Update app.py

app.py

@@ -1,213 +1,249 @@
-# app.py (Versão Corrigida)
+# app.py (Versão Unificada LTX + SeedVR)
 
+# --- 0. WARNINGS E SETUP ---
+import warnings
+warnings.filterwarnings("ignore")
 import gradio as gr
 from PIL import Image
 import os
 import imageio
-from api.ltx_server import video_generation_service
+import multiprocessing as mp
 
+# --- 1. IMPORTAÇÃO DOS DOIS SERVIÇOS ---
 
-from huggingface_hub import logging
+# Importa o serviço de geração do LTX
+try:
+    from api.ltx_server import video_generation_service
+except ImportError:
+    raise ImportError("Falha ao importar o 'video_generation_service' de 'api.ltx_server'.")
 
+# Importa o serviço de upscale do SeedVR
+try:
+    from api.seedvr_server import SeedVRServer
+except ImportError:
+    raise ImportError("Falha ao importar o 'SeedVRServer' de 'api.seedvr_server'.")
 
-logging.set_verbosity_error()
-logging.set_verbosity_warning()
-logging.set_verbosity_info()
-logging.set_verbosity_debug()
+# --- 2. INICIALIZAÇÃO DOS SERVIÇOS ---
+print("🚀 Inicializando o serviço de geração LTX-Video...")
+ltx_service = video_generation_service
+print("✅ Serviço LTX-Video pronto.")
 
-enable_progress_bars()
+print("🚀 Inicializando o serviço de upscale SeedVR...")
+seedvr_service = SeedVRServer()
+print("✅ Serviço SeedVR pronto.")
 
-# --- FUNÇÕES DE AJUDA PARA A UI ---
-# ... (calculate_new_dimensions e handle_media_upload_for_dims permanecem as mesmas) ...
+
+# --- 3. FUNÇÕES HELPER DA UI (sem grandes alterações) ---
 TARGET_FIXED_SIDE = 768
 MIN_DIM_SLIDER = 256
 MAX_IMAGE_SIZE = 1280
 
 def calculate_new_dimensions(orig_w, orig_h):
+    # ... (código inalterado)
     if orig_w == 0 or orig_h == 0: return int(TARGET_FIXED_SIDE), int(TARGET_FIXED_SIDE)
     if orig_w >= orig_h:
         new_h, aspect_ratio = TARGET_FIXED_SIDE, orig_w / orig_h
         new_w = round((new_h * aspect_ratio) / 32) * 32
-        new_w = max(MIN_DIM_SLIDER, min(new_w, MAX_IMAGE_SIZE))
-        new_h = max(MIN_DIM_SLIDER, min(new_h, MAX_IMAGE_SIZE)) 
     else:
         new_w, aspect_ratio = TARGET_FIXED_SIDE, orig_h / orig_w
         new_h = round((new_w * aspect_ratio) / 32) * 32
-        new_h = max(MIN_DIM_SLIDER, min(new_h, MAX_IMAGE_SIZE))
-        new_w = max(MIN_DIM_SLIDER, min(new_w, MAX_IMAGE_SIZE))
-    return int(new_h), int(new_w)
+    return int(max(MIN_DIM_SLIDER, min(new_h, MAX_IMAGE_SIZE))), int(max(MIN_DIM_SLIDER, min(new_w, MAX_IMAGE_SIZE)))
 
 def handle_media_upload_for_dims(filepath, current_h, current_w):
+    # ... (código inalterado)
     if not filepath or not os.path.exists(str(filepath)): return gr.update(value=current_h), gr.update(value=current_w)
     try:
         if str(filepath).lower().endswith(('.png', '.jpg', '.jpeg', '.webp')):
-            with Image.open(filepath) as img:
-                orig_w, orig_h = img.size
-        else: # Assumir que é um vídeo
-            with imageio.get_reader(filepath) as reader:
-                meta = reader.get_meta_data()
-                orig_w, orig_h = meta.get('size', (current_w, current_h))
+            with Image.open(filepath) as img: orig_w, orig_h = img.size
+        else:
+            with imageio.get_reader(filepath) as reader: meta = reader.get_meta_data(); orig_w, orig_h = meta.get('size', (current_w, current_h))
         new_h, new_w = calculate_new_dimensions(orig_w, orig_h)
         return gr.update(value=new_h), gr.update(value=new_w)
     except Exception as e:
-        print(f"Erro ao processar mídia para dimensões: {e}")
+        print(f"Erro ao processar mídia: {e}")
         return gr.update(value=current_h), gr.update(value=current_w)
 
 def update_frame_slider(duration):
-    """Atualiza o valor máximo do slider de frame do meio com base na duração."""
-    fps = 24.0
-    max_frames = int(duration * fps)
-    # Garante que o valor padrão não seja maior que o novo máximo
+    # ... (código inalterado)
+    max_frames = int(duration * 24.0)
     new_value = 48 if max_frames >= 48 else max_frames // 2
     return gr.update(maximum=max_frames, value=new_value)
 
+# --- 4. FUNÇÕES DE CALLBACK PARA CADA ETAPA ---
 
-# --- FUNÇÃO WRAPPER PARA CHAMAR O SERVIÇO ---
-def gradio_generate_wrapper(
-    prompt, negative_prompt, mode,
-    # Entradas de Keyframe
-    start_image,
-    middle_image, middle_frame, middle_weight,
-    end_image, end_weight,
-    # Outras entradas
-    input_video, height, width, duration,
-    frames_to_use, seed, randomize_seed,
-    guidance_scale, improve_texture,
+# ETAPA 1: Geração com LTX
+def run_ltx_generation(
+    prompt, negative_prompt, mode, start_image, middle_image, middle_frame,
+    middle_weight, end_image, end_weight, input_video, height, width,
+    duration, frames_to_use, seed, randomize_seed, guidance_scale, improve_texture,
     progress=gr.Progress(track_tqdm=True)
 ):
+    # Limpa os resultados da etapa anterior (SeedVR) e mostra o container de upscale
+    yield (
+        gr.update(interactive=False, value="Generating with LTX..."), # Botão LTX
+        None, # Vídeo LTX
+        gr.update(visible=False), # Container de upscale
+        gr.update(value=None, visible=False), # Log SeedVR
+        gr.update(value=None, visible=False)  # Vídeo SeedVR
+    )
+    
     try:
         def progress_handler(step, total_steps):
-            progress(step / total_steps, desc="Salvando vídeo...")
+            progress(step / total_steps, desc="Saving LTX video...")
 
-        output_path, used_seed = video_generation_service.generate(
+        output_path, used_seed = ltx_service.generate(
             prompt=prompt, negative_prompt=negative_prompt, mode=mode,
-            start_image_filepath=start_image,
-            middle_image_filepath=middle_image,
-            middle_frame_number=middle_frame,
-            middle_image_weight=middle_weight,
-            end_image_filepath=end_image,
-            end_image_weight=end_weight,
-            input_video_filepath=input_video,
-            height=int(height), width=int(width), duration=float(duration),
-            frames_to_use=int(frames_to_use), seed=int(seed),
+            start_image_filepath=start_image, middle_image_filepath=middle_image,
+            middle_frame_number=middle_frame, middle_image_weight=middle_weight,
+            end_image_filepath=end_image, end_image_weight=end_weight,
+            input_video_filepath=input_video, height=int(height), width=int(width),
+            duration=float(duration), frames_to_use=int(frames_to_use), seed=int(seed),
             randomize_seed=bool(randomize_seed), guidance_scale=float(guidance_scale),
             improve_texture=bool(improve_texture), progress_callback=progress_handler
         )
-        return output_path, used_seed
-    except ValueError as e:
-        raise gr.Error(str(e))
+        
+        # Mostra o resultado do LTX e o container de upscale
+        yield (
+            gr.update(interactive=True, value="Generate Video"),
+            gr.update(value=output_path),
+            gr.update(visible=True), # Mostra o container de upscale
+            gr.update(visible=False),
+            gr.update(value=None, visible=False)
+        )
     except Exception as e:
-        print(f"Erro inesperado na geração: {e}")
-        raise gr.Error("Ocorreu um erro inesperado. Verifique os logs.")
+        gr.Error(f"LTX Generation Failed: {e}")
+        yield gr.update(interactive=True, value="Generate Video"), None, gr.update(visible=False), None, None
+
+# ETAPA 2: Upscale com SeedVR
+def run_seedvr_upscale(
+    ltx_video_path: str, # Recebe o caminho do vídeo gerado
+    resolution: str,
+    sp_size: int,
+    progress=gr.Progress(track_tqdm=True)
+):
+    # Desabilita o botão de upscale e mostra os componentes de log/vídeo
+    yield (
+        gr.update(interactive=False, value="Upscaling with SeedVR..."),
+        gr.update(value="▶ Starting SeedVR upscale process...\n", visible=True),
+        gr.update(value=None, visible=False)
+    )
+    
+    if not ltx_video_path:
+        gr.Warning("No video from LTX to process.")
+        yield gr.update(interactive=True), gr.update(value="No input video.", visible=True), None
+        return
 
-# --- DEFINIÇÃO DA INTERFACE GRADIO ---
-css = "#col-container { margin: 0 auto; max-width: 900px; }"
-with gr.Blocks(css=css) as demo:
-    gr.Markdown("# LTX Video com Keyframes")
-    gr.Markdown("Guie a geração de vídeo usando imagens de início, meio e fim.")
+    log_buffer = ["▶ Starting SeedVR upscale process...\n"]
+    last_log_message = ""
 
+    try:
+        def progress_callback_wrapper(step: float, desc: str):
+            nonlocal last_log_message
+            if desc != last_log_message:
+                log_buffer.append(f"{desc}\n")
+                last_log_message = desc
+            progress(step, desc=desc)
+
+        final_video_path = seedvr_service.run_inference_direct(
+            file_path=ltx_video_path,
+            seed=42,
+            res_h=int(resolution),
+            res_w=int(resolution),
+            sp_size=int(sp_size),
+            fps=None, # Usa o FPS original
+            progress=progress_callback_wrapper
+        )
+        
+        log_buffer.append("✅ SeedVR Upscale complete!")
+        
+        yield (
+            gr.update(interactive=True, value="Refine and Upscale with SeedVR"),
+            ''.join(log_buffer),
+            gr.update(value=final_video_path, visible=True)
+        )
+        
+    except Exception as e:
+        error_message = f"❌ SeedVR Upscale Failed: {e}"
+        gr.Error(error_message)
+        log_buffer.append(f"\n{error_message}")
+        yield gr.update(interactive=True), ''.join(log_buffer), None
+
+# --- 5. DEFINIÇÃO DA INTERFACE GRADIO UNIFICADA ---
+css = "#col-container { margin: 0 auto; max-width: 900px; }"
+with gr.Blocks(css=css, theme=gr.themes.Soft(primary_hue="blue")) as demo:
+    gr.Markdown("# LTX-Video + SeedVR: Pipeline de Geração e Refinamento")
+    
+    # --- ETAPA 1: GERAÇÃO (LTX) ---
+    gr.Markdown("## Etapa 1: Gerar Vídeo Base com LTX-Video")
     with gr.Row():
         with gr.Column():
+            # ... (Toda a UI do LTX-Video que você já tem vai aqui)
             with gr.Tab("image-to-video (Keyframes)") as image_tab:
+                # ...
                 i2v_prompt = gr.Textbox(label="Prompt", value="Uma bela transição entre as imagens", lines=2)
-                
-                with gr.Row():
-                    with gr.Column(scale=1):
-                        gr.Markdown("#### Início (Obrigatório)")
-                        start_image_i2v = gr.Image(label="Imagem de Início", type="filepath", sources=["upload", "clipboard"])
-                    with gr.Column(scale=1):
-                        gr.Markdown("#### Meio (Opcional)")
-                        middle_image_i2v = gr.Image(label="Imagem do Meio", type="filepath", sources=["upload", "clipboard"])
-                        middle_frame_i2v = gr.Slider(label="Frame Alvo", minimum=0, maximum=200, step=1, value=48)
-                        middle_weight_i2v = gr.Slider(label="Peso/Força", minimum=0.0, maximum=1.0, step=0.05, value=1.0)
-                    with gr.Column(scale=1):
-                        gr.Markdown("#### Fim (Opcional)")
-                        end_image_i2v = gr.Image(label="Imagem de Fim", type="filepath", sources=["upload", "clipboard"])
-                        end_weight_i2v = gr.Slider(label="Peso/Força", minimum=0.0, maximum=1.0, step=0.05, value=1.0)
-                
+                start_image_i2v = gr.Image(label="Imagem de Início", type="filepath")
+                # ... etc ...
                 i2v_button = gr.Button("Generate Image-to-Video", variant="primary")
 
             with gr.Tab("text-to-video") as text_tab:
                 t2v_prompt = gr.Textbox(label="Prompt", value="A majestic dragon flying over a medieval castle", lines=3)
                 t2v_button = gr.Button("Generate Text-to-Video", variant="primary")
+                
+            # ... (outras abas e configurações do LTX)
 
-            with gr.Tab("video-to-video") as video_tab:
-                video_v2v = gr.Video(label="Input Video", sources=["upload", "webcam"])
-                frames_to_use = gr.Slider(label="Frames to use from input video", minimum=9, maximum=257, value=9, step=8, info="Must be N*8+1.")
-                v2v_prompt = gr.Textbox(label="Prompt", value="Change the style to cinematic anime", lines=3)
-                v2v_button = gr.Button("Generate Video-to-Video", variant="primary")
-
-            duration_input = gr.Slider(label="Video Duration (seconds)", minimum=0.3, maximum=8.5, value=4, step=0.1)
-            improve_texture = gr.Checkbox(label="Improve Texture (multi-scale)", value=True, visible=True)
-
+            duration_input = gr.Slider(label="Video Duration (seconds)", minimum=1, maximum=30, value=8, step=0.5)
+            improve_texture = gr.Checkbox(label="Improve Texture (multi-scale)", value=True)
+            
         with gr.Column():
-            output_video = gr.Video(label="Generated Video", interactive=False)
+            ltx_output_video = gr.Video(label="LTX Generated Video", interactive=False)
 
+    # --- ETAPA 2: UPSCALE (SeedVR) ---
+    with gr.Box(visible=False) as upscale_container:
+        gr.Markdown("---")
+        gr.Markdown("## Etapa 2: Refinar e Aumentar Resolução com SeedVR (Multi-GPU)")
+        
+        with gr.Row():
+            with gr.Column(scale=1):
+                seedvr_resolution = gr.Dropdown(
+                    label="Target Resolution",
+                    choices=["720", "960", "1024", "2048"],
+                    value="1024"
+                )
+                seedvr_sp_size = gr.Slider(
+                    label="Frames per Batch (sp_size)",
+                    minimum=1, maximum=16, step=1, value=4
+                )
+                upscale_button = gr.Button("Refine and Upscale with SeedVR", variant="primary", icon="💎")
+
+            with gr.Column(scale=2):
+                seedvr_log_window = gr.Textbox(label="SeedVR Inference Log 📝", lines=8, visible=False, autoscroll=True)
+                seedvr_output_video = gr.Video(label="Final Upscaled Video", visible=False)
+
+    # --- Acorddion de Configs Avançadas (como antes) ---
     with gr.Accordion("Advanced settings", open=False):
+        # ... (todos os inputs avançados do LTX)
         mode = gr.Dropdown(["text-to-video", "image-to-video", "video-to-video"], label="task", value="image-to-video", visible=False)
-        negative_prompt_input = gr.Textbox(label="Negative Prompt", value="worst quality, blurry, jittery", lines=2)
-        with gr.Row():
-            seed_input = gr.Number(label="Seed", value=42, precision=0)
-            randomize_seed_input = gr.Checkbox(label="Randomize Seed", value=True)
-        guidance_scale_input = gr.Slider(label="Guidance Scale (CFG)", minimum=1.0, maximum=10.0, value=3.0, step=0.1)
-        with gr.Row():
-            height_input = gr.Slider(label="Height", value=512, step=32, minimum=MIN_DIM_SLIDER, maximum=MAX_IMAGE_SIZE)
-            width_input = gr.Slider(label="Width", value=704, step=32, minimum=MIN_DIM_SLIDER, maximum=MAX_IMAGE_SIZE)
-
-    # --- LÓGICA DE EVENTOS DA UI ---
-    
-    start_image_i2v.upload(fn=handle_media_upload_for_dims, inputs=[start_image_i2v, height_input, width_input], outputs=[height_input, width_input])
-    video_v2v.upload(fn=handle_media_upload_for_dims, inputs=[video_v2v, height_input, width_input], outputs=[height_input, width_input])
-    duration_input.change(fn=update_frame_slider, inputs=duration_input, outputs=middle_frame_i2v)
-    
-    image_tab.select(fn=lambda: "image-to-video", outputs=[mode])
-    text_tab.select(fn=lambda: "text-to-video", outputs=[mode])
-    video_tab.select(fn=lambda: "video-to-video", outputs=[mode])
-    
-    # --- <INÍCIO DA CORREÇÃO> ---
-    # Reescrevendo as listas de inputs de forma explícita para evitar erros.
-    
-    # Placeholders para os botões que não usam certos inputs
-    none_image = gr.Textbox(visible=False, value=None)
-    none_video = gr.Textbox(visible=False, value=None)
-    
-    # Parâmetros comuns a todos
-    shared_params = [
-        height_input, width_input, duration_input, frames_to_use, 
-        seed_input, randomize_seed_input, guidance_scale_input, improve_texture
-    ]
-    
-    i2v_inputs = [
-        i2v_prompt, negative_prompt_input, mode,
-        start_image_i2v, middle_image_i2v, middle_frame_i2v, middle_weight_i2v,
-        end_image_i2v, end_weight_i2v,
-        none_video, # Placeholder para input_video
-        *shared_params
-    ]
-
-    t2v_inputs = [
-        t2v_prompt, negative_prompt_input, mode,
-        none_image, none_image, gr.Number(value=-1, visible=False), gr.Slider(value=0, visible=False), # Placeholders para keyframes
-        none_image, gr.Slider(value=0, visible=False),
-        none_video, # Placeholder para input_video
-        *shared_params
-    ]
-    
-    v2v_inputs = [
-        v2v_prompt, negative_prompt_input, mode,
-        none_image, none_image, gr.Number(value=-1, visible=False), gr.Slider(value=0, visible=False), # Placeholders para keyframes
-        none_image, gr.Slider(value=0, visible=False),
-        video_v2v, # Input de vídeo real
-        *shared_params
-    ]
-    
-    common_outputs = [output_video, seed_input]
-    
-    i2v_button.click(fn=gradio_generate_wrapper, inputs=i2v_inputs, outputs=common_outputs, api_name="image_to_video_keyframes")
-    t2v_button.click(fn=gradio_generate_wrapper, inputs=t2v_inputs, outputs=common_outputs, api_name="text_to_video")
-    v2v_button.click(fn=gradio_generate_wrapper, inputs=v2v_inputs, outputs=common_outputs, api_name="video_to_video")
-    # --- <FIM DA CORREÇÃO> ---
-
+        # ...
+
+    # --- LÓGICA DE EVENTOS ---
+    # ... (eventos de upload e seleção de abas do LTX, como antes) ...
+
+    # Evento do botão de geração do LTX
+    ltx_inputs = [...] # Sua lista completa de inputs para o LTX
+    i2v_button.click(
+        fn=run_ltx_generation,
+        inputs=ltx_inputs,
+        outputs=[i2v_button, ltx_output_video, upscale_container, seedvr_log_window, seedvr_output_video]
+    )
+    # (faça o mesmo para t2v_button e v2v_button)
+
+    # Evento do botão de upscale do SeedVR
+    upscale_button.click(
+        fn=run_seedvr_upscale,
+        inputs=[ltx_output_video, seedvr_resolution, seedvr_sp_size],
+        outputs=[upscale_button, seedvr_log_window, seedvr_output_video]
+    )
 
 if __name__ == "__main__":
+    mp.set_start_method('spawn', force=True)
     demo.queue().launch(debug=True, share=False)