Update Dockerfile

Dockerfile

@@ -1,144 +1,31 @@
-# app.py (Interface final com 3 abas: SeedVR, V-INT Edit, V-INT Pipeline)
+# Dockerfile (VERSÃO FINAL COM OS DOIS PROJETOS)
 
-import gradio as gr
-import os
-import subprocess
-import shutil
-import uuid
-from huggingface_hub import snapshot_download
-import spaces
+FROM nvidia/cuda:12.1.1-devel-ubuntu22.04
 
-# --- 1. CONFIGURAÇÃO E DOWNLOAD DOS MODELOS ---
+ENV DEBIAN_FRONTEND=noninteractive
+RUN apt-get update && apt-get install -y --no-install-recommends wget git && apt-get clean && rm -rf /var/lib/apt/lists/*
 
-SEEDVR_DIR = "/app/SeedVR"
-VINCIE_DIR = "/app/VINCIE"
-HF_TOKEN = os.environ.get("HF_TOKEN")
+RUN wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda.sh && \
+    /bin/bash ~/miniconda.sh -b -p /opt/conda && \
+    rm ~/miniconda.sh
 
-@spaces.GPU
-def download_models():
-    """Baixa os modelos para SeedVR e V-INT se eles não existirem."""
-    # Download do SeedVR
-    if not os.path.exists(os.path.join(SEEDVR_DIR, "ckpts", "seedvr2_ema_3b.pth")):
-        print("Baixando modelo do SeedVR-3B...")
-        snapshot_download(repo_id="ByteDance-Seed/SeedVR2-3B", local_dir=os.path.join(SEEDVR_DIR, "ckpts"), token=HF_TOKEN, local_dir_use_symlinks=False)
-    else: print("Modelo do SeedVR já existe.")
+ENV PATH /opt/conda/bin:$PATH
 
-    # Download do V-INT
-    if not os.path.exists(os.path.join(VINCIE_DIR, "ckpt", "VINCIE-3B")):
-        print("Baixando modelo do VINCIE-3B...")
-        snapshot_download(repo_id="ByteDance-Seed/VINCIE-3B", local_dir=os.path.join(VINCIE_DIR, "ckpt", "VINCIE-3B"), token=HF_TOKEN, local_dir_use_symlinks=False)
-    else: print("Modelo do VINCIE já existe.")
+COPY . /app
+WORKDIR /app
 
-    # Download de assets e configs do V-INT (para os exemplos)
-    if not os.path.exists(os.path.join(VINCIE_DIR, "assets", "woman_pineapple.png")):
-         print("Baixando assets e configs do V-INT...")
-         snapshot_download(repo_id="ByteDance-Seed/VINCIE", repo_type="space", local_dir=VINCIE_DIR, token=HF_TOKEN, allow_patterns=["assets/*", "configs/*"], local_dir_use_symlinks=False)
-    else: print("Assets e configs do V-INT já existem.")
+RUN yes | conda tos accept
+RUN conda update -n base -c defaults conda
+RUN conda env create -f environment.yml && conda clean --all -y
 
-download_models()
+# Instala flash_attn para ambos os projetos
+# V-INT usa uma versão mais nova, então instalamos essa.
+RUN conda run -n seedvr env FLASH_ATTENTION_SKIP_CUDA_BUILD=TRUE \
+    pip install "flash_attn==2.6.3" --no-build-isolation --no-cache-dir
 
-# --- 2. LÓGICA DE INFERÊNCIA ---
+# Clona os repositórios dos projetos
+RUN git clone https://github.com/ByteDance-Seed/SeedVR.git
+RUN git clone https://github.com/ByteDance-Seed/VINCIE.git
 
-def run_subprocess_with_logs(command, cwd):
-    """Função genérica para rodar um subprocesso e streamar os logs para o Gradio."""
-    log_output = f"Executando comando:\n{' '.join(command)}\n\n"
-    yield [], log_output
-    
-    env = os.environ.copy(); env["PYTHONUNBUFFERED"] = "1"
-    process = subprocess.Popen(command, cwd=cwd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True, encoding='utf-8', env=env)
-    
-    while True:
-        output = process.stdout.readline()
-        if output == '' and process.poll() is not None: break
-        if output: log_output += output; yield [], log_output
-            
-    if process.poll() != 0: raise gr.Error("A inferência falhou. Verifique os logs.")
-
-def run_seedvr_inference(video_path, seed):
-    # (Lógica específica do SeedVR)
-    if video_path is None: raise gr.Error("Por favor, faça o upload de um arquivo para o SeedVR.")
-    job_id = str(uuid.uuid4())
-    input_dir = os.path.join("/app", "temp_inputs", job_id); os.makedirs(input_dir, exist_ok=True)
-    output_dir = os.path.join("/app", "temp_outputs", job_id); os.makedirs(output_dir, exist_ok=True)
-    shutil.copy(video_path, input_dir)
-    
-    input_folder_relative = os.path.relpath(input_dir, SEEDVR_DIR)
-    output_folder_relative = os.path.relpath(output_dir, SEEDVR_DIR)
-    command = ["torchrun", "--nproc-per-node=4", "projects/inference_seedvr2_3b.py", "--video_path", input_folder_relative, "--output_dir", output_folder_relative, "--seed", str(seed), "--res_h", "720", "--res_w", "1280"]
-    
-    for gallery, logs in run_subprocess_with_logs(command, SEEDVR_DIR):
-        yield None, logs # Retorna None para o output enquanto os logs são atualizados
-    
-    output_files = [os.path.join(output_dir, f) for f in os.listdir(output_dir) if f.endswith(('.mp4', '.png'))]
-    if not output_files: raise gr.Error("Nenhum arquivo de saída encontrado.")
-    yield output_files[0], logs
-
-def run_vincie_edit_inference(files, prompts_str):
-    # (Lógica específica para o modo de EDIÇÃO do V-INT)
-    if not files: raise gr.Error("Por favor, faça o upload de uma imagem para editar.")
-    if not prompts_str: raise gr.Error("Por favor, forneça os prompts de edição.")
-
-    job_id = str(uuid.uuid4())
-    output_dir = os.path.join(VINCIE_DIR, "output", job_id)
-    
-    image_paths_str = ", ".join([f'"{f.name}"' for f in files])
-    prompts_list_str = ", ".join([f'"{p.strip()}"' for p in prompts_str.split(';')])
-    command = ["python", "main.py", "configs/generate.yaml", f'generation.positive_prompt.image_path=[{image_paths_str}]', f'generation.positive_prompt.prompts=[{prompts_list_str}]', f'generation.output.dir={output_dir}']
-    
-    for gallery, logs in run_subprocess_with_logs(command, VINCIE_DIR):
-        yield gallery, logs
-    
-    output_files = [os.path.join(output_dir, f) for f in os.listdir(output_dir) if f.endswith(('.png', '.jpg'))]
-    if not output_files: raise gr.Error("Nenhum arquivo de saída encontrado.")
-    yield output_files, logs
-
-def run_vincie_pipeline_inference(files, final_prompt):
-    # (NOVA LÓGICA para o modo de PIPELINE do V-INT)
-    if not files: raise gr.Error("Por favor, faça o upload de múltiplas imagens para a composição.")
-    if not final_prompt: raise gr.Error("Por favor, forneça o prompt de composição final.")
-
-    job_id = str(uuid.uuid4())
-    output_dir = os.path.join(VINCIE_DIR, "output", job_id)
-
-    # Gera os prompts de placeholder
-    placeholder_prompts = [f"<IMG{i}>: " for i in range(len(files))]
-    all_prompts = placeholder_prompts + [final_prompt]
-
-    image_paths_str = ", ".join([f'"{f.name}"' for f in files])
-    prompts_list_str = ", ".join([f'"{p}"' for p in all_prompts])
-    command = ["python", "main.py", "configs/generate.yaml", "generation.pad_img_placehoder=False", f'generation.positive_prompt.image_path=[{image_paths_str}]', f'generation.positive_prompt.prompts=[{prompts_list_str}]', f'generation.output.dir={output_dir}']
-
-    for gallery, logs in run_subprocess_with_logs(command, VINCIE_DIR):
-        yield gallery, logs
-
-    output_files = [os.path.join(output_dir, f) for f in os.listdir(output_dir) if f.endswith(('.png', '.jpg'))]
-    if not output_files: raise gr.Error("Nenhum arquivo de saída foi encontrado.")
-    yield output_files, logs
-
-# --- 3. INTERFACE GRADIO COM 3 ABAS ---
-
-with gr.Blocks() as demo:
-    gr.Markdown("<h1><center>Super-Space: SeedVR & V-INT</center></h1>")
-    
-    with gr.Tabs():
-        # --- ABA SEEDVR ---
-        with gr.TabItem("SeedVR (Restauração de Vídeo)"):
-            with gr.Row():
-                with gr.Column(scale=1):
-                    seedvr_input_video = gr.Video(label="Upload de Vídeo")
-                    seedvr_seed = gr.Number(value=666, label="Seed")
-                    seedvr_run_button = gr.Button("Executar SeedVR", variant="primary")
-                with gr.Column(scale=2):
-                    seedvr_output = gr.Video(label="Vídeo Restaurado")
-                    seedvr_logs = gr.Textbox(label="Logs", lines=10, interactive=False)
-            seedvr_run_button.click(fn=run_seedvr_inference, inputs=[seedvr_input_video, seedvr_seed], outputs=[seedvr_output, seedvr_logs])
-
-        # --- ABA V-INT EDIÇÃO ---
-        with gr.TabItem("V-INT (Edição de Imagem)"):
-            with gr.Row():
-                with gr.Column(scale=1):
-                    vincie_edit_input = gr.Files(label="Upload de Imagem(ns) para Editar", file_types=["image"])
-                    vincie_edit_prompts = gr.Textbox(label="Prompts de Edição (separados por ';')", lines=5, placeholder="Ex: Add a crown to her head; Change the background...")
-                    vincie_edit_button = gr.Button("Executar Edição", variant="primary")
-                with gr.Column(scale=2):
-                    vincie_edit_output 
+WORKDIR /app
+CMD ["conda", "run", "-n", "seedvr", "env", "PYTHONUNBUFFERED=1", "python", "app.py", "--share"]