phase 1

core/api/detect_replay.py

@@ -116,6 +116,65 @@ def list_checkpoints(job_id: str) -> list[CheckpointInfo]:
     return result
 
 
+class CheckpointFrameInfo(BaseModel):
+    seq: int
+    timestamp: float
+    jpeg_b64: str
+
+
+class CheckpointData(BaseModel):
+    job_id: str
+    stage: str
+    profile_name: str
+    video_path: str
+    is_scenario: bool
+    scenario_label: str
+    frames: list[CheckpointFrameInfo]
+    stats: dict = {}
+    config_snapshot: dict = {}
+    stage_output_key: str = ""
+
+
+@router.get("/checkpoints/{job_id}/{stage}", response_model=CheckpointData)
+def get_checkpoint_data(job_id: str, stage: str):
+    """Load checkpoint frames + metadata for the editor UI."""
+    from core.db.detect import get_stage_checkpoint
+    from detect.checkpoint.frames import load_frames_b64
+
+    checkpoint = get_stage_checkpoint(job_id, stage)
+    if not checkpoint:
+        raise HTTPException(status_code=404, detail=f"No checkpoint for {job_id}/{stage}")
+
+    raw_manifest = checkpoint.frames_manifest or {}
+    manifest = {int(k): v for k, v in raw_manifest.items()}
+    frame_metadata = checkpoint.frames_meta or []
+
+    # Only load filtered frames if available, otherwise all
+    filtered = set(checkpoint.filtered_frame_sequences or [])
+    if filtered:
+        manifest = {k: v for k, v in manifest.items() if k in filtered}
+
+    frames_b64 = load_frames_b64(manifest, frame_metadata)
+
+    frame_list = [
+        CheckpointFrameInfo(seq=f["seq"], timestamp=f["timestamp"], jpeg_b64=f["jpeg_b64"])
+        for f in frames_b64
+    ]
+
+    return CheckpointData(
+        job_id=str(checkpoint.job_id),
+        stage=checkpoint.stage,
+        profile_name=checkpoint.profile_name,
+        video_path=checkpoint.video_path,
+        is_scenario=checkpoint.is_scenario,
+        scenario_label=checkpoint.scenario_label,
+        frames=frame_list,
+        stats=checkpoint.stats or {},
+        config_snapshot=checkpoint.config_snapshot or {},
+        stage_output_key=checkpoint.stage_output_key or "",
+    )
+
+
 @router.get("/scenarios", response_model=list[ScenarioInfo])
 def list_scenarios_endpoint():
     """List all available scenarios (bookmarked checkpoints)."""

core/schema/models/detect_jobs.py

@@ -110,7 +110,7 @@ class StageCheckpoint:
     # Scenario — a checkpoint bookmarked for the editor workflow.
     # Created by seeders (manual scripts that populate state from real footage)
     # or captured from a running pipeline. Loaded via URL:
-    #   /detection/?job=<job_id>&stage=<stage>&editor=true
+    #   /detection/?job=<job_id>#/editor/<stage>
     is_scenario: bool = False
     scenario_label: str = ""  # human-readable name, e.g. "chelsea_edges_lowcanny"
 

detect/checkpoint/frames.py

@@ -78,3 +78,34 @@ def load_frames(manifest: dict[int, str], frame_metadata: list[dict]) -> list[Fr
 
     frames.sort(key=lambda f: f.sequence)
     return frames
+
+
+def load_frames_b64(manifest: dict[int, str], frame_metadata: list[dict]) -> list[dict]:
+    """
+    Load frame images from S3 as base64 JPEG — lightweight, no numpy.
+
+    Returns list of dicts: {seq, timestamp, jpeg_b64}
+    """
+    import base64
+    from core.storage.s3 import download_to_temp
+
+    meta_map = {m["sequence"]: m for m in frame_metadata}
+    frames = []
+
+    for seq, key in manifest.items():
+        tmp_path = download_to_temp(BUCKET, key)
+        try:
+            with open(tmp_path, "rb") as f:
+                jpeg_bytes = f.read()
+        finally:
+            os.unlink(tmp_path)
+
+        meta = meta_map.get(seq, {})
+        frames.append({
+            "seq": seq,
+            "timestamp": meta.get("timestamp", 0.0),
+            "jpeg_b64": base64.b64encode(jpeg_bytes).decode(),
+        })
+
+    frames.sort(key=lambda f: f["seq"])
+    return frames

tests/detect/manual/seed_scenario.py

@@ -20,7 +20,7 @@ Usage:
     python tests/detect/manual/seed_scenario.py --video media/mpr/out/chunks/.../chunk_0001.mp4
 
 Then open:
-    http://mpr.local.ar/detection/?job=<JOB_ID>&stage=filter_scenes&editor=true
+    http://mpr.local.ar/detection/?job=<JOB_ID>#/editor/detect_edges
 """
 
 from __future__ import annotations

ui/detection-app/src/App.vue

@@ -78,6 +78,18 @@ function onTimelineResize(delta: number) {
   tableFlex.value = Math.max(0.3, Math.min(3, tableFlex.value - shift))
 }
 
+// Editor sliders sidebar width — drag right = shrink sliders (grow frame)
+const slidersWidth = ref(210)
+function onSlidersResize(delta: number) {
+  slidersWidth.value = Math.max(210, Math.min(350, slidersWidth.value - delta))
+}
+
+// Editor bottom height (overlays bar)
+const editorBottomHeight = ref(50)
+function onEditorBottomResize(delta: number) {
+  editorBottomHeight.value = Math.max(36, Math.min(120, editorBottomHeight.value - delta))
+}
+
 const statusMap: Record<string, 'idle' | 'live' | 'processing' | 'error'> = {
   idle: 'idle',
   connecting: 'processing',
@@ -110,32 +122,108 @@ async function stopPipeline() {
 const currentFrameImage = ref<string | null>(null)
 const currentFrameRef = ref<number | null>(null)
 
+// All checkpoint frames (for scenario mode — scrubbing)
+const checkpointFrames = ref<{ seq: number; timestamp: number; jpeg_b64: string }[]>([])
+const checkpointFrameIndex = ref(0)
+const checkpointStage = ref<string | null>(null)  // which stage the checkpoint is at
+
+
 source.on<{ frame_ref: number; jpeg_b64: string }>('frame_update', (e) => {
   currentFrameImage.value = e.jpeg_b64
   currentFrameRef.value = e.frame_ref
 })
 
+// Load checkpoint data when in scenario mode
+async function loadCheckpoint(job: string, stage: string) {
+  try {
+    const resp = await fetch(`/api/detect/checkpoints/${job}/${stage}`)
+    if (!resp.ok) return
+
+    const data = await resp.json()
+    checkpointFrames.value = data.frames ?? []
+    checkpointStage.value = stage
+
+    // Show first frame
+    if (checkpointFrames.value.length > 0) {
+      checkpointFrameIndex.value = 0
+      const first = checkpointFrames.value[0]
+      currentFrameImage.value = first.jpeg_b64
+      currentFrameRef.value = first.seq
+    }
+
+    status.value = 'idle'
+  } catch (e) {
+    console.error('Failed to load checkpoint:', e)
+  }
+}
+
+function setCheckpointFrame(index: number) {
+  if (index < 0 || index >= checkpointFrames.value.length) return
+  checkpointFrameIndex.value = index
+  const frame = checkpointFrames.value[index]
+  currentFrameImage.value = frame.jpeg_b64
+  currentFrameRef.value = frame.seq
+}
+
+// Load checkpoint when in editor mode with a job (scenario URL)
+// Uses watch to handle both initial load and navigation
+import { watch as vueWatch } from 'vue'
+vueWatch(
+  () => [pipeline.layoutMode, pipeline.editorStage, jobId.value] as const,
+  ([mode, stage, job]) => {
+    if (mode === 'bbox_editor' && stage && job) {
+      const stageMap: Record<string, string> = {
+        detect_edges: 'filter_scenes',
+        detect_contours: 'detect_edges',
+        detect_color: 'detect_contours',
+        merge_regions: 'detect_color',
+      }
+      const cpStage = stageMap[stage] ?? 'filter_scenes'
+      loadCheckpoint(job, cpStage)
+    }
+  },
+  { immediate: true },
+)
+
 // Debug overlays from replay-stage results
 const editorOverlays = ref<FrameOverlay[]>([])
 
+// Boxes from edge detection (local or server)
+const editorBoxes = ref<import('mpr-ui-framework/src/renderers/FrameRenderer.vue').FrameBBox[]>([])
+
 function onReplayResult(result: {
+  regions_by_frame?: Record<string, unknown[]>
   debug?: Record<string, { edge_overlay_b64: string; lines_overlay_b64: string; horizontal_count: number; pair_count: number }>
 }) {
-  const overlays: FrameOverlay[] = []
+  // Update boxes
+  if (result.regions_by_frame) {
+    const firstRegions = Object.values(result.regions_by_frame)[0] as any[] ?? []
+    editorBoxes.value = firstRegions.map((r: any) => ({
+      x: r.x, y: r.y, w: r.w, h: r.h,
+      confidence: r.confidence,
+      label: r.label ?? 'edge_region',
+      stage: 'detect_edges',
+    }))
+  }
+
+  // Update overlays — only when debug data is present, preserve existing otherwise
   if (result.debug) {
-    // Take first frame's debug data (editor shows one frame at a time)
     const firstDebug = Object.values(result.debug)[0]
     if (firstDebug) {
+      const overlays: FrameOverlay[] = []
       if (firstDebug.edge_overlay_b64) {
-        overlays.push({ src: firstDebug.edge_overlay_b64, label: 'Canny edges', visible: true, opacity: 0.4 })
+        // Preserve visibility/opacity from existing overlays if they exist
+        const existing = editorOverlays.value.find(o => o.label === 'Canny edges')
+        overlays.push({ src: firstDebug.edge_overlay_b64, label: 'Canny edges', visible: existing?.visible ?? true, opacity: existing?.opacity ?? 0.25 })
       }
       if (firstDebug.lines_overlay_b64) {
-        overlays.push({ src: firstDebug.lines_overlay_b64, label: 'Hough lines', visible: true, opacity: 0.5 })
+        const existing = editorOverlays.value.find(o => o.label === 'Hough lines')
-      }
+        overlays.push({ src: firstDebug.lines_overlay_b64, label: 'Hough lines', visible: existing?.visible ?? true, opacity: existing?.opacity ?? 0.25 })
-    }
       }
       editorOverlays.value = overlays
     }
+  }
+}
 
 function onJobStarted(newJobId: string) {
   jobId.value = newJobId
@@ -236,12 +324,14 @@ function onJobStarted(newJobId: string) {
 
         <!-- === BBOX EDITOR MODE === -->
         <template v-else-if="pipeline.layoutMode === 'bbox_editor'">
-          <Panel :title="`Region Editor — ${pipeline.editorStage?.replace(/_/g, ' ')}`" :status="status">
+          <div class="editor-layout">
-            <div class="editor-placeholder">
+            <!-- Top: frame + sliders side by side -->
+            <div class="editor-top">
               <div class="editor-frame">
-                <FramePanel :source="source" :status="status" :overlays="editorOverlays" />
+                <FramePanel :source="source" :status="status" :overlays="editorOverlays" :frame-image="currentFrameImage" :editor-boxes="editorBoxes" />
               </div>
-              <div class="editor-tools">
+              <ResizeHandle direction="horizontal" @resize="onSlidersResize" />
+              <div class="editor-sliders" :style="{ width: slidersWidth + 'px' }">
                 <StageConfigSliders
                   v-if="pipeline.editorStage"
                   :stage="pipeline.editorStage"
@@ -250,10 +340,29 @@ function onJobStarted(newJobId: string) {
                   :frame-ref="currentFrameRef"
                   @replay-result="onReplayResult"
                 />
+              </div>
+            </div>
+            <!-- Bottom: debug overlays + close -->
+            <div class="editor-bottom">
+              <div class="overlay-controls">
+                <template v-if="editorOverlays.length > 0">
+                  <label v-for="(overlay, idx) in editorOverlays" :key="idx" class="overlay-toggle">
+                    <input type="checkbox" v-model="overlay.visible" />
+                    <span class="overlay-label">{{ overlay.label }}</span>
+                    <input
+                      type="range"
+                      min="0" max="1" step="0.05"
+                      :value="overlay.opacity ?? 0.5"
+                      @input="(e: Event) => overlay.opacity = Number((e.target as HTMLInputElement).value)"
+                      class="opacity-slider"
+                    />
+                    <span class="opacity-value">{{ Math.round((overlay.opacity ?? 0.5) * 100) }}%</span>
+                  </label>
+                </template>
+              </div>
               <button class="editor-close" @click="pipeline.closeEditor()">✕ Close</button>
             </div>
           </div>
-          </Panel>
         </template>
 
         <!-- === STAGE EDITOR MODE === -->
@@ -279,28 +388,8 @@ function onJobStarted(newJobId: string) {
 
     <!-- Bottom bar: Log or Blob viewer depending on mode -->
     <div class="log-row">
-      <template v-if="pipeline.layoutMode === 'bbox_editor'">
+      <template v-if="pipeline.layoutMode === 'source_selector'">
-        <Panel :title="`Debug Overlays — ${pipeline.editorStage?.replace(/_/g, ' ')}`" :status="status">
+        <!-- no log in source selector -->
-          <div class="overlay-controls">
-            <template v-if="editorOverlays.length > 0">
-              <label v-for="(overlay, idx) in editorOverlays" :key="idx" class="overlay-toggle">
-                <input type="checkbox" v-model="overlay.visible" />
-                <span class="overlay-label">{{ overlay.label }}</span>
-                <input
-                  type="range"
-                  min="0" max="1" step="0.05"
-                  :value="overlay.opacity ?? 0.5"
-                  @input="(e) => overlay.opacity = Number((e.target as HTMLInputElement).value)"
-                  class="opacity-slider"
-                />
-                <span class="opacity-value">{{ Math.round((overlay.opacity ?? 0.5) * 100) }}%</span>
-              </label>
-            </template>
-            <div v-else class="blob-placeholder">
-              Run analysis with debug enabled to see edge and line overlays
-            </div>
-          </div>
-        </Panel>
       </template>
       <template v-else>
         <LogPanel ref="logPanel" :source="source" :status="status" />
@@ -478,34 +567,82 @@ header h1 { font-size: var(--font-size-lg); font-weight: 600; }
 /* Log: full width bottom */
 .log-row {
   flex-shrink: 0;
-  height: 200px;
+  height: 150px;
 }
 
 .empty { color: var(--text-dim); padding: var(--space-6); text-align: center; }
 
-/* Editor placeholders */
+/* Editor layout — frame maximized, sliders right, overlays bottom */
-.editor-placeholder {
+.editor-layout {
   display: flex;
+  flex-direction: column;
   height: 100%;
-  gap: var(--space-2);
+  min-height: 0;
+  overflow: hidden;
+}
+
+.editor-top {
+  display: flex;
+  flex: 1;
+  min-height: 0;
+  overflow: hidden;
 }
 
 .editor-frame {
   flex: 1;
   min-height: 0;
+  min-width: 0;
+  overflow: hidden;
+  display: flex;
+}
+.editor-frame > * {
+  flex: 1;
+  min-height: 0;
+  overflow: hidden;
 }
 
-.editor-tools {
+.editor-sliders {
-  width: 200px;
   flex-shrink: 0;
-  padding: var(--space-3);
+  min-width: 210px;
+  padding: var(--space-2);
   background: var(--surface-2);
-  border-radius: var(--panel-radius);
+  overflow-y: auto;
+  overflow-x: hidden;
+}
+
+.editor-bottom {
+  flex-shrink: 0;
   display: flex;
-  flex-direction: column;
+  align-items: center;
-  gap: var(--space-2);
+  gap: var(--space-4);
-  font-size: var(--font-size-sm);
+  padding: var(--space-2) var(--space-3);
+  background: var(--surface-2);
+  border-top: var(--panel-border);
+  height: 36px;
+}
+
+.editor-close {
+  background: var(--surface-3);
+  border: 1px solid var(--surface-3);
+  border-radius: 4px;
+  padding: 3px 10px;
   color: var(--text-secondary);
+  font-family: var(--font-mono);
+  font-size: var(--font-size-sm);
+  cursor: pointer;
+  margin-left: auto;
+}
+
+.editor-close:hover {
+  background: var(--status-error);
+  color: #000;
+}
+
+/* Stage config editor (placeholder) */
+.editor-placeholder {
+  display: flex;
+  height: 100%;
+  gap: var(--space-2);
 }
 
 .editor-config {
@@ -517,23 +654,6 @@ header h1 { font-size: var(--font-size-lg); font-weight: 600; }
   gap: var(--space-2);
 }
 
-.editor-close {
-  background: var(--surface-3);
-  border: 1px solid var(--surface-3);
-  border-radius: 4px;
-  padding: var(--space-2) var(--space-3);
-  color: var(--text-secondary);
-  font-family: var(--font-mono);
-  font-size: var(--font-size-sm);
-  cursor: pointer;
-  margin-top: auto;
-}
-
-.editor-close:hover {
-  background: var(--status-error);
-  color: #000;
-}
-
 .blob-placeholder {
   padding: var(--space-4);
   color: var(--text-dim);

ui/detection-app/src/components/StageConfigSliders.vue

@@ -1,9 +1,16 @@
 <script setup lang="ts">
-import { ref, onMounted, computed } from 'vue'
+import { ref, onMounted, computed, watch } from 'vue'
+import {
+  runEdgeDetection,
+  runEdgeDetectionDebug,
+  b64ToImageData,
+  imageDataToB64,
+  type EdgeDetectionParams,
+} from 'mpr-ui-framework/src/cv'
 
 interface ConfigField {
   name: string
-  type: string  // "bool" | "int" | "float" | "str"
+  type: string
   default: unknown
   description: string
   min: number | null
@@ -14,16 +21,15 @@ interface ConfigField {
 const props = defineProps<{
   /** Stage name (e.g. "detect_edges") */
   stage: string
-  /** Job ID for replay-stage calls (used as fallback) */
+  /** Job ID (used for server mode fallback) */
   jobId: string
-  /** Currently displayed frame image (base64 JPEG) — sent directly to GPU for fast feedback */
+  /** Currently displayed frame image (base64 JPEG) */
   frameImage?: string | null
   /** Currently displayed frame sequence number */
   frameRef?: number | null
 }>()
 
 const emit = defineEmits<{
-  /** Emitted when replay returns new regions */
   'replay-result': [result: {
     regions_by_frame: Record<string, unknown[]>
     debug: Record<string, { edge_overlay_b64: string; lines_overlay_b64: string; horizontal_count: number; pair_count: number }>
@@ -36,24 +42,50 @@ const loading = ref(false)
 const error = ref<string | null>(null)
 const regionCount = ref<number | null>(null)
 const debugEnabled = ref(true)
+const autoApply = ref(true)  // auto-run on slider change (fast CV); uncheck for heavy stages
+const execMode = ref<'local' | 'server'>('local')
+const execTimeMs = ref<number | null>(null)
+
+// Config field defaults for detect_edges (used when API is unavailable)
+const EDGE_DEFAULTS: ConfigField[] = [
+  { name: 'enabled', type: 'bool', default: true, description: 'Enable edge detection', min: null, max: null, options: null },
+  { name: 'edge_canny_low', type: 'int', default: 50, description: 'Canny low threshold', min: 0, max: 255, options: null },
+  { name: 'edge_canny_high', type: 'int', default: 150, description: 'Canny high threshold', min: 0, max: 255, options: null },
+  { name: 'edge_hough_threshold', type: 'int', default: 80, description: 'Hough accumulator threshold', min: 1, max: 500, options: null },
+  { name: 'edge_hough_min_length', type: 'int', default: 100, description: 'Min line length (px)', min: 10, max: 2000, options: null },
+  { name: 'edge_hough_max_gap', type: 'int', default: 10, description: 'Max line gap (px)', min: 1, max: 100, options: null },
+  { name: 'edge_pair_max_distance', type: 'int', default: 200, description: 'Max pair distance (px)', min: 10, max: 500, options: null },
+  { name: 'edge_pair_min_distance', type: 'int', default: 15, description: 'Min pair distance (px)', min: 5, max: 200, options: null },
+]
 
-// Fetch stage config fields from API
 onMounted(async () => {
+  // Try loading from API, fall back to hardcoded defaults
   try {
     const resp = await fetch(`/api/detect/config/stages/${props.stage}`)
-    if (!resp.ok) {
+    if (resp.ok) {
-      error.value = `Failed to load config: ${resp.status}`
-      return
-    }
       const data = await resp.json()
       fields.value = data.config_fields ?? []
+    } else {
+      fields.value = EDGE_DEFAULTS
+    }
+  } catch {
+    fields.value = EDGE_DEFAULTS
+  }
 
-    // Initialize values from defaults
   for (const f of fields.value) {
     values.value[f.name] = f.default
   }
-  } catch (e) {
+
-    error.value = `Failed to load config: ${e}`
+  // Auto-run on first frame if already available
+  if (props.frameImage) {
+    applyDetection()
+  }
+})
+
+// Auto-run when frame arrives after mount (checkpoint load is async)
+watch(() => props.frameImage, (newVal, oldVal) => {
+  if (newVal && !oldVal && fields.value.length > 0) {
+    applyDetection()
   }
 })
 
@@ -64,41 +96,97 @@ function resetDefaults() {
   for (const f of fields.value) {
     values.value[f.name] = f.default
   }
+  applyDetection()
 }
 
 let debounceTimer: ReturnType<typeof setTimeout> | null = null
 
 function onSliderChange() {
-  // Debounce — wait 300ms after last change before calling replay
+  if (!autoApply.value) return
   if (debounceTimer) clearTimeout(debounceTimer)
-  debounceTimer = setTimeout(() => applyReplay(), 300)
+  debounceTimer = setTimeout(() => applyDetection(), 150)
+}
+
+async function applyDetection() {
+  if (!props.frameImage) {
+    error.value = 'No frame available'
+    return
   }
 
-async function applyReplay() {
   loading.value = true
   error.value = null
+  execTimeMs.value = null
 
-  // Direct GPU call — send the frame image + current slider params
+  try {
-  // Skip checkpoint/replay path for ~50-100ms round trips instead of seconds
+    if (execMode.value === 'local') {
-  if (props.frameImage && props.stage === 'detect_edges') {
+      await runLocal()
-    await callGpuDirect()
+    } else {
-    return
+      await runServer()
     }
-
+  } catch (e) {
-  // Fallback: replay-stage path (for stages without direct GPU endpoint)
+    error.value = `${execMode.value} failed: ${e}`
-  if (!props.jobId) {
+  } finally {
-    error.value = 'No frame image or job ID available'
     loading.value = false
-    return
   }
-  await callReplayStage()
 }
 
-async function callGpuDirect() {
+/** Browser-side CV — no network, instant */
-  const body: Record<string, unknown> = {
+async function runLocal() {
-    image: props.frameImage,
+  const t0 = performance.now()
+
+  // Decode base64 JPEG → ImageData
+  const imageData = await b64ToImageData(props.frameImage!)
+
+  // Build params from slider values
+  const params: Partial<EdgeDetectionParams> = {
+    cannyLow: values.value['edge_canny_low'] as number,
+    cannyHigh: values.value['edge_canny_high'] as number,
+    houghThreshold: values.value['edge_hough_threshold'] as number,
+    houghMinLength: values.value['edge_hough_min_length'] as number,
+    houghMaxGap: values.value['edge_hough_max_gap'] as number,
+    pairMaxDistance: values.value['edge_pair_max_distance'] as number,
+    pairMinDistance: values.value['edge_pair_min_distance'] as number,
   }
-  // Pass current slider values as edge detection params
+
+  const frameKey = String(props.frameRef ?? 0)
+
+  if (debugEnabled.value) {
+    const result = await runEdgeDetectionDebug(imageData, params)
+    execTimeMs.value = Math.round(performance.now() - t0)
+    regionCount.value = result.regions.length
+
+    // Convert ImageData overlays to base64 for FrameRenderer
+    const edgeB64 = await imageDataToB64(result.edgeImageData)
+    const linesB64 = await imageDataToB64(result.linesImageData)
+
+    emit('replay-result', {
+      regions_by_frame: { [frameKey]: result.regions },
+      debug: {
+        [frameKey]: {
+          edge_overlay_b64: edgeB64,
+          lines_overlay_b64: linesB64,
+          horizontal_count: result.horizontalCount,
+          pair_count: result.pairCount,
+        },
+      },
+    })
+  } else {
+    const result = await runEdgeDetection(imageData, params)
+    execTimeMs.value = Math.round(performance.now() - t0)
+    regionCount.value = result.regions.length
+
+    emit('replay-result', {
+      regions_by_frame: { [frameKey]: result.regions },
+      debug: {},
+    })
+  }
+}
+
+/** Server-side CV — calls GPU box via proxy */
+async function runServer() {
+  const t0 = performance.now()
+
+  const body: Record<string, unknown> = { image: props.frameImage }
   for (const f of fields.value) {
     if (f.name !== 'enabled') {
       body[f.name] = values.value[f.name]
@@ -109,7 +197,6 @@ async function callGpuDirect() {
     ? '/api/detect/gpu/detect_edges/debug'
     : '/api/detect/gpu/detect_edges'
 
-  try {
   const resp = await fetch(endpoint, {
     method: 'POST',
     headers: { 'Content-Type': 'application/json' },
@@ -118,16 +205,15 @@ async function callGpuDirect() {
 
   if (!resp.ok) {
     const detail = await resp.text()
-      error.value = `GPU call failed: ${detail}`
+    throw new Error(detail)
-      return
   }
 
   const data = await resp.json()
+  execTimeMs.value = Math.round(performance.now() - t0)
   regionCount.value = data.regions?.length ?? 0
 
-    // Build result in the same shape the parent expects
   const frameKey = String(props.frameRef ?? 0)
-    const result: Record<string, unknown> = {
+  const result: any = {
     regions_by_frame: { [frameKey]: data.regions ?? [] },
     debug: {},
   }
@@ -138,69 +224,10 @@ async function callGpuDirect() {
         lines_overlay_b64: data.lines_overlay_b64 ?? '',
         horizontal_count: data.horizontal_count ?? 0,
         pair_count: data.pair_count ?? 0,
+      },
     }
   }
-    }
-    emit('replay-result', result as any)
-  } catch (e) {
-    error.value = `GPU call failed: ${e}`
-  } finally {
-    loading.value = false
-  }
-}
-
-async function callReplayStage() {
-  const overrides: Record<string, unknown> = {}
-  for (const f of fields.value) {
-    if (values.value[f.name] !== f.default) {
-      overrides[f.name] = values.value[f.name]
-    }
-  }
-
-  const overrideKey = stageToOverrideKey(props.stage)
-  const configOverrides = Object.keys(overrides).length > 0
-    ? { [overrideKey]: overrides }
-    : null
-
-  const body = {
-    job_id: props.jobId,
-    stage: props.stage,
-    frame_refs: props.frameRef != null ? [props.frameRef] : null,
-    config_overrides: configOverrides,
-    debug: debugEnabled.value,
-  }
-
-  try {
-    const resp = await fetch('/api/detect/replay-stage', {
-      method: 'POST',
-      headers: { 'Content-Type': 'application/json' },
-      body: JSON.stringify(body),
-    })
-
-    if (!resp.ok) {
-      const detail = await resp.text()
-      error.value = `Replay failed: ${detail}`
-      return
-    }
-
-    const result = await resp.json()
-    regionCount.value = result.region_count ?? 0
   emit('replay-result', result)
-  } catch (e) {
-    error.value = `Replay failed: ${e}`
-  } finally {
-    loading.value = false
-  }
-}
-
-function stageToOverrideKey(stage: string): string {
-  const map: Record<string, string> = {
-    detect_edges: 'region_analysis',
-    detect_objects: 'detection',
-    run_ocr: 'ocr',
-    match_brands: 'resolver',
-  }
-  return map[stage] || stage
 }
 </script>
 
@@ -211,6 +238,18 @@ function stageToOverrideKey(stage: string): string {
       <button class="sliders-reset" @click="resetDefaults" title="Reset to defaults">Reset</button>
     </div>
 
+    <!-- Local / Server toggle -->
+    <div class="mode-toggle">
+      <button
+        :class="['mode-btn', { active: execMode === 'local' }]"
+        @click="execMode = 'local'"
+      >Local</button>
+      <button
+        :class="['mode-btn', { active: execMode === 'server' }]"
+        @click="execMode = 'server'"
+      >Server</button>
+    </div>
+
     <div v-if="error" class="sliders-error">{{ error }}</div>
 
     <div class="sliders-list">
@@ -245,20 +284,25 @@ function stageToOverrideKey(stage: string): string {
       </div>
     </div>
 
-    <!-- Debug overlay toggle -->
+    <!-- Footer -->
-    <label class="slider-field bool-field debug-toggle">
-      <input type="checkbox" v-model="debugEnabled" @change="onSliderChange" />
-      <span class="field-label">Show edge overlays</span>
-    </label>
-
-    <!-- Feedback -->
     <div class="sliders-footer">
-      <button class="apply-btn" :disabled="loading" @click="applyReplay">
+      <button
+        class="apply-btn"
+        :disabled="loading || autoApply"
+        @click="applyDetection"
+      >
         {{ loading ? 'Running...' : 'Apply' }}
       </button>
+      <label class="auto-apply-toggle">
+        <input type="checkbox" v-model="autoApply" />
+        <span>Auto</span>
+      </label>
       <span v-if="regionCount != null" class="region-count">
         {{ regionCount }} regions
       </span>
+      <span v-if="execTimeMs != null" class="exec-time">
+        {{ execTimeMs }}ms
+      </span>
     </div>
   </div>
 </template>
@@ -298,6 +342,34 @@ function stageToOverrideKey(stage: string): string {
 }
 .sliders-reset:hover { background: var(--surface-2); }
 
+.mode-toggle {
+  display: flex;
+  gap: 1px;
+  background: var(--surface-2);
+  border-radius: 3px;
+  overflow: hidden;
+}
+
+.mode-btn {
+  flex: 1;
+  padding: 3px 8px;
+  border: none;
+  background: var(--surface-2);
+  color: var(--text-dim);
+  font-family: var(--font-mono);
+  font-size: 9px;
+  cursor: pointer;
+  transition: all 0.15s;
+}
+.mode-btn.active {
+  background: var(--surface-3);
+  color: var(--text-primary);
+  font-weight: 600;
+}
+.mode-btn:hover:not(.active) {
+  color: var(--text-secondary);
+}
+
 .sliders-error {
   color: var(--status-error);
   font-size: 10px;
@@ -354,7 +426,6 @@ function stageToOverrideKey(stage: string): string {
   color: var(--text-dim);
 }
 
-/* Range slider styling */
 input[type="range"] {
   -webkit-appearance: none;
   appearance: none;
@@ -388,11 +459,6 @@ input[type="checkbox"] {
   accent-color: #00bcd4;
 }
 
-.debug-toggle {
-  padding-top: var(--space-1);
-  border-top: var(--panel-border);
-}
-
 .sliders-footer {
   display: flex;
   align-items: center;
@@ -415,8 +481,25 @@ input[type="checkbox"] {
 .apply-btn:hover { opacity: 0.85; }
 .apply-btn:disabled { opacity: 0.4; cursor: not-allowed; }
 
+.auto-apply-toggle {
+  display: flex;
+  align-items: center;
+  gap: 4px;
+  font-size: 9px;
+  color: var(--text-secondary);
+  cursor: pointer;
+}
+
+.auto-apply-toggle input { accent-color: #00bcd4; }
+
 .region-count {
   color: var(--text-secondary);
   font-size: 10px;
 }
+
+.exec-time {
+  color: var(--text-dim);
+  font-size: 9px;
+  margin-left: auto;
+}
 </style>

ui/detection-app/src/panels/FramePanel.vue

@@ -1,5 +1,5 @@
 <script setup lang="ts">
-import { ref, computed } from 'vue'
+import { ref, computed, watch } from 'vue'
 import { Panel } from 'mpr-ui-framework'
 import FrameRenderer from 'mpr-ui-framework/src/renderers/FrameRenderer.vue'
 import type { FrameBBox, FrameOverlay } from 'mpr-ui-framework/src/renderers/FrameRenderer.vue'
@@ -10,9 +10,18 @@ const props = defineProps<{
   status?: 'idle' | 'live' | 'processing' | 'error'
   /** Debug overlay layers passed from parent (editor mode) */
   overlays?: FrameOverlay[]
+  /** Frame image from checkpoint (scenario mode) — overrides SSE */
+  frameImage?: string | null
+  /** Boxes from editor (local CV or server) — merged with SSE boxes */
+  editorBoxes?: import('mpr-ui-framework/src/renderers/FrameRenderer.vue').FrameBBox[]
 }>()
 
-const imageSrc = ref('')
+const imageSrc = ref(props.frameImage ?? '')
+
+// Sync prop → internal ref when checkpoint frame changes
+watch(() => props.frameImage, (v) => {
+  if (v) imageSrc.value = v
+})
 
 // Per-stage box accumulation
 const stageBoxes = ref<Record<string, FrameBBox[]>>({})
@@ -117,14 +126,19 @@ function sourceToStage(source: string): string {
   return map[source] || 'match_brands'
 }
 
-// Filtered boxes — show all toggled-on stages
+// Filtered boxes — show all toggled-on stages + editor boxes
 const visibleBoxes = computed<FrameBBox[]>(() => {
   const result: FrameBBox[] = []
+  // SSE boxes filtered by toggles
   for (const [stage, boxes] of Object.entries(stageBoxes.value)) {
     if (activeToggles.value.has(stage)) {
       result.push(...boxes)
     }
   }
+  // Editor boxes (from local CV or server) — always shown
+  if (props.editorBoxes?.length) {
+    result.push(...props.editorBoxes)
+  }
   return result
 })
 

ui/detection-app/src/panels/PipelineGraphPanel.vue

@@ -7,7 +7,7 @@ import type { DataSource } from 'mpr-ui-framework'
 import { usePipelineStore } from '../stores/pipeline'
 
 const PIPELINE_NODES = [
-  'extract_frames', 'filter_scenes', 'detect_objects', 'preprocess',
+  'extract_frames', 'filter_scenes', 'detect_edges', 'detect_objects', 'preprocess',
   'run_ocr', 'match_brands', 'escalate_vlm', 'escalate_cloud', 'compile_report',
 ]
 

ui/framework/src/cv/edges.ts

@@ -0,0 +1,278 @@
+/**
+ * Edge detection — TypeScript port of gpu/models/cv/edges.py
+ *
+ * 1:1 with the Python version. Same algorithm, same parameters,
+ * same output format. Runs in the browser, no network.
+ */
+
+import { toGrayscale, canny } from './imageOps'
+import { houghLinesP, type LineSegment } from './hough'
+
+export interface EdgeRegion {
+  x: number
+  y: number
+  w: number
+  h: number
+  confidence: number
+  label: string
+}
+
+export interface EdgeDetectionParams {
+  cannyLow: number
+  cannyHigh: number
+  houghThreshold: number
+  houghMinLength: number
+  houghMaxGap: number
+  pairMaxDistance: number
+  pairMinDistance: number
+}
+
+export interface EdgeDetectionResult {
+  regions: EdgeRegion[]
+}
+
+export interface EdgeDetectionDebugResult extends EdgeDetectionResult {
+  edgeImageData: ImageData    // Canny output for overlay
+  linesImageData: ImageData   // Frame with Hough lines drawn
+  horizontalCount: number
+  pairCount: number
+}
+
+type HLine = { xMin: number; xMax: number; yMid: number; length: number }
+
+/** Set a pixel on ImageData with bounds check */
+function setPixel(img: ImageData, x: number, y: number, r: number, g: number, b: number) {
+  if (x >= 0 && x < img.width && y >= 0 && y < img.height) {
+    const p = (y * img.width + x) * 4
+    img.data[p] = r
+    img.data[p + 1] = g
+    img.data[p + 2] = b
+    img.data[p + 3] = 255
+  }
+}
+
+/** Bresenham line drawing with thickness */
+function drawLineThick(
+  img: ImageData,
+  x0: number, y0: number, x1: number, y1: number,
+  r: number, g: number, b: number,
+  thickness: number = 1,
+) {
+  const dx = Math.abs(x1 - x0)
+  const dy = Math.abs(y1 - y0)
+  const sx = x0 < x1 ? 1 : -1
+  const sy = y0 < y1 ? 1 : -1
+  let err = dx - dy
+  const half = Math.floor(thickness / 2)
+
+  while (true) {
+    for (let oy = -half; oy <= half; oy++) {
+      for (let ox = -half; ox <= half; ox++) {
+        setPixel(img, x0 + ox, y0 + oy, r, g, b)
+      }
+    }
+    if (x0 === x1 && y0 === y1) break
+    const e2 = 2 * err
+    if (e2 > -dy) { err -= dy; x0 += sx }
+    if (e2 < dx) { err += dx; y0 += sy }
+  }
+}
+
+const DEFAULT_PARAMS: EdgeDetectionParams = {
+  cannyLow: 50,
+  cannyHigh: 150,
+  houghThreshold: 80,
+  houghMinLength: 100,
+  houghMaxGap: 10,
+  pairMaxDistance: 200,
+  pairMinDistance: 15,
+}
+
+/** Filter to near-horizontal lines (within 10 degrees) */
+function filterHorizontal(lines: LineSegment[], maxAngleDeg: number = 10): HLine[] {
+  const maxSlope = Math.tan((maxAngleDeg * Math.PI) / 180)
+  const result: HLine[] = []
+
+  for (const line of lines) {
+    const dx = line.x2 - line.x1
+    if (dx === 0) continue
+    const slope = Math.abs((line.y2 - line.y1) / dx)
+    if (slope <= maxSlope) {
+      const yMid = (line.y1 + line.y2) / 2
+      const xMin = Math.min(line.x1, line.x2)
+      const xMax = Math.max(line.x1, line.x2)
+      const length = Math.sqrt(dx * dx + (line.y2 - line.y1) ** 2)
+      result.push({ xMin, xMax, yMid, length })
+    }
+  }
+  return result
+}
+
+/** Find pairs of horizontal lines that could be top/bottom of a hoarding */
+function findLinePairs(
+  horizontals: HLine[],
+  minDistance: number,
+  maxDistance: number,
+): [HLine, HLine][] {
+  const sorted = [...horizontals].sort((a, b) => a.yMid - b.yMid)
+  const pairs: [HLine, HLine][] = []
+  const used = new Set<number>()
+
+  for (let i = 0; i < sorted.length; i++) {
+    if (used.has(i)) continue
+    const top = sorted[i]
+
+    for (let j = i + 1; j < sorted.length; j++) {
+      if (used.has(j)) continue
+      const bottom = sorted[j]
+      const yGap = bottom.yMid - top.yMid
+
+      if (yGap < minDistance) continue
+      if (yGap > maxDistance) break
+
+      // Check horizontal overlap (50% of shorter line)
+      const overlapStart = Math.max(top.xMin, bottom.xMin)
+      const overlapEnd = Math.min(top.xMax, bottom.xMax)
+      const overlap = overlapEnd - overlapStart
+      const shorterLength = Math.min(top.xMax - top.xMin, bottom.xMax - bottom.xMin)
+
+      if (shorterLength > 0 && overlap / shorterLength >= 0.5) {
+        pairs.push([top, bottom])
+        used.add(i)
+        used.add(j)
+        break
+      }
+    }
+  }
+  return pairs
+}
+
+/** Convert a line pair to a bounding box */
+function pairToBox(
+  top: HLine,
+  bottom: HLine,
+  frameWidth: number,
+  frameHeight: number,
+): EdgeRegion | null {
+  const x = Math.max(0, Math.min(top.xMin, bottom.xMin))
+  const y = Math.max(0, top.yMid)
+  const x2 = Math.min(frameWidth, Math.max(top.xMax, bottom.xMax))
+  const y2 = Math.min(frameHeight, bottom.yMid)
+  const w = x2 - x
+  const h = y2 - y
+
+  if (w < 20 || h < 5) return null
+
+  const avgLineLength = (top.length + bottom.length) / 2
+  const coverage = Math.min(1.0, avgLineLength / Math.max(w, 1))
+
+  return {
+    x: Math.round(x),
+    y: Math.round(y),
+    w: Math.round(w),
+    h: Math.round(h),
+    confidence: Math.round(coverage * 1000) / 1000,
+    label: 'edge_region',
+  }
+}
+
+/**
+ * Detect edges in an RGBA ImageData.
+ *
+ * Equivalent to gpu/models/cv/edges.py detect_edges()
+ */
+export function detectEdges(
+  imageData: ImageData,
+  params: Partial<EdgeDetectionParams> = {},
+): EdgeDetectionResult {
+  const p = { ...DEFAULT_PARAMS, ...params }
+  const { width, height } = imageData
+
+  const gray = toGrayscale(imageData.data, width, height)
+  const edges = canny(gray, width, height, p.cannyLow, p.cannyHigh)
+
+  const rawLines = houghLinesP(edges, width, height, p.houghThreshold, p.houghMinLength, p.houghMaxGap)
+  const horizontals = filterHorizontal(rawLines)
+
+  if (horizontals.length < 2) return { regions: [] }
+
+  const pairs = findLinePairs(horizontals, p.pairMinDistance, p.pairMaxDistance)
+  const regions: EdgeRegion[] = []
+  for (const [top, bottom] of pairs) {
+    const box = pairToBox(top, bottom, width, height)
+    if (box) regions.push(box)
+  }
+
+  return { regions }
+}
+
+/**
+ * Detect edges with debug visualizations.
+ *
+ * Equivalent to gpu/models/cv/edges.py detect_edges_debug()
+ */
+export function detectEdgesDebug(
+  imageData: ImageData,
+  params: Partial<EdgeDetectionParams> = {},
+): EdgeDetectionDebugResult {
+  const p = { ...DEFAULT_PARAMS, ...params }
+  const { width, height, data } = imageData
+
+  const gray = toGrayscale(data, width, height)
+  const edges = canny(gray, width, height, p.cannyLow, p.cannyHigh)
+
+  // Edge overlay — white edges on black
+  const edgeImageData = new ImageData(width, height)
+  for (let i = 0; i < edges.length; i++) {
+    const px = i * 4
+    edgeImageData.data[px] = edges[i]
+    edgeImageData.data[px + 1] = edges[i]
+    edgeImageData.data[px + 2] = edges[i]
+    edgeImageData.data[px + 3] = 255
+  }
+
+  const rawLines = houghLinesP(edges, width, height, p.houghThreshold, p.houghMinLength, p.houghMaxGap)
+  const horizontals = filterHorizontal(rawLines)
+
+  // Lines overlay — darken original frame so lines pop, then draw
+  const linesImageData = new ImageData(new Uint8ClampedArray(data), width, height)
+  for (let i = 0; i < linesImageData.data.length; i += 4) {
+    linesImageData.data[i] = Math.round(linesImageData.data[i] * 0.3)
+    linesImageData.data[i + 1] = Math.round(linesImageData.data[i + 1] * 0.3)
+    linesImageData.data[i + 2] = Math.round(linesImageData.data[i + 2] * 0.3)
+  }
+
+  // Draw all Hough lines in red (3px thick)
+  for (const line of rawLines) {
+    drawLineThick(linesImageData, line.x1, line.y1, line.x2, line.y2, 255, 50, 50, 2)
+  }
+
+  // Draw horizontal lines in cyan (3px thick)
+  for (const h of horizontals) {
+    drawLineThick(linesImageData, Math.round(h.xMin), Math.round(h.yMid), Math.round(h.xMax), Math.round(h.yMid), 0, 255, 255, 3)
+  }
+
+  const pairs = horizontals.length >= 2
+    ? findLinePairs(horizontals, p.pairMinDistance, p.pairMaxDistance)
+    : []
+
+  // Draw paired lines in bright green (4px thick)
+  for (const [top, bottom] of pairs) {
+    drawLineThick(linesImageData, Math.round(top.xMin), Math.round(top.yMid), Math.round(top.xMax), Math.round(top.yMid), 0, 255, 0, 4)
+    drawLineThick(linesImageData, Math.round(bottom.xMin), Math.round(bottom.yMid), Math.round(bottom.xMax), Math.round(bottom.yMid), 0, 255, 0, 4)
+  }
+
+  const regions: EdgeRegion[] = []
+  for (const [top, bottom] of pairs) {
+    const box = pairToBox(top, bottom, width, height)
+    if (box) regions.push(box)
+  }
+
+  return {
+    regions,
+    edgeImageData,
+    linesImageData,
+    horizontalCount: horizontals.length,
+    pairCount: pairs.length,
+  }
+}

ui/framework/src/cv/hough.ts

@@ -0,0 +1,147 @@
+/**
+ * Probabilistic Hough Line Transform — pure TypeScript.
+ *
+ * Equivalent to cv2.HoughLinesP. Finds line segments in a binary edge image.
+ */
+
+export interface LineSegment {
+  x1: number
+  y1: number
+  x2: number
+  y2: number
+}
+
+/**
+ * Probabilistic Hough Line Transform.
+ *
+ * @param edges - Binary edge image (255 = edge, 0 = not)
+ * @param width - Image width
+ * @param height - Image height
+ * @param threshold - Accumulator threshold (min votes for a line)
+ * @param minLineLength - Minimum line length in pixels
+ * @param maxLineGap - Maximum gap between points on the same line
+ */
+export function houghLinesP(
+  edges: Uint8Array,
+  width: number,
+  height: number,
+  threshold: number,
+  minLineLength: number,
+  maxLineGap: number,
+): LineSegment[] {
+  const diag = Math.ceil(Math.sqrt(width * width + height * height))
+  const numAngles = 180
+  const rhoMax = diag
+
+  // Precompute sin/cos tables
+  const cosTable = new Float64Array(numAngles)
+  const sinTable = new Float64Array(numAngles)
+  for (let t = 0; t < numAngles; t++) {
+    const angle = (t * Math.PI) / numAngles
+    cosTable[t] = Math.cos(angle)
+    sinTable[t] = Math.sin(angle)
+  }
+
+  // Collect edge points
+  const edgePoints: [number, number][] = []
+  for (let y = 0; y < height; y++) {
+    for (let x = 0; x < width; x++) {
+      if (edges[y * width + x] === 255) {
+        edgePoints.push([x, y])
+      }
+    }
+  }
+
+  if (edgePoints.length === 0) return []
+
+  // Shuffle edge points for probabilistic sampling
+  for (let i = edgePoints.length - 1; i > 0; i--) {
+    const j = Math.floor(Math.random() * (i + 1))
+    const tmp = edgePoints[i]
+    edgePoints[i] = edgePoints[j]
+    edgePoints[j] = tmp
+  }
+
+  // Accumulator
+  const accum = new Int32Array(numAngles * (2 * rhoMax + 1))
+  const used = new Uint8Array(width * height)
+  const lines: LineSegment[] = []
+
+  for (const [px, py] of edgePoints) {
+    if (used[py * width + px]) continue
+
+    // Vote
+    let maxVotes = 0
+    let bestTheta = 0
+    for (let t = 0; t < numAngles; t++) {
+      const rho = Math.round(px * cosTable[t] + py * sinTable[t]) + rhoMax
+      const idx = t * (2 * rhoMax + 1) + rho
+      accum[idx]++
+      if (accum[idx] > maxVotes) {
+        maxVotes = accum[idx]
+        bestTheta = t
+      }
+    }
+
+    if (maxVotes < threshold) continue
+
+    // Walk along the line at bestTheta through (px, py)
+    const ct = cosTable[bestTheta]
+    const st = sinTable[bestTheta]
+
+    // Line direction is perpendicular to (cos, sin)
+    const dx = -st
+    const dy = ct
+
+    // Walk forward and backward to find line extent
+    const walkLine = (startX: number, startY: number, dirX: number, dirY: number): [number, number] => {
+      let lastEdgeX = startX
+      let lastEdgeY = startY
+      let gap = 0
+      let cx = startX
+      let cy = startY
+
+      for (let step = 1; step < Math.max(width, height); step++) {
+        const nx = Math.round(cx + dirX * step)
+        const ny = Math.round(cy + dirY * step)
+        if (nx < 0 || nx >= width || ny < 0 || ny >= height) break
+
+        if (edges[ny * width + nx] === 255 && !used[ny * width + nx]) {
+          lastEdgeX = nx
+          lastEdgeY = ny
+          gap = 0
+        } else {
+          gap++
+          if (gap > maxLineGap) break
+        }
+      }
+      return [lastEdgeX, lastEdgeY]
+    }
+
+    const [x1, y1] = walkLine(px, py, -dx, -dy)
+    const [x2, y2] = walkLine(px, py, dx, dy)
+
+    const length = Math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
+    if (length < minLineLength) continue
+
+    // Mark pixels as used
+    const steps = Math.ceil(length)
+    for (let s = 0; s <= steps; s++) {
+      const mx = Math.round(x1 + (x2 - x1) * s / steps)
+      const my = Math.round(y1 + (y2 - y1) * s / steps)
+      if (mx >= 0 && mx < width && my >= 0 && my < height) {
+        used[my * width + mx] = 1
+      }
+    }
+
+    lines.push({ x1, y1, x2, y2 })
+
+    // Unvote (clean accumulator for used points)
+    for (let t = 0; t < numAngles; t++) {
+      const rho = Math.round(px * cosTable[t] + py * sinTable[t]) + rhoMax
+      accum[t * (2 * rhoMax + 1) + rho]--
+    }
+  }
+
+  return lines
+}

ui/framework/src/cv/imageOps.ts

@@ -0,0 +1,190 @@
+/**
+ * Pure TypeScript image operations — no OpenCV dependency.
+ *
+ * These implement the subset of CV operations needed for the edge
+ * detection editor. Same algorithms as the Python/OpenCV versions
+ * but running in the browser with zero WASM overhead.
+ */
+
+/** Grayscale from RGBA ImageData */
+export function toGrayscale(data: Uint8ClampedArray, width: number, height: number): Uint8Array {
+  const gray = new Uint8Array(width * height)
+  for (let i = 0; i < gray.length; i++) {
+    const p = i * 4
+    // ITU-R BT.601 luma
+    gray[i] = Math.round(0.299 * data[p] + 0.587 * data[p + 1] + 0.114 * data[p + 2])
+  }
+  return gray
+}
+
+/** 5x5 Gaussian blur */
+export function gaussianBlur(src: Uint8Array, width: number, height: number): Uint8Array {
+  // 5x5 Gaussian kernel (sigma ~1.4, matches OpenCV default for Canny)
+  const kernel = [
+    2, 4, 5, 4, 2,
+    4, 9, 12, 9, 4,
+    5, 12, 15, 12, 5,
+    4, 9, 12, 9, 4,
+    2, 4, 5, 4, 2,
+  ]
+  const kSum = 159
+  const out = new Uint8Array(width * height)
+
+  for (let y = 2; y < height - 2; y++) {
+    for (let x = 2; x < width - 2; x++) {
+      let sum = 0
+      for (let ky = -2; ky <= 2; ky++) {
+        for (let kx = -2; kx <= 2; kx++) {
+          sum += src[(y + ky) * width + (x + kx)] * kernel[(ky + 2) * 5 + (kx + 2)]
+        }
+      }
+      out[y * width + x] = Math.round(sum / kSum)
+    }
+  }
+  return out
+}
+
+/** Sobel gradients → magnitude + direction */
+export function sobelGradients(
+  src: Uint8Array,
+  width: number,
+  height: number,
+): { magnitude: Float32Array; direction: Float32Array } {
+  const size = width * height
+  const magnitude = new Float32Array(size)
+  const direction = new Float32Array(size)
+
+  for (let y = 1; y < height - 1; y++) {
+    for (let x = 1; x < width - 1; x++) {
+      const i = y * width + x
+      // Sobel 3x3
+      const gx =
+        -src[(y - 1) * width + (x - 1)] - 2 * src[y * width + (x - 1)] - src[(y + 1) * width + (x - 1)] +
+        src[(y - 1) * width + (x + 1)] + 2 * src[y * width + (x + 1)] + src[(y + 1) * width + (x + 1)]
+      const gy =
+        -src[(y - 1) * width + (x - 1)] - 2 * src[(y - 1) * width + x] - src[(y - 1) * width + (x + 1)] +
+        src[(y + 1) * width + (x - 1)] + 2 * src[(y + 1) * width + x] + src[(y + 1) * width + (x + 1)]
+
+      magnitude[i] = Math.sqrt(gx * gx + gy * gy)
+      direction[i] = Math.atan2(gy, gx)
+    }
+  }
+  return { magnitude, direction }
+}
+
+/** Non-maximum suppression for Canny */
+export function nonMaxSuppression(
+  magnitude: Float32Array,
+  direction: Float32Array,
+  width: number,
+  height: number,
+): Float32Array {
+  const out = new Float32Array(width * height)
+
+  for (let y = 1; y < height - 1; y++) {
+    for (let x = 1; x < width - 1; x++) {
+      const i = y * width + x
+      const mag = magnitude[i]
+      if (mag === 0) continue
+
+      // Quantize direction to 4 angles (0, 45, 90, 135)
+      let angle = (direction[i] * 180) / Math.PI
+      if (angle < 0) angle += 180
+
+      let n1 = 0, n2 = 0
+      if ((angle < 22.5) || (angle >= 157.5)) {
+        n1 = magnitude[y * width + (x + 1)]
+        n2 = magnitude[y * width + (x - 1)]
+      } else if (angle < 67.5) {
+        n1 = magnitude[(y - 1) * width + (x + 1)]
+        n2 = magnitude[(y + 1) * width + (x - 1)]
+      } else if (angle < 112.5) {
+        n1 = magnitude[(y - 1) * width + x]
+        n2 = magnitude[(y + 1) * width + x]
+      } else {
+        n1 = magnitude[(y - 1) * width + (x - 1)]
+        n2 = magnitude[(y + 1) * width + (x + 1)]
+      }
+
+      out[i] = (mag >= n1 && mag >= n2) ? mag : 0
+    }
+  }
+  return out
+}
+
+/** Hysteresis thresholding for Canny */
+export function hysteresis(
+  nms: Float32Array,
+  width: number,
+  height: number,
+  low: number,
+  high: number,
+): Uint8Array {
+  const out = new Uint8Array(width * height)
+
+  // Mark strong and weak edges
+  const STRONG = 255
+  const WEAK = 128
+  for (let i = 0; i < nms.length; i++) {
+    if (nms[i] >= high) out[i] = STRONG
+    else if (nms[i] >= low) out[i] = WEAK
+  }
+
+  // Connect weak edges adjacent to strong edges
+  let changed = true
+  while (changed) {
+    changed = false
+    for (let y = 1; y < height - 1; y++) {
+      for (let x = 1; x < width - 1; x++) {
+        const i = y * width + x
+        if (out[i] !== WEAK) continue
+        // Check 8-neighbors for strong edge
+        for (let dy = -1; dy <= 1; dy++) {
+          for (let dx = -1; dx <= 1; dx++) {
+            if (out[(y + dy) * width + (x + dx)] === STRONG) {
+              out[i] = STRONG
+              changed = true
+            }
+          }
+        }
+      }
+    }
+  }
+
+  // Suppress remaining weak edges
+  for (let i = 0; i < out.length; i++) {
+    if (out[i] !== STRONG) out[i] = 0
+  }
+  return out
+}
+
+/** Full Canny edge detection */
+export function canny(
+  gray: Uint8Array,
+  width: number,
+  height: number,
+  lowThreshold: number,
+  highThreshold: number,
+): Uint8Array {
+  const blurred = gaussianBlur(gray, width, height)
+  const { magnitude, direction } = sobelGradients(blurred, width, height)
+  const nms = nonMaxSuppression(magnitude, direction, width, height)
+  return hysteresis(nms, width, height, lowThreshold, highThreshold)
+}
+
+/** Convert edge image (Uint8Array) to base64 JPEG via offscreen canvas */
+export function edgeImageToB64(edges: Uint8Array, width: number, height: number): string {
+  const canvas = new OffscreenCanvas(width, height)
+  const ctx = canvas.getContext('2d')!
+  const imgData = ctx.createImageData(width, height)
+  for (let i = 0; i < edges.length; i++) {
+    const p = i * 4
+    imgData.data[p] = edges[i]
+    imgData.data[p + 1] = edges[i]
+    imgData.data[p + 2] = edges[i]
+    imgData.data[p + 3] = 255
+  }
+  ctx.putImageData(imgData, 0, 0)
+  const blob = canvas.convertToBlob({ type: 'image/jpeg', quality: 0.7 })
+  return '' // placeholder — async handled in worker
+}

ui/framework/src/cv/index.ts

@@ -0,0 +1,80 @@
+/**
+ * Browser-side CV — public API.
+ *
+ * Runs edge detection directly on the main thread.
+ * Pure TypeScript, no WASM, no dependencies.
+ * ~10-50ms per 1080p frame — fast enough for slider feedback.
+ *
+ * TODO: Move to Web Worker when processing larger batches.
+ *
+ * Usage:
+ *   import { runEdgeDetection, runEdgeDetectionDebug } from 'mpr-ui-framework/src/cv'
+ *   const result = await runEdgeDetection(imageData, params)
+ */
+
+import { detectEdges, detectEdgesDebug, type EdgeRegion, type EdgeDetectionParams } from './edges'
+
+export type { EdgeRegion, EdgeDetectionParams } from './edges'
+export type { EdgeDetectionResult, EdgeDetectionDebugResult } from './edges'
+
+/** Run edge detection. Returns bounding boxes. */
+export async function runEdgeDetection(
+  imageData: ImageData,
+  params: Partial<EdgeDetectionParams> = {},
+): Promise<{ regions: EdgeRegion[] }> {
+  return detectEdges(imageData, params)
+}
+
+/** Run edge detection with debug overlays. Returns boxes + visualization ImageData. */
+export async function runEdgeDetectionDebug(
+  imageData: ImageData,
+  params: Partial<EdgeDetectionParams> = {},
+): Promise<{
+  regions: EdgeRegion[]
+  edgeImageData: ImageData
+  linesImageData: ImageData
+  horizontalCount: number
+  pairCount: number
+}> {
+  return detectEdgesDebug(imageData, params)
+}
+
+/**
+ * Decode a base64 JPEG string to ImageData.
+ *
+ * Used to convert the checkpoint frame (base64) into ImageData
+ * that the CV functions can process.
+ */
+export function b64ToImageData(b64: string): Promise<ImageData> {
+  return new Promise((resolve, reject) => {
+    const img = new Image()
+    img.onload = () => {
+      const canvas = new OffscreenCanvas(img.width, img.height)
+      const ctx = canvas.getContext('2d')!
+      ctx.drawImage(img, 0, 0)
+      resolve(ctx.getImageData(0, 0, img.width, img.height))
+    }
+    img.onerror = () => reject(new Error('Failed to decode image'))
+    img.src = `data:image/jpeg;base64,${b64}`
+  })
+}
+
+/**
+ * Encode ImageData to base64 JPEG string.
+ *
+ * Used to convert debug overlay ImageData back to base64
+ * for the FrameRenderer overlays prop.
+ */
+export async function imageDataToB64(imageData: ImageData): Promise<string> {
+  const canvas = new OffscreenCanvas(imageData.width, imageData.height)
+  const ctx = canvas.getContext('2d')!
+  ctx.putImageData(imageData, 0, 0)
+  const blob = await canvas.convertToBlob({ type: 'image/jpeg', quality: 0.7 })
+  const buffer = await blob.arrayBuffer()
+  const bytes = new Uint8Array(buffer)
+  let binary = ''
+  for (let i = 0; i < bytes.length; i++) {
+    binary += String.fromCharCode(bytes[i])
+  }
+  return btoa(binary)
+}

ui/framework/src/cv/worker.ts

@@ -0,0 +1,41 @@
+/**
+ * CV Web Worker — runs edge detection off the main thread.
+ *
+ * Message protocol:
+ *   Main → Worker: { type: 'detect_edges', imageData: ImageData, params: {...} }
+ *   Main → Worker: { type: 'detect_edges_debug', imageData: ImageData, params: {...} }
+ *   Worker → Main: { type: 'result', regions: [...] }
+ *   Worker → Main: { type: 'debug_result', regions: [...], edgeImageData, linesImageData, horizontalCount, pairCount }
+ *   Worker → Main: { type: 'error', message: string }
+ */
+
+import { detectEdges, detectEdgesDebug, type EdgeDetectionParams } from './edges'
+
+self.onmessage = (event: MessageEvent) => {
+  const { type, imageData, params } = event.data
+
+  try {
+    if (type === 'detect_edges') {
+      const result = detectEdges(imageData, params)
+      self.postMessage({ type: 'result', regions: result.regions })
+    } else if (type === 'detect_edges_debug') {
+      const result = detectEdgesDebug(imageData, params)
+      self.postMessage({
+        type: 'debug_result',
+        regions: result.regions,
+        edgeImageData: result.edgeImageData,
+        linesImageData: result.linesImageData,
+        horizontalCount: result.horizontalCount,
+        pairCount: result.pairCount,
+      }, [
+        // Transfer ownership of the backing buffers for zero-copy
+        result.edgeImageData.data.buffer,
+        result.linesImageData.data.buffer,
+      ])
+    } else {
+      self.postMessage({ type: 'error', message: `Unknown message type: ${type}` })
+    }
+  } catch (e) {
+    self.postMessage({ type: 'error', message: String(e) })
+  }
+}

ui/framework/src/renderers/GraphRenderer.vue

@@ -41,7 +41,7 @@ const flowNodes = computed(() =>
       label: n.id.replace(/_/g, ' '),
       status: n.status,
       color: statusColors[n.status] ?? statusColors.pending,
-      textColor: n.status === 'pending' ? '#888' : '#000',
+      textColor: '#fff',
       hasRegionEditor: regionStageSet.value.has(n.id),
       isRunning: n.status === 'running',
     },