app.py

import spaces
import gradio as gr
import os

is_shared_ui = True if "fffiloni/Stand-In" in os.environ['SPACE_ID'] else False

import torch
import time
from PIL import Image
import tempfile
import os

from data.video import save_video
from wan_loader import load_wan_pipe
from models.set_condition_branch import set_stand_in
from preprocessor import FaceProcessor

from huggingface_hub import snapshot_download

print("Downloading models, please wait...")

snapshot_download("Wan-AI/Wan2.1-T2V-14B", local_dir="checkpoints/base_model/")

snapshot_download(
    "DIAMONIK7777/antelopev2", 
    local_dir="checkpoints/antelopev2/models/antelopev2"
)
snapshot_download("BowenXue/Stand-In", local_dir="checkpoints/Stand-In/")

try:
    ANTELOPEV2_PATH = "checkpoints/antelopev2"
    BASE_MODEL_PATH = "checkpoints/base_model/"
    LORA_MODEL_PATH = "checkpoints/Stand-In/Stand-In_wan2.1_T2V_14B_ver1.0.ckpt"

    if not os.path.exists(ANTELOPEV2_PATH):
        raise FileNotFoundError(
            f"AntelopeV2 checkpoint not found at: {ANTELOPEV2_PATH}"
        )
    if not os.path.exists(BASE_MODEL_PATH):
        raise FileNotFoundError(f"Base model not found at: {BASE_MODEL_PATH}")
    if not os.path.exists(LORA_MODEL_PATH):
        raise FileNotFoundError(f"LoRA model not found at: {LORA_MODEL_PATH}")

    print(f"Is CUDA available: {torch.cuda.is_available()}")
    if torch.cuda.is_available() and not is_shared_ui:
        face_processor = FaceProcessor(antelopv2_path=ANTELOPEV2_PATH)
        pipe = load_wan_pipe(base_path=BASE_MODEL_PATH, torch_dtype=torch.bfloat16)
        set_stand_in(pipe, model_path=LORA_MODEL_PATH)
        print("Model loaded successfully!")
    else:
        print("Will load models on ZeroGPU on inference if available")

 
except Exception as e:
    print(f"Model loading failed: {e}")
    with gr.Blocks() as demo:
        gr.Markdown("# Error: Model Loading Failed")
        gr.Markdown(f"""
        Please check the following:
        1.  Make sure the checkpoint files are placed in the correct directory.
        2.  Ensure all dependencies are properly installed.
        3.  Check the console output for detailed error information.
        
        **Error details**: {e}
        """)
    demo.launch()
    exit()

@spaces.GPU(duration=300)
def generate_video(
    pil_image: Image.Image,
    prompt: str,
    seed: int,
    negative_prompt: str,
    num_steps: int,
    fps: int,
    quality: int,
    progress=gr.Progress(track_tqdm=True)
):
    if pil_image is None:
        raise gr.Error("Please upload a face image first!")

    if is_shared_ui:
        print("Loading models...")
        face_processor = FaceProcessor(antelopv2_path=ANTELOPEV2_PATH)
        pipe = load_wan_pipe(base_path=BASE_MODEL_PATH, torch_dtype=torch.bfloat16)
        set_stand_in(pipe, model_path=LORA_MODEL_PATH)
        print("Model loaded successfully!")

    print("Processing face...")
    ip_image = face_processor.process(pil_image)
    print("Face processing completed.")

    if is_shared_ui: 
        num_steps = 10
        quality = 6
        #fps = 12
        
    
    print("Generating video...")
    start_time = time.time()
    video = pipe(
        prompt=prompt,
        negative_prompt=negative_prompt,
        seed=int(seed),
        ip_image=ip_image,
        num_inference_steps=int(num_steps),
        tiled=False,
    )
    end_time = time.time()
    print(f"Video generated in {end_time - start_time:.2f} seconds.")

    with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as temp_file:
        video_path = temp_file.name
        save_video(video, video_path, fps=int(fps), quality=quality)
        print(f"Video saved to: {video_path}")
        return video_path


with gr.Blocks() as demo:
    gr.Markdown(
        """
        # Stand-In IP2V
        """
    )
    gr.Markdown("A Lightweight and Plug-and-Play Identity Control for Video Generation")
    gr.Markdown("On fffiloni's shared UI, advanced settings are disabled to optimize best results on ZeroGPU.")
    gr.HTML("""
    <div style="display:flex;column-gap:4px;">
        <a href="https://github.com/WeChatCV/Stand-In">
            <img src='https://img.shields.io/badge/GitHub-Repo-blue'>
        </a> 
        <a href="https://stand-in-video.github.io/">
            <img src='https://img.shields.io/badge/Project-Page-green'>
        </a>
        <a href="https://arxiv.org/abs/2508.07901">
            <img src='https://img.shields.io/badge/ArXiv-Paper-red'>
        </a>
        <a href="https://huggingface.co/spaces/fffiloni/Stand-In?duplicate=true">
            <img src="https://huggingface.co/datasets/huggingface/badges/resolve/main/duplicate-this-space-sm.svg" alt="Duplicate this Space">
        </a>
    </div>
    """)

    with gr.Row():
        with gr.Column(scale=1):
            gr.Markdown("### 1. Upload a Face Image")
            input_image = gr.Image(
                label="Upload Image",
                type="pil",
                image_mode="RGB",
                height=300,
            )

            gr.Markdown("### 2. Enter Core Parameters")
            input_prompt = gr.Textbox(
                label="Prompt",
                lines=4,
                value="A man sits comfortably at his desk, facing the camera, as if conversing with a friend or family member in front of a screen. His eyes are focused yet gentle, and a natural smile plays on his lips. The background is his meticulously decorated personal space, with photos and a world map on the wall, conveying a sense of intimacy and modern communication.",
                placeholder="Please enter a detailed description of the scene, character actions, expressions, etc...",
            )

            input_seed = gr.Slider(
                label="Seed",
                minimum=0,
                maximum=100000,
                step=1,
                value=0,
                info="The same seed and parameters will generate the same result.",
            )

            with gr.Accordion("Advanced Options", open=False):
                input_negative_prompt = gr.Textbox(
                    label="Negative Prompt",
                    lines=3,
                    interactive = False if is_shared_ui else True,
                    value="Vibrant colors, overexposure, static, blurred details, subtitles, style, artwork, painting, still image, overall grayness, worst quality, low quality, JPEG compression residue, ugly, mutilated, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still image, cluttered background, three legs, crowded background, walking backwards",
                )
                input_steps = gr.Slider(
                    label="Inference Steps",
                    minimum=10,
                    maximum=50,
                    step=1,
                    value=10,
                    interactive = False if is_shared_ui else True,
                    info="More steps may improve details but will take longer to generate.",
                )
                output_fps = gr.Slider(
                    label="Video FPS", minimum=10, maximum=30, step=1, value=25,
                    interactive = False if is_shared_ui else True,
                )
                output_quality = gr.Slider(
                    label="Video Quality", minimum=1, maximum=10, step=1, value=6,
                    interactive = False if is_shared_ui else True
                )

            generate_btn = gr.Button("Generate Video", variant="primary")


        with gr.Column(scale=2):
            gr.Markdown("### 3. View Generated Result")
            output_video = gr.Video(
                label="Generated Video",
                #height=480,
            )

            examples = gr.Examples(
                examples = [
                    [
                        "./examples/standin_example1.jpg", 
                        "In a corridor where the walls ripple like water, a woman reaches out to touch the flowing surface, causing circles of ripples to spread. The camera moves from a medium shot to a close-up, capturing her curious expression as she sees her distorted reflection.",
                        42, 
                        "Vibrant colors, overexposure, static, blurred details, subtitles, style, artwork, painting, still image, overall grayness, worst quality, low quality, JPEG compression residue, ugly, mutilated, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still image, cluttered background, three legs, crowded background, walking backwards",
                        20,
                        25, 9
                    ],
                    [
                        "./examples/standin_example4.jpg",
                        "A man in a white lab coat stands in front of a laboratory bench. Having just completed a critical step, he turns toward the camera, his eyes shining with the excitement of discovery. The background is filled with precise instruments and an array of beakers and test tubes, capturing the rigor and allure of scientific exploration.",
                        420, 
                        "Vibrant colors, overexposure, static, blurred details, subtitles, style, artwork, painting, still image, overall grayness, worst quality, low quality, JPEG compression residue, ugly, mutilated, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still image, cluttered background, three legs, crowded background, walking backwards",
                        20,
                        25, 9
                    ],
                    [
                        "./examples/standin_example8.png", 
                        "The video features a man standing at an easel, focused intently as his brush dances across the canvas. His expression is one of deep concentration, with a hint of satisfaction as each brushstroke adds color and form. He wears a paint-splattered apron, and his hands move with confident precision. The setting, filled with scattered art supplies, open paint tubes, and unfinished sketches pinned to the wall, suggests an artist's studio. A large window on one side allows sunlight to stream in, casting a soft glow across the room and illuminating the colors on his canvas. The atmosphere is creative and inspired, with the man's intense focus and the lively colors on the canvas indicating a moment of artistic passion and expression.",
                        4200, 
                        "Vibrant colors, overexposure, static, blurred details, subtitles, style, artwork, painting, still image, overall grayness, worst quality, low quality, JPEG compression residue, ugly, mutilated, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still image, cluttered background, three legs, crowded background, walking backwards",
                        20,
                        25, 9
                    ]
                ],
                fn=generate_video,
                inputs=[
                    input_image,
                    input_prompt,
                    input_seed,
                    input_negative_prompt,
                    input_steps,
                    output_fps,
                    output_quality,
                ],
                outputs=output_video,
                cache_examples=False,
               # cache_mode="lazy"
            )
    
    generate_btn.click(
        fn=generate_video,
        inputs=[
            input_image,
            input_prompt,
            input_seed,
            input_negative_prompt,
            input_steps,
            output_fps,
            output_quality,
        ],
        outputs=output_video,
        #api_name="generate_video",
    )

if __name__ == "__main__":
    demo.queue().launch(ssr_mode=False, show_error=True, show_api=False)