Update deformes4D_engine.py

deformes4D_engine.py

@@ -190,62 +190,36 @@ class Deformes4DEngine:
         del tensors_para_concatenar; gc.collect(); torch.cuda.empty_cache()
 
         logger.info(f"Concatenação concluída. Shape do super-latente: {processed_latents.shape}")
-        
-        if use_refiner:
-            progress(0.8, desc="Refinando continuidade visual...")
-            # [REATORADO] Chamada para o novo especialista
-            processed_latents = latent_enhancer_specialist_singleton.refine(processed_latents, **refine_ltx_params)
-        
-        logger.info("--- DIVIDINDO SUPER-LATENTE E PROCESSANDO FRAGMENTOS INDIVIDUALMENTE ---")
-        
-        adjusted_lengths = [l - 1 if i < len(latent_fragment_lengths) - 1 else l for i, l in enumerate(latent_fragment_lengths)]
-        
-        refined_fragments = torch.split(processed_latents, adjusted_lengths, dim=2)
-        del processed_latents; gc.collect(); torch.cuda.empty_cache()
-        
-        final_video_paths = []
-        num_final_fragments = len(refined_fragments)
-
-        for i, fragment_latent in enumerate(refined_fragments):
-            progress(0.85 + (0.1 * (i / num_final_fragments)), desc=f"Finalizando Clipe {i+1}/{num_final_fragments}")
-            
-            base_name = f"fragment_{i}_{int(time.time())}"
-            current_path = os.path.join(self.workspace_dir, f"{base_name}_temp.mp4")
 
-            if use_audio:
-                current_path = self._generate_video_and_audio_from_latents(fragment_latent, global_prompt, base_name)
-            else:
-                pixel_tensor = self.latents_to_pixels(fragment_latent)
-                self.save_video_from_tensor(pixel_tensor, current_path, fps=24)
-                del pixel_tensor
-
-            gc.collect(); torch.cuda.empty_cache()
+        base_name = f"fragment_{i}_{int(time.time())}"
+        current_path = os.path.join(self.workspace_dir, f"{base_name}_temp.mp4")
 
-            if use_hd:
-                hd_output_path = os.path.join(self.workspace_dir, f"{base_name}_hd.mp4")
-                try:
-                    hd_specialist_singleton.process_video(input_video_path=current_path, output_video_path=hd_output_path, prompt=" ")
-                    os.remove(current_path)
-                    final_video_paths.append(hd_output_path)
-                except Exception as e:
-                    logger.error(f"Falha na masterização HD do fragmento {i+1}: {e}. Usando versão padrão.")
-                    os.rename(current_path, hd_output_path)
-                    final_video_paths.append(hd_output_path)
-            else:
-                final_video_paths.append(current_path)
+        if use_audio:
+            current_path = self._generate_video_and_audio_from_latents(processed_latents, " ", base_name)
+        else:
+            current_path = self.latents_to_pixels(processed_latents)
+            self.save_video_from_tensor(pixel_tensor, current_path, fps=24)
+            del pixel_tensor
+                
 
-        del refined_fragments; gc.collect(); torch.cuda.empty_cache()
-
-        progress(0.98, desc="Montagem final...")
-        final_movie_path = os.path.join(self.workspace_dir, f"movie_{int(time.time())}_FINAL.mp4")
-        self.concatenate_videos_ffmpeg(final_video_paths, final_movie_path)
+        if use_hd:
+            current_path = os.path.join(self.workspace_dir, f"{base_name}_hd.mp4")
+            try:
+                 hd_specialist_singleton.process_video(input_video_path=current_path, output_video_path=current_path, prompt=" ")
+            except Exception as e:
+                 logger.error(f"Falha na masterização HD do fragmento {i+1}: {e}. Usando versão padrão.")
+                        
+        #if use_refiner:
+        #    progress(0.8, desc="Refinando continuidade visual...")
+        #    # [REATORADO] Chamada para o novo especialista
+        #
         
-        for path in final_video_paths:
-            if os.path.exists(path):
-                os.remove(path)
+         
         
-        logger.info(f"Processo concluído! Vídeo final salvo em: {final_movie_path}")
-        yield {"final_path": final_movie_path}
+        progress(0.98, desc="Montagem final...")
+                   
+        logger.info(f"Processo concluído! Vídeo final salvo em: {current_path}")
+        yield {"final_path": current_path}
 
     def _generate_video_and_audio_from_latents(self, latent_tensor, audio_prompt, base_name):
         silent_video_path = os.path.join(self.workspace_dir, f"{base_name}_silent_for_audio.mp4")