
AI 文字轉圖片生成器
使用領先 AI 圖片模型、彈性設定與快速瀏覽器工作流程,從提示詞建立精緻圖片。
透過 Alibaba Happy Horse 1.1 API 建立參考引導影片,具備可控動作、穩定效能和可擴展創意製作工作流程。開放權重快樂馬AI 適合角色動作、品牌素材、參考驅動短片、視覺探索和靈活參考轉影片生成,便於圍繞參考圖像持續迭代創意並保持主體風格一致。
// 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: 'happyhorse-1.1-reference-to-video',
prompt: 'Subject moves naturally while preserving reference style and appearance',
duration: 5,
resolution: '1080p',
aspect_ratio: '16:9',
images: [
'https://example.com/ref-1.jpg',
'https://example.com/ref-2.jpg'
],
seed: 42
})
});
const { data } = await response.json();
const taskId = data.task_id;
// Use the @ (AT) reference feature in prompt through <<<...>>> placeholders.
// Placeholder numbering is 1-based and follows the images array order:
// <<<image_1>>> = images[0], <<<image_2>>> = images[1], <<<image_3>>> = images[2]
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: 'happyhorse-1.1-reference-to-video',
prompt: 'Show the person from <<<image_1>>> walking beside the bicycle from <<<image_2>>> through the street in <<<image_3>>>, preserving all reference details',
duration: 5,
resolution: '1080p',
aspect_ratio: '16:9',
images: [
'https://example.com/person-reference.jpg',
'https://example.com/bicycle-reference.jpg',
'https://example.com/street-reference.jpg'
],
seed: 42
})
});
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[0].url);
break;
}
if (status === 'failed') {
console.error(pollResultData.data.task_status_msg);
break;
}
await new Promise(resolve => setTimeout(resolve, 10000));
}
# 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': 'happyhorse-1.1-reference-to-video',
'prompt': 'Subject moves naturally while preserving reference style and appearance',
'duration': 5,
'resolution': '1080p',
'aspect_ratio': '16:9',
'images': [
'https://example.com/ref-1.jpg',
'https://example.com/ref-2.jpg'
],
'seed': 42
}
)
result = response.json()
task_id = result['data']['task_id']
# Use the @ (AT) reference feature in prompt through <<<...>>> placeholders.
# Placeholder numbering is 1-based and follows the images array order:
# <<<image_1>>> = images[0], <<<image_2>>> = images[1], <<<image_3>>> = images[2]
media_reference_response = requests.post(
'https://api.flaq.ai/api/v1/video/task',
headers={
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
json={
'model_name': 'happyhorse-1.1-reference-to-video',
'prompt': 'Show the person from <<<image_1>>> walking beside the bicycle from <<<image_2>>> through the street in <<<image_3>>>, preserving all reference details',
'duration': 5,
'resolution': '1080p',
'aspect_ratio': '16:9',
'images': [
'https://example.com/person-reference.jpg',
'https://example.com/bicycle-reference.jpg',
'https://example.com/street-reference.jpg'
],
'seed': 42
}
)
media_reference_result = media_reference_response.json()
media_reference_task_id = media_reference_result['data']['task_id']
# 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 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": "happyhorse-1.1-reference-to-video",
"prompt": "Subject moves naturally while preserving reference style and appearance",
"duration": 5,
"resolution": "1080p",
"aspect_ratio": "16:9",
"images": ["https://example.com/ref-1.jpg", "https://example.com/ref-2.jpg"],
"seed": 42
}'
# Use the @ (AT) reference feature in prompt through <<<...>>> placeholders.
# Placeholder numbering is 1-based and follows the images array order:
# <<<image_1>>> = images[0], <<<image_2>>> = images[1], <<<image_3>>> = images[2]
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": "happyhorse-1.1-reference-to-video",
"prompt": "Show the person from <<<image_1>>> walking beside the bicycle from <<<image_2>>> through the street in <<<image_3>>>, preserving all reference details",
"duration": 5,
"resolution": "1080p",
"aspect_ratio": "16:9",
"images": [
"https://example.com/person-reference.jpg",
"https://example.com/bicycle-reference.jpg",
"https://example.com/street-reference.jpg"
],
"seed": 42
}'
# 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"
| 參數 | 價格 | 原價 | 折扣 |
|---|
Happy Horse 1.1 參考圖生影片 API 為需要在生成片段中保持角色、產品、場景和品牌資產一致性的團隊提供升級版阿里巴巴影片生成能力。這個專業級參考圖生影片 API 整合以參考圖片作為視覺錨點,再生成精緻的影片輸出,相比 Happy Horse 1.0,具備更強的主體一致性、更好的提示詞遵循能力和更豐富的視覺質感。Happy Horse 1.1 參考圖生影片面向 Flaq AI 上可擴展的創意生產而建構,非常適合廣告、短劇、電商、角色工作流和多資產內容管線。
注意 請確保你的提示詞和參考圖片符合阿里巴巴的安全準則。如果發生錯誤, 請檢查輸入是否包含受限內容,調整後再試。
Happy Horse 1.1 Reference-to-Video vs. Happy Horse 1.0
Happy Horse 1.0 支援實用的文字和圖片影片生成。Happy Horse 1.1 參考圖生影片透過更強的參考錨定、更好的主體一致性、更準確的提示詞遵循和更豐富的視覺質感推進工作流。
Happy Horse 1.1 Reference-to-Video vs. Seedance 2.0 Reference-to-Video
Seedance 2.0 Reference-to-Video 提供字節跳動參考引導影片創作。Happy Horse 1.1 參考圖生影片強調阿里巴巴升級版多參考理解和主體一致性,適用於商務、角色和行銷活動工作流。
Happy Horse 1.1 Reference-to-Video vs. Kling Reference-to-Video
Kling 參考工作流在富有表現力的角色動態方面很強。Happy Horse 1.1 專注於一致的視覺錨定、更好的提示詞遵循,以及面向需要可重複輸出團隊的生產級 API 整合。
Happy Horse 1.1 Reference-to-Video vs. Runway Video Tools
Runway 提供面向創作者的廣泛影片控制。Happy Horse 1.1 參考圖生影片 API 更適合程式化生成、多參考創意自動化,以及應用內部可擴展的生產。
Happy Horse 1.1 Reference-to-Video vs. Pika
Pika 為創作者提供易用的影片生成。Happy Horse 1.1 參考圖生影片則提供更偏生產的 API 路徑,用於一致的參考引導片段、品牌安全的視覺復用和自動化創意系統。
在瀏覽器中探索多種 AI 創作工具,快速完成圖片與影片工作流程,然後透過 Flaq AI 的生產級模型 API 擴展成功想法。Flaq AI 為所有模型提供統一 API 層,讓你的工作流程更容易使用和擴展。