使用 Seedance 2.0 Fast API 快速创建参考引导视频。结合真实人物支持、内置声音、灵活比例和稳定输出,更快生成符合参考方向的视频素材。 适合快速复用参考节奏、动作和人物表现,提升视频创意验证效率。
ByteDance Seedance V2.0 Fast 参考生视频 API 在 Best Image AI 上提供经济高效的参考引导视频生成,适用于快速 创意工作流。当前 API 集成接受文本提示词和至少一张参考图像或一个参考视频,还可选择添加其他图像、 视频和音频参考。它支持 480p 和 720p 输出、可配置的 时长、多种宽高比,以及可选的生成声音设置。
注意 至少需要一张参考图像或一个参考视频;不能将音频单独用作唯一的参考输入。 请确保您的提示词和参考媒体符合 ByteDance 的内容安全准则。
Seedance V2.0 Fast 与 Seedance V2.0 Standard 参考生视频 两个版本在 Best Image AI 上提供相同的参考媒体 类型和核心控制项。Fast 版本使用 480p 和 720p 输出档位,而标准版本还 提供 1080p 和 4K 选项。
Seedance V2.0 Fast 与 Seedance V2.0 Fast 文生视频 Fast 文生视频根据文本提示词运行。Fast 参考生视频增加了受支持的图像、视频和可选音频输入,以及在提示词中提及媒体的功能。
Seedance V2.0 Fast 与 Wan 2.7 参考生视频 两种 API 都接受图像和视频参考。Wan 2.7 还提供负面提示词和种子控制,而 Seedance V2.0 Fast 支持多个可选的音频 参考和生成声音开关。
Seedance V2.0 Fast 与 Vidu Q3 参考生视频 在当前 Best Image AI 配置中,Vidu Q3 参考生视频使用图像参考。Seedance V2.0 Fast 还接受参考视频和可选的参考音频。
Seedance V2.0 Fast 与 Runway 视频工具 Runway 提供更广泛的交互式创作套件。Seedance V2.0 Fast 参考生视频围绕提示词、受支持的参考素材上传、高效的输出 设置和生成声音,提供专注的 API 工作流。
// Step 1: Submit generation request
const response = await fetch('https://api.flaq.ai/api/v1/video/task', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
body: JSON.stringify({
model_name: 'seedance-v2.0-fast-reference-to-video',
prompt: 'Use image one for the subject, follow the movement from video one, and use audio one for the atmosphere',
resolution: '720p',
duration: 8,
aspect_ratio: '9:16',
sound: true,
images: ['https://example.com/subject-reference.jpg'],
videos: ['https://example.com/motion-reference.mp4'],
audios: ['https://example.com/atmosphere-reference.mp3']
})
});
const { data } = await response.json();
const taskId = data.task_id;
// Use the @ (AT) reference feature in prompt through <<<...>>> placeholders.
// Placeholder numbering is 1-based for each media array:
// <<<image_1>>> = images[0], <<<image_2>>> = images[1]
// <<<video_1>>> = videos[0], <<<audio_1>>> = audios[0]
const mediaReferenceResponse = await fetch('https://api.flaq.ai/api/v1/video/task', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
body: JSON.stringify({
model_name: 'seedance-v2.0-fast-reference-to-video',
prompt: 'Have the dancer from <<<image_1>>> perform the movement from <<<video_1>>> on the stage in <<<image_2>>>, using the rhythm from <<<audio_1>>>',
resolution: '720p',
duration: 10,
aspect_ratio: '9:16',
sound: true,
images: [
'https://example.com/dancer-reference.jpg',
'https://example.com/stage-reference.jpg'
],
videos: ['https://example.com/dance-movement-reference.mp4'],
audios: ['https://example.com/rhythm-reference.mp3']
})
});
const { data: mediaReferenceData } = await mediaReferenceResponse.json();
const mediaReferenceTaskId = mediaReferenceData.task_id;
// Step 2: Poll for results
const taskId = data.task_id;
const pollResult = async (taskId) => {
const res = await fetch(`https://api.flaq.ai/api/v1/video/${taskId}`, {
headers: { 'Authorization': 'Bearer YOUR_API_KEY' }
});
return res.json();
};
while (true) {
const pollResultData = await pollResult(taskId);
const status = pollResultData.data.task_status;
if (status === 'succeed') {
console.log(pollResultData.data.task_result.videos[].);
;
}
(status === ) {
.(pollResultData..);
;
}
( (resolve, ));
}
# Step 1: Submit generation request
import requests
response = requests.post(
'https://api.flaq.ai/api/v1/video/task',
headers={
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
json={
'model_name': ,
: ,
: ,
: ,
: ,
: ,
: [],
: [],
: []
}
)
result = response.json()
task_id = result[][]
media_reference_response = requests.post(
,
headers={
: ,
:
},
json={
: ,
: ,
: ,
: ,
: ,
: ,
: [
,
],
: [],
: []
}
)
media_reference_result = media_reference_response.json()
media_reference_task_id = media_reference_result[][]
# Step 1: Submit generation request
curl -X POST https://api.flaq.ai/api/v1/video/task \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model_name": "seedance-v2.0-fast-reference-to-video",
"prompt": "Use image one for the subject, follow the movement from video one, and use audio one for the atmosphere",
"resolution": "720p",
"duration": 8,
"aspect_ratio": "9:16",
"sound": true,
"images": ["https://example.com/subject-reference.jpg"],
"videos": ["https://example.com/motion-reference.mp4"],
"audios": ["https://example.com/atmosphere-reference.mp3"]
}'
# Use the @ (AT) reference feature in prompt through <<<...>>> placeholders.
# Placeholder numbering is 1-based for each media array:
curl -X POST https://api.flaq.ai/api/v1/video/task \
-H \
-H \
-d
# Step 2: Poll for results
task_id = response.json()['data']['task_id']
poll_url = f"https://api.flaq.ai/api/v1/video/{task_id}"
while True:
poll_result = requests.get(poll_url, headers={'Authorization': 'Bearer YOUR_API_KEY'}).json()
status = poll_result['data']['task_status']
if status == 'succeed':
print(poll_result['data']['task_result']['videos'][0]['url'])
break
if status == 'failed':
print(poll_result['data']['task_status_msg'])
break
time.sleep(10)
# Step 2: Poll for results
# Replace {task_id} with the task_id returned from the submit response
curl -X GET "https://api.flaq.ai/api/v1/video/{task_id}" \
-H "Authorization: Bearer YOUR_API_KEY"