diff --git a/.memory/worklog.json b/.memory/worklog.json
index f3c50d0..561e758 100644
--- a/.memory/worklog.json
+++ b/.memory/worklog.json
@@ -3173,6 +3173,19 @@
       "type": "session-heartbeat",
       "message": "Claude 会话活跃 · 最近命令：claude · 3 项未提交变更 · 最近提交：auto-save 2026-05-14 04:10 (~4)",
       "files_changed": 3
+    },
+    {
+      "ts": "2026-05-14T04:15:56+08:00",
+      "type": "commit",
+      "message": "auto-save 2026-05-14 04:15 (~4)",
+      "hash": "b52642b",
+      "files_changed": 4
+    },
+    {
+      "ts": "2026-05-13T20:18:50Z",
+      "type": "session-heartbeat",
+      "message": "Codex 会话活跃 · 最近命令：codex · 6 项未提交变更 · 最近提交：auto-save 2026-05-14 04:15 (~4)",
+      "files_changed": 6
     }
   ]
 }
diff --git a/api/main.py b/api/main.py
index 3173cfa..c93767e 100644
--- a/api/main.py
+++ b/api/main.py
@@ -607,6 +607,7 @@ async def pipeline_analyze(
     frame_count: int = KEYFRAME_COUNT,
     target: FrameExtractTarget = "balanced",
     mode: FrameExtractMode = "replace",
+    quality: FrameExtractQuality = "accurate",
 ) -> None:
     """阶段 2：拆音轨 + 抽关键帧。ASR/翻译是独立文案轨，不阻塞视觉素材流。"""
     job = JOBS[job_id]
@@ -629,11 +630,11 @@ async def pipeline_analyze(
 
         n = max(1, min(int(frame_count), 20))
         target_label = FRAME_TARGET_LABELS.get(target, FRAME_TARGET_LABELS["balanced"])
+        quality_label = FRAME_QUALITY_LABELS.get(quality, FRAME_QUALITY_LABELS["accurate"])
         duration = max(float(job.duration or 1.0), 0.1)
-        scan_fps = min(2.0, max(0.02, 180.0 / duration))
-        estimated_scan_count = max(1, int(duration * scan_fps))
+        scan_fps, scan_width, metric_width, estimated_scan_count = _scan_profile(duration, quality)
 
-        update(job, message=f"低清扫描候选 · {target_label} · 约 {estimated_scan_count} 帧…", progress=45)
+        update(job, message=f"本地{quality_label}扫描 · {target_label} · 约 {estimated_scan_count} 帧…", progress=45)
         frames_dir = d / "frames"
         replacing = mode == "replace"
         existing_frames = list(job.frames) if not replacing else []
@@ -648,7 +649,7 @@ async def pipeline_analyze(
         # 1) 低分辨率、低帧率扫描。扫描图只用于候选评分，最终不直接作为关键帧。
         run([
             "ffmpeg", "-y", "-i", str(mp4),
-            "-vf", f"fps={scan_fps:.4f},scale=360:-2",
+            "-vf", f"fps={scan_fps:.4f},scale={scan_width}:-2",
             "-q:v", "4",
             str(scan_dir / "s_%05d.jpg"),
         ])
@@ -660,7 +661,7 @@ async def pipeline_analyze(
         candidates: list[dict] = []
         for i, p in enumerate(scan_paths):
             t = min(i / scan_fps, max(duration - 0.05, 0.0))
-            item = _frame_metrics(p, i, t)
+            item = _frame_metrics(p, i, t, metric_width)
             if item:
                 candidates.append(item)
         if not candidates:
@@ -668,7 +669,7 @@ async def pipeline_analyze(
 
         # 2) 目标化筛选：pHash 去重 + 清晰度 / 中心细节 / 转场变化 / 动作强度 + 时序分桶。
         selection_count = n if replacing else min(len(candidates), max(n * 4, n + len(existing_frames) + 2))
-        update(job, message=f"{target_label}筛选 {n} / {len(candidates)} 张…", progress=60)
+        update(job, message=f"{quality_label}筛选 · {target_label} · {n} / {len(candidates)} 张…", progress=60)
         chosen = _select_keyframes(candidates, selection_count, target)
 
         # 3) 只对最终选中的时间点，从原视频抽高质量关键帧。
@@ -708,7 +709,7 @@ async def pipeline_analyze(
             status="frames_extracted",
             frames=merged_frames,
             progress=70,
-            message=f"已按「{target_label}」{action_label} {len(renamed)} 张关键帧 · 共 {len(merged_frames)} 张",
+            message=f"已按「{quality_label} · {target_label}」{action_label} {len(renamed)} 张关键帧 · 共 {len(merged_frames)} 张",
         )
 
     except Exception as e:
@@ -1083,13 +1084,14 @@ async def trigger_analyze(
     frames: int = KEYFRAME_COUNT,
     target: FrameExtractTarget = "balanced",
     mode: FrameExtractMode = "replace",
+    quality: FrameExtractQuality = "accurate",
 ) -> Job:
     job = JOBS.get(job_id)
     if not job:
         raise HTTPException(404, "job not found")
     if job.status not in {"downloaded", "frames_extracted", "transcribed", "failed"}:
         raise HTTPException(409, f"status must be downloaded/failed, got {job.status}")
-    bg.add_task(pipeline_analyze, job_id, frames, target, mode)
+    bg.add_task(pipeline_analyze, job_id, frames, target, mode, quality)
     return job
 
 
diff --git a/docs/source-analysis.html b/docs/source-analysis.html
index c9e0469..0be467b 100644
--- a/docs/source-analysis.html
+++ b/docs/source-analysis.html
@@ -701,7 +701,7 @@ api/main.py
             <tr><td>创建任务</td><td><code>POST /jobs</code></td><td><code>createJob</code></td><td>提交 TK 链接，后台开始下载，停在 downloaded 等用户点解析。</td></tr>
             <tr><td>上传视频</td><td><code>POST /jobs/upload</code></td><td><code>uploadJob</code></td><td>保存 source.mp4，然后同样进入下载完成状态。</td></tr>
             <tr><td>删除输入视频</td><td><code>DELETE /jobs/{id}</code></td><td><code>deleteJob</code></td><td>从任务队列、URL 和磁盘 <code>jobs/&lt;id&gt;</code> 目录移除整个 job，包括源视频、关键帧、元素提取图和生成视频。</td></tr>
-            <tr><td>解析视频</td><td><code>POST /jobs/{id}/analyze?frames=&amp;target=&amp;mode=</code></td><td><code>analyzeJob</code></td><td>拆轨 + 目标化抽关键帧。<code>target</code> 支持综合、清晰主体、转场变化、表情瞬间、动作峰值；<code>mode=append</code> 追加新关键帧，<code>mode=replace</code> 重抽覆盖。</td></tr>
+            <tr><td>解析视频</td><td><code>POST /jobs/{id}/analyze?frames=&amp;target=&amp;mode=&amp;quality=</code></td><td><code>analyzeJob</code></td><td>拆轨 + 目标化抽关键帧。<code>target</code> 支持综合、清晰主体、转场变化、表情瞬间、动作峰值；<code>mode=append</code> 追加新关键帧；<code>quality</code> 支持快速、精细、极准本地扫描。</td></tr>
             <tr><td>手动加帧</td><td><code>POST /jobs/{id}/frames?t=</code></td><td><code>addManualFrame</code></td><td>按视频时间戳抽一帧，index 递增但 frames 按 timestamp 排序。</td></tr>
             <tr><td>Vision 识别</td><td><code>POST /frames/{idx}/describe</code></td><td><code>describeFrame</code></td><td>写入 frame.description，后续可从 objects 加候选元素。</td></tr>
             <tr><td>清洗水印</td><td><code>POST /frames/{idx}/cleanup</code></td><td><code>cleanupFrame</code></td><td>支持全图和区域清洗，生成 cleaned 待应用版本。</td></tr>
@@ -723,7 +723,7 @@ api/main.py
           <tbody>
             <tr>
               <td><span class="tag blue">输入 Input</span></td>
-              <td>创建/上传任务，显示视频就绪；每个视频缩略图上方都有绑定自己的自动抽帧快捷工具条，可快速选目标、张数并多次追加；单击视频缩略图打开画布内抽帧面板。</td>
+              <td>创建/上传任务，显示视频就绪；每个视频缩略图上方都有绑定自己的自动抽帧快捷工具条，可快速选目标、张数、精度并多次追加；单击视频缩略图打开画布内抽帧面板。</td>
               <td>不要自动一路跑到 ASR 或生图；用户需要控制解析节奏。</td>
               <td><code>page.tsx</code>、<code>InputNode</code>、<code>VideoFramePanelNode</code>、<code>api/main.py</code></td>
             </tr>
@@ -817,6 +817,18 @@ api/main.py
         <h2>变更记录</h2>
         <p>这个记录不是 git log 的替代品。它记录“产品理解发生了什么变化、影响了哪些源码、你以后描述需求时该怎么说”。后续每次改功能都要补一条。</p>
         <div class="changelog">
+          <article class="change">
+            <header>
+              <h3>2026-05-14 · 自动抽帧增加本地精度模式</h3>
+              <span class="tag violet">Input</span>
+              <span class="tag blue">Performance</span>
+            </header>
+            <div class="body">
+              <p><strong>问题：</strong>当前抽帧默认偏轻量，用户机器是 Apple M2 Max、12 核 CPU、38 核 GPU、64GB 内存，足以承受更密集的本地候选扫描；但需要在 UI 里提示算力档位，避免长视频误用重模式。</p>
+              <p><strong>改动：</strong>后端 <code>/jobs/{id}/analyze</code> 新增 <code>quality</code> 参数：快速为 2fps/360px，精细为 8fps/720px，极准为 12fps/960px；高精度模式还会提高本地评分图分辨率，保留竖屏比例，不再把竖屏压扁到 16:9。每个缩略图工具条新增精度选择。</p>
+              <p><strong>影响：</strong><code>api/main.py</code>、<code>web/lib/api.ts</code>、<code>web/app/page.tsx</code>、<code>web/components/nodes/index.tsx</code>、<code>docs/source-analysis.html</code>。实测本机 64.5s、1080×1920、60fps 视频，12fps/960px 扫描 774 张候选约 2.61s；重型 ffmpeg 场景/模糊滤镜约 21.63s，因此继续使用本地 PIL/NumPy 评分更划算。</p>
+            </div>
+          </article>
           <article class="change">
             <header>
               <h3>2026-05-14 · 每个输入视频缩略图绑定自己的抽帧工具条</h3>
@@ -825,7 +837,7 @@ api/main.py
             </header>
             <div class="body">
               <p><strong>问题：</strong>统一放在缩略图浮条上方的抽帧工具条仍然不够明确，用户无法一眼判断当前会抽哪一个视频。</p>
-              <p><strong>改动：</strong>抽帧目标、张数和抽帧按钮改为渲染在每个视频缩略图正上方，并且每个 job 独立保存目标和张数设置。点击某个缩略图上方的抽帧按钮时，前端直接把该 <code>jobId</code> 传给 <code>analyzeJob</code>，同时切换 active job 并进入该 job 的进度轮询。</p>
+              <p><strong>改动：</strong>抽帧目标、张数、精度和抽帧按钮改为渲染在每个视频缩略图正上方，并且每个 job 独立保存目标、张数和精度设置。点击某个缩略图上方的抽帧按钮时，前端直接把该 <code>jobId</code> 传给 <code>analyzeJob</code>，同时切换 active job 并进入该 job 的进度轮询。</p>
               <p><strong>影响：</strong><code>web/app/page.tsx</code>、<code>web/components/nodes/index.tsx</code>、<code>docs/source-analysis.html</code>。后续与输入视频相关的快捷操作都应优先贴近对应缩略图，不再依赖全局当前选择的心智。</p>
             </div>
           </article>
diff --git a/web/app/page.tsx b/web/app/page.tsx
index 73de92b..33df0f6 100644
--- a/web/app/page.tsx
+++ b/web/app/page.tsx
@@ -19,7 +19,7 @@ import { ThemeToggle } from "@/components/theme-toggle"
 import {
   addManualFrame, analyzeJob, createJob, getJob, listJobs, uploadJob, deleteJob, deleteFrame, deleteGeneratedImage,
   deleteGeneratedVideo, deleteCutout, generateStoryboardVideo,
-  type Job, type ImageRef, type StoryboardScene, type FrameExtractMode, type FrameExtractTarget,
+  type Job, type ImageRef, type StoryboardScene, type FrameExtractMode, type FrameExtractQuality, type FrameExtractTarget,
 } from "@/lib/api"
 
 const NODE_TYPES = {
@@ -41,6 +41,11 @@ const FRAME_TARGET_LABELS: Record<FrameExtractTarget, string> = {
   expression: "表情瞬间",
   motion: "动作峰值",
 }
+const FRAME_QUALITY_LABELS: Record<FrameExtractQuality, string> = {
+  fast: "快速",
+  accurate: "精细",
+  ultra: "极准",
+}
 
 // 合并 input + download + split 为一个节点
 // 分叉：上路 input → visual lab ↘
@@ -94,6 +99,7 @@ export default function Home() {
   const [analyzing, setAnalyzing] = useState(false)
   const [frameTargets, setFrameTargets] = useState<Record<string, FrameExtractTarget>>({})
   const [frameCounts, setFrameCounts] = useState<Record<string, number>>({})
+  const [frameQualities, setFrameQualities] = useState<Record<string, FrameExtractQuality>>({})
   const [selectedFrames, setSelectedFrames] = useState<Set<number>>(new Set())
   const [expandedFrame, setExpandedFrame] = useState<number | null>(null)
   const [framePanelScale, setFramePanelScale] = useState(1)
@@ -172,17 +178,18 @@ export default function Home() {
     if (!targetJob) return
     const frameTarget = frameTargets[jobId] ?? "balanced"
     const frameCount = frameCounts[jobId] ?? 5
+    const frameQuality = frameQualities[jobId] ?? "accurate"
     const mode = options?.mode ?? (targetJob.frames.length > 0 ? "append" : "replace")
     setActiveJobId(jobId)
     setAnalyzing(true)
     if (mode === "replace") setSelectedFrames(new Set())
     try {
-      await analyzeJob(jobId, frameCount, frameTarget, mode)
-      toast.info(`${mode === "append" ? "追加抽帧" : "开始解析"}：${FRAME_TARGET_LABELS[frameTarget]} · ${frameCount} 张`)
+      await analyzeJob(jobId, frameCount, frameTarget, mode, frameQuality)
+      toast.info(`${mode === "append" ? "追加抽帧" : "开始解析"}：${FRAME_QUALITY_LABELS[frameQuality]} · ${FRAME_TARGET_LABELS[frameTarget]} · ${frameCount} 张`)
       setJobs((prev) => prev.map((item) => item.id === jobId ? {
         ...item,
         status: "splitting",
-        message: `${mode === "append" ? "追加抽帧中" : "拆轨中"} · ${FRAME_TARGET_LABELS[frameTarget]}…`,
+        message: `${mode === "append" ? "追加抽帧中" : "拆轨中"} · ${FRAME_QUALITY_LABELS[frameQuality]} · ${FRAME_TARGET_LABELS[frameTarget]}…`,
         progress: 30,
       } : item))
     } catch (e) {
@@ -190,7 +197,7 @@ export default function Home() {
     } finally {
       setAnalyzing(false)
     }
-  }, [jobs, frameCounts, frameTargets])
+  }, [jobs, frameCounts, frameQualities, frameTargets])
 
   const handleAnalyze = useCallback(async (options?: { mode?: FrameExtractMode }) => {
     if (!job) return
@@ -205,6 +212,10 @@ export default function Home() {
     setFrameCounts((prev) => ({ ...prev, [jobId]: Math.max(1, Math.min(20, count)) }))
   }, [])
 
+  const handleFrameQualityChange = useCallback((jobId: string, quality: FrameExtractQuality) => {
+    setFrameQualities((prev) => ({ ...prev, [jobId]: quality }))
+  }, [])
+
   const handleAddManualFrameForJob = useCallback(async (jobId: string, t: number) => {
     try {
       const updated = await addManualFrame(jobId, t)
@@ -529,6 +540,7 @@ export default function Home() {
     analyzing,
     frameTargets,
     frameCounts,
+    frameQualities,
     selectedFrames,
     expandedFrame,
     framePanelScale,
@@ -543,6 +555,7 @@ export default function Home() {
     onAnalyzeJob: handleAnalyzeJob,
     onFrameTargetChange: handleFrameTargetChange,
     onFrameCountChange: handleFrameCountChange,
+    onFrameQualityChange: handleFrameQualityChange,
     onToggleFrame: handleToggleFrame,
     onExpandFrame: setExpandedFrame,
     onOpenFramePanel: handleOpenFramePanel,
@@ -572,7 +585,7 @@ export default function Home() {
     onCopyImage: handleCopyImage,
     pinnedNodes,
     onToggleNodePin: handleToggleNodePin,
-  }), [job, jobs, activeJobId, submitting, analyzing, frameTargets, frameCounts, selectedFrames, expandedFrame, framePanelScale, framePanelPinned, framePanelDock, videoPanelJobId, videoPanelScale, videoPanelDock, handleSubmit, handleUpload, handleAnalyze, handleAnalyzeJob, handleFrameTargetChange, handleFrameCountChange, handleToggleFrame, handleOpenFramePanel, handleFramePanelScaleChange, handleAddManualFrame, handleAddManualFrameForJob, handleOpenVideoPanel, handleVideoPanelScaleChange, handleSwitchJob, setJob, handleDeleteJob, handleDeleteFrame, handleDeleteFrameForJob, handleDeleteGenerated, handleDeleteVideo, handleDeleteCutout, handleCopyImage, pinnedNodes, handleToggleNodePin])
+  }), [job, jobs, activeJobId, submitting, analyzing, frameTargets, frameCounts, frameQualities, selectedFrames, expandedFrame, framePanelScale, framePanelPinned, framePanelDock, videoPanelJobId, videoPanelScale, videoPanelDock, handleSubmit, handleUpload, handleAnalyze, handleAnalyzeJob, handleFrameTargetChange, handleFrameCountChange, handleFrameQualityChange, handleToggleFrame, handleOpenFramePanel, handleFramePanelScaleChange, handleAddManualFrame, handleAddManualFrameForJob, handleOpenVideoPanel, handleVideoPanelScaleChange, handleSwitchJob, setJob, handleDeleteJob, handleDeleteFrame, handleDeleteFrameForJob, handleDeleteGenerated, handleDeleteVideo, handleDeleteCutout, handleCopyImage, pinnedNodes, handleToggleNodePin])
 
   // 用 useNodesState 让 ReactFlow 自己管位置（避免轮询时重置 drag）
   const savedSizes = useMemo(() => loadNodeSizes(), [])
diff --git a/web/components/nodes/index.tsx b/web/components/nodes/index.tsx
index e3c9d54..4550256 100644
--- a/web/components/nodes/index.tsx
+++ b/web/components/nodes/index.tsx
@@ -16,7 +16,7 @@ import { toast } from "sonner"
 import { NodeShell, type NodeStatus, type NodeKind } from "./node-shell"
 import { HoverPreview } from "./hover-preview"
 import {
-  type Job, type ImageRef, type FrameExtractMode, type FrameExtractTarget,
+  type Job, type ImageRef, type FrameExtractMode, type FrameExtractQuality, type FrameExtractTarget,
   apiAssetUrl, effectiveFrameUrl, videoUrl, hasCutout, representativeCutoutUrl,
 } from "@/lib/api"
 import { FrameLightbox } from "@/components/lightbox"
@@ -31,6 +31,7 @@ export interface NodeData {
   analyzing: boolean
   frameTargets: Record<string, FrameExtractTarget>
   frameCounts: Record<string, number>
+  frameQualities: Record<string, FrameExtractQuality>
   selectedFrames: Set<number>
   expandedFrame: number | null
   framePanelScale?: number
@@ -45,6 +46,7 @@ export interface NodeData {
   onAnalyzeJob: (jobId: string, options?: { mode?: FrameExtractMode }) => void
   onFrameTargetChange: (jobId: string, target: FrameExtractTarget) => void
   onFrameCountChange: (jobId: string, count: number) => void
+  onFrameQualityChange: (jobId: string, quality: FrameExtractQuality) => void
   onToggleFrame: (idx: number) => void
   onExpandFrame: (idx: number) => void
   onOpenFramePanel?: (idx: number) => void  // 打开/找回画布内关键帧详情面板
@@ -132,6 +134,11 @@ const FRAME_TARGET_OPTIONS: Array<{ value: FrameExtractTarget; label: string; hi
   { value: "motion", label: "动作峰值", hint: "动作变化更明显" },
 ]
 const FRAME_COUNT_OPTIONS = [3, 5, 8, 12]
+const FRAME_QUALITY_OPTIONS: Array<{ value: FrameExtractQuality; label: string; hint: string }> = [
+  { value: "fast", label: "快速", hint: "2fps / 360px，长视频省电" },
+  { value: "accurate", label: "精细", hint: "8fps / 720px，M2 Max 轻松可用" },
+  { value: "ultra", label: "极准", hint: "12fps / 960px，本机约 3 秒扫描 1 分钟视频" },
+]
 
 function canvasThumbnailAnchor(root: HTMLDivElement | null, target: HTMLElement) {
   if (!root) return { x: 160, y: 0 }
@@ -410,23 +417,28 @@ function DeleteConfirmDialog({
 function FrameExtractQuickBar({
   target,
   count,
+  quality,
   disabled,
   running,
   hasFrames,
   onTargetChange,
   onCountChange,
+  onQualityChange,
   onAnalyze,
 }: {
   target: FrameExtractTarget
   count: number
+  quality: FrameExtractQuality
   disabled: boolean
   running: boolean
   hasFrames: boolean
   onTargetChange: (target: FrameExtractTarget) => void
   onCountChange: (count: number) => void
+  onQualityChange: (quality: FrameExtractQuality) => void
   onAnalyze: () => void
 }) {
   const option = FRAME_TARGET_OPTIONS.find((item) => item.value === target) ?? FRAME_TARGET_OPTIONS[0]
+  const qualityOption = FRAME_QUALITY_OPTIONS.find((item) => item.value === quality) ?? FRAME_QUALITY_OPTIONS[1]
 
   return (
     <div
@@ -458,6 +470,18 @@ function FrameExtractQuickBar({
             <option key={item} value={item}>{item} 张</option>
           ))}
         </select>
+        <select
+          value={quality}
+          disabled={disabled}
+          onChange={(e) => onQualityChange(e.target.value as FrameExtractQuality)}
+          title={qualityOption.hint}
+          className="h-7 min-w-0 flex-1 cursor-pointer rounded-md border border-white/12 bg-white/[0.08] px-1.5 text-[10px] font-bold text-white outline-none transition focus:ring-2 focus:ring-violet-300/70 disabled:cursor-not-allowed disabled:opacity-45"
+          aria-label="选择抽帧精度"
+        >
+          {FRAME_QUALITY_OPTIONS.map((item) => (
+            <option key={item.value} value={item.value}>{item.label}</option>
+          ))}
+        </select>
         <button
           type="button"
           disabled={disabled}
@@ -525,36 +549,40 @@ export function InputNode({ data, selected }: NodeProps<{ data: NodeData }> | an
             const isActive = j.id === d.activeJobId
             const ready = !!j.video_url
             const aspectStr = ready ? `${j.width}/${j.height}` : "9/16"
-            const thumbWidth = ready && j.height ? Math.max(118, Math.round(THUMBNAIL_HEIGHT * j.width / j.height)) : 118
+            const thumbNaturalWidth = ready && j.height ? Math.max(96, Math.round(THUMBNAIL_HEIGHT * j.width / j.height)) : 96
+            const toolWidth = Math.max(148, thumbNaturalWidth)
             const target = d.frameTargets[j.id] ?? "balanced"
             const count = d.frameCounts[j.id] ?? 5
+            const quality = d.frameQualities[j.id] ?? "accurate"
             const jHasFrames = j.frames.length > 0
             const jRunning = ["splitting", "transcribing"].includes(j.status)
             return (
               <div
                 key={j.id}
                 className="group relative flex shrink-0 flex-col gap-1.5"
-                style={{ width: thumbWidth }}
+                style={{ width: toolWidth }}
               >
                 {ready ? (
                   <FrameExtractQuickBar
                     target={target}
                     count={count}
+                    quality={quality}
                     disabled={jRunning || d.analyzing}
                     running={jRunning}
                     hasFrames={jHasFrames}
                     onTargetChange={(next) => d.onFrameTargetChange(j.id, next)}
                     onCountChange={(next) => d.onFrameCountChange(j.id, next)}
+                    onQualityChange={(next) => d.onFrameQualityChange(j.id, next)}
                     onAnalyze={() => d.onAnalyzeJob(j.id, { mode: jHasFrames ? "append" : "replace" })}
                   />
                 ) : (
                   <div className="h-[72px] rounded-lg border border-white/10 bg-white/[0.03]" />
                 )}
                 <div
-                  className={`relative rounded-md overflow-visible border shadow-lg transition hover:-translate-y-0.5 ${
+                  className={`relative self-center rounded-md overflow-visible border shadow-lg transition hover:-translate-y-0.5 ${
                     isActive ? "border-violet-400 ring-2 ring-violet-400/60" : "border-white/25"
                   }`}
-                  style={{ height: THUMBNAIL_HEIGHT, aspectRatio: aspectStr }}
+                  style={{ width: thumbNaturalWidth, height: THUMBNAIL_HEIGHT, aspectRatio: aspectStr }}
                   onMouseEnter={(e) => setHoverPreviewJob({ id: j.id, ...canvasThumbnailAnchor(rootRef.current, e.currentTarget) })}
                   onMouseLeave={() => setHoverPreviewJob(null)}
                 >
diff --git a/web/lib/api.ts b/web/lib/api.ts
index cc4a601..fc44eb4 100644
--- a/web/lib/api.ts
+++ b/web/lib/api.ts
@@ -130,6 +130,7 @@ export interface KeyFrame {
 
 export type FrameExtractTarget = "balanced" | "subject" | "transition" | "expression" | "motion"
 export type FrameExtractMode = "replace" | "append"
+export type FrameExtractQuality = "fast" | "accurate" | "ultra"
 
 export interface TranscriptSegment {
   index: number
@@ -267,8 +268,9 @@ export async function analyzeJob(
   frames = 5,
   target: FrameExtractTarget = "balanced",
   mode: FrameExtractMode = "replace",
+  quality: FrameExtractQuality = "accurate",
 ): Promise<Job> {
-  const qs = new URLSearchParams({ frames: String(frames), target, mode })
+  const qs = new URLSearchParams({ frames: String(frames), target, mode, quality })
   const res = await fetch(`${API_BASE}/jobs/${id}/analyze?${qs.toString()}`, { method: "POST" })
   if (!res.ok) {
     const t = await res.text().catch(() => "")