vidu/start-end-to-video-2.0

Open and Advanced Large-Scale Video Generative Models.

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vidu/start-end-to-video-2.0
图生视频

Open and Advanced Large-Scale Video Generative Models.

输入

正在加载参数配置...

输出

空闲
生成的视频将在这里显示
配置参数后点击运行开始生成

每次运行将花费 0.075。$10 可运行约 133 次。

你可以继续:

1. 代码示例

2. Schema

3. LLM 提示词

4. 参数

import requests
import time

# Step 1: Start video generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "vidu/start-end-to-video-2.0",
    "prompt": "A beautiful sunset over the ocean with gentle waves",
    "width": 512,
    "height": 512,
    "duration": 3,
    "fps": 24
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] in ["completed", "succeeded"]:
            print("Generated video:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

video_url = check_status()

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Vidu2.0 Start end to Video creates coherent video by adding motion between the start and end frames, and is an effective tool for scene transitions and storytelling.

Key Features

  • Bi-frame guided synthesis

  • Strong narrative continuity

  • Object-aware and human-aware motion interpolation

  • Adaptive to camera movement and layout shifts

Use Cases

  • Storyboarding and concept animation

  • Scene interpolation in long-form content

  • Instructional visual sequences

  • Film previsualization

Accelerated Inference

Our accelerated inference approach leverages advanced optimization technology from WaveSpeedAI. This innovative fusion technique significantly reduces computational overhead and latency, enabling rapid image generation without compromising quality. The entire system is designed to efficiently handle large-scale inference tasks while ensuring that real-time applications achieve an optimal balance between speed and accuracy. For further details, please refer to the blog post.

详细规格

概览:

模型提供商:VIDU
模型类型:image-to-video
部署方式:推理 API;Playground
定价:$0.075

关键参数:

尺寸上限:最大宽度 × 高度(用户可配置)
LoRA 支持:
种子选项:N/A

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