{"parentUuid":null,"isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":"/home/lucas/Android-app/ClearCam 저장소의 현재 미커밋 변경사항을 리뷰해 주세요(읽기 전용, 수정 금지). Android 문서 스캐너 앱입니다.\n\n변경 의도(사용자 버그: 자동 스캔 시 문서 오른쪽 가장자리 내용이 잘림 + 4코너 자동검출 부정확):\n1. `EdgeSnapper.kt` 재작성 — 기존 \"법선 스캔에서 최강 그래디언트\" 선택이 종이 안쪽 표 테두리(더 강한 엣지)에 끌려가 사각형이 종이 안으로 파고드는 문제. 새 규칙: 방향성 그래디언트(법선과 내적, \"안쪽으로 밝아지는\" 전이 = 배경→종이)가 임계 이상인 후보 중 **가장 바깥쪽**을 선택, 없으면 기존 최강 크기로 폴백. 직선 적합에 이상치 제거(잔차 > max(2×중앙값, 2px) 트림 후 1회 재적합) 추가. 이 알고리즘은 python+OpenCV 시뮬레이션으로 실증 검증됨(어두운 배경/밝은 회색/노이즈/그림자 시나리오에서 코너 오차 19~91px → ≤3.4px).\n2. `CornerCandidates.kt` — AI 검출 결과에 무조건 적용하던 1.5% 중심 수축(inset) 제거(내용이 종이 끝까지 찬 양식에서 글자 잘림 원인, 문서폭 2094px 기준 오른쪽 ~16px 손실). 이로써 미사용이 된 `inset()` 함수 삭제.\n3. 단위 테스트 추가: `EdgeSnapperTest`(6개 — 바깥 우선 선택, 폴백, 신호 없음 거부, 이상치 트림, 교점 계산, 평행선 null), `PerspectiveTransformerTest.fullSelectionIsLossless`.\n4. versionCode 87→88, versionName 1.086→1.087.\n\n검토 관점:\n- EdgeSnapper.fitEdge의 수학적 정확성: 법선 방향(TL,TR,BR,BL 시계방향에서 +n=안쪽), 바깥→안 스캔 순서(-band..band), 방향성 내적 부호, 이상치 트림 로직, fitLine PCA, 잔차 게이트\n- refine()의 Mat 누수(release 경로), 예외 안전성\n- 회귀 위험: 기존 동작 대비 폴백 경로가 보존되는지(방향성 후보가 없을 때 기존과 동일하게 최강 크기 사용), CLAMP_FRAC 폴백, openCvReady 가드\n- inset 제거의 부작용: 호출처(EditorActivity 자동검출, ScanPipeline 배치)에서 문제 없는지\n- 테스트가 의도를 실제로 검증하는지(빌드+테스트는 이미 exit=0 통과)\n- 파일 길이 300줄 제한(EdgeSnapper.kt 줄 수 확인)\n\n발견 문제를 심각도(blocker/major/minor)와 파일:라인으로 보고하고, 없으면 \"통과\"를 명시해 주세요."},"uuid":"2ed5cb46-c2ed-4ba5-9166-2f3800f338a6","timestamp":"2026-06-11T14:31:07.849Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"2ed5cb46-c2ed-4ba5-9166-2f3800f338a6","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"type":"text","text":"review\nreview\ntrue"},{"type":"text","text":"\n You are an expert code reviewer. Follow these steps:\n\n 1. If no PR number is provided in the args, run `gh pr list` to show open PRs\n 2. If a PR number is provided, run `gh pr view --json title,body,author,baseRefName,headRefName,state,additions,deletions,changedFiles,labels` to get PR details\n 3. Run `gh pr diff ` to get the diff\n 4. Analyze the changes and provide a thorough code review that includes:\n - Overview of what the PR does\n - Analysis of code quality and style\n - Specific suggestions for improvements\n - Any potential issues or risks\n\n Keep your review concise but thorough. Focus on:\n - Code correctness\n - Following project conventions\n - Performance implications\n - Test coverage\n - Security considerations\n\n Format your review with clear sections and bullet points.\n\n PR number: \n "}]},"isMeta":true,"uuid":"0a1cfd27-1e93-4b39-b56f-32c8c4465d17","timestamp":"2026-06-11T14:31:07.862Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"0a1cfd27-1e93-4b39-b56f-32c8c4465d17","isSidechain":true,"agentId":"ad154ea4230933d32","message":{"model":"claude-sonnet-4-6","id":"msg_01YCfksJh5V6Wc5p8jvraPTC","type":"message","role":"assistant","content":[{"type":"text","text":"I'll review the uncommitted changes in the repository systematically. Let me start by examining the changed files."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":22535,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":22535,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CbwdiUUX1DyrCxTqTrDrK","attributionAgent":"reviewer","type":"assistant","uuid":"87b780da-3910-4f62-842e-83572c538e7d","timestamp":"2026-06-11T14:31:10.754Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
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{"parentUuid":"32915a29-6889-43dd-ac28-5ca729c4da0d","isSidechain":true,"agentId":"ad154ea4230933d32","message":{"model":"claude-sonnet-4-6","id":"msg_01YCfksJh5V6Wc5p8jvraPTC","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01G4M9gahgWm3BxHuAPMAxkN","name":"Bash","input":{"command":"git status","description":"Show git status"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":22535,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":22535,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CbwdiUUX1DyrCxTqTrDrK","attributionAgent":"reviewer","type":"assistant","uuid":"ffbf7907-52cf-4171-bdfa-4f611c8fc808","timestamp":"2026-06-11T14:31:11.681Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"32915a29-6889-43dd-ac28-5ca729c4da0d","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01PwsbM8P3w5CTwffbjBHHNf","type":"tool_result","content":" app/build.gradle.kts | 4 +-\n .../cc/lucasai/clearcam/editor/CornerCandidates.kt | 24 ++-----\n .../java/cc/lucasai/clearcam/editor/EdgeSnapper.kt | 78 +++++++++++++++++-----\n .../clearcam/editor/PerspectiveTransformerTest.kt | 10 +++\n 4 files changed, 78 insertions(+), 38 deletions(-)","is_error":false}]},"uuid":"3dc2b2c9-d47b-46b5-afdb-c66b57f7c65b","timestamp":"2026-06-11T14:31:11.860Z","sourceToolAssistantUUID":"32915a29-6889-43dd-ac28-5ca729c4da0d","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"ffbf7907-52cf-4171-bdfa-4f611c8fc808","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01G4M9gahgWm3BxHuAPMAxkN","type":"tool_result","content":"On branch main\nYour branch is ahead of 'origin/main' by 1 commit.\n (use \"git push\" to publish your local commits)\n\nChanges not staged for commit:\n (use \"git add ...\" to update what will be committed)\n (use \"git restore ...\" to discard changes in working directory)\n\tmodified: app/build.gradle.kts\n\tmodified: app/src/main/java/cc/lucasai/clearcam/editor/CornerCandidates.kt\n\tmodified: app/src/main/java/cc/lucasai/clearcam/editor/EdgeSnapper.kt\n\tmodified: app/src/test/java/cc/lucasai/clearcam/editor/PerspectiveTransformerTest.kt\n\nUntracked files:\n (use \"git add ...\" to include in what will be committed)\n\tapp/src/test/java/cc/lucasai/clearcam/editor/EdgeSnapperTest.kt\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")","is_error":false}]},"uuid":"55f93132-0dfc-486a-88ca-8b4a6eb7bf72","timestamp":"2026-06-11T14:31:11.895Z","sourceToolAssistantUUID":"ffbf7907-52cf-4171-bdfa-4f611c8fc808","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
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{"parentUuid":"9d723fea-3399-4791-b2ca-49feae85312a","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01JJqBu9QMBE7zn3Mvo3Zs2W","type":"tool_result","content":"diff --git a/app/src/main/java/cc/lucasai/clearcam/editor/EdgeSnapper.kt b/app/src/main/java/cc/lucasai/clearcam/editor/EdgeSnapper.kt\nindex ca95e78..1cb5ae1 100644\n--- a/app/src/main/java/cc/lucasai/clearcam/editor/EdgeSnapper.kt\n+++ b/app/src/main/java/cc/lucasai/clearcam/editor/EdgeSnapper.kt\n@@ -1,5 +1,7 @@\n // ML이 준 대략적 4코너를, 그 근처에서 찾은 실제 종이 경계선에 스냅해 정밀하게 보정한다.\n-// 변마다 법선 방향으로 최강 그래디언트(경계)를 모아 직선 적합 → 인접 직선 교점 = 정밀 코너.\n+// 사람이 종이 실루엣을 보듯 \"안쪽으로 밝아지는(배경→종이) 전이 중 가장 바깥쪽\"을 경계로 삼아,\n+// 종이 안쪽의 더 강한 표 테두리·텍스트나 종이 밖 그림자 경계에 끌려가지 않는다.\n+// 변마다 경계점을 모아 이상치 제거 직선 적합 → 인접 직선 교점 = 정밀 코너.\n // 경계가 약하거나 ML에서 너무 멀면 ML 코너로 폴백(모호한 겹친 문서에서 안전).\n package cc.lucasai.clearcam.editor\n \n@@ -34,8 +36,13 @@ object EdgeSnapper {\n Imgproc.Sobel(gray, gy, CvType.CV_32F, 0, 1, 3)\n Core.magnitude(gx, gy, grad)\n Imgproc.GaussianBlur(grad, grad, Size(5.0, 5.0), 0.0)\n+ // 방향성 판단용 부드러운 그래디언트(법선과 내적해 \"안쪽으로 밝아짐\"을 검사).\n+ Imgproc.GaussianBlur(gx, gx, Size(5.0, 5.0), 0.0)\n+ Imgproc.GaussianBlur(gy, gy, Size(5.0, 5.0), 0.0)\n val w = gray.cols(); val h = gray.rows()\n val g = FloatArray(w * h); grad.get(0, 0, g)\n+ val dgx = FloatArray(w * h); gx.get(0, 0, dgx)\n+ val dgy = FloatArray(w * h); gy.get(0, 0, dgy)\n val gmean = Core.mean(grad).`val`[0]\n val band = maxOf(6, (minOf(w, h) * BAND_FRAC).toInt())\n val thr = gmean * 3.0\n@@ -44,7 +51,7 @@ object EdgeSnapper {\n val edges = arrayOf(intArrayOf(0, 1), intArrayOf(1, 2), intArrayOf(2, 3), intArrayOf(3, 0))\n val lines = arrayOfNulls(4)\n for (e in 0 until 4) {\n- lines[e] = fitEdge(corners, edges[e][0], edges[e][1], g, w, h, band, thr)\n+ lines[e] = fitEdge(corners, edges[e][0], edges[e][1], g, dgx, dgy, w, h, band, thr)\n }\n // 코너 i = (이전 변 ∩ 다음 변).\n val meet = arrayOf(intArrayOf(3, 0), intArrayOf(0, 1), intArrayOf(1, 2), intArrayOf(2, 3))\n@@ -66,9 +73,13 @@ object EdgeSnapper {\n }\n }\n \n- // 한 변을 따라 법선 방향 최강 경계점을 모아 총최소제곱 직선을 적합한다.\n- private fun fitEdge(\n- c: FloatArray, ia: Int, ib: Int, g: FloatArray, w: Int, h: Int, band: Int, thr: Double,\n+ // 한 변을 따라 법선 스캔으로 경계점을 모아 이상치 제거 총최소제곱 직선을 적합한다.\n+ // 각 스캔(바깥→안)에서 \"안쪽으로 밝아지는\" 전이(d≥thr) 중 가장 바깥 점을 우선하고,\n+ // 없으면 최강 그래디언트 크기(>thr)로 폴백한다. TL,TR,BR,BL 시계방향이면 +법선=안쪽.\n+ internal fun fitEdge(\n+ c: FloatArray, ia: Int, ib: Int,\n+ g: FloatArray, dgx: FloatArray, dgy: FloatArray,\n+ w: Int, h: Int, band: Int, thr: Double,\n ): DoubleArray? {\n val ax = c[ia * 2].toDouble(); val ay = c[ia * 2 + 1].toDouble()\n val bx = c[ib * 2].toDouble(); val by = c[ib * 2 + 1].toDouble()\n@@ -80,20 +91,46 @@ object EdgeSnapper {\n for (i in 0 until SAMPLES) {\n val t = 0.12 + (0.88 - 0.12) * i / (SAMPLES - 1)\n val ox = ax + evx * (t * len); val oy = ay + evy * (t * len)\n- var bestV = thr; var bxp = 0.0; var byp = 0.0; var found = false\n- for (s in -band..band) {\n+ var pickX = 0.0; var pickY = 0.0; var picked = false\n+ var bestV = thr; var fbX = 0.0; var fbY = 0.0; var fallback = false\n+ for (s in -band..band) { // 바깥(-)→안(+) 순서로 스캔\n val qx = ox + nx * s; val qy = oy + ny * s\n val xi = Math.round(qx).toInt(); val yi = Math.round(qy).toInt()\n if (xi in 0 until w && yi in 0 until h) {\n- val v = g[yi * w + xi].toDouble()\n- if (v > bestV) { bestV = v; bxp = qx; byp = qy; found = true }\n+ val idx = yi * w + xi\n+ if (!picked) {\n+ val d = dgx[idx] * nx + dgy[idx] * ny // 안쪽으로 밝아지면 양수\n+ if (d >= thr) { pickX = qx; pickY = qy; picked = true }\n+ }\n+ val v = g[idx].toDouble()\n+ if (v > bestV) { bestV = v; fbX = qx; fbY = qy; fallback = true }\n }\n }\n- if (found) { px.add(bxp); py.add(byp) }\n+ if (picked) { px.add(pickX); py.add(pickY) }\n+ else if (fallback) { px.add(fbX); py.add(fbY) }\n }\n if (px.size < (SAMPLES * 0.6).toInt()) return null\n- // 총최소제곱: 무게중심 + 주성분 방향\n+ var fit = fitLine(px, py) ?: return null\n+ // 이상치 제거 후 1회 재적합: 잔차가 중앙값의 2배(최소 2px) 넘는 점을 버린다.\n+ val res = residuals(px, py, fit)\n+ val med = median(res)\n+ val cut = maxOf(2.0 * med, 2.0)\n+ val kx = ArrayList(); val ky = ArrayList()\n+ for (k in px.indices) if (res[k] <= cut) { kx.add(px[k]); ky.add(py[k]) }\n+ if (kx.size >= maxOf(4, px.size / 2)) {\n+ fit = fitLine(kx, ky) ?: fit\n+ val res2 = residuals(kx, ky, fit)\n+ if (res2.average() > band * 0.5) return null\n+ return fit\n+ }\n+ if (res.average() > band * 0.5) return null\n+ return fit\n+ }\n+\n+ // 총최소제곱(무게중심 + 주성분 방향) 직선 [mx,my,dx,dy].\n+ private fun fitLine(px: List, py: List): DoubleArray? {\n val n = px.size\n+ if (n < 2) return null\n var mx = 0.0; var my = 0.0\n for (k in 0 until n) { mx += px[k]; my += py[k] }\n mx /= n; my /= n\n@@ -103,16 +140,21 @@ object EdgeSnapper {\n sxx += dx * dx; syy += dy * dy; sxy += dx * dy\n }\n val ang = 0.5 * atan2(2 * sxy, sxx - syy)\n- val dx = cos(ang); val dy = sin(ang)\n- // 잔차(법선 거리) 평균이 band 절반 이상이면 적합 불량 → 폴백\n- var res = 0.0\n- for (k in 0 until n) res += abs((px[k] - mx) * (-dy) + (py[k] - my) * dx)\n- if (res / n > band * 0.5) return null\n- return doubleArrayOf(mx, my, dx, dy)\n+ return doubleArrayOf(mx, my, cos(ang), sin(ang))\n+ }\n+\n+ // 각 점의 직선까지 법선 거리.\n+ private fun residuals(px: List, py: List, l: DoubleArray): DoubleArray =\n+ DoubleArray(px.size) { k -> abs((px[k] - l[0]) * (-l[3]) + (py[k] - l[1]) * l[2]) }\n+\n+ private fun median(a: DoubleArray): Double {\n+ if (a.isEmpty()) return 0.0\n+ val s = a.sorted()\n+ return if (s.size % 2 == 1) s[s.size / 2] else (s[s.size / 2 - 1] + s[s.size / 2]) / 2.0\n }\n \n // 점-방향 형식 두 직선의 교점.\n- private fun intersect(l1: DoubleArray, l2: DoubleArray): DoubleArray? {\n+ internal fun intersect(l1: DoubleArray, l2: DoubleArray): DoubleArray? {\n val det = l1[2] * (-l2[3]) - l1[3] * (-l2[2])\n if (abs(det) < 1e-6) return null\n val rx = l2[0] - l1[0]; val ry = l2[1] - l1[1]","is_error":false}]},"uuid":"e19f66c0-224c-4961-8558-eade2c03894e","timestamp":"2026-06-11T14:31:25.525Z","sourceToolAssistantUUID":"9d723fea-3399-4791-b2ca-49feae85312a","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
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{"parentUuid":"9032ae27-56db-43f1-8ae1-6bcf755c27ec","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01JEZgqVzcw83LL5yC6xHDP1","type":"tool_result","content":"diff --git a/app/src/main/java/cc/lucasai/clearcam/editor/CornerCandidates.kt b/app/src/main/java/cc/lucasai/clearcam/editor/CornerCandidates.kt\nindex ae9df6c..89f5d62 100644\n--- a/app/src/main/java/cc/lucasai/clearcam/editor/CornerCandidates.kt\n+++ b/app/src/main/java/cc/lucasai/clearcam/editor/CornerCandidates.kt\n@@ -1,4 +1,4 @@\n-// 문서 코너 후보 생성: AI(DocAligner+엣지스냅)·OpenCV 윤곽 검출 + 전체/인셋 헬퍼.\n+// 문서 코너 후보 생성: AI(DocAligner+엣지스냅)·OpenCV 윤곽 검출 + 전체 헬퍼.\n package cc.lucasai.clearcam.editor\n \n import android.graphics.Bitmap\n@@ -14,8 +14,9 @@ object CornerCandidates {\n try {\n val onOrig = DocAlignerDetector.detect(bitmap)\n if (onOrig != null) {\n- // ML 코너를 실제 종이 경계선에 스냅한 뒤 살짝(1.5%) 인셋.\n- list.add(\"AI 검출\" to inset(EdgeSnapper.refine(bitmap, onOrig), 0.015f))\n+ // ML 코너를 실제 종이 경계선에 스냅한다. 인셋은 두지 않는다 —\n+ // 내용이 종이 가장자리까지 찬 문서(표 양식 등)에서 글자가 잘리기 때문.\n+ list.add(\"AI 검출\" to EdgeSnapper.refine(bitmap, onOrig))\n } else {\n // 어두운 사진은 모델이 문서를 못 본다(실측: peak 0.001). 밝게 보정한 사본으로\n // 재검출하고 좌표는 같은 크기의 원본에 그대로 적용(보정본은 검출용일 뿐).\n@@ -24,14 +25,14 @@ object CornerCandidates {\n val onBright = try { DocAlignerDetector.detect(bright) } catch (e: Exception) { null }\n bright.recycle()\n if (onBright != null) {\n- list.add(\"AI(밝게) 검출\" to inset(EdgeSnapper.refine(bitmap, onBright), 0.015f))\n+ list.add(\"AI(밝게) 검출\" to EdgeSnapper.refine(bitmap, onBright))\n } else if (ClearCamApp.openCvReady) {\n // 저대비 배경(흰 종이 위 밝은 바닥): 대비 스트레치 후 재검출.\n val str = ImageFilters.contrastStretch(bitmap)\n val onStr = try { DocAlignerDetector.detect(str) } catch (e: Exception) { null }\n str.recycle()\n if (onStr != null) {\n- list.add(\"AI(대비) 검출\" to inset(EdgeSnapper.refine(bitmap, onStr), 0.015f))\n+ list.add(\"AI(대비) 검출\" to EdgeSnapper.refine(bitmap, onStr))\n }\n }\n }\n@@ -50,17 +51,4 @@ object CornerCandidates {\n val w = bitmap.width.toFloat(); val h = bitmap.height.toFloat()\n return floatArrayOf(0f, 0f, w, 0f, w, h, 0f, h)\n }\n-\n- // 4코너를 무게중심 방향으로 ratio만큼 수축(헐거운 검출 가장자리 잡티 감소).\n- fun inset(c: FloatArray, ratio: Float): FloatArray {\n- var cx = 0f; var cy = 0f\n- for (i in 0 until 4) { cx += c[i * 2]; cy += c[i * 2 + 1] }\n- cx /= 4f; cy /= 4f\n- val out = FloatArray(8)\n- for (i in 0 until 4) {\n- out[i * 2] = c[i * 2] + (cx - c[i * 2]) * ratio\n- out[i * 2 + 1] = c[i * 2 + 1] + (cy - c[i * 2 + 1]) * ratio\n- }\n- return out\n- }\n }","is_error":false}]},"uuid":"c5989e2d-e995-49bb-8c9e-3d6f1b48b297","timestamp":"2026-06-11T14:31:25.975Z","sourceToolAssistantUUID":"9032ae27-56db-43f1-8ae1-6bcf755c27ec","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
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{"parentUuid":"008541cd-e887-4881-b624-835aaebece2b","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01UXaEFbqpm5wpJrjtpThTkc","type":"tool_result","content":"diff --git a/app/src/test/java/cc/lucasai/clearcam/editor/PerspectiveTransformerTest.kt b/app/src/test/java/cc/lucasai/clearcam/editor/PerspectiveTransformerTest.kt\nindex b9827c3..86bb5b7 100644\n--- a/app/src/test/java/cc/lucasai/clearcam/editor/PerspectiveTransformerTest.kt\n+++ b/app/src/test/java/cc/lucasai/clearcam/editor/PerspectiveTransformerTest.kt\n@@ -14,6 +14,16 @@ class PerspectiveTransformerTest {\n assertEquals(100, h)\n }\n \n+ // \"전체\" 선택(이미지 전체 꼭짓점) → 출력 크기 = 원본 크기. 한 픽셀도 잘리지 않아야 한다.\n+ @Test\n+ fun fullSelectionIsLossless() {\n+ val w = 2094f; val h = 3001f // 사용자 보고 사례의 문서 크기\n+ val corners = floatArrayOf(0f, 0f, w, 0f, w, h, 0f, h)\n+ val (ow, oh) = PerspectiveTransformer.outputSize(corners)\n+ assertEquals(2094, ow)\n+ assertEquals(3001, oh)\n+ }\n+\n // 사다리꼴: 상변 100, 하변 200 → 너비 평균 150.\n // 좌/우변은 빗변 hypot(50,80)=94.34 → 높이 평균 94 (유클리드 길이, 문서 스캔 표준).\n @Test","is_error":false}]},"uuid":"7677d0af-8c50-4b4c-ae9a-17380e8b40b2","timestamp":"2026-06-11T14:31:31.331Z","sourceToolAssistantUUID":"008541cd-e887-4881-b624-835aaebece2b","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
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{"parentUuid":"4833e7e9-610f-4bed-813c-4dbf6541956d","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_017tjzganrvvamwgzhZfZ8zW","type":"tool_result","content":"diff --git a/app/build.gradle.kts b/app/build.gradle.kts\nindex 24c1ed4..8e7a040 100644\n--- a/app/build.gradle.kts\n+++ b/app/build.gradle.kts\n@@ -20,8 +20,8 @@ android {\n // minSdk 29: Android 10+의 MediaStore로 저장 권한 없이 동작 → 런타임 권한 0개 유지.\n minSdk = 29\n targetSdk = 34\n- versionCode = 87\n- versionName = \"1.086\"\n+ versionCode = 88\n+ versionName = \"1.087\"\n ndk { abiFilters += \"arm64-v8a\" }\n }","is_error":false}]},"uuid":"98d6923d-8f5d-46a7-aeae-224a1da8b898","timestamp":"2026-06-11T14:31:31.721Z","sourceToolAssistantUUID":"4833e7e9-610f-4bed-813c-4dbf6541956d","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
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{"parentUuid":"1c22aa39-ade7-4e1a-81ce-0ece7dbf5fff","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_016rYjnYJLwcFLcadM27ZHfy","type":"tool_result","content":"1\t// EdgeSnapper의 순수 로직(fitEdge·intersect) 단위 테스트.\n2\t// 핵심 보장: ① \"안쪽으로 밝아지는\" 전이 중 가장 바깥을 종이 경계로 선택(표 테두리·그림자 배제)\n3\t// ② 방향성 후보가 없으면 최강 그래디언트로 폴백 ③ 직선 교점 계산.\n4\tpackage cc.lucasai.clearcam.editor\n5\t\n6\timport org.junit.Assert.assertEquals\n7\timport org.junit.Assert.assertNotNull\n8\timport org.junit.Assert.assertNull\n9\timport org.junit.Test\n10\timport kotlin.math.abs\n11\t\n12\tclass EdgeSnapperTest {\n13\t\n14\t private val w = 200\n15\t private val h = 200\n16\t\n17\t // 수직 경계 후보 2개를 가진 그래디언트 필드를 만든다.\n18\t // outerX: 종이 경계(안쪽(+x)으로 밝아짐 → dgx 양수), innerX: 표 테두리(더 강하지만 어두워짐 → dgx 음수).\n19\t private fun field(outerX: Int, outerMag: Float, innerX: Int, innerMag: Float): Triple {\n20\t val g = FloatArray(w * h)\n21\t val dgx = FloatArray(w * h)\n22\t val dgy = FloatArray(w * h)\n23\t for (y in 0 until h) {\n24\t g[y * w + outerX] = outerMag\n25\t dgx[y * w + outerX] = outerMag // 안쪽(+x)으로 밝아지는 전이\n26\t g[y * w + innerX] = innerMag\n27\t dgx[y * w + innerX] = -innerMag // 밝은 종이 → 어두운 표 선(방향성 탈락)\n28\t }\n29\t return Triple(g, dgx, dgy)\n30\t }\n31\t\n32\t // 왼쪽 변(BL→TL, 안쪽 법선 = +x)을 적합할 ML 코너. 변의 x좌표 = mlX.\n33\t private fun cornersWithLeftAt(mlX: Float): FloatArray =\n34\t floatArrayOf(mlX, 10f, 180f, 10f, 180f, 190f, mlX, 190f)\n35\t\n36\t @Test\n37\t fun picksOutermostInwardBrighteningEdgeOverStrongerInnerLine() {\n38\t // 종이 경계 x=40(크기 100), 표 테두리 x=60(크기 500). 기존 \"최강\" 규칙이면 60에 끌려간다.\n39\t val (g, dgx, dgy) = field(outerX = 40, outerMag = 100f, innerX = 60, innerMag = 500f)\n40\t val ml = cornersWithLeftAt(50f)\n41\t val line = EdgeSnapper.fitEdge(ml, 3, 0, g, dgx, dgy, w, h, band = 20, thr = 50.0)\n42\t assertNotNull(\"종이 경계에 적합한 직선이 나와야 한다\", line)\n43\t assertEquals(\"직선이 x=40(바깥 경계)을 지나야 한다\", 40.0, line!![0], 1.0)\n44\t }\n45\t\n46\t @Test\n47\t fun fallsBackToStrongestMagnitudeWhenNoDirectionalCandidate() {\n48\t // 방향성 후보 없음(dgx 전부 음수) → 최강 크기 x=60으로 폴백.\n49\t val (g, dgx, dgy) = field(outerX = 40, outerMag = 30f, innerX = 60, innerMag = 500f)\n50\t // 바깥 경계(30)는 thr=50 미달 → 방향성 후보 없음.\n51\t val ml = cornersWithLeftAt(50f)\n52\t val line = EdgeSnapper.fitEdge(ml, 3, 0, g, dgx, dgy, w, h, band = 20, thr = 50.0)\n53\t assertNotNull(line)\n54\t assertEquals(60.0, line!![0], 1.0)\n55\t }\n56\t\n57\t @Test\n58\t fun rejectsEdgeWhenTooFewBoundaryPoints() {\n59\t // 그래디언트가 전혀 없으면(경계 신호 없음) null → 호출부가 ML 코너 유지.\n60\t val g = FloatArray(w * h)\n61\t val ml = cornersWithLeftAt(50f)\n62\t val line = EdgeSnapper.fitEdge(ml, 3, 0, g, g, g, w, h, band = 20, thr = 50.0)\n63\t assertNull(line)\n64\t }\n65\t\n66\t @Test\n67\t fun outlierPointsAreTrimmedFromLineFit() {\n68\t // 경계 x=40이지만 일부 스캔라인에서 노이즈 스파이크가 x=55에 있는 필드.\n69\t val g = FloatArray(w * h)\n70\t val dgx = FloatArray(w * h)\n71\t val dgy = FloatArray(w * h)\n72\t for (y in 0 until h) {\n73\t g[y * w + 40] = 100f\n74\t dgx[y * w + 40] = 100f\n75\t }\n76\t // 변 위쪽 일부 구간(y 30..55)에만 더 바깥쪽(x=35) 가짜 전이를 깐다 → 이상치.\n77\t for (y in 30..55) {\n78\t g[y * w + 35] = 100f\n79\t dgx[y * w + 35] = 100f\n80\t }\n81\t val ml = cornersWithLeftAt(45f)\n82\t val line = EdgeSnapper.fitEdge(ml, 3, 0, g, dgx, dgy, w, h, band = 20, thr = 50.0)\n83\t assertNotNull(line)\n84\t // 이상치 제거 재적합으로 x=40 본선에 수렴해야 한다(이상치 평균 쪽이 아니라).\n85\t assertEquals(40.0, line!![0], 1.5)\n86\t // 직선 방향이 수직(dx≈0, |dy|≈1)이어야 한다.\n87\t assertEquals(0.0, abs(line[2]), 0.05)\n88\t }\n89\t\n90\t @Test\n91\t fun intersectFindsCrossingOfTwoLines() {\n92\t val vertical = doubleArrayOf(40.0, 100.0, 0.0, 1.0) // x=40\n93\t val horizontal = doubleArrayOf(100.0, 70.0, 1.0, 0.0) // y=70\n94\t val p = EdgeSnapper.intersect(vertical, horizontal)\n95\t assertNotNull(p)\n96\t assertEquals(40.0, p!![0], 1e-6)\n97\t assertEquals(70.0, p[1], 1e-6)\n98\t }\n99\t\n100\t @Test\n101\t fun intersectReturnsNullForParallelLines() {\n102\t val l1 = doubleArrayOf(0.0, 0.0, 1.0, 0.0)\n103\t val l2 = doubleArrayOf(0.0, 10.0, 1.0, 0.0)\n104\t assertNull(EdgeSnapper.intersect(l1, l2))\n105\t }\n106\t}\n107\t"}]},"uuid":"4997f150-d858-47aa-8343-92eefa67e5ac","timestamp":"2026-06-11T14:31:36.948Z","sourceToolAssistantUUID":"1c22aa39-ade7-4e1a-81ce-0ece7dbf5fff","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
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{"parentUuid":"c34b9945-b553-4284-9d23-a8c5f0042853","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013Niaw7P5rg1CqdTowt6b4X","type":"tool_result","content":"1\t// ML이 준 대략적 4코너를, 그 근처에서 찾은 실제 종이 경계선에 스냅해 정밀하게 보정한다.\n2\t// 사람이 종이 실루엣을 보듯 \"안쪽으로 밝아지는(배경→종이) 전이 중 가장 바깥쪽\"을 경계로 삼아,\n3\t// 종이 안쪽의 더 강한 표 테두리·텍스트나 종이 밖 그림자 경계에 끌려가지 않는다.\n4\t// 변마다 경계점을 모아 이상치 제거 직선 적합 → 인접 직선 교점 = 정밀 코너.\n5\t// 경계가 약하거나 ML에서 너무 멀면 ML 코너로 폴백(모호한 겹친 문서에서 안전).\n6\tpackage cc.lucasai.clearcam.editor\n7\t\n8\timport android.graphics.Bitmap\n9\timport cc.lucasai.clearcam.ClearCamApp\n10\timport org.opencv.android.Utils\n11\timport org.opencv.core.Core\n12\timport org.opencv.core.CvType\n13\timport org.opencv.core.Mat\n14\timport org.opencv.core.Size\n15\timport org.opencv.imgproc.Imgproc\n16\timport kotlin.math.abs\n17\timport kotlin.math.atan2\n18\timport kotlin.math.cos\n19\timport kotlin.math.hypot\n20\timport kotlin.math.sin\n21\t\n22\tobject EdgeSnapper {\n23\t\n24\t private const val BAND_FRAC = 0.03 // 경계 탐색 폭(짧은 변 대비)\n25\t private const val CLAMP_FRAC = 0.07 // ML 코너에서 이보다 멀면 폴백\n26\t private const val SAMPLES = 24 // 변당 샘플 수\n27\t\n28\t // corners: 비트맵 좌표 8 floats(TL,TR,BR,BL). 보정된 8 floats 반환.\n29\t fun refine(bitmap: Bitmap, corners: FloatArray): FloatArray {\n30\t if (!ClearCamApp.openCvReady) return corners\n31\t val src = Mat(); val gray = Mat(); val gx = Mat(); val gy = Mat(); val grad = Mat()\n32\t try {\n33\t Utils.bitmapToMat(bitmap, src)\n34\t Imgproc.cvtColor(src, gray, Imgproc.COLOR_RGBA2GRAY)\n35\t Imgproc.Sobel(gray, gx, CvType.CV_32F, 1, 0, 3)\n36\t Imgproc.Sobel(gray, gy, CvType.CV_32F, 0, 1, 3)\n37\t Core.magnitude(gx, gy, grad)\n38\t Imgproc.GaussianBlur(grad, grad, Size(5.0, 5.0), 0.0)\n39\t // 방향성 판단용 부드러운 그래디언트(법선과 내적해 \"안쪽으로 밝아짐\"을 검사).\n40\t Imgproc.GaussianBlur(gx, gx, Size(5.0, 5.0), 0.0)\n41\t Imgproc.GaussianBlur(gy, gy, Size(5.0, 5.0), 0.0)\n42\t val w = gray.cols(); val h = gray.rows()\n43\t val g = FloatArray(w * h); grad.get(0, 0, g)\n44\t val dgx = FloatArray(w * h); gx.get(0, 0, dgx)\n45\t val dgy = FloatArray(w * h); gy.get(0, 0, dgy)\n46\t val gmean = Core.mean(grad).`val`[0]\n47\t val band = maxOf(6, (minOf(w, h) * BAND_FRAC).toInt())\n48\t val thr = gmean * 3.0\n49\t\n50\t // 변: top(0,1) right(1,2) bottom(2,3) left(3,0). 각 변의 직선 [mx,my,dx,dy] 또는 null.\n51\t val edges = arrayOf(intArrayOf(0, 1), intArrayOf(1, 2), intArrayOf(2, 3), intArrayOf(3, 0))\n52\t val lines = arrayOfNulls(4)\n53\t for (e in 0 until 4) {\n54\t lines[e] = fitEdge(corners, edges[e][0], edges[e][1], g, dgx, dgy, w, h, band, thr)\n55\t }\n56\t // 코너 i = (이전 변 ∩ 다음 변).\n57\t val meet = arrayOf(intArrayOf(3, 0), intArrayOf(0, 1), intArrayOf(1, 2), intArrayOf(2, 3))\n58\t val out = corners.copyOf()\n59\t val clamp = minOf(w, h) * CLAMP_FRAC\n60\t for (ci in 0 until 4) {\n61\t val l1 = lines[meet[ci][0]]; val l2 = lines[meet[ci][1]]\n62\t if (l1 != null && l2 != null) {\n63\t val ip = intersect(l1, l2) ?: continue\n64\t val dx = ip[0] - corners[ci * 2]; val dy = ip[1] - corners[ci * 2 + 1]\n65\t if (hypot(dx, dy) < clamp) { out[ci * 2] = ip[0].toFloat(); out[ci * 2 + 1] = ip[1].toFloat() }\n66\t }\n67\t }\n68\t return out\n69\t } catch (e: Exception) {\n70\t return corners\n71\t } finally {\n72\t src.release(); gray.release(); gx.release(); gy.release(); grad.release()\n73\t }\n74\t }\n75\t\n76\t // 한 변을 따라 법선 스캔으로 경계점을 모아 이상치 제거 총최소제곱 직선을 적합한다.\n77\t // 각 스캔(바깥→안)에서 \"안쪽으로 밝아지는\" 전이(d≥thr) 중 가장 바깥 점을 우선하고,\n78\t // 없으면 최강 그래디언트 크기(>thr)로 폴백한다. TL,TR,BR,BL 시계방향이면 +법선=안쪽.\n79\t internal fun fitEdge(\n80\t c: FloatArray, ia: Int, ib: Int,\n81\t g: FloatArray, dgx: FloatArray, dgy: FloatArray,\n82\t w: Int, h: Int, band: Int, thr: Double,\n83\t ): DoubleArray? {\n84\t val ax = c[ia * 2].toDouble(); val ay = c[ia * 2 + 1].toDouble()\n85\t val bx = c[ib * 2].toDouble(); val by = c[ib * 2 + 1].toDouble()\n86\t var evx = bx - ax; var evy = by - ay; val len = hypot(evx, evy)\n87\t if (len < 2) return null\n88\t evx /= len; evy /= len\n89\t val nx = -evy; val ny = evx\n90\t val px = ArrayList(); val py = ArrayList()\n91\t for (i in 0 until SAMPLES) {\n92\t val t = 0.12 + (0.88 - 0.12) * i / (SAMPLES - 1)\n93\t val ox = ax + evx * (t * len); val oy = ay + evy * (t * len)\n94\t var pickX = 0.0; var pickY = 0.0; var picked = false\n95\t var bestV = thr; var fbX = 0.0; var fbY = 0.0; var fallback = false\n96\t for (s in -band..band) { // 바깥(-)→안(+) 순서로 스캔\n97\t val qx = ox + nx * s; val qy = oy + ny * s\n98\t val xi = Math.round(qx).toInt(); val yi = Math.round(qy).toInt()\n99\t if (xi in 0 until w && yi in 0 until h) {\n100\t val idx = yi * w + xi\n101\t if (!picked) {\n102\t val d = dgx[idx] * nx + dgy[idx] * ny // 안쪽으로 밝아지면 양수\n103\t if (d >= thr) { pickX = qx; pickY = qy; picked = true }\n104\t }\n105\t val v = g[idx].toDouble()\n106\t if (v > bestV) { bestV = v; fbX = qx; fbY = qy; fallback = true }\n107\t }\n108\t }\n109\t if (picked) { px.add(pickX); py.add(pickY) }\n110\t else if (fallback) { px.add(fbX); py.add(fbY) }\n111\t }\n112\t if (px.size < (SAMPLES * 0.6).toInt()) return null\n113\t var fit = fitLine(px, py) ?: return null\n114\t // 이상치 제거 후 1회 재적합: 잔차가 중앙값의 2배(최소 2px) 넘는 점을 버린다.\n115\t val res = residuals(px, py, fit)\n116\t val med = median(res)\n117\t val cut = maxOf(2.0 * med, 2.0)\n118\t val kx = ArrayList(); val ky = ArrayList()\n119\t for (k in px.indices) if (res[k] <= cut) { kx.add(px[k]); ky.add(py[k]) }\n120\t if (kx.size >= maxOf(4, px.size / 2)) {\n121\t fit = fitLine(kx, ky) ?: fit\n122\t val res2 = residuals(kx, ky, fit)\n123\t if (res2.average() > band * 0.5) return null\n124\t return fit\n125\t }\n126\t if (res.average() > band * 0.5) return null\n127\t return fit\n128\t }\n129\t\n130\t // 총최소제곱(무게중심 + 주성분 방향) 직선 [mx,my,dx,dy].\n131\t private fun fitLine(px: List, py: List): DoubleArray? {\n132\t val n = px.size\n133\t if (n < 2) return null\n134\t var mx = 0.0; var my = 0.0\n135\t for (k in 0 until n) { mx += px[k]; my += py[k] }\n136\t mx /= n; my /= n\n137\t var sxx = 0.0; var syy = 0.0; var sxy = 0.0\n138\t for (k in 0 until n) {\n139\t val dx = px[k] - mx; val dy = py[k] - my\n140\t sxx += dx * dx; syy += dy * dy; sxy += dx * dy\n141\t }\n142\t val ang = 0.5 * atan2(2 * sxy, sxx - syy)\n143\t return doubleArrayOf(mx, my, cos(ang), sin(ang))\n144\t }\n145\t\n146\t // 각 점의 직선까지 법선 거리.\n147\t private fun residuals(px: List, py: List, l: DoubleArray): DoubleArray =\n148\t DoubleArray(px.size) { k -> abs((px[k] - l[0]) * (-l[3]) + (py[k] - l[1]) * l[2]) }\n149\t\n150\t private fun median(a: DoubleArray): Double {\n151\t if (a.isEmpty()) return 0.0\n152\t val s = a.sorted()\n153\t return if (s.size % 2 == 1) s[s.size / 2] else (s[s.size / 2 - 1] + s[s.size / 2]) / 2.0\n154\t }\n155\t\n156\t // 점-방향 형식 두 직선의 교점.\n157\t internal fun intersect(l1: DoubleArray, l2: DoubleArray): DoubleArray? {\n158\t val det = l1[2] * (-l2[3]) - l1[3] * (-l2[2])\n159\t if (abs(det) < 1e-6) return null\n160\t val rx = l2[0] - l1[0]; val ry = l2[1] - l1[1]\n161\t val t = (rx * (-l2[3]) - ry * (-l2[2])) / det\n162\t return doubleArrayOf(l1[0] + l1[2] * t, l1[1] + l1[3] * t)\n163\t }\n164\t}\n165\t"}]},"uuid":"859713f6-4651-4d82-a717-ebe9420df7b8","timestamp":"2026-06-11T14:31:37.247Z","sourceToolAssistantUUID":"c34b9945-b553-4284-9d23-a8c5f0042853","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
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{"parentUuid":"e179c94a-0b8f-4626-910d-e01ae69486dc","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01VzCx866sFWoDWvNyPWc19R","type":"tool_result","content":"1\t// 문서 코너 후보 생성: AI(DocAligner+엣지스냅)·OpenCV 윤곽 검출 + 전체 헬퍼.\n2\tpackage cc.lucasai.clearcam.editor\n3\t\n4\timport android.graphics.Bitmap\n5\timport android.util.Log\n6\timport cc.lucasai.clearcam.ClearCamApp\n7\t\n8\tobject CornerCandidates {\n9\t\n10\t // 두 엔진 결과를 (라벨, 비트맵좌표 코너) 후보 목록으로 반환한다(없으면 빈 목록).\n11\t fun detect(bitmap: Bitmap): List> {\n12\t val list = mutableListOf>()\n13\t if (DocAlignerDetector.isReady) {\n14\t try {\n15\t val onOrig = DocAlignerDetector.detect(bitmap)\n16\t if (onOrig != null) {\n17\t // ML 코너를 실제 종이 경계선에 스냅한다. 인셋은 두지 않는다 —\n18\t // 내용이 종이 가장자리까지 찬 문서(표 양식 등)에서 글자가 잘리기 때문.\n19\t list.add(\"AI 검출\" to EdgeSnapper.refine(bitmap, onOrig))\n20\t } else {\n21\t // 어두운 사진은 모델이 문서를 못 본다(실측: peak 0.001). 밝게 보정한 사본으로\n22\t // 재검출하고 좌표는 같은 크기의 원본에 그대로 적용(보정본은 검출용일 뿐).\n23\t // 반전·CLAHE는 효과 없거나 역효과라 밝기 보정만 쓴다.\n24\t val bright = ImageFilters.apply(bitmap, ImageFilters.brightnessContrastMatrix(90f, 1.4f))\n25\t val onBright = try { DocAlignerDetector.detect(bright) } catch (e: Exception) { null }\n26\t bright.recycle()\n27\t if (onBright != null) {\n28\t list.add(\"AI(밝게) 검출\" to EdgeSnapper.refine(bitmap, onBright))\n29\t } else if (ClearCamApp.openCvReady) {\n30\t // 저대비 배경(흰 종이 위 밝은 바닥): 대비 스트레치 후 재검출.\n31\t val str = ImageFilters.contrastStretch(bitmap)\n32\t val onStr = try { DocAlignerDetector.detect(str) } catch (e: Exception) { null }\n33\t str.recycle()\n34\t if (onStr != null) {\n35\t list.add(\"AI(대비) 검출\" to EdgeSnapper.refine(bitmap, onStr))\n36\t }\n37\t }\n38\t }\n39\t } catch (e: Exception) { Log.e(\"ClearCam\", \"AI 검출 오류\", e) }\n40\t }\n41\t if (ClearCamApp.openCvReady) {\n42\t try {\n43\t DocumentDetector.detect(bitmap)?.let { list.add(\"윤곽 검출\" to it) }\n44\t } catch (e: Exception) { Log.e(\"ClearCam\", \"윤곽 검출 오류\", e) }\n45\t }\n46\t return list\n47\t }\n48\t\n49\t // 이미지 전체 꼭짓점(크롭 없음) TL,TR,BR,BL.\n50\t fun full(bitmap: Bitmap): FloatArray {\n51\t val w = bitmap.width.toFloat(); val h = bitmap.height.toFloat()\n52\t return floatArrayOf(0f, 0f, w, 0f, w, h, 0f, h)\n53\t }\n54\t}\n55\t"}]},"uuid":"50c4d03f-2d42-4ccb-adf9-f9c4aff0dcb8","timestamp":"2026-06-11T14:31:43.337Z","sourceToolAssistantUUID":"e179c94a-0b8f-4626-910d-e01ae69486dc","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
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{"parentUuid":"7de7c71b-19a0-4c9e-b98d-cd28b3b537ce","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01YDEJxUKNcegn7rbnzXcG3v","type":"tool_result","content":"/home/lucas/Android-app/ClearCam/app/src/main/java/cc/lucasai/clearcam/editor/EditorActivity.kt:267: val found = withContext(Dispatchers.Default) { CornerCandidates.detect(sourceBitmap) }\n/home/lucas/Android-app/ClearCam/app/src/main/java/cc/lucasai/clearcam/editor/EditorActivity.kt:288: binding.overlay.setBitmapCorners(CornerCandidates.full(sourceBitmap))\n/home/lucas/Android-app/ClearCam/app/src/main/java/cc/lucasai/clearcam/gallery/ScanPipeline.kt:11:import cc.lucasai.clearcam.editor.CornerCandidates\n/home/lucas/Android-app/ClearCam/app/src/main/java/cc/lucasai/clearcam/gallery/ScanPipeline.kt:26: val corners = CornerCandidates.detect(src).firstOrNull()?.second","is_error":false}]},"uuid":"5c871bdf-1d68-450f-b097-2e292a1af943","timestamp":"2026-06-11T14:31:44.972Z","sourceToolAssistantUUID":"7de7c71b-19a0-4c9e-b98d-cd28b3b537ce","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
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{"parentUuid":"396218b6-492a-4c09-bfd1-0df9b4bd4124","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01DWkxiz7j8xfqwiVih4zLAu","type":"tool_result","content":"(Bash completed with no output)","is_error":false}]},"uuid":"0601fd67-3695-4632-b8e3-ccb2d5ee971b","timestamp":"2026-06-11T14:31:58.667Z","sourceToolAssistantUUID":"396218b6-492a-4c09-bfd1-0df9b4bd4124","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"0601fd67-3695-4632-b8e3-ccb2d5ee971b","isSidechain":true,"agentId":"ad154ea4230933d32","message":{"model":"claude-sonnet-4-6","id":"msg_01MKnoXDum3hgJQoUPQ9GcEx","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01AaEvLYXgT5L1UskA9eTzEu","name":"Bash","input":{"command":"# Verify normal (inward) direction computation for TL,TR,BR,BL clockwise corners\n# Edge TL→TR (e=0, ia=0,ib=1): evx=+1,evy=0 => nx=-evy=0, ny=evx=+1. So +n points DOWN = inside. Correct.\n# Edge TR→BR (e=1, ia=1,ib=2): evx=0,evy=+1 => nx=-1, ny=0. So +n points LEFT = inside. Correct.\n# Edge BR→BL (e=2, ia=2,ib=3): evx=-1,evy=0 => nx=0, ny=-1. So +n points UP = inside. Correct.\n# Edge BL→TL (e=3, ia=3,ib=0): evx=0,evy=-1 => nx=+1, ny=0. So +n points RIGHT = inside. Correct.\necho \"Normal direction check: if +n is inside, then -band scans outward. This is correct for all 4 edges.\"\n# Scan: for s in -band..band, position = origin + nx*s\n# s negative -> steps in -n direction (OUTSIDE), s positive -> steps in +n direction (INSIDE)\n# So -band..band starts at outside and ends at inside. \"Outward to inward\" scan order is confirmed.\necho \"Scan order: s=-band is outermost, s=+band is innermost. Correct.\"\n# Directional dot product: d = dgx*nx + dgy*ny\n# This is grad . n_inward. For background->paper transition (brighter inside), \n# gradient points inward, so d > 0. \n# First qualifying point (smallest s i.e. most outward) is picked.\necho \"Directional dot: grad.n_inward > 0 means background->paper (correct). Outermost qualifying = paper boundary.\"","description":"Verify normal direction math for TL,TR,BR,BL clockwise layout"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":285,"cache_read_input_tokens":37796,"cache_creation":{"ephemeral_5m_input_tokens":285,"ephemeral_1h_input_tokens":0},"output_tokens":36,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CbwdnDxzzrhGeb6knT1ML","attributionAgent":"reviewer","type":"assistant","uuid":"2210c844-45a9-4a17-96e8-259774be877c","timestamp":"2026-06-11T14:32:10.154Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"2210c844-45a9-4a17-96e8-259774be877c","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AaEvLYXgT5L1UskA9eTzEu","type":"tool_result","content":"Normal direction check: if +n is inside, then -band scans outward. This is correct for all 4 edges.\nScan order: s=-band is outermost, s=+band is innermost. Correct.\nDirectional dot: grad.n_inward > 0 means background->paper (correct). Outermost qualifying = paper boundary.","is_error":false}]},"uuid":"d1b1f565-e2f5-4fcd-9950-b75f097403f0","timestamp":"2026-06-11T14:32:10.388Z","sourceToolAssistantUUID":"2210c844-45a9-4a17-96e8-259774be877c","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"d1b1f565-e2f5-4fcd-9950-b75f097403f0","isSidechain":true,"agentId":"ad154ea4230933d32","message":{"model":"claude-sonnet-4-6","id":"msg_015frAFjxv6gpXci7JMtxmLc","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_0142bRSwBd6BA2DrcARvktdQ","name":"Bash","input":{"command":"# Check the outlier trimming math edge case\n# When median = 0 (all points perfectly on the line), cut = max(0, 2.0) = 2.0px\n# All residuals = 0 <= 2.0, so all points pass -> kx.size == px.size >= max(4, px.size/2). Good.\n# When px.size = 14 (minimum: SAMPLES*0.6 = 24*0.6 = 14 rounded down = 14):\n# max(4, 14/2) = max(4, 7) = 7. kx.size >= 7. If almost all trimmed, falls back to original fit.\necho \"Outlier trim: minimum inliers = max(4, px.size/2). With px.size=14, needs >=7 inliers. OK.\"\n\n# kx.size < max(4, px.size/2): falls through to the fallback path at line 126\n# This path uses the original fit (before outlier removal) with original residuals check. Good.\n\n# Check the residual gate after outlier removal (line 122-124):\n# After refitting kx/ky, if res2.average() > band*0.5, returns null.\n# This is a quality gate: if even inliers are spread >band/2 from the fitted line, reject.\necho \"Quality gate: average residual of inliers > band/2 -> null. Conservative.\"\n\n# POTENTIAL ISSUE: When kx.size < max(4, px.size/2), the code falls to line 126:\n# if (res.average() > band * 0.5) return null; return fit\n# But 'fit' here is the INITIAL fit (before outlier removal attempt).\n# The initial residuals include outliers. This is intentional: if even with outliers\n# the initial fit is decent, keep it. This is correct fallback behavior.\necho \"Fallback path uses initial fit + initial residuals. Intentional and correct.\"","description":"Verify outlier trimming logic and edge cases"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":656,"cache_read_input_tokens":38081,"cache_creation":{"ephemeral_5m_input_tokens":656,"ephemeral_1h_input_tokens":0},"output_tokens":38,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CbwdoCQWydYkMtamzhptC","attributionAgent":"reviewer","type":"assistant","uuid":"b3ce89e7-ad65-46e4-85db-8c9900d55b41","timestamp":"2026-06-11T14:32:24.450Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"b3ce89e7-ad65-46e4-85db-8c9900d55b41","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0142bRSwBd6BA2DrcARvktdQ","type":"tool_result","content":"Outlier trim: minimum inliers = max(4, px.size/2). With px.size=14, needs >=7 inliers. OK.\nQuality gate: average residual of inliers > band/2 -> null. Conservative.\nFallback path uses initial fit + initial residuals. Intentional and correct.","is_error":false}]},"uuid":"c99bc74c-5d58-4edc-a65e-db09728260f9","timestamp":"2026-06-11T14:32:24.655Z","sourceToolAssistantUUID":"b3ce89e7-ad65-46e4-85db-8c9900d55b41","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"c99bc74c-5d58-4edc-a65e-db09728260f9","isSidechain":true,"agentId":"ad154ea4230933d32","message":{"model":"claude-sonnet-4-6","id":"msg_01XSWyWYBNfzXajBAagEV546","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01KtpKSEAaqGP8BwW9BqT44E","name":"Bash","input":{"command":"# Check for potential double-counting issue in fallback path:\n# Line 95: var bestV = thr (initialized to threshold, not 0)\n# So fallback fires only when g[idx] > thr (strictly greater)\n# But directional path fires when d >= thr (greater or equal)\n# This means if d == thr exactly, directional wins. Fine.\n# \n# Critical: if picked==true for some scan, fallback STILL updates (lines 105-106 are NOT inside 'if (!picked)')\n# So fallback always tracks the maximum-magnitude point regardless of picked state.\n# When picked==true -> use picked result (correct)\n# When picked==false and fallback==true -> use fallback (correct)\n# No issue: the fallback tracking continues past 'picked' state, which is harmless since it's only used\n# when picked==false.\necho \"Directional/fallback independence: fallback tracking is always running, but only used when !picked. OK.\"\n\n# Check: thr = gmean * 3.0 and directional threshold is ALSO thr.\n# gmean is mean of BLURRED magnitude. For typical documents, this could be quite low.\n# The directional dot product d = dgx*nx + dgy*ny can have a different magnitude scale than g[].\n# g[] is from Core.magnitude(gx,gy,grad) then GaussianBlur\n# dgx/dgy are from GaussianBlur(gx,gy) directly\n# So d = |blurred_gx * nx + blurred_gy * ny| <= blurred_magnitude (by Cauchy-Schwarz)\n# Using same threshold thr for both magnitude and directional projection is potentially problematic:\n# directional component <= total magnitude, so thr based on mean total magnitude\n# could be harder to meet for directional signal than for total magnitude.\necho \"CONCERN: thr applied to both total magnitude AND directional dot product.\"\necho \"Since |d| <= |grad|, directional threshold is HARDER to satisfy than fallback threshold.\"\necho \"This is intentional design: directional must be a dominant signal. But may be overly strict.\"","description":"Verify threshold usage for directional vs fallback paths"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":648,"cache_read_input_tokens":38737,"cache_creation":{"ephemeral_5m_input_tokens":648,"ephemeral_1h_input_tokens":0},"output_tokens":47,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CbwdpEts67FUvZVDXj6uD","attributionAgent":"reviewer","type":"assistant","uuid":"7078ea3b-4f52-4761-8399-86be2862eaeb","timestamp":"2026-06-11T14:32:40.878Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"7078ea3b-4f52-4761-8399-86be2862eaeb","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01KtpKSEAaqGP8BwW9BqT44E","type":"tool_result","content":"Directional/fallback independence: fallback tracking is always running, but only used when !picked. OK.\nCONCERN: thr applied to both total magnitude AND directional dot product.\nSince |d| <= |grad|, directional threshold is HARDER to satisfy than fallback threshold.\nThis is intentional design: directional must be a dominant signal. But may be overly strict.","is_error":false}]},"uuid":"d13374b4-5daa-4b18-b013-77a2e3fd196e","timestamp":"2026-06-11T14:32:41.086Z","sourceToolAssistantUUID":"7078ea3b-4f52-4761-8399-86be2862eaeb","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"d13374b4-5daa-4b18-b013-77a2e3fd196e","isSidechain":true,"agentId":"ad154ea4230933d32","message":{"model":"claude-sonnet-4-6","id":"msg_01Ksi2VwWmaz8gzvkoTMzHFt","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01QkjnwDjkdCWJHvLAtjaNMb","name":"Bash","input":{"command":"# Check Mat memory management in refine()\n# Mats allocated: src, gray, gx, gy, grad (line 31)\n# All released in finally block: src.release(); gray.release(); gx.release(); gy.release(); grad.release()\n# Note: GaussianBlur(gx, gx, ...) and GaussianBlur(gy, gy, ...) are in-place operations\n# In OpenCV for Android, in-place blur IS supported for Mat — destination == source is allowed.\n# No new Mat is created; gx and gy are modified in-place. These are already in the finally block.\necho \"Mat lifecycle: 5 mats created, all released in finally. In-place blur ok.\"\n\n# Check: dgx/dgy are FloatArrays (Java primitives), NOT Mat objects. No leak risk.\necho \"dgx/dgy arrays: Java heap, GC-managed. No OpenCV leak.\"\n\n# Exception safety: try/catch(Exception) wraps all OpenCV work, returns original corners on exception.\n# finally always runs release(). \necho \"Exception safety: full try/catch/finally. Mat always released. OK.\"","description":"Verify Mat lifecycle and exception safety in refine()"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":684,"cache_read_input_tokens":39385,"cache_creation":{"ephemeral_5m_input_tokens":684,"ephemeral_1h_input_tokens":0},"output_tokens":37,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CbwdqTg6QWB7a2NrN1pwB","attributionAgent":"reviewer","type":"assistant","uuid":"b067112b-f5c7-46a2-a153-7fd9a1f72e40","timestamp":"2026-06-11T14:32:51.040Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"b067112b-f5c7-46a2-a153-7fd9a1f72e40","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01QkjnwDjkdCWJHvLAtjaNMb","type":"tool_result","content":"Mat lifecycle: 5 mats created, all released in finally. In-place blur ok.\ndgx/dgy arrays: Java heap, GC-managed. No OpenCV leak.\nException safety: full try/catch/finally. Mat always released. OK.","is_error":false}]},"uuid":"38af1b50-c769-4924-a9b9-a0fd9b6804e5","timestamp":"2026-06-11T14:32:51.241Z","sourceToolAssistantUUID":"b067112b-f5c7-46a2-a153-7fd9a1f72e40","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"38af1b50-c769-4924-a9b9-a0fd9b6804e5","isSidechain":true,"agentId":"ad154ea4230933d32","message":{"model":"claude-sonnet-4-6","id":"msg_01RbugyxQMtEP7SxVNCe9iWH","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01MLcf7X7EZCd8c1TXViZ8ft","name":"Bash","input":{"command":"# Verify test: picksOutermostInwardBrighteningEdgeOverStrongerInnerLine\n# cornersWithLeftAt(50f): TL=(50,10), TR=(180,10), BR=(180,190), BL=(50,190)\n# fitEdge called with ia=3(BL), ib=0(TL): left edge\n# ax=50, ay=190; bx=50, by=10\n# evx=0, evy=-1 (pointing up), len=180\n# nx=-evy=1, ny=evx=0 => normal points RIGHT (+x is inside)\n# For s in -band..band: s<0 is LEFT (outside), s>0 is RIGHT (inside)\n# origin x = 50 (ML edge x), outerX=40 is at s=-10 (outside), innerX=60 is at s=+10 (inside)\n# dgx[outerX] = +outerMag = +100. d = dgx*nx + dgy*ny = 100*1 + 0*0 = 100 >= thr=50. PICK.\n# dgx[innerX] = -innerMag = -500. d = -500*1 + 0 = -500 < thr. No pick.\n# outerX=40 is at s=-10 (more negative = more outside), so it's hit first in the scan.\n# Test expects line[0] ≈ 40. Correct.\necho \"Test 1 (outermost inward): math verified correct.\"\n\n# Verify test: fallsBackToStrongestMagnitudeWhenNoDirectionalCandidate\n# outerMag=30 < thr=50: no directional (30 < 50)\n# dgx[outerX] is +30, but d=30 < 50. No directional pick.\n# innerMag=500 > thr=50: fallback fires at innerX=60.\n# Test expects line[0] ≈ 60. But wait: dgx[innerX] = -500. d = -500 < thr. No directional pick.\n# Fallback: g[outerX]=30 < thr=50, g[innerX]=500 > thr=50. Fallback picks innerX=60. Correct.\necho \"Test 2 (fallback): math verified correct.\"","description":"Verify test case mathematics"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":424,"cache_read_input_tokens":40069,"cache_creation":{"ephemeral_5m_input_tokens":424,"ephemeral_1h_input_tokens":0},"output_tokens":37,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CbwdrCU58hFF3PsgLoMAN","attributionAgent":"reviewer","type":"assistant","uuid":"f363777e-4c95-4e3d-a294-d24aea2fc7c5","timestamp":"2026-06-11T14:33:06.427Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"f363777e-4c95-4e3d-a294-d24aea2fc7c5","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01MLcf7X7EZCd8c1TXViZ8ft","type":"tool_result","content":"Test 1 (outermost inward): math verified correct.\nTest 2 (fallback): math verified correct.","is_error":false}]},"uuid":"8b676158-a5fe-4d1f-8265-622def4d1bfe","timestamp":"2026-06-11T14:33:06.643Z","sourceToolAssistantUUID":"f363777e-4c95-4e3d-a294-d24aea2fc7c5","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"8b676158-a5fe-4d1f-8265-622def4d1bfe","isSidechain":true,"agentId":"ad154ea4230933d32","message":{"model":"claude-sonnet-4-6","id":"msg_017qz6yFVm6fU4DswFYiUMj2","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01HunELNBtBsz2cm4jreNm9H","name":"Bash","input":{"command":"# Check the outlier test more carefully\n# cornersWithLeftAt(45f): BL=(45,190), TL=(45,10)\n# Left edge: ax=45,ay=190, bx=45,by=10. evx=0,evy=-1,len=180. nx=1,ny=0.\n# band=20. Origin at x=45 for each sample.\n# For each sample y in ~[10..190]:\n# Scan s=-20..+20 => qx = 45+s, range x=25..65\n# At outerX=40 => s=-5: d = dgx[y*200+40]*1 = 100 >= 50. PICK on first hit.\n# But for y in 30..55: also outerX=35 at s=-10: d = 100 >= 50. PICKED at s=-10 (more outer).\n# So samples in y=30..55 pick x=35 (outlier), others pick x=40 (main boundary).\n# ~26 outlier samples (y 30..55) vs ~(180-26)/180*24 ≈ 21 main samples... \n# Wait, SAMPLES=24 total, not per-y. Let me recalculate.\n# t = 0.12 + 0.76*i/23 for i=0..23. oy = 190 + (-1)*(t*180) = 190 - t*180\n# t range: 0.12 to 0.88. oy range: 190-21.6=168.4 to 190-158.4=31.6\n# For oy in 31.6..55, that's a small range. t = (190-oy)/180. For oy=55: t=(135)/180=0.75. i=(0.75-0.12)/0.76*23≈19.\n# For oy=31.6: t=0.88, i=23. So i=19..23 = 5 samples are in outlier zone (y 30..55 approx).\n# 5 outlier samples pick x=35, 19 main samples pick x=40.\n# After initial fitLine: centroid x ≈ (19*40 + 5*35)/24 ≈ (760+175)/24 ≈ 38.96\n# Residuals: outliers at x=35 have dist |35-mx|*|ny=0| + but the line is nearly vertical...\n# Actually residual = abs((px[k]-mx)*(-dy) + (py[k]-my)*dx) with dx=0, dy=1:\n# = abs((px[k]-mx)*(-1) + (py[k]-my)*0) = abs(mx - px[k]) = |40-38.96| ≈ 1.04 for main\n# and |35-38.96| ≈ 3.96 for outliers.\n# median of [1.04*19, 3.96*5 in sorted order]: 24 values, median = 12th value = 1.04.\n# cut = max(2*1.04, 2.0) = max(2.08, 2.0) = 2.08.\n# outliers have residual 3.96 > 2.08 -> trimmed.\n# kx.size = 19 >= max(4, 24/2=12). Refit with 19 points at x=40 -> line[0]=40.0. \n# Test asserts line[0] ≈ 40 with tolerance 1.5. CORRECT.\necho \"Test 3 (outlier trim): math verified correct.\"","description":"Verify outlier trimming test mathematics"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":692,"cache_read_input_tokens":40493,"cache_creation":{"ephemeral_5m_input_tokens":692,"ephemeral_1h_input_tokens":0},"output_tokens":46,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CbwdsLeE1CnH57HJCqGDT","attributionAgent":"reviewer","type":"assistant","uuid":"06672b7a-6d2f-4f4e-9cb9-9485fd579718","timestamp":"2026-06-11T14:33:28.232Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"06672b7a-6d2f-4f4e-9cb9-9485fd579718","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01HunELNBtBsz2cm4jreNm9H","type":"tool_result","content":"Test 3 (outlier trim): math verified correct.","is_error":false}]},"uuid":"9d57b416-aec1-4251-8ca2-709b6170be71","timestamp":"2026-06-11T14:33:28.425Z","sourceToolAssistantUUID":"06672b7a-6d2f-4f4e-9cb9-9485fd579718","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"9d57b416-aec1-4251-8ca2-709b6170be71","isSidechain":true,"agentId":"ad154ea4230933d32","message":{"model":"claude-sonnet-4-6","id":"msg_01F5W64cLe92EBKLhPQVg9LT","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_013mCAsDbHRxbXWBFfBJcgMZ","name":"Bash","input":{"command":"# Check: what happens when ALL 24 samples pick the directional candidate but they're ALL outliers?\n# e.g. noisy scan where every sample picks a slightly different x due to aliasing.\n# The outlier trimming might trim too aggressively if the distribution is truly bimodal.\n# kx.size < max(4, px.size/2) -> falls back to initial fit with initial residuals check.\n# That's the conservative path: if we can't get a clean inlier set, use initial fit or reject. OK.\n\n# Another edge case: SAMPLES * 0.6 = 14.4, rounded down = 14.\n# px.size must be >= 14 to proceed to fitLine. This means at least 14 out of 24 samples\n# must find a candidate (either directional or fallback). Reasonable.\n\n# Check: when median = 0.0 returned from empty array.\n# median(DoubleArray) has guard: if (a.isEmpty()) return 0.0\n# But residuals() always returns DoubleArray of same size as px, and px.size >= 14 here.\n# So a.isEmpty() guard is defensive but never triggered at this call site. OK.\necho \"Edge case analysis: all defensive. No unreachable crash paths found.\"\n\n# Sobel -> magnitude -> GaussianBlur(grad,grad,...) -> GaussianBlur(gx,gx,...) -> GaussianBlur(gy,gy,...)\n# Important: magnitude is computed from UNBLURRED gx,gy, then gx,gy are blurred separately.\n# So g[] = blur(|gx,gy|) and dgx/dgy = blur(gx), blur(gy) separately.\n# |blur(gx), blur(gy)| != blur(|gx,gy|) in general.\n# g[] is overall edge strength (blurred magnitude), dgx/dgy is smoothed directional gradient.\n# This is correct: we want smooth direction but we compute magnitude separately for the fallback threshold.\necho \"Gradient computation order: magnitude computed before blur, directional computed after blur. Correct design.\"","description":"Verify edge cases in algorithm and gradient pipeline"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1007,"cache_read_input_tokens":41185,"cache_creation":{"ephemeral_5m_input_tokens":1007,"ephemeral_1h_input_tokens":0},"output_tokens":41,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011Cbwdtxgge1VSFVJZMZfdb","attributionAgent":"reviewer","type":"assistant","uuid":"bfc8b312-6797-4256-9521-d014ca639e50","timestamp":"2026-06-11T14:33:43.246Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"bfc8b312-6797-4256-9521-d014ca639e50","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013mCAsDbHRxbXWBFfBJcgMZ","type":"tool_result","content":"Edge case analysis: all defensive. No unreachable crash paths found.\nGradient computation order: magnitude computed before blur, directional computed after blur. Correct design.","is_error":false}]},"uuid":"1a38b6cb-465c-48f6-9dca-49d31c60065b","timestamp":"2026-06-11T14:33:43.452Z","sourceToolAssistantUUID":"bfc8b312-6797-4256-9521-d014ca639e50","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"1a38b6cb-465c-48f6-9dca-49d31c60065b","isSidechain":true,"agentId":"ad154ea4230933d32","message":{"model":"claude-sonnet-4-6","id":"msg_01WDueLSx8yrPCDPbi4jy5Uv","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01W1vub7QLQWHnUzRJPLKk2Y","name":"Bash","input":{"command":"# Check: is thr (= gmean * 3.0) applied consistently?\n# For directional: d >= thr (>= not >)\n# For fallback: v > bestV where bestV starts at thr (so v > thr strictly)\n# This minor asymmetry means a directional point at exactly d==thr will be picked,\n# but a fallback point at exactly v==thr will NOT be picked.\n# This is fine: directional is the preferred path and slightly more permissive is OK.\necho \"Threshold asymmetry: directional uses >=, fallback uses >. Minor, intentional or incidental. No bug.\"\n\n# Check the test for fullSelectionIsLossless in PerspectiveTransformerTest\n# corners = [0,0, 2094,0, 2094,3001, 0,3001]\n# This tests PerspectiveTransformer.outputSize(corners)\n# Not directly related to EdgeSnapper changes, but tests that full-image selection is pixel-perfect.\n# The test documents a regression risk: if inset was applied to full() result, it would fail.\n# Now that inset is removed, full() returns exact image corners, and this test verifies outputSize\n# returns exact dimensions. This is a good regression guard.\necho \"PerspectiveTransformerTest.fullSelectionIsLossless: correct regression guard for removed inset.\"","description":"Final threshold and test analysis"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":634,"cache_read_input_tokens":42192,"cache_creation":{"ephemeral_5m_input_tokens":634,"ephemeral_1h_input_tokens":0},"output_tokens":38,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011Cbwdv3j5KrFuAsgfQn4Wx","attributionAgent":"reviewer","type":"assistant","uuid":"2e594474-5c21-41ea-8b91-c16b8b920c41","timestamp":"2026-06-11T14:33:55.442Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"2e594474-5c21-41ea-8b91-c16b8b920c41","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01W1vub7QLQWHnUzRJPLKk2Y","type":"tool_result","content":"Threshold asymmetry: directional uses >=, fallback uses >. Minor, intentional or incidental. No bug.\nPerspectiveTransformerTest.fullSelectionIsLossless: correct regression guard for removed inset.","is_error":false}]},"uuid":"ceb7fc43-191b-443a-9bb4-b62dff19a743","timestamp":"2026-06-11T14:33:55.647Z","sourceToolAssistantUUID":"2e594474-5c21-41ea-8b91-c16b8b920c41","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"ceb7fc43-191b-443a-9bb4-b62dff19a743","isSidechain":true,"agentId":"ad154ea4230933d32","message":{"model":"claude-sonnet-4-6","id":"msg_01PfuoP55p7WR7GqK7tWAtYM","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_012nezgm4LjnYNZYA8RGVmFf","name":"Bash","input":{"command":"# One concern: the test fullSelectionIsLossless uses CornerCandidates.full() NOT EdgeSnapper.refine().\n# The test exercises PerspectiveTransformer.outputSize(), not the inset removal directly.\n# The actual inset removal is tested only through CornerCandidates.detect() which requires\n# DocAlignerDetector (TFLite) to be available -- not testable in a JVM unit test.\n# But the unit-test coverage of EdgeSnapper itself is strong (6 tests for the new algorithm).\n# The integration behavior (no-inset -> no clipping) is documented in the code comment.\necho \"Test coverage gap: inset removal path in CornerCandidates.detect() not unit-testable (requires TFLite). Acceptable.\"\n\n# Final: check if CLAMP_FRAC (0.07) path is still preserved\n# refine() line 65: if (hypot(dx, dy) < clamp) { apply } else { keep original ML corner }\n# clamp = minOf(w,h) * 0.07\n# This is unchanged from before. Fallback to ML corner when snap moves too far: preserved. OK.\necho \"CLAMP_FRAC fallback preserved: intersected corner must be within 7% of shorter dim from ML corner.\"","description":"Check remaining coverage gaps and CLAMP_FRAC preservation"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":466,"cache_read_input_tokens":42826,"cache_creation":{"ephemeral_5m_input_tokens":466,"ephemeral_1h_input_tokens":0},"output_tokens":47,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CbwdvwnAvz2oJdkyXxbRe","attributionAgent":"reviewer","type":"assistant","uuid":"96decac3-a22f-4ab1-9834-3a58e3083dd8","timestamp":"2026-06-11T14:34:05.967Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"96decac3-a22f-4ab1-9834-3a58e3083dd8","isSidechain":true,"promptId":"8af7757c-b238-4bab-97be-0d43126a3fb3","agentId":"ad154ea4230933d32","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_012nezgm4LjnYNZYA8RGVmFf","type":"tool_result","content":"Test coverage gap: inset removal path in CornerCandidates.detect() not unit-testable (requires TFLite). Acceptable.\nCLAMP_FRAC fallback preserved: intersected corner must be within 7% of shorter dim from ML corner.","is_error":false}]},"uuid":"49550626-f91f-42df-99aa-3192df7aa16f","timestamp":"2026-06-11T14:34:06.161Z","sourceToolAssistantUUID":"96decac3-a22f-4ab1-9834-3a58e3083dd8","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}
{"parentUuid":"49550626-f91f-42df-99aa-3192df7aa16f","isSidechain":true,"agentId":"ad154ea4230933d32","message":{"model":"claude-sonnet-4-6","id":"msg_01LumunvukpnbxSeyaHhkEFD","type":"message","role":"assistant","content":[{"type":"text","text":"All the analysis is complete. Here is the full review.\n\n---\n\n## Code Review Result\n\n### Summary\n\nChanged files: `EdgeSnapper.kt` (algorithm rewrite), `CornerCandidates.kt` (inset removal), `EdgeSnapperTest.kt` (new, 6 tests), `PerspectiveTransformerTest.kt` (1 test added), `app/build.gradle.kts` (version bump).\n\nReview result: **APPROVE**\n\n---\n\n### TRUST 5 Score\n\n| Item | Status | Note |\n|------|--------|------|\n| Tested | PASS | 6 new unit tests for EdgeSnapper, 1 regression guard for PerspectiveTransformer. Core algorithm paths all covered. |\n| Readable | PASS | Functions under 50 lines. Korean comments explain intent clearly. `fitEdge` is 53 lines but the split into `fitLine`/`residuals`/`median` keeps each piece focused. |\n| Unified | PASS | Style matches existing codebase. `internal` visibility on `fitEdge`/`intersect` is correct for test access. |\n| Secured | PASS | Bounds checks on `xi in 0 until w && yi in 0 until h` present. No user-controlled input. |\n| Trackable | PASS | Version bump is consistent (87→88, 1.086→1.087). No SPEC reference needed for a bugfix iteration. |\n\n---\n\n### Structural Check\n\n| File | Lines | Status |\n|------|-------|--------|\n| `EdgeSnapper.kt` | 164 | PASS (well under 200) |\n| `CornerCandidates.kt` | 54 | PASS |\n| `EdgeSnapperTest.kt` | 106 | PASS |\n| `PerspectiveTransformerTest.kt` | 36 | PASS |\n\n---\n\n### Mathematical Correctness Analysis\n\n**Normal direction (TL, TR, BR, BL clockwise).**\n- Top edge (TL→TR): evx=+1, evy=0 → nx=0, ny=+1 (normal points down = inside). Correct.\n- Right edge (TR→BR): evx=0, evy=+1 → nx=-1, ny=0 (normal points left = inside). Correct.\n- Bottom edge (BR→BL): evx=-1, evy=0 → nx=0, ny=-1 (normal points up = inside). Correct.\n- Left edge (BL→TL): evx=0, evy=-1 → nx=+1, ny=0 (normal points right = inside). Correct.\n\n**Scan direction.** Loop `for (s in -band..band)` starts at the outermost position (s=-band), scanning inward. The first directional hit is therefore the outermost paper boundary. This is the core correctness requirement and it is satisfied.\n\n**Directional dot product.** `d = dgx*nx + dgy*ny` is the projection of the (smoothed) gradient onto the inward normal. For a background→paper transition the image gets brighter going inward, meaning the gradient points inward, giving d > 0. Picking the first such point selects the paper boundary over any inner table-border edge. Correct.\n\n**Outlier trimming.** With SAMPLES=24 and the 60% threshold, the minimum point count entering `fitLine` is 14. The cut = max(2×median, 2px) is a robust MAD-style gate. When fewer than max(4, px.size/2) inliers survive trimming, the code falls back to the initial fit with the original residual gate. No crash path found. The math was verified against the test scenario (5 outlier samples at x=35, 19 main samples at x=40): the cut of 2.08px correctly trims the outliers, refitting to x=40. Correct.\n\n**`fitLine` PCA.** `ang = 0.5 * atan2(2*sxy, sxx-syy)` is the standard formula for the principal axis of the 2x2 covariance matrix. Correct.\n\n**`residuals` formula.** `abs((px[k]-l[0]) * (-l[3]) + (py[k]-l[1]) * l[2])` is the perpendicular distance from point (px[k], py[k]) to line through (l[0],l[1]) with direction (l[2],l[3]), using the normal (-l[3], l[2]). Correct.\n\n**`intersect` formula.** Standard Cramer's rule on the 2×2 determinant. The `abs(det) < 1e-6` guard correctly rejects parallel lines. Verified against the test (x=40 vertical meets y=70 horizontal → (40,70)). Correct.\n\n---\n\n### Mat Lifecycle and Exception Safety\n\nFive `Mat` objects (`src`, `gray`, `gx`, `gy`, `grad`) are declared on line 31 and released unconditionally in the `finally` block. `GaussianBlur(gx, gx, ...)` is an in-place operation — OpenCV for Android supports this; no extra `Mat` is created. `dgx`/`dgy` are Java `FloatArray` (heap-managed). No Mat leak found.\n\nThe outer `try/catch(Exception)` returns the original corners on any failure. The `finally` always runs `release()` regardless of exception. Exception safety is complete.\n\n---\n\n### Fallback Regression Verification\n\nWhen no directional candidate exists for any sample (all d < thr), the code falls to the `fallback` path which tracks the strongest-magnitude point, matching pre-rewrite behavior. CLAMP_FRAC (0.07) is unchanged: if the snapped corner is more than 7% of the shorter image dimension away from the ML corner, the ML corner is kept. Both regression-safety paths are preserved.\n\n---\n\n### `inset` Removal Side Effects\n\n`grep` over all source files confirms `inset` has zero remaining callers. The three call sites in `CornerCandidates.detect()` have been updated. `EditorActivity.kt` and `ScanPipeline.kt` call `CornerCandidates.detect()` and `CornerCandidates.full()` — neither ever called `inset` directly. No orphaned reference.\n\n---\n\n### Test Coverage Assessment\n\n| Test | What it verifies | Assessment |\n|------|-----------------|------------|\n| `picksOutermostInwardBrighteningEdgeOverStrongerInnerLine` | Core new behavior: outer directional beats stronger inner edge | Directly tests the bug fix |\n| `fallsBackToStrongestMagnitudeWhenNoDirectionalCandidate` | Regression: fallback path identical to pre-rewrite | Verifies no regression |\n| `rejectsEdgeWhenTooFewBoundaryPoints` | null return when signal absent | ML fallback trigger |\n| `outlierPointsAreTrimmedFromLineFit` | Outlier trimming re-fit converges to true line | New trimming logic |\n| `intersectFindsCrossingOfTwoLines` | Basic intersection math | Geometry correctness |\n| `intersectReturnsNullForParallelLines` | det < 1e-6 guard | Null safety |\n| `fullSelectionIsLossless` | outputSize of full corners is exact | Regression guard for removed inset |\n\nCoverage is proportionate to the risk of the change. The inset removal in `CornerCandidates.detect()` is not directly unit-testable because it requires TFLite (`DocAlignerDetector`), which is acceptable — the behavior is well-documented in the code comment.\n\n---\n\n### Advisory (non-blocking)\n\n**Threshold asymmetry.** The directional path uses `d >= thr` and the fallback path uses `v > bestV` starting at `thr` (so effectively `v > thr` strictly). This means a point at exactly `d == thr` will be picked directionally but a point at exactly `v == thr` will not be picked as fallback. This is a minor incidental asymmetry with no practical consequence (floating-point equality to a computed threshold is essentially impossible in real gradient data), but could be made consistent if desired.\n\n**Shared threshold for directional and magnitude.** `thr = gmean * 3.0` is applied to both the total gradient magnitude (fallback) and the directional dot product (primary). Since `|d| = |grad . n| <= |grad|` by Cauchy-Schwarz, the directional path has a structurally harder threshold to meet than the fallback. This is the intended design choice (directional must be a dominant signal to qualify), confirmed by the Python simulation results. The fallback provides safety when the directional signal is oblique.\n\n---\n\n### Required Changes\n\nNone.\n\n---\n\n```\n🐙 reviewer ─────────────────────\n Verdict: APPROVE | Issues: 0개\n Next: Ready to commit. Use Lore format with versionCode 88 bump as the scope anchor.\n```"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":467,"cache_read_input_tokens":43292,"cache_creation":{"ephemeral_5m_input_tokens":467,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CbwdwirZjToFYXszRRhBb","attributionAgent":"reviewer","type":"assistant","uuid":"72c70348-ff07-494f-bc5e-5f1e3c165246","timestamp":"2026-06-11T14:34:53.951Z","userType":"external","entrypoint":"cli","cwd":"/home/lucas/Android-app/ClearCam","sessionId":"2f7c1ed7-2fe3-4930-ad37-1aa8a7b3d290","version":"2.1.173","gitBranch":"main"}