feat: 静画に対応

core/__init__.py

@@ -1,5 +1,5 @@
 """Core module exports."""
 
-from .async_bake_generator import AsyncBakeGenerator, get_bake_generator
-from .async_generator import AsyncMaskGenerator, get_generator
-from .compositor_setup import create_mask_blur_node_tree, get_or_create_blur_node_tree
+from .async_bake_generator import AsyncBakeGenerator as AsyncBakeGenerator, get_bake_generator as get_bake_generator
+from .async_generator import AsyncMaskGenerator as AsyncMaskGenerator, get_generator as get_generator
+from .compositor_setup import create_mask_blur_node_tree as create_mask_blur_node_tree, get_or_create_blur_node_tree as get_or_create_blur_node_tree

core/async_bake_generator.py

@@ -64,12 +64,95 @@ class AsyncBakeGenerator:
             first_interval=0.1,
         )
 
+    def start_images(
+        self,
+        image_dir: str,
+        filenames: list,
+        output_dir: str,
+        detections_path: str,
+        blur_size: int,
+        display_scale: float,
+        on_complete=None,
+        on_progress=None,
+    ):
+        """画像シーケンスのぼかしBakeを非同期で開始する。"""
+        global bpy
+        import bpy as _bpy
+        bpy = _bpy
+
+        if self.is_running:
+            raise RuntimeError("Blur bake already in progress")
+
+        self.is_running = True
+        self.total_frames = len(filenames)
+        self.current_frame = 0
+        self._on_complete = on_complete
+        self._on_progress = on_progress
+
+        self.worker_thread = threading.Thread(
+            target=self._worker_images,
+            args=(image_dir, filenames, output_dir, detections_path, blur_size, display_scale),
+            daemon=True,
+        )
+        self.worker_thread.start()
+        bpy.app.timers.register(self._check_progress, first_interval=0.1)
+
     def cancel(self):
         """Cancel the current bake processing."""
         self.is_running = False
         if self.worker_thread and self.worker_thread.is_alive():
             self.worker_thread.join(timeout=2.0)
 
+    def _worker_images(
+        self,
+        image_dir: str,
+        filenames: list,
+        output_dir: str,
+        detections_path: str,
+        blur_size: int,
+        display_scale: float,
+    ):
+        import time
+        from .inference_client import get_client
+
+        task_id = None
+        try:
+            client = get_client()
+            task_id = client.bake_image_blur(
+                image_dir=image_dir,
+                filenames=filenames,
+                output_dir=output_dir,
+                detections_path=detections_path,
+                blur_size=blur_size,
+                display_scale=display_scale,
+            )
+            while self.is_running:
+                status = client.get_task_status(task_id)
+                state = status.get("status")
+                total = status.get("total", 0)
+                if total > 0:
+                    self.total_frames = total
+                progress = status.get("progress", 0)
+                if progress >= 0:
+                    self.progress_queue.put(("progress", progress))
+                if state == "completed":
+                    result_path = status.get("result_path", output_dir)
+                    self.result_queue.put(("done", result_path))
+                    return
+                if state == "failed":
+                    self.result_queue.put(("error", status.get("message", "Unknown error")))
+                    return
+                if state == "cancelled":
+                    self.result_queue.put(("cancelled", None))
+                    return
+                time.sleep(0.5)
+
+            if task_id:
+                client.cancel_task(task_id)
+            self.result_queue.put(("cancelled", None))
+        except Exception as e:
+            self.result_queue.put(("error", str(e)))
+
     def _worker(
         self,
         video_path: str,

core/async_generator.py

@@ -104,12 +104,105 @@ class AsyncMaskGenerator:
             first_interval=0.1,
         )
     
+    def start_images(
+        self,
+        image_dir: str,
+        filenames: list,
+        output_dir: str,
+        start_index: int,
+        end_index: int,
+        conf_threshold: float = 0.5,
+        iou_threshold: float = 0.45,
+        on_complete=None,
+        on_progress=None,
+    ):
+        """画像シーケンスの顔検出を非同期で開始する。"""
+        global bpy
+        import bpy as _bpy
+        bpy = _bpy
+
+        if self.is_running:
+            raise RuntimeError("Mask generation already in progress")
+
+        self.is_running = True
+        self.total_frames = end_index - start_index + 1
+        self.current_frame = 0
+        self._on_complete = on_complete
+        self._on_progress = on_progress
+
+        os.makedirs(output_dir, exist_ok=True)
+
+        self.worker_thread = threading.Thread(
+            target=self._worker_images,
+            args=(image_dir, filenames, output_dir, start_index, end_index,
+                  conf_threshold, iou_threshold),
+            daemon=True,
+        )
+        self.worker_thread.start()
+        bpy.app.timers.register(self._check_progress, first_interval=0.1)
+
     def cancel(self):
         """Cancel the current processing."""
         self.is_running = False
         if self.worker_thread and self.worker_thread.is_alive():
             self.worker_thread.join(timeout=2.0)
 
+    def _worker_images(
+        self,
+        image_dir: str,
+        filenames: list,
+        output_dir: str,
+        start_index: int,
+        end_index: int,
+        conf_threshold: float,
+        iou_threshold: float,
+    ):
+        import time
+        from .inference_client import get_client
+
+        try:
+            client = get_client()
+            task_id = client.generate_mask_images(
+                image_dir=image_dir,
+                filenames=filenames,
+                output_dir=output_dir,
+                start_index=start_index,
+                end_index=end_index,
+                conf_threshold=conf_threshold,
+                iou_threshold=iou_threshold,
+            )
+            while self.is_running:
+                status = client.get_task_status(task_id)
+                state = status.get("status")
+                total = status.get("total", 0)
+                if total > 0:
+                    self.total_frames = total
+                if state == "completed":
+                    progress = status.get("progress", self.total_frames)
+                    if progress >= 0:
+                        self.progress_queue.put(("progress", progress))
+                    result_path = status.get(
+                        "result_path",
+                        os.path.join(output_dir, "detections.msgpack"),
+                    )
+                    self.result_queue.put(("done", result_path))
+                    return
+                elif state == "failed":
+                    self.result_queue.put(("error", status.get("message", "Unknown error")))
+                    return
+                elif state == "cancelled":
+                    self.result_queue.put(("cancelled", None))
+                    return
+                progress = status.get("progress", 0)
+                if progress >= 0:
+                    self.progress_queue.put(("progress", progress))
+                time.sleep(0.5)
+
+            client.cancel_task(task_id)
+            self.result_queue.put(("cancelled", None))
+        except Exception as e:
+            self.result_queue.put(("error", str(e)))
+
     def _worker(
         self,
         video_path: str,

core/inference_client.py

@@ -305,6 +305,76 @@ class InferenceClient:
         except urllib.error.HTTPError as e:
             raise RuntimeError(f"Server error: {e.read().decode('utf-8')}")
 
+    def generate_mask_images(
+        self,
+        image_dir: str,
+        filenames: list,
+        output_dir: str,
+        start_index: int,
+        end_index: int,
+        conf_threshold: float,
+        iou_threshold: float,
+    ) -> str:
+        """画像シーケンスの顔検出タスクを開始して task_id を返す。"""
+        if not self.is_server_running():
+            self.start_server()
+
+        data = {
+            "image_dir": image_dir,
+            "filenames": filenames,
+            "output_dir": output_dir,
+            "start_index": start_index,
+            "end_index": end_index,
+            "conf_threshold": conf_threshold,
+            "iou_threshold": iou_threshold,
+        }
+        req = urllib.request.Request(
+            f"{self.SERVER_URL}/generate_images",
+            data=json.dumps(data).encode("utf-8"),
+            headers={"Content-Type": "application/json"},
+            method="POST",
+        )
+        try:
+            with urllib.request.urlopen(req) as response:
+                result = json.loads(response.read().decode("utf-8"))
+                return result["id"]
+        except urllib.error.HTTPError as e:
+            raise RuntimeError(f"Server error: {e.read().decode('utf-8')}")
+
+    def bake_image_blur(
+        self,
+        image_dir: str,
+        filenames: list,
+        output_dir: str,
+        detections_path: str,
+        blur_size: int,
+        display_scale: float,
+    ) -> str:
+        """画像シーケンスのぼかしBakeタスクを開始して task_id を返す。"""
+        if not self.is_server_running():
+            self.start_server()
+
+        data = {
+            "image_dir": image_dir,
+            "filenames": filenames,
+            "output_dir": output_dir,
+            "detections_path": detections_path,
+            "blur_size": blur_size,
+            "display_scale": display_scale,
+        }
+        req = urllib.request.Request(
+            f"{self.SERVER_URL}/bake_image_blur",
+            data=json.dumps(data).encode("utf-8"),
+            headers={"Content-Type": "application/json"},
+            method="POST",
+        )
+        try:
+            with urllib.request.urlopen(req) as response:
+                result = json.loads(response.read().decode("utf-8"))
+                return result["id"]
+        except urllib.error.HTTPError as e:
+            raise RuntimeError(f"Server error: {e.read().decode('utf-8')}")
+
     def cancel_task(self, task_id: str):
         """Cancel a task."""
         try:

operators/apply_blur.py

@@ -37,6 +37,12 @@ def _output_path(video_strip, detections_path: str, fmt: str) -> str:
     return os.path.join(out_dir, f"{safe_name}_blurred.{ext}")
 
 
+def _output_dir_for_images(strip, detections_path: str) -> str:
+    out_dir = os.path.dirname(detections_path)
+    safe_name = strip.name.replace("/", "_").replace("\\", "_")
+    return os.path.join(out_dir, f"{safe_name}_blurred")
+
+
 def _reload_movie_strip(strip):
     if hasattr(strip, "reload"):
         try:
@@ -45,8 +51,11 @@ def _reload_movie_strip(strip):
             pass
 
 
-def _set_strip_source(strip, filepath: str):
-    strip.filepath = filepath
+def _set_strip_source(strip, path: str):
+    if strip.type == "IMAGE":
+        strip.directory = path
+    else:
+        strip.filepath = path
         _reload_movie_strip(strip)
 
 
@@ -56,29 +65,42 @@ def _start_bake_impl(operator, context, force: bool = False, strip=None, on_comp
     strip: 処理対象のstrip。None の場合は active_strip を使用。
     on_complete_extra: 非同期Bake完了時に追加で呼ばれるコールバック (status, data)。
                        キャッシュヒット即時完了の場合は呼ばれない。
+    MOVIE / IMAGE 両対応。
     """
     seq_editor = context.scene.sequence_editor
     scene = context.scene
     video_strip = strip if strip is not None else seq_editor.active_strip
+    is_image = video_strip.type == "IMAGE"
 
-    video_path = bpy.path.abspath(video_strip.filepath)
     detections_path = get_detections_path_for_strip(video_strip.name)
-    if not os.path.exists(video_path):
-        operator.report({"ERROR"}, f"Source video not found: {video_path}")
-        return {"CANCELLED"}
     if not os.path.exists(detections_path):
         operator.report({"ERROR"}, f"Detection cache not found: {detections_path}")
         return {"CANCELLED"}
 
-    bake_format = scene.facemask_bake_format
-    output_path = _output_path(video_strip, detections_path, bake_format)
     blur_size = int(scene.facemask_bake_blur_size)
     display_scale = float(scene.facemask_bake_display_scale)
 
+    if is_image:
+        image_dir = bpy.path.abspath(video_strip.directory)
+        filenames = [elem.filename for elem in video_strip.elements]
+        if not os.path.isdir(image_dir):
+            operator.report({"ERROR"}, f"Image directory not found: {image_dir}")
+            return {"CANCELLED"}
+        output_dir = _output_dir_for_images(video_strip, detections_path)
+        original_source = image_dir
+        bake_format = None  # IMAGE strips don't use format
+    else:
+        video_path = bpy.path.abspath(video_strip.filepath)
+        if not os.path.exists(video_path):
+            operator.report({"ERROR"}, f"Source video not found: {video_path}")
+            return {"CANCELLED"}
+        bake_format = scene.facemask_bake_format
+        output_path = _output_path(video_strip, detections_path, bake_format)
+        original_source = video_path
+
     if not force:
         # パラメータが一致するキャッシュがあればswapのみ
         cached_baked_path = video_strip.get(KEY_BAKED)
-        cached_format = video_strip.get(KEY_FORMAT)
         cached_blur_size = video_strip.get(KEY_BLUR_SIZE)
         cached_display_scale = video_strip.get(KEY_DISPLAY_SCALE)
         try:
@@ -89,13 +111,16 @@ def _start_bake_impl(operator, context, force: bool = False, strip=None, on_comp
             cached_display_scale_f = float(cached_display_scale)
         except (TypeError, ValueError):
             cached_display_scale_f = None
-        if (
-            cached_baked_path
-            and os.path.exists(cached_baked_path)
-            and cached_format == bake_format
+
+        cache_exists = (
+            cached_baked_path and os.path.exists(cached_baked_path)
             and cached_blur_size_int == blur_size
             and cached_display_scale_f == display_scale
-        ):
+        )
+        if not is_image:
+            cache_exists = cache_exists and video_strip.get(KEY_FORMAT) == bake_format
+
+        if cache_exists:
             if video_strip.get(KEY_MODE) != "baked":
                 video_strip[KEY_MODE] = "baked"
                 _set_strip_source(video_strip, cached_baked_path)
@@ -112,18 +137,18 @@ def _start_bake_impl(operator, context, force: bool = False, strip=None, on_comp
             return
 
         if status == "done":
-            result_path = data or output_path
-            original_path = strip.get(KEY_ORIGINAL)
+            result = data or (output_dir if is_image else output_path)
             current_mode = strip.get(KEY_MODE, "original")
-            if not original_path or current_mode != "baked":
-                strip[KEY_ORIGINAL] = video_path
-            strip[KEY_BAKED] = result_path
+            if not strip.get(KEY_ORIGINAL) or current_mode != "baked":
+                strip[KEY_ORIGINAL] = original_source
+            strip[KEY_BAKED] = result
             strip[KEY_MODE] = "baked"
-            strip[KEY_FORMAT] = bake_format
             strip[KEY_BLUR_SIZE] = blur_size
             strip[KEY_DISPLAY_SCALE] = display_scale
-            _set_strip_source(strip, result_path)
-            print(f"[FaceMask] Bake completed and source swapped: {result_path}")
+            if not is_image:
+                strip[KEY_FORMAT] = bake_format
+            _set_strip_source(strip, result)
+            print(f"[FaceMask] Bake completed and source swapped: {result}")
         elif status == "error":
             print(f"[FaceMask] Bake failed: {data}")
         elif status == "cancelled":
@@ -147,6 +172,18 @@ def _start_bake_impl(operator, context, force: bool = False, strip=None, on_comp
     wm.bake_total = 1
 
     try:
+        if is_image:
+            bake_generator.start_images(
+                image_dir=image_dir,
+                filenames=filenames,
+                output_dir=output_dir,
+                detections_path=detections_path,
+                blur_size=blur_size,
+                display_scale=display_scale,
+                on_complete=on_complete,
+                on_progress=on_progress,
+            )
+        else:
             bake_generator.start(
                 video_path=video_path,
                 detections_path=detections_path,
@@ -182,7 +219,7 @@ class SEQUENCER_OT_bake_and_swap_blur_source(Operator):
         if get_bake_generator().is_running:
             return False
         strip = context.scene.sequence_editor.active_strip
-        return bool(strip and strip.type == "MOVIE")
+        return bool(strip and strip.type in {"MOVIE", "IMAGE"})
 
     def execute(self, context):
         return _start_bake_impl(self, context, force=False)
@@ -205,7 +242,7 @@ class SEQUENCER_OT_force_rebake_blur(Operator):
         if get_bake_generator().is_running:
             return False
         strip = context.scene.sequence_editor.active_strip
-        return bool(strip and strip.type == "MOVIE")
+        return bool(strip and strip.type in {"MOVIE", "IMAGE"})
 
     def execute(self, context):
         return _start_bake_impl(self, context, force=True)
@@ -226,7 +263,7 @@ class SEQUENCER_OT_swap_to_baked_blur(Operator):
         if get_bake_generator().is_running:
             return False
         strip = context.scene.sequence_editor.active_strip
-        if not strip or strip.type != "MOVIE":
+        if not strip or strip.type not in {"MOVIE", "IMAGE"}:
             return False
         baked_path = strip.get(KEY_BAKED)
         return bool(baked_path and os.path.exists(baked_path))
@@ -255,7 +292,7 @@ class SEQUENCER_OT_restore_original_source(Operator):
         if get_bake_generator().is_running:
             return False
         strip = context.scene.sequence_editor.active_strip
-        if not strip or strip.type != "MOVIE":
+        if not strip or strip.type not in {"MOVIE", "IMAGE"}:
             return False
         if strip.get(KEY_MODE, "original") == "original":
             return False

operators/batch_bake.py

@@ -15,11 +15,11 @@ from .apply_blur import KEY_ORIGINAL, KEY_MODE, _set_strip_source
 
 
 class SEQUENCER_OT_batch_bake_selected(Operator):
-    """Generate detection cache and bake blur for all selected MOVIE strips."""
+    """Generate detection cache and bake blur for all selected MOVIE/IMAGE strips."""
 
     bl_idname = "sequencer.batch_bake_selected"
     bl_label = "Batch Bake Selected"
-    bl_description = "Generate detection cache and bake blur for all selected MOVIE strips"
+    bl_description = "Generate detection cache and bake blur for all selected MOVIE/IMAGE strips"
     bl_options = {"REGISTER"}
 
     @classmethod
@@ -33,14 +33,14 @@ class SEQUENCER_OT_batch_bake_selected(Operator):
         if get_bake_generator().is_running:
             return False
         seq_editor = context.scene.sequence_editor
-        return any(s.select and s.type == "MOVIE" for s in seq_editor.strips)
+        return any(s.select and s.type in {"MOVIE", "IMAGE"} for s in seq_editor.strips)
 
     def execute(self, context):
         seq_editor = context.scene.sequence_editor
-        strips = [s for s in seq_editor.strips if s.select and s.type == "MOVIE"]
+        strips = [s for s in seq_editor.strips if s.select and s.type in {"MOVIE", "IMAGE"}]
 
         if not strips:
-            self.report({"WARNING"}, "No MOVIE strips selected")
+            self.report({"WARNING"}, "No MOVIE or IMAGE strips selected")
             return {"CANCELLED"}
 
         batch = get_batch_processor()
@@ -64,11 +64,11 @@ class SEQUENCER_OT_batch_bake_selected(Operator):
 
 
 class SEQUENCER_OT_batch_regenerate_cache(Operator):
-    """Regenerate detection cache for all selected MOVIE strips (ignore existing cache)."""
+    """Regenerate detection cache for all selected MOVIE/IMAGE strips (ignore existing cache)."""
 
     bl_idname = "sequencer.batch_regenerate_cache"
     bl_label = "Batch Regenerate Cache"
-    bl_description = "Regenerate detection cache for all selected MOVIE strips"
+    bl_description = "Regenerate detection cache for all selected MOVIE/IMAGE strips"
     bl_options = {"REGISTER"}
 
     @classmethod
@@ -82,14 +82,14 @@ class SEQUENCER_OT_batch_regenerate_cache(Operator):
         if get_bake_generator().is_running:
             return False
         seq_editor = context.scene.sequence_editor
-        return any(s.select and s.type == "MOVIE" for s in seq_editor.strips)
+        return any(s.select and s.type in {"MOVIE", "IMAGE"} for s in seq_editor.strips)
 
     def execute(self, context):
         seq_editor = context.scene.sequence_editor
-        strips = [s for s in seq_editor.strips if s.select and s.type == "MOVIE"]
+        strips = [s for s in seq_editor.strips if s.select and s.type in {"MOVIE", "IMAGE"}]
 
         if not strips:
-            self.report({"WARNING"}, "No MOVIE strips selected")
+            self.report({"WARNING"}, "No MOVIE or IMAGE strips selected")
             return {"CANCELLED"}
 
         batch = get_batch_processor()
@@ -109,11 +109,11 @@ class SEQUENCER_OT_batch_regenerate_cache(Operator):
 
 
 class SEQUENCER_OT_batch_restore_original(Operator):
-    """Restore original source for all selected MOVIE strips."""
+    """Restore original source for all selected MOVIE/IMAGE strips."""
 
     bl_idname = "sequencer.batch_restore_original"
     bl_label = "Batch Restore Original"
-    bl_description = "Restore original source filepath for all selected MOVIE strips"
+    bl_description = "Restore original source filepath for all selected MOVIE/IMAGE strips"
     bl_options = {"REGISTER", "UNDO"}
 
     @classmethod
@@ -123,11 +123,11 @@ class SEQUENCER_OT_batch_restore_original(Operator):
         if get_batch_processor().is_running:
             return False
         seq_editor = context.scene.sequence_editor
-        return any(s.select and s.type == "MOVIE" for s in seq_editor.strips)
+        return any(s.select and s.type in {"MOVIE", "IMAGE"} for s in seq_editor.strips)
 
     def execute(self, context):
         seq_editor = context.scene.sequence_editor
-        strips = [s for s in seq_editor.strips if s.select and s.type == "MOVIE"]
+        strips = [s for s in seq_editor.strips if s.select and s.type in {"MOVIE", "IMAGE"}]
 
         restored = 0
         skipped = 0

operators/generate_mask.py

@@ -34,11 +34,28 @@ def compute_strip_frame_range(strip, scene, client) -> tuple:
     return start_frame, end_frame, source_fps
 
 
+def get_image_strip_files(strip) -> tuple:
+    """IMAGE strip の (abs_image_dir, filenames_list) を返す。"""
+    image_dir = bpy.path.abspath(strip.directory)
+    filenames = [elem.filename for elem in strip.elements]
+    return image_dir, filenames
+
+
+def compute_image_strip_range(strip) -> tuple:
+    """IMAGE strip のアクティブ範囲 (start_index, end_index) を返す。"""
+    total_elements = len(strip.elements)
+    start_idx = max(0, int(strip.frame_offset_start))
+    end_idx = start_idx + int(strip.frame_final_duration) - 1
+    start_idx = min(start_idx, total_elements - 1)
+    end_idx = max(start_idx, min(end_idx, total_elements - 1))
+    return start_idx, end_idx
+
+
 def start_mask_gen_for_strip(context, strip, on_complete, on_progress):
-    """Strip のマスク生成を開始する共通処理。
+    """Strip のマスク生成を開始する共通処理（MOVIE / IMAGE 両対応）。
 
     generator.is_running 等のエラー時は例外を送出する。
-    wm.mask_progress / mask_total を初期化してから generator.start() を呼ぶ。
+    wm.mask_progress / mask_total を初期化してから generator.start*() を呼ぶ。
     """
     scene = context.scene
     wm = context.window_manager
@@ -47,15 +64,31 @@ def start_mask_gen_for_strip(context, strip, on_complete, on_progress):
     if generator.is_running:
         raise RuntimeError("Mask generation already in progress")
 
-    client = get_client()
-    start_frame, end_frame, source_fps = compute_strip_frame_range(strip, scene, client)
-
     output_dir = get_cache_dir_for_strip(strip.name)
     os.makedirs(output_dir, exist_ok=True)
-
     wm.mask_progress = 0
-    wm.mask_total = end_frame - start_frame + 1
 
+    if strip.type == "IMAGE":
+        image_dir, filenames = get_image_strip_files(strip)
+        if not filenames:
+            raise ValueError("Image strip has no elements")
+        start_idx, end_idx = compute_image_strip_range(strip)
+        wm.mask_total = end_idx - start_idx + 1
+        generator.start_images(
+            image_dir=image_dir,
+            filenames=filenames,
+            output_dir=output_dir,
+            start_index=start_idx,
+            end_index=end_idx,
+            conf_threshold=scene.facemask_conf_threshold,
+            iou_threshold=scene.facemask_iou_threshold,
+            on_complete=on_complete,
+            on_progress=on_progress,
+        )
+    else:
+        client = get_client()
+        start_frame, end_frame, source_fps = compute_strip_frame_range(strip, scene, client)
+        wm.mask_total = end_frame - start_frame + 1
         generator.start(
             video_path=bpy.path.abspath(strip.filepath),
             output_dir=output_dir,

panels/vse_panel.py

@@ -232,10 +232,10 @@ class SEQUENCER_PT_face_mask(Panel):
         )
 
     def _draw_batch_controls(self, layout, context, seq_editor):
-        """Draw batch bake button when multiple MOVIE strips are selected."""
+        """Draw batch bake button when multiple MOVIE/IMAGE strips are selected."""
         if not seq_editor:
             return
-        selected_movies = [s for s in seq_editor.strips if s.select and s.type == "MOVIE"]
+        selected_movies = [s for s in seq_editor.strips if s.select and s.type in {"MOVIE", "IMAGE"}]
         if not selected_movies:
             return
         count = len(selected_movies)
@@ -303,6 +303,7 @@ class SEQUENCER_PT_face_mask(Panel):
         col = box.column(align=True)
         col.prop(context.scene, "facemask_bake_blur_size")
         col.prop(context.scene, "facemask_bake_display_scale")
+        if strip.type == "MOVIE":
             col.prop(context.scene, "facemask_bake_format")
 
         box.separator()

server/main.py

@@ -132,6 +132,25 @@ class BakeRequest(BaseModel):
     format: str = "mp4"
 
 
+class GenerateImagesRequest(BaseModel):
+    image_dir: str
+    filenames: List[str]
+    output_dir: str
+    start_index: int = 0
+    end_index: int = -1
+    conf_threshold: float = 0.5
+    iou_threshold: float = 0.45
+
+
+class BakeImagesRequest(BaseModel):
+    image_dir: str
+    filenames: List[str]
+    output_dir: str
+    detections_path: str
+    blur_size: int = 50
+    display_scale: float = 1.0
+
+
 class _FFmpegPipeWriter:
     """Write BGR frames to ffmpeg stdin."""
 
@@ -302,6 +321,267 @@ def _scale_bbox(
     return [x1, y1, out_w, out_h]
 
 
+def _apply_face_blur_inplace(
+    frame: np.ndarray,
+    frame_boxes: list,
+    src_width: int,
+    src_height: int,
+    blur_size: int,
+    display_scale: float,
+    blur_margin: int,
+) -> None:
+    """検出済み顔領域にガウスぼかしを適用する（in-place）。"""
+    if not frame_boxes:
+        return
+
+    for box in frame_boxes:
+        if not isinstance(box, list) or len(box) < 4:
+            continue
+        x, y, w, h = int(box[0]), int(box[1]), int(box[2]), int(box[3])
+        if w <= 0 or h <= 0:
+            continue
+
+        cx = x + w / 2
+        cy = y + h / 2
+        dw = max(1, int(w * display_scale))
+        dh = max(1, int(h * display_scale))
+        dx = int(cx - dw / 2)
+        dy = int(cy - dh / 2)
+
+        roi_x1 = max(0, dx - blur_margin)
+        roi_y1 = max(0, dy - blur_margin)
+        roi_x2 = min(src_width, dx + dw + blur_margin)
+        roi_y2 = min(src_height, dy + dh + blur_margin)
+        roi_width = roi_x2 - roi_x1
+        roi_height = roi_y2 - roi_y1
+        if roi_width <= 0 or roi_height <= 0:
+            continue
+
+        roi_src = frame[roi_y1:roi_y2, roi_x1:roi_x2]
+        small_w = max(1, roi_width // 2)
+        small_h = max(1, roi_height // 2)
+        roi_small = cv2.resize(roi_src, (small_w, small_h), interpolation=cv2.INTER_LINEAR)
+        small_blur_size = max(3, (blur_size // 2) | 1)
+        roi_small_blurred = cv2.GaussianBlur(roi_small, (small_blur_size, small_blur_size), 0)
+        roi_blurred = cv2.resize(roi_small_blurred, (roi_width, roi_height), interpolation=cv2.INTER_LINEAR)
+
+        roi_mask = np.zeros((roi_height, roi_width), dtype=np.uint8)
+        center = (int(cx) - roi_x1, int(cy) - roi_y1)
+        axes = (max(1, dw // 2), max(1, dh // 2))
+        cv2.ellipse(roi_mask, center, axes, 0, 0, 360, 255, -1)
+
+        result = roi_src.copy()
+        cv2.copyTo(roi_blurred, roi_mask, result)
+        frame[roi_y1:roi_y2, roi_x1:roi_x2] = result
+
+
+def process_images_task(task_id: str, req: GenerateImagesRequest):
+    """画像シーケンスから顔を検出して msgpack キャッシュを保存する。"""
+    try:
+        tasks[task_id].status = TaskStatus.PROCESSING
+        cancel_event = cancel_events.get(task_id)
+
+        if not os.path.exists(req.image_dir):
+            tasks[task_id].status = TaskStatus.FAILED
+            tasks[task_id].message = f"Image directory not found: {req.image_dir}"
+            return
+        if not req.filenames:
+            tasks[task_id].status = TaskStatus.FAILED
+            tasks[task_id].message = "No filenames provided"
+            return
+
+        detector = get_detector(
+            conf_threshold=req.conf_threshold,
+            iou_threshold=req.iou_threshold,
+        )
+        _ = detector.model
+
+        total_files = len(req.filenames)
+        start_idx = max(0, req.start_index)
+        end_idx = req.end_index if req.end_index >= 0 else total_files - 1
+        end_idx = min(end_idx, total_files - 1)
+
+        if start_idx > end_idx:
+            tasks[task_id].status = TaskStatus.FAILED
+            tasks[task_id].message = "Invalid index range"
+            return
+
+        indices = list(range(start_idx, end_idx + 1))
+        tasks[task_id].total = len(indices)
+        os.makedirs(req.output_dir, exist_ok=True)
+        output_msgpack_path = os.path.join(req.output_dir, "detections.msgpack")
+
+        # 画像サイズを最初のファイルから取得
+        first_path = os.path.join(req.image_dir, req.filenames[start_idx])
+        first_img = cv2.imread(first_path)
+        if first_img is None:
+            tasks[task_id].status = TaskStatus.FAILED
+            tasks[task_id].message = f"Cannot read image: {first_path}"
+            return
+        height, width = first_img.shape[:2]
+
+        frame_buffer: List[np.ndarray] = []
+        frame_detections: List[List[List[float]]] = []
+        batch_size = 5
+        current_count = 0
+
+        def process_batch():
+            nonlocal current_count
+            if not frame_buffer:
+                return
+            batch_det = detector.detect_batch(frame_buffer)
+            for detections in batch_det:
+                packed: List[List[float]] = []
+                for x, y, w, h, conf in detections:
+                    bx, by, bw, bh = int(x), int(y), int(w), int(h)
+                    bx = max(0, bx)
+                    by = max(0, by)
+                    bw = min(width - bx, bw)
+                    bh = min(height - by, bh)
+                    if bw <= 0 or bh <= 0:
+                        continue
+                    packed.append([bx, by, bw, bh, float(conf)])
+                frame_detections.append(packed)
+                current_count += 1
+                tasks[task_id].progress = current_count
+            frame_buffer.clear()
+
+        print(
+            f"[FaceMask] Starting image detection: {req.image_dir} "
+            f"({len(indices)} images) -> {output_msgpack_path}"
+        )
+
+        for file_idx in indices:
+            if cancel_event and cancel_event.is_set():
+                tasks[task_id].status = TaskStatus.CANCELLED
+                tasks[task_id].message = "Cancelled by user"
+                break
+
+            img_path = os.path.join(req.image_dir, req.filenames[file_idx])
+            frame = cv2.imread(img_path)
+            if frame is None:
+                frame_detections.append([])
+                current_count += 1
+                tasks[task_id].progress = current_count
+                continue
+
+            frame_buffer.append(frame)
+            if len(frame_buffer) >= batch_size:
+                process_batch()
+
+        if frame_buffer:
+            process_batch()
+
+        if tasks[task_id].status == TaskStatus.PROCESSING:
+            payload = {
+                "version": 1,
+                "image_dir": req.image_dir,
+                "filenames": req.filenames,
+                "start_frame": start_idx,
+                "end_frame": start_idx + len(frame_detections) - 1,
+                "width": width,
+                "height": height,
+                "fps": 0.0,
+                "mask_scale": 1.0,
+                "frames": frame_detections,
+            }
+            with open(output_msgpack_path, "wb") as f:
+                f.write(msgpack.packb(payload, use_bin_type=True))
+
+            tasks[task_id].status = TaskStatus.COMPLETED
+            tasks[task_id].result_path = output_msgpack_path
+            tasks[task_id].message = "Image detection cache completed"
+            print(f"[FaceMask] Image detection done: {output_msgpack_path}")
+
+    except Exception as e:
+        tasks[task_id].status = TaskStatus.FAILED
+        tasks[task_id].message = str(e)
+        traceback.print_exc()
+    finally:
+        if task_id in cancel_events:
+            del cancel_events[task_id]
+
+
+def process_bake_images_task(task_id: str, req: BakeImagesRequest):
+    """画像シーケンスに顔ぼかしを適用して新ディレクトリへ書き出す。"""
+    try:
+        tasks[task_id].status = TaskStatus.PROCESSING
+        cancel_event = cancel_events.get(task_id)
+
+        if not os.path.exists(req.image_dir):
+            tasks[task_id].status = TaskStatus.FAILED
+            tasks[task_id].message = f"Image directory not found: {req.image_dir}"
+            return
+        if not os.path.exists(req.detections_path):
+            tasks[task_id].status = TaskStatus.FAILED
+            tasks[task_id].message = f"Detections file not found: {req.detections_path}"
+            return
+
+        with open(req.detections_path, "rb") as f:
+            payload = msgpack.unpackb(f.read(), raw=False)
+        frames_detections = payload.get("frames")
+        if not isinstance(frames_detections, list):
+            tasks[task_id].status = TaskStatus.FAILED
+            tasks[task_id].message = "Invalid detections format: 'frames' is missing"
+            return
+
+        det_start_frame = int(payload.get("start_frame", 0))
+
+        blur_size = max(1, int(req.blur_size))
+        if blur_size % 2 == 0:
+            blur_size += 1
+        display_scale = max(0.1, float(req.display_scale))
+        blur_margin = blur_size // 2
+
+        os.makedirs(req.output_dir, exist_ok=True)
+        total = len(req.filenames)
+        tasks[task_id].total = total
+
+        print(
+            f"[FaceMask] Starting image bake: {req.image_dir} "
+            f"({total} images) -> {req.output_dir}"
+        )
+
+        for i, filename in enumerate(req.filenames):
+            if cancel_event and cancel_event.is_set():
+                tasks[task_id].status = TaskStatus.CANCELLED
+                tasks[task_id].message = "Cancelled by user"
+                return
+
+            src_path = os.path.join(req.image_dir, filename)
+            frame = cv2.imread(src_path)
+            if frame is None:
+                tasks[task_id].progress = i + 1
+                continue
+
+            h, w = frame.shape[:2]
+            det_idx = i - det_start_frame
+            frame_boxes = (
+                frames_detections[det_idx]
+                if 0 <= det_idx < len(frames_detections)
+                else []
+            )
+            _apply_face_blur_inplace(frame, frame_boxes, w, h, blur_size, display_scale, blur_margin)
+
+            out_path = os.path.join(req.output_dir, filename)
+            cv2.imwrite(out_path, frame)
+            tasks[task_id].progress = i + 1
+
+        if tasks[task_id].status == TaskStatus.PROCESSING:
+            tasks[task_id].status = TaskStatus.COMPLETED
+            tasks[task_id].result_path = req.output_dir
+            tasks[task_id].message = "Image blur bake completed"
+            print(f"[FaceMask] Image bake completed: {req.output_dir}")
+
+    except Exception as e:
+        tasks[task_id].status = TaskStatus.FAILED
+        tasks[task_id].message = str(e)
+        traceback.print_exc()
+    finally:
+        if task_id in cancel_events:
+            del cancel_events[task_id]
+
+
 def process_video_task(task_id: str, req: GenerateRequest):
     """Background task to detect faces and save bbox cache as msgpack."""
     cap = None
@@ -971,6 +1251,26 @@ def bake_blur_endpoint(req: BakeRequest, background_tasks: BackgroundTasks):
     background_tasks.add_task(process_bake_task, task_id, req)
     return task
 
+@app.post("/generate_images", response_model=Task)
+def generate_images_endpoint(req: GenerateImagesRequest, background_tasks: BackgroundTasks):
+    task_id = str(uuid.uuid4())
+    task = Task(id=task_id, status=TaskStatus.PENDING)
+    tasks[task_id] = task
+    cancel_events[task_id] = threading.Event()
+    background_tasks.add_task(process_images_task, task_id, req)
+    return task
+
+
+@app.post("/bake_image_blur", response_model=Task)
+def bake_image_blur_endpoint(req: BakeImagesRequest, background_tasks: BackgroundTasks):
+    task_id = str(uuid.uuid4())
+    task = Task(id=task_id, status=TaskStatus.PENDING)
+    tasks[task_id] = task
+    cancel_events[task_id] = threading.Event()
+    background_tasks.add_task(process_bake_images_task, task_id, req)
+    return task
+
+
 @app.get("/tasks/{task_id}", response_model=Task)
 def get_task(task_id: str):
     if task_id not in tasks: