修复LAMA模式100%卡死：帧区间扩展超出视频总帧数导致FramePrefetcher死锁

- 限制字幕区间end不超过frame_count，防止内循环消费哨兵后外层永久阻塞
- LAMA批量推理改为mini-batch(4帧)，避免GPU OOM
- 各inpaint模型空inpaint_area时返回原始帧
- FFmpeg子进程添加600s超时保护

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/inpaint/lama_inpaint.py

@@ -28,35 +28,42 @@ class LamaInpaint:
             return cur_res
 
     def _inpaint_batch(self, images: List[np.ndarray], masks: List[np.ndarray]):
-        """批量推理：将多帧合并为一个 batch tensor 一次性送入 GPU"""
+        """批量推理：将多帧分小批次送入 GPU，避免单次推理过大导致卡死"""
         if len(images) == 1:
             return [self.inpaint(images[0], masks[0])]
 
         orig_height, orig_width = images[0].shape[:2]
-        batch_imgs = []
-        batch_masks = []
-        for img, msk in zip(images, masks):
-            batch_imgs.append(get_image(img))
-            batch_masks.append(get_image(msk))
+        # 分小批次推理，每批最多 4 帧
+        mini_batch_size = 4
+        results = [None] * len(images)
+        for start in range(0, len(images), mini_batch_size):
+            end = min(start + mini_batch_size, len(images))
+            batch_imgs = []
+            batch_masks = []
+            for i in range(start, end):
+                batch_imgs.append(get_image(images[i]))
+                batch_masks.append(get_image(masks[i]))
 
-        # 堆叠为 (B, C, H, W) 并 pad 到 8 的倍数
-        batch_imgs = np.stack(batch_imgs)
-        batch_masks = np.stack(batch_masks)
+            padded_imgs = np.stack([pad_img_to_modulo(img, 8) for img in batch_imgs])
+            padded_masks = np.stack([pad_img_to_modulo(m, 8) for m in batch_masks])
 
-        # 对每个样本做 pad
-        padded_imgs = np.stack([pad_img_to_modulo(img, 8) for img in batch_imgs])
-        padded_masks = np.stack([pad_img_to_modulo(m, 8) for m in batch_masks])
+            img_tensor = torch.from_numpy(padded_imgs).to(self.device)
+            mask_tensor = torch.from_numpy(padded_masks).to(self.device)
+            mask_tensor = (mask_tensor > 0) * 1
 
-        img_tensor = torch.from_numpy(padded_imgs).to(self.device)
-        mask_tensor = torch.from_numpy(padded_masks).to(self.device)
-        mask_tensor = (mask_tensor > 0) * 1
+            with torch.inference_mode():
+                inpainted = self.model(img_tensor, mask_tensor)
+                batch_results = inpainted.permute(0, 2, 3, 1).detach().cpu().numpy()
+                batch_results = np.clip(batch_results * 255, 0, 255).astype('uint8')
 
-        with torch.inference_mode():
-            inpainted = self.model(img_tensor, mask_tensor)
-            results = inpainted.permute(0, 2, 3, 1).detach().cpu().numpy()
-            results = np.clip(results * 255, 0, 255).astype('uint8')
+            for i in range(end - start):
+                results[start + i] = batch_results[i][:orig_height, :orig_width]
 
-        return [results[i][:orig_height, :orig_width] for i in range(len(images))]
+            del img_tensor, mask_tensor, padded_imgs, padded_masks
+            if torch.cuda.is_available():
+                torch.cuda.empty_cache()
+
+        return results
 
     def __call__(self, input_frames: List[np.ndarray], input_mask: np.ndarray):
         """
@@ -98,6 +105,9 @@ class LamaInpaint:
                 for k in range(len(inpaint_area)):
                     frame[inpaint_area[k][0]:inpaint_area[k][1], :, :] = comps[k][j]
                 inpainted_frames.append(frame)
+        else:
+            # 无需处理的区域，返回原始帧
+            inpainted_frames = frames_hr
 
         if torch.cuda.is_available():
             torch.cuda.empty_cache()

backend/inpaint/propainter_inpaint.py

@@ -413,6 +413,8 @@ class PropainterInpaint:
                 # 将最终帧添加到列表
                 inpainted_frames.append(frame)
                 # print(f'processing frame, {len(frames_hr) - j} left')
+        else:
+            inpainted_frames = frames_hr
         return inpainted_frames
 
 

backend/inpaint/sttn_auto_inpaint.py

@@ -92,6 +92,8 @@ class STTNInpaint:
                 # 将最终帧添加到列表
                 inpainted_frames.append(frame)
                 # print(f'processing frame, {len(frames_hr) - j} left')
+        else:
+            inpainted_frames = frames_hr
         return inpainted_frames
 
     @staticmethod

backend/inpaint/sttn_det_inpaint.py

@@ -94,6 +94,8 @@ class STTNDetInpaint:
                 # 将最终帧添加到列表
                 inpainted_frames.append(frame)
                 # print(f'processing frame, {len(frames_hr) - j} left')
+        else:
+            inpainted_frames = frames_hr
         return inpainted_frames
 
     @staticmethod

backend/main.py

@@ -271,9 +271,9 @@ class SubtitleRemover:
         del sub_detector
         gc.collect()
         start_end_map = dict()
-        for interval in continuous_frame_no_list:
-            start, end = interval
-            start_end_map[start] = end
+        for start, end in continuous_frame_no_list:
+            # 确保区间不超出视频总帧数，否则会导致 FramePrefetcher 哨兵被内循环消费后外层死锁
+            start_end_map[start] = min(end, self.frame_count)
         current_frame_index = 0
         self.append_output(tr['Main']['ProcessingStartRemovingSubtitles'])
         # 使用帧预读取，I/O 与推理重叠
@@ -423,7 +423,7 @@ class SubtitleRemover:
                                  "-vn", "-loglevel", "error", temp.name]
         use_shell = True if os.name == "nt" else False
         try:
-            subprocess.check_output(audio_extract_command, stdin=open(os.devnull), shell=use_shell)
+            subprocess.check_output(audio_extract_command, stdin=open(os.devnull), shell=use_shell, timeout=600)
         except Exception as e:
             traceback.print_exc()
             self.append_output(tr['Main']['FailToExtractAudio'].format(str(e)))
@@ -437,7 +437,7 @@ class SubtitleRemover:
                                        "-acodec", "copy",
                                        "-loglevel", "error", self.video_out_path]
                 try:
-                    subprocess.check_output(audio_merge_command, stdin=open(os.devnull), shell=use_shell)
+                    subprocess.check_output(audio_merge_command, stdin=open(os.devnull), shell=use_shell, timeout=600)
                 except Exception as e:
                     traceback.print_exc()
                     self.append_output(tr['Main']['FailToMergeAudio'].format(str(e)))

backend/tools/video_io.py

@@ -97,4 +97,8 @@ class FFmpegVideoWriter:
             self._process.stdin.close()
         except BrokenPipeError:
             pass
-        self._process.wait()
+        try:
+            self._process.wait(timeout=600)
+        except subprocess.TimeoutExpired:
+            self._process.terminate()
+            self._process.wait(timeout=5)