dphn/Dolphin3.0-Mistral-24B is the ungated mirror of the Dolphin 3.0 Mistral 24B — exactly what you asked for. It's ~48GB fp16, which needs GPU+CPU split (device_map="auto" with 32GB on GPU, ~16GB in RAM). Let me kick off the download and update the service in parallel.

backlog.md

@@ -49,3 +49,5 @@ rating based pose, thumbs up/down find good/bad poses easier
   (pairs well with the new pose index — could weight similar-pose results by rating)
 
 when refresh page, we lose track of current jobs running.
+
+generating poses themself should use the adviced dimensions rather than the base image reference.  

tour-comfy/car.html

@@ -1834,7 +1834,10 @@
                             </div>
                             <div id="lbFaceBook" style="display:none;margin-bottom:8px">
                                 <div class="sb-label" style="margin-bottom:4px">Face reference</div>
-                                <img id="lbFaceThumb" style="width:72px;height:72px;object-fit:cover;border-radius:6px;border:1px solid #333;cursor:pointer" onclick="window.open(this.src,'_blank')" title="Face crop — click to view full">
+                                <div style="display:flex;gap:8px;align-items:flex-start">
+                                    <img id="lbFaceThumb" style="width:72px;height:72px;object-fit:cover;border-radius:6px;border:1px solid #333;cursor:pointer;flex-shrink:0" onclick="window.open(this.src,'_blank')" title="Face crop — click to view full">
+                                    <button class="sb-btn" onclick="lbFindSimilarFaces()" title="Find groups with matching faces">Similar faces</button>
+                                </div>
                             </div>
                             <div class="sb-sep"></div>
                             <div class="sb-label">Order & visibility</div>
@@ -2968,6 +2971,86 @@
             if (btn) btn.disabled = false;
         }
 
+        async function lbFindSimilarFaces() {
+            if (!lbCurrentGid) return;
+            try {
+                const r = await fetch(`${API}/faces/similar`, {
+                    method: 'POST', headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ group_id: lbCurrentGid, limit: 12 }),
+                });
+                if (r.status === 404) { _renderFaceResults(null); return; }
+                if (!r.ok) { showToast('Similar faces failed: ' + await r.text(), 'error'); return; }
+                const d = await r.json();
+                _renderFaceResults(d.similar || []);
+            } catch (e) { showToast('Similar faces failed: ' + e, 'error'); }
+        }
+
+        async function lbBuildFaceIndex() {
+            try {
+                const r = await fetch(`${API}/faces/index`, { method: 'POST' });
+                if (!r.ok) { showToast('Face index failed: ' + await r.text(), 'error'); return; }
+                showToast('Building face index…', 'info');
+                _pollFaceIndex();
+            } catch (e) { showToast('Face index failed: ' + e, 'error'); }
+        }
+
+        async function _pollFaceIndex() {
+            try {
+                const r = await fetch(`${API}/faces/index/status`);
+                if (r.ok) {
+                    const s = await r.json();
+                    if (s.running) {
+                        showToast(`Face index: ${s.done}/${s.total}…`, 'info', 2500);
+                        setTimeout(_pollFaceIndex, 2000);
+                    } else {
+                        showToast(`Face index ready (${s.indexed} embeddings)`, 'success');
+                    }
+                }
+            } catch (e) {}
+        }
+
+        function _renderFaceResults(items) {
+            document.getElementById('faceResults')?.remove();
+            const viewer = document.getElementById('studioViewer');
+            if (!viewer) return;
+            const panel = document.createElement('div');
+            panel.id = 'faceResults';
+            panel.style.cssText = 'position:absolute;left:0;right:0;bottom:0;z-index:103;background:rgba(0,0,0,0.85);'
+                + 'padding:8px;display:flex;gap:8px;overflow-x:auto;align-items:center;';
+            if (!items || !items.length) {
+                const msg = items === null
+                    ? 'No face embedding for this group — build the index first'
+                    : 'No similar faces found';
+                panel.innerHTML = `<span style="color:#aaa;font-size:12px;flex:1">${msg}</span>`
+                    + '<button class="sb-btn" onclick="lbBuildFaceIndex();document.getElementById(\'faceResults\')?.remove()">Build index</button>'
+                    + '<button class="sb-btn" onclick="document.getElementById(\'faceResults\')?.remove()">Close</button>';
+            } else {
+                panel.innerHTML = '<span style="color:#aaa;font-size:11px;flex-shrink:0">Similar faces:</span>'
+                    + items.map(it => {
+                        const u = IMAGE_FOLDER + it.filename + '?t=' + Date.now();
+                        const gid = (it.group_id || '').replace(/'/g, "\\'");
+                        const fn  = it.filename.replace(/'/g, "\\'");
+                        return `<div title="dist ${it.distance}" style="flex-shrink:0;cursor:pointer;text-align:center"
+                            onclick="openFaceResult('${gid}','${fn}')">
+                            <img src="${u}" loading="lazy" style="width:64px;height:64px;object-fit:cover;border-radius:5px;border:1px solid #444" onerror="this.style.opacity='0.3'">
+                            <div style="font-size:9px;color:#777">${it.distance}</div></div>`;
+                    }).join('')
+                    + '<button class="sb-btn" style="flex-shrink:0" onclick="document.getElementById(\'faceResults\')?.remove()">Close</button>';
+            }
+            viewer.appendChild(panel);
+        }
+
+        function openFaceResult(gid, fname) {
+            document.getElementById('faceResults')?.remove();
+            if (gid && groupData.has(gid)) {
+                openStudio(gid, 0);
+            } else {
+                const i = lbNames.indexOf(fname);
+                if (i >= 0) { lbIdx = i; updateStudio(); }
+                else showToast('Group not found in gallery: ' + fname, 'info', 5000);
+            }
+        }
+
         function _renderPoseResults(items) {
             document.getElementById('poseResults')?.remove();
             const viewer = document.getElementById('studioViewer');
@@ -5236,19 +5319,15 @@
                 html += '</div>';
             }
             html += `<div class="scene-frame-preview" id="sceneFramePreview" style="${_sceneVideo||_sceneFrameBytes?'':'display:none'}">
-                <video id="sceneVideoEl" muted preload="auto" playsinline autoplay loop
+                <video id="sceneVideoEl" muted preload="auto" playsinline loop controls
                        style="${_sceneVideo&&!_sceneFrameBytes?'':'display:none'};width:100%;height:100%;object-fit:contain"></video>
                 <img id="sceneFrameImg" style="${_sceneFrameBytes?'':'display:none'};width:100%;height:100%;object-fit:contain"
                      ${_sceneFrameBytes?`src="data:image/png;base64,${_sceneFrameBytes}"`:''}/>
-                <div id="sceneFrameLoading" style="display:none;position:absolute;inset:0;background:rgba(0,0,0,.5);display:flex;align-items:center;justify-content:center;font-size:11px;color:#aaa">Loading…</div>
             </div>
-            <input type="range" class="scene-scrubber" id="sceneScrubber"
-                   min="0" max="${_sceneDuration||100}" value="0" step="0.1"
-                   oninput="sceneSeekVideo(this.value)"
-                   style="${_sceneVideo?'':'display:none'}">
-            <div id="sceneTimeLabel" style="font-size:10px;color:#555;margin-bottom:4px;${_sceneVideo?'':'display:none'}">0:00</div>
             <button class="sb-btn" id="sceneExtractBtn" onclick="sceneExtractFrame()"
-                    style="${_sceneVideo?'':'display:none'};margin-bottom:8px">Extract frame as reference</button>
+                    style="${_sceneVideo&&!_sceneFrameBytes?'':'display:none'};margin-bottom:8px">Extract frame as reference</button>
+            <button class="sb-btn" id="sceneReleaseBtn" onclick="sceneReleaseFrame()"
+                    style="${_sceneFrameBytes?'':'display:none'};margin-bottom:8px">&#10006; Change frame</button>
             <div class="sb-sep"></div>
             <div class="sb-label">Or upload image</div>
             <input type="file" id="sceneUploadInput" accept="image/*" style="display:none" onchange="sceneHandleUpload(event)">
@@ -5268,10 +5347,9 @@
             if (_sceneVideo) {
                 const vid = document.getElementById('sceneVideoEl');
                 vid.src = `${API}/wireframe/${encodeURIComponent(_sceneVideo)}`;
-                if (_sceneDuration) {
-                    const scrubber = document.getElementById('sceneScrubber');
-                    if (scrubber) { scrubber.max = _sceneDuration; scrubber.step = Math.max(0.05, _sceneDuration / 500); }
-                }
+                vid.addEventListener('seeking', () => {
+                    if (_sceneFrameBytes) sceneReleaseFrame();
+                });
             }
             // Cards show static poster frames; videos mount only on hover (_tplPlay).
         }
@@ -5279,58 +5357,20 @@
         async function sceneSelectVideo(v) {
             _sceneVideo = v; _sceneFrameBytes = null;
             renderSidebarScenery();
-            try {
-                const r = await fetch(`${API}/wireframe/duration/${encodeURIComponent(v)}`);
-                if (r.ok) {
-                    _sceneDuration = (await r.json()).duration || 0;
-                    const scrubber = document.getElementById('sceneScrubber');
-                    if (scrubber) { scrubber.max = _sceneDuration; scrubber.step = Math.max(0.05, _sceneDuration / 500); }
-                }
-            } catch (_) {}
         }
 
-        let _sceneScrubTimer = null;
-
-        function sceneSeekVideo(val) {
-            const t = parseFloat(val);
-            const lbl = document.getElementById('sceneTimeLabel');
-            if (lbl) lbl.textContent = formatSecs(t);
-            // If a captured frame was locked, release it so scrubbing works again
-            if (_sceneFrameBytes) {
-                _sceneFrameBytes = null;
-                const btn = document.getElementById('sceneExtractBtn');
-                if (btn) btn.textContent = 'Extract frame as reference';
-                const genBtn = document.getElementById('sceneGenBtn');
-                if (genBtn) genBtn.disabled = !_sceneVideo;
-            }
-            // Show video live while the user is dragging
+        function sceneReleaseFrame() {
+            _sceneFrameBytes = null;
             const vid = document.getElementById('sceneVideoEl');
             const img = document.getElementById('sceneFrameImg');
-            if (vid) { vid.style.display = ''; vid.currentTime = t; }
+            const extractBtn = document.getElementById('sceneExtractBtn');
+            const releaseBtn = document.getElementById('sceneReleaseBtn');
+            const genBtn    = document.getElementById('sceneGenBtn');
+            if (vid) vid.style.display = '';
             if (img) img.style.display = 'none';
-            // After settling, fetch exact server-rendered frame and freeze on it
-            clearTimeout(_sceneScrubTimer);
-            _sceneScrubTimer = setTimeout(() => _sceneShowFrame(t), 300);
-        }
-
-        async function _sceneShowFrame(t) {
-            if (!_sceneVideo) return;
-            try {
-                const r = await fetch(`${API}/wireframe/frame`, {
-                    method: 'POST',
-                    headers: { 'Content-Type': 'application/json' },
-                    body: JSON.stringify({ video_name: _sceneVideo, time: t }),
-                });
-                if (!r.ok) return;
-                const d = await r.json();
-                const vid = document.getElementById('sceneVideoEl');
-                const img = document.getElementById('sceneFrameImg');
-                if (!img) return;
-                if (vid) vid.style.display = 'none';
-                img.src = 'data:image/png;base64,' + d.frame_b64;
-                img.style.display = '';
-                img.dataset.pendingFrame = d.frame_b64;  // ready to capture without re-fetch
-            } catch (_) { /* video stays visible on error */ }
+            if (extractBtn) extractBtn.style.display = '';
+            if (releaseBtn) releaseBtn.style.display = 'none';
+            if (genBtn) genBtn.disabled = !_sceneVideo;
         }
 
         async function sceneExtractFrame() {

tour-comfy/database.py

@@ -111,6 +111,7 @@ def migrate_schema():
             "ALTER TABLE person ADD COLUMN IF NOT EXISTS content_type TEXT DEFAULT 'image'",
             "ALTER TABLE person ADD COLUMN IF NOT EXISTS faceswap_source_video TEXT",
             "ALTER TABLE person ADD COLUMN IF NOT EXISTS archived BOOLEAN DEFAULT FALSE",
+            "ALTER TABLE person ADD COLUMN IF NOT EXISTS face_embedding vector(512)",
         ]:
             cur.execute(sql)
         conn.commit()
@@ -122,16 +123,18 @@ def upsert_person(filename, filepath=None, name=None, group_id=None, tags=None,
                   embedding=None, clip_description=None, prompt=None, pose=None,
                   sort_order=None, group_name=None, hidden=None,
                   has_background=None, source_refs=None, has_clothing=None,
-                  content_type=None, faceswap_source_video=None, archived=None):
+                  content_type=None, faceswap_source_video=None, archived=None,
+                  face_embedding=None):
     conn = get_db_connection()
     cur = conn.cursor()
+    face_embedding_str = ("[" + ",".join(map(str, face_embedding)) + "]") if face_embedding is not None else None
     try:
         cur.execute("""
             INSERT INTO person (filename, filepath, name, group_id, tags, embedding,
                                 clip_description, prompt, pose, sort_order, group_name, hidden,
                                 has_background, source_refs, has_clothing,
-                                content_type, faceswap_source_video, archived)
-            VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
+                                content_type, faceswap_source_video, archived, face_embedding)
+            VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
             ON CONFLICT (filename) DO UPDATE
             SET filepath              = COALESCE(EXCLUDED.filepath,              person.filepath),
                 name                  = COALESCE(EXCLUDED.name,                  person.name),
@@ -149,12 +152,13 @@ def upsert_person(filename, filepath=None, name=None, group_id=None, tags=None,
                 has_clothing          = COALESCE(EXCLUDED.has_clothing,          person.has_clothing),
                 content_type          = COALESCE(EXCLUDED.content_type,          person.content_type),
                 faceswap_source_video = COALESCE(EXCLUDED.faceswap_source_video, person.faceswap_source_video),
-                archived              = COALESCE(EXCLUDED.archived,              person.archived);
+                archived              = COALESCE(EXCLUDED.archived,              person.archived),
+                face_embedding        = COALESCE(EXCLUDED.face_embedding,        person.face_embedding);
         """, (filename, filepath, name, group_id,
               json.dumps(tags) if tags else None,
               embedding, clip_description, prompt, pose, sort_order, group_name, hidden,
               has_background, source_refs, has_clothing,
-              content_type, faceswap_source_video, archived))
+              content_type, faceswap_source_video, archived, face_embedding_str))
         conn.commit()
     finally:
         cur.close()
@@ -330,3 +334,55 @@ def get_all_group_names():
     finally:
         cur.close()
         _put_db_connection(conn)
+
+
+def get_face_embedding(filename):
+    """Return the face_embedding as a list of floats for a filename, or None."""
+    conn = get_db_connection()
+    cur = conn.cursor()
+    try:
+        cur.execute("SELECT face_embedding FROM person WHERE filename = %s", (filename,))
+        row = cur.fetchone()
+        if row and row[0] is not None:
+            val = row[0]
+            # psycopg2 without a pgvector adapter returns vectors as plain strings "[f,f,...]"
+            if isinstance(val, str):
+                return [float(x) for x in val.strip("[]").split(",")]
+            return list(val)
+        return None
+    finally:
+        cur.close()
+        _put_db_connection(conn)
+
+
+def search_similar_face(embedding, limit=12, exclude_group_id=None):
+    """Cosine search on face_embedding (stored only for *_face.png rows).
+
+    Returns [(filename, group_id, distance), ...] sorted ascending by distance.
+    Rows belonging to exclude_group_id are skipped so a group doesn't match itself.
+    """
+    conn = get_db_connection()
+    cur = conn.cursor()
+    try:
+        embedding_str = "[" + ",".join(map(str, embedding)) + "]"
+        if exclude_group_id:
+            cur.execute("""
+                SELECT filename, group_id, face_embedding <=> %s AS distance
+                FROM person
+                WHERE face_embedding IS NOT NULL
+                  AND (group_id IS NULL OR group_id != %s)
+                ORDER BY distance ASC
+                LIMIT %s
+            """, (embedding_str, exclude_group_id, limit))
+        else:
+            cur.execute("""
+                SELECT filename, group_id, face_embedding <=> %s AS distance
+                FROM person
+                WHERE face_embedding IS NOT NULL
+                ORDER BY distance ASC
+                LIMIT %s
+            """, (embedding_str, limit))
+        return cur.fetchall()
+    finally:
+        cur.close()
+        _put_db_connection(conn)

tour-comfy/edit_api.py

@@ -1486,6 +1486,7 @@ def list_videos():
 @app.get("/wireframe/frame/{video_name}")
 def wireframe_frame(video_name: str, t: float = 0.5):
     """Extract a single frame at normalized time t (0–1) from a wireframe video. Returns PNG."""
+    import cv2
     wireframe_dir = _load_wireframe_dir()
     video_path = os.path.join(wireframe_dir, video_name)
     if not os.path.exists(video_path):
@@ -1916,10 +1917,12 @@ def _extract_face_bg(filename: str, fpath: str):
         face_fname = f"{gid_tag}_face.png"
         face_path = os.path.join(os.path.dirname(fpath), face_fname)
         cropped.save(face_path)
+        face_embed = face.normed_embedding.tolist() if hasattr(face, 'normed_embedding') and face.normed_embedding is not None else None
         database.upsert_person(face_fname, filepath=face_path, group_id=group_id,
                                name=person[0] if person else None,
-                               source_refs=json.dumps([filename]))
-        print(f"[extract-face] saved {face_fname}")
+                               source_refs=json.dumps([filename]),
+                               face_embedding=face_embed)
+        print(f"[extract-face] saved {face_fname}" + (" + face embedding" if face_embed else ""))
     except Exception as e:
         print(f"[extract-face] error for {filename}: {e}")
 
@@ -2120,6 +2123,88 @@ def extract_face_endpoint(filename: str):
     return {"status": "queued", "filename": filename}
 
 
+class FaceSimilarRequest(BaseModel):
+    group_id: str
+    limit: int = 12
+
+
+@app.post("/faces/similar")
+def face_similar(req: FaceSimilarRequest):
+    """Find groups with visually similar faces using insightface embeddings.
+
+    Looks up the face embedding stored for {group_id}_face.png and returns
+    the top-N closest matches from other groups.
+    """
+    face_fname = f"{req.group_id.replace('/', '_')}_face.png"
+    embedding = database.get_face_embedding(face_fname)
+    if embedding is None:
+        raise HTTPException(404, "No face embedding found for this group — set a preferred image first")
+
+    rows = database.search_similar_face(embedding, limit=req.limit, exclude_group_id=req.group_id)
+    # Each row is (filename, group_id, distance). Return the group thumbnail filename
+    # (the _face.png itself) so the frontend can render it directly.
+    results = [
+        {"filename": r[0], "group_id": r[1], "distance": round(float(r[2]), 4)}
+        for r in rows
+    ]
+    return {"similar": results}
+
+
+_face_index_status: dict = {"running": False, "done": 0, "total": 0, "indexed": 0}
+
+
+def _face_index_worker():
+    """Backfill face embeddings for all *_face.png files that lack one."""
+    global _face_index_status
+    output_dir = _load_output_dir()
+    face_files = [f for f in os.listdir(output_dir) if f.endswith("_face.png")]
+    _face_index_status.update({"running": True, "done": 0, "total": len(face_files), "indexed": 0})
+    try:
+        import cv2
+        app_fa, _ = _load_faceswapper()
+    except Exception as e:
+        print(f"[face-index] failed to load insightface: {e}")
+        _face_index_status["running"] = False
+        return
+    indexed = 0
+    for i, fname in enumerate(face_files):
+        existing = database.get_face_embedding(fname)
+        if existing is not None:
+            _face_index_status["done"] = i + 1
+            continue
+        fpath = os.path.join(output_dir, fname)
+        try:
+            bgr = cv2.imread(fpath)
+            if bgr is None:
+                continue
+            faces = app_fa.get(bgr)
+            if not faces:
+                continue
+            face = max(faces, key=lambda f: (f.bbox[2] - f.bbox[0]) * (f.bbox[3] - f.bbox[1]))
+            if not hasattr(face, 'normed_embedding') or face.normed_embedding is None:
+                continue
+            database.upsert_person(fname, face_embedding=face.normed_embedding.tolist())
+            indexed += 1
+        except Exception as e:
+            print(f"[face-index] {fname}: {e}")
+        _face_index_status.update({"done": i + 1, "indexed": indexed})
+    _face_index_status["running"] = False
+    print(f"[face-index] done: {indexed}/{len(face_files)} embeddings stored")
+
+
+@app.post("/faces/index")
+def build_face_index():
+    if _face_index_status.get("running"):
+        return {"status": "already_running", **_face_index_status}
+    threading.Thread(target=_face_index_worker, daemon=True).start()
+    return {"status": "started"}
+
+
+@app.get("/faces/index/status")
+def face_index_status():
+    return _face_index_status
+
+
 @app.get("/faces/{group_id}")
 def face_status(group_id: str):
     """Report whether a face crop exists for a group.