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| # app.py | |
| import os | |
| import oss2 | |
| import sys | |
| import uuid | |
| import shutil | |
| import time | |
| import gradio as gr | |
| import requests | |
| import dashscope | |
| from dashscope.utils.oss_utils import check_and_upload_local | |
| DASHSCOPE_API_KEY = os.getenv("DASHSCOPE_API_KEY") | |
| dashscope.api_key = DASHSCOPE_API_KEY | |
| class WanAnimateApp: | |
| def __init__(self, url, get_url): | |
| self.url = url | |
| self.get_url = get_url | |
| def predict( | |
| self, | |
| ref_img, | |
| video, | |
| model_id, | |
| model, | |
| ): | |
| # Upload files to OSS if needed and get URLs | |
| _, image_url = check_and_upload_local(model_id, ref_img, DASHSCOPE_API_KEY) | |
| _, video_url = check_and_upload_local(model_id, video, DASHSCOPE_API_KEY) | |
| # Prepare the request payload | |
| payload = { | |
| "model": model_id, | |
| "input": { | |
| "image_url": image_url, | |
| "video_url": video_url | |
| }, | |
| "parameters": { | |
| "check_image": True, | |
| "mode": model, | |
| } | |
| } | |
| # Set up headers | |
| headers = { | |
| "X-DashScope-Async": "enable", | |
| "X-DashScope-OssResourceResolve": "enable", | |
| "Authorization": f"Bearer {DASHSCOPE_API_KEY}", | |
| "Content-Type": "application/json" | |
| } | |
| # Make the initial API request | |
| url = self.url | |
| response = requests.post(url, json=payload, headers=headers) | |
| # Check if request was successful | |
| if response.status_code != 200: | |
| raise Exception(f"Initial request failed with status code {response.status_code}: {response.text}") | |
| # Get the task ID from response | |
| result = response.json() | |
| task_id = result.get("output", {}).get("task_id") | |
| if not task_id: | |
| raise Exception("Failed to get task ID from response") | |
| # Poll for results | |
| get_url = f"{self.get_url}/{task_id}" | |
| headers = { | |
| "Authorization": f"Bearer {DASHSCOPE_API_KEY}", | |
| "Content-Type": "application/json" | |
| } | |
| while True: | |
| response = requests.get(get_url, headers=headers) | |
| if response.status_code != 200: | |
| raise Exception(f"Failed to get task status: {response.status_code}: {response.text}") | |
| result = response.json() | |
| print(result) | |
| task_status = result.get("output", {}).get("task_status") | |
| if task_status == "SUCCEEDED": | |
| # Task completed successfully, return video URL | |
| video_url = result["output"]["results"]["video_url"] | |
| return video_url, "SUCCEEDED" | |
| elif task_status == "FAILED": | |
| # Task failed, raise an exception with error message | |
| error_msg = result.get("output", {}).get("message", "Unknown error") | |
| code_msg = result.get("output", {}).get("code", "Unknown code") | |
| print(f"\n\nTask failed: {error_msg} Code: {code_msg} TaskId: {task_id}\n\n") | |
| return None, f"Task failed: {error_msg} Code: {code_msg} TaskId: {task_id}" | |
| # raise Exception(f"Task failed: {error_msg} TaskId: {task_id}") | |
| else: | |
| # Task is still running, wait and retry | |
| time.sleep(5) # Wait 5 seconds before polling again | |
| def start_app(): | |
| import argparse | |
| parser = argparse.ArgumentParser(description="Wan2.2-Animate 视频生成工具") | |
| args = parser.parse_args() | |
| url = "https://dashscope.aliyuncs.com/api/v1/services/aigc/image2video/video-synthesis/" | |
| # url = "https://poc-dashscope.aliyuncs.com/api/v1/services/aigc/image2video/video-synthesis" | |
| get_url = f"https://dashscope.aliyuncs.com/api/v1/tasks/" | |
| # get_url = f"https://poc-dashscope.aliyuncs.com/api/v1/tasks" | |
| app = WanAnimateApp(url=url, get_url=get_url) | |
| with gr.Blocks(title="Wan2.2-Animate 视频生成") as demo: | |
| gr.HTML(""" | |
| <div style="padding: 2rem; text-align: center; max-width: 1200px; margin: 0 auto; font-family: Arial, sans-serif;"> | |
| <h1 style="font-size: 2.5rem; font-weight: bold; margin-bottom: 0.5rem; color: #333;"> | |
| Wan2.2-Animate: Unified Character Animation and Replacement with Holistic Replication | |
| </h1> | |
| <h3 style="font-size: 2.5rem; font-weight: bold; margin-bottom: 0.5rem; color: #333;"> | |
| Wan2.2-Animate: 统一的角色动画和视频人物替换模型 | |
| </h3> | |
| <div style="font-size: 1.25rem; margin-bottom: 1.5rem; color: #555;"> | |
| Tongyi Lab, Alibaba | |
| </div> | |
| <div style="display: flex; flex-wrap: wrap; justify-content: center; gap: 1rem; margin-bottom: 1rem;"> | |
| <!-- 第一行按钮 --> | |
| <a href="https://arxiv.org/abs/2509.14055" target="_blank" | |
| style="display: inline-flex; align-items: center; padding: 0.5rem 1rem; background-color: #f0f0f0; /* 浅灰色背景 */ color: #333; /* 深色文字 */ text-decoration: none; border-radius: 9999px; font-weight: 500; transition: background-color 0.3s;"> | |
| <span style="margin-right: 0.5rem;">📄</span> <!-- 使用文档图标 --> | |
| <span>Paper</span> | |
| </a> | |
| <a href="https://github.com/Wan-Video/Wan2.2" target="_blank" | |
| style="display: inline-flex; align-items: center; padding: 0.5rem 1rem; background-color: #f0f0f0; color: #333; text-decoration: none; border-radius: 9999px; font-weight: 500; transition: background-color 0.3s;"> | |
| <span style="margin-right: 0.5rem;">💻</span> <!-- 使用电脑图标 --> | |
| <span>GitHub</span> | |
| </a> | |
| <a href="https://huggingface.co/Wan-AI/Wan2.2-Animate-14B" target="_blank" | |
| style="display: inline-flex; align-items: center; padding: 0.5rem 1rem; background-color: #f0f0f0; color: #333; text-decoration: none; border-radius: 9999px; font-weight: 500; transition: background-color 0.3s;"> | |
| <span style="margin-right: 0.5rem;">🤗</span> | |
| <span>HF Model</span> | |
| </a> | |
| <a href="https://www.modelscope.cn/models/Wan-AI/Wan2.2-Animate-14B" target="_blank" | |
| style="display: inline-flex; align-items: center; padding: 0.5rem 1rem; background-color: #f0f0f0; color: #333; text-decoration: none; border-radius: 9999px; font-weight: 500; transition: background-color 0.3s;"> | |
| <span style="margin-right: 0.5rem;">🤖</span> | |
| <span>MS Model</span> | |
| </a> | |
| </div> | |
| <div style="display: flex; flex-wrap: wrap; justify-content: center; gap: 1rem;"> | |
| <!-- 第二行按钮 --> | |
| <a href="https://huggingface.co/spaces/Wan-AI/Wan2.2-Animate" target="_blank" | |
| style="display: inline-flex; align-items: center; padding: 0.5rem 1rem; background-color: #f0f0f0; color: #333; text-decoration: none; border-radius: 9999px; font-weight: 500; transition: background-color 0.3s;"> | |
| <span style="margin-right: 0.5rem;">🤗</span> | |
| <span>HF Space</span> | |
| </a> | |
| <a href="https://www.modelscope.cn/studios/Wan-AI/Wan2.2-Animate" target="_blank" | |
| style="display: inline-flex; align-items: center; padding: 0.5rem 1rem; background-color: #f0f0f0; color: #333; text-decoration: none; border-radius: 9999px; font-weight: 500; transition: background-color 0.3s;"> | |
| <span style="margin-right: 0.5rem;">🤖</span> | |
| <span>MS Studio</span> | |
| </a> | |
| </div> | |
| </div> | |
| """) | |
| gr.HTML(""" | |
| <details> | |
| <summary>‼️Usage (使用说明)</summary> | |
| Wan-Animate supports two mode: | |
| <ul> | |
| <li>Move Mode: animate the character in input image with movements from the input video</li> | |
| <li>Mix Mode: replace the character in input video with the character in input image</li> | |
| </ul> | |
| Wan-Animate 支持两种模式: | |
| <ul> | |
| <li>Move模式: 用输入视频中提取的动作,驱动输入图片中的角色</li> | |
| <li>Mix模式: 用输入图片中的角色,替换输入视频中的角色</li> | |
| </ul> | |
| Currently, the following restrictions apply to inputs: | |
| <ul> <li>Video file size: Less than 200MB</li> | |
| <li>Video resolution: The shorter side must be greater than 200, and the longer side must be less than 2048</li> | |
| <li>Video duration: 2s to 30s</li> | |
| <li>Video aspect ratio: 1:3 to 3:1</li> | |
| <li>Video formats: mp4, avi, mov</li> | |
| <li>Image file size: Less than 5MB</li> | |
| <li>Image resolution: The shorter side must be greater than 200, and the longer side must be less than 4096</li> | |
| <li>Image formats: jpg, png, jpeg, webp, bmp</li> </ul> | |
| 当前,对于输入有以下的限制 | |
| <ul> | |
| <li>视频文件大小: 小于 200MB</li> | |
| <li>视频分辨率: 最小边大于 200, 最大边小于2048</li> | |
| <li>视频时长: 2s ~ 30s </li> | |
| <li>视频比例:1:3 ~ 3:1 </li> | |
| <li>视频格式: mp4, avi, mov </li> | |
| <li>图片文件大小: 小于5MB </li> | |
| <li>图片分辨率:最小边大于200,最大边小于4096 </li> | |
| <li>图片格式: jpg, png, jpeg, webp, bmp </li> | |
| </ul> | |
| <p> Currently, the inference quality has two variants. You can use our open-source code for more flexible configuration. </p> | |
| <p>当前,推理质量有两个变种。 您可以使用我们的开源代码,来进行更灵活的设置。</p> | |
| <ul> | |
| <li> wan-pro: 25fps, 720p </li> | |
| <li> wan-std: 15fps, 720p </li> | |
| </ul> | |
| </details> | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| ref_img = gr.Image( | |
| label="Reference Image(参考图像)", | |
| type="filepath", | |
| sources=["upload"], | |
| ) | |
| video = gr.Video( | |
| label="Template Video(模版视频)", | |
| sources=["upload"], | |
| ) | |
| with gr.Row(): | |
| model_id = gr.Dropdown( | |
| label="Mode(模式)", | |
| choices=["wan2.2-animate-move", "wan2.2-animate-mix"], | |
| value="wan2.2-animate-move", | |
| info="" | |
| ) | |
| model = gr.Dropdown( | |
| label="推理质量(Inference Quality)", | |
| choices=["wan-pro", "wan-std"], | |
| value="wan-pro", | |
| ) | |
| run_button = gr.Button("Generate Video(生成视频)") | |
| with gr.Column(): | |
| output_video = gr.Video(label="Output Video(输出视频)") | |
| output_status = gr.Textbox(label="Status(状态)") | |
| run_button.click( | |
| fn=app.predict, | |
| inputs=[ | |
| ref_img, | |
| video, | |
| model_id, | |
| model, | |
| ], | |
| outputs=[output_video, output_status], | |
| ) | |
| example_data = [ | |
| ['./examples/mov/1/1.jpeg', './examples/mov/1/1.mp4', 'wan2.2-animate-move', 'wan-pro'], | |
| ['./examples/mov/2/2.jpeg', './examples/mov/2/2.mp4', 'wan2.2-animate-move', 'wan-pro'], | |
| ['./examples/mix/1/1.jpeg', './examples/mix/1/1.mp4', 'wan2.2-animate-mix', 'wan-pro'], | |
| ['./examples/mix/2/2.jpeg', './examples/mix/2/2.mp4', 'wan2.2-animate-mix', 'wan-pro'] | |
| ] | |
| if example_data: | |
| gr.Examples( | |
| examples=example_data, | |
| inputs=[ref_img, video, model_id, model], | |
| outputs=[output_video, output_status], | |
| fn=app.predict, | |
| cache_examples="lazy", | |
| ) | |
| demo.queue(default_concurrency_limit=100) | |
| demo.launch( | |
| server_name="0.0.0.0", | |
| server_port=7860 | |
| ) | |
| if __name__ == "__main__": | |
| start_app() |