {
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task androidSourcesJar(type: Jar) {
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archiveClassifier.convention('sources')
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archiveClassifier.set('sources')
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from android.sourceSets.main.java.source
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}
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task androidJavadocsJar(type: Jar, dependsOn: dokkaJavadoc) {
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archiveClassifier.convention('javadoc')
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archiveClassifier.set('javadoc')
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from dokkaJavadoc.outputDirectory
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}
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publishing {
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publications {
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release(MavenPublication) {
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from components.release
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groupId = 'com.github.smartbank-inc'
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artifactId = 'android-rectangle-detector'
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version = version_name
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artifact androidSourcesJar
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artifact androidJavadocsJar
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}
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}
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}

‎library/src/androidTest/java/jp/co/smartbank/rectangledetector/RectangleDetectorImplTest.kt‎

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@@ -13,7 +13,7 @@ import org.junit.runner.RunWith
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@RunWith(AndroidJUnit4::class)
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class RectangleDetectorImplTest : TestCase() {
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private val detector = RectangleDetectorImpl()
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private val detector = RectangleDetectorImpl(DetectionAccuracy.Passive)
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private val resources = InstrumentationRegistry.getInstrumentation().targetContext.resources
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@Test

‎library/src/main/java/jp/co/smartbank/rectangledetector/DetectionAccuracy.kt‎

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package jp.co.smartbank.rectangledetector
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import jp.co.smartbank.rectangledetector.strategy.AdaptiveThresholdStrategy
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import jp.co.smartbank.rectangledetector.strategy.CannyAlgorithmStrategy
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import jp.co.smartbank.rectangledetector.strategy.CompositeContourDetectionStrategy
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import jp.co.smartbank.rectangledetector.strategy.ContourDetectionStrategy
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/**
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* Mode of accuracy of rectangle detection in [RectangleDetector].
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*/
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enum class DetectionAccuracy {
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/**
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* [DetectionAccuracy] that prioritizes the number of detections over the accuracy of the results.
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*/
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Aggressive,
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/**
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* [DetectionAccuracy] that prioritizes the accuracy of the results.
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*/
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Passive;
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internal fun buildContourStrategy(): ContourDetectionStrategy = when (this) {
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Aggressive -> CompositeContourDetectionStrategy(
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listOf(
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AdaptiveThresholdStrategy(),
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CannyAlgorithmStrategy()
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)
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)
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Passive -> CannyAlgorithmStrategy()
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}
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}

‎library/src/main/java/jp/co/smartbank/rectangledetector/RectangleDetector.kt‎

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@@ -10,8 +10,8 @@ interface RectangleDetector {
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fun detectRectangles(bitmap: Bitmap): DetectionResult
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companion object {
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fun getInstance(): RectangleDetector {
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return RectangleDetectorImpl()
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fun getInstance(detectionAccuracy: DetectionAccuracy = DetectionAccuracy.Passive): RectangleDetector {
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return RectangleDetectorImpl(detectionAccuracy)
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}
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}
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}

‎library/src/main/java/jp/co/smartbank/rectangledetector/RectangleDetectorImpl.kt‎

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@@ -10,13 +10,12 @@ import kotlin.math.max
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import kotlin.math.min
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import kotlin.math.roundToInt
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import org.opencv.android.Utils
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import org.opencv.core.CvType
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import org.opencv.core.Mat
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import org.opencv.core.MatOfPoint
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import org.opencv.core.MatOfPoint2f
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import org.opencv.imgproc.Imgproc
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internal class RectangleDetectorImpl : RectangleDetector {
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internal class RectangleDetectorImpl(detectionAccuracy: DetectionAccuracy) : RectangleDetector {
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private val strategy = detectionAccuracy.buildContourStrategy()
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init {
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System.loadLibrary("opencv_java4")
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}
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val scaledBitmap = bitmap.scaled(scaleRatio, true)
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val mat = Mat().also { Utils.bitmapToMat(scaledBitmap, it) }
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val edgeMat = markEdgesWithCannyAlgorithm(mat)
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val edgeClosedMat = closeEdges(edgeMat)
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val contours = detectContours(edgeClosedMat)
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val contours = strategy.detectContours(mat)
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// Combine Rectangles approximated to other into one.
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val rectangles = contourToRectangles(contours).map { it.scaled(1 / scaleRatio) }
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val distanceTolerance = max(scaledBitmap.width, scaledBitmap.height) / 50f
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val reducedRectangles = rectangles.fold(emptyList<Rectangle>()) { result, rectangle ->
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val approximatedRectangle = result.firstOrNull { it.isApproximated(rectangle, 8f) }
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val approximatedRectangle = result.firstOrNull { it.isApproximated(rectangle, distanceTolerance) }
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if (approximatedRectangle != null) {
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result - approximatedRectangle + rectangle.average(approximatedRectangle)
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} else {
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)
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}
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private fun markEdgesWithCannyAlgorithm(mat: Mat): Mat {
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val result = Mat()
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Imgproc.blur(mat, result, org.opencv.core.Size(5.0, 5.0))
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Imgproc.Canny(mat, result, 250.0, 100.0, 3, true)
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return result
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}
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private fun closeEdges(mat: Mat): Mat {
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val result = Mat()
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Imgproc.morphologyEx(
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mat, result, Imgproc.MORPH_CLOSE,
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Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, org.opencv.core.Size(5.0, 5.0))
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)
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return result
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}
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private fun detectContours(mat: Mat): List<MatOfPoint> {
68-
val contours = arrayListOf<MatOfPoint>()
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val hierarchy = Mat.zeros(org.opencv.core.Size(5.0, 5.0), CvType.CV_8UC1)
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Imgproc.findContours(
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mat,
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contours,
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hierarchy,
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Imgproc.RETR_LIST,
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Imgproc.CHAIN_APPROX_NONE
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)
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return contours.mapNotNull {
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// Ignore extremely small size rectangles.
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if (Imgproc.contourArea(it) < mat.size().area() / 100) {
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return@mapNotNull null
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}
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84-
val pointMat = MatOfPoint2f(*it.toArray())
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val approx = MatOfPoint2f()
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val approx2 = MatOfPoint()
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val arcLength = Imgproc.arcLength(pointMat, true)
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Imgproc.approxPolyDP(pointMat, approx, 0.03 * arcLength, true)
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approx.convertTo(approx2, CvType.CV_32S)
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if (approx2.size().area() == 4.0) {
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approx2
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} else {
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null
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}
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}
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}
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private fun contourToRectangles(contour: List<MatOfPoint>): List<Rectangle> = contour.map {
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val points = it.toList().map { point ->
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Point(point.x.roundToInt(), point.y.roundToInt())

‎library/src/main/java/jp/co/smartbank/rectangledetector/strategy/AdaptiveThresholdStrategy.kt‎

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package jp.co.smartbank.rectangledetector.strategy
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import org.opencv.core.Mat
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import org.opencv.core.MatOfPoint
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import org.opencv.imgproc.Imgproc
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/**
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* An implementation of [ContourDetectionStrategy] thresholding images.
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*/
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internal class AdaptiveThresholdStrategy : ContourDetectionStrategy() {
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override fun detectContours(originalImageMat: Mat): List<MatOfPoint> {
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val grayScaleMat = convertToGrayScale(originalImageMat)
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val thresholdingMat = thresholdImage(grayScaleMat)
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val noiseReducedMat = reduceNoises(thresholdingMat)
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return findContours(noiseReducedMat, allowanceRatioToArcLength = 0.02)
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}
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private fun convertToGrayScale(mat: Mat): Mat {
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val result = Mat()
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Imgproc.cvtColor(mat, result, Imgproc.COLOR_BGR2GRAY)
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return result
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}
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private fun thresholdImage(mat: Mat): Mat {
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val result = Mat()
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Imgproc.adaptiveThreshold(
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mat, result, 255.0, Imgproc.ADAPTIVE_THRESH_MEAN_C,
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Imgproc.THRESH_BINARY, 21, 3.0
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)
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return result
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}
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private fun reduceNoises(mat: Mat): Mat {
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val result = Mat()
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Imgproc.medianBlur(mat, result, 9)
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return result
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}
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}

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