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muapi-drone-style-video

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Original

English
🇨🇳

Translation

Chinese

Drone-Style Video

无人机风格视频

Generate aerial drone-perspective footage — sweeping bird's-eye views, orbit shots, and flyover sequences for landscapes, architecture, and events.
Estimated credits: ~80 per run.
生成无人机航拍视角视频素材——涵盖用于景观、建筑和活动拍摄的全景鸟瞰镜头、环绕镜头以及飞越镜头序列。
预估消耗点数： 每次运行约80点。

Inputs

输入参数

NameTypeRequiredDefaultDescription
location_or_subject
textyes—What to shoot from above (e.g. "mountain valley at sunrise", "luxury villa by the ocean", "crowded city intersection").
shot_type
textnorevealCamera movement style — 'reveal' (ascend & reveal), 'orbit' (circle subject), 'flyover' (pass over), 'top-down' (bird's eye static).
style
textnogolden hour, cinematic, 4K, ultra-detailedVisual atmosphere (e.g. "dramatic storm clouds", "misty morning", "blue hour city lights").
aspect_ratio
textno16:9Output aspect ratio.
reference_image
image_urlno—Optional aerial/location reference image.
名称类型是否必填默认值描述
location_or_subject
文本是—航拍的对象或地点（例如：“日出时的山谷”、“海边的豪华别墅”、“拥挤的城市十字路口”）。
shot_type
文本否reveal相机运动风格——'reveal'（上升并展示）、'orbit'（环绕拍摄对象）、'flyover'（飞越）、'top-down'（静态鸟瞰）。
style
文本否golden hour, cinematic, 4K, ultra-detailed视觉氛围（例如：“戏剧性的风暴云”、“薄雾清晨”、“蓝调时刻的城市灯光”）。
aspect_ratio
文本否16:9输出画面比例。
reference_image
图片链接否—可选的航拍/地点参考图片链接。

Steps

步骤

Phase A — Generate Drone Footage

阶段A — 生成无人机视频素材

Submit the plan with ONE step:
  1. Aerial video — If 
    {{reference_image}}
    is provided, use 
    muapi video generate
    (model=
    veo3.1-image-to-video
    ); otherwise use 
    muapi video generate
    (model=
    veo3.1-text-to-video
    ).
    • Build prompt based on 
      {{shot_type}}
      :
      • reveal: 
        Drone camera starts low, slowly ascends and reveals {{location_or_subject}}, sweeping wide aerial perspective, {{style}}
      • orbit: 
        Drone camera orbits {{location_or_subject}} in a smooth circular arc, 360-degree aerial rotation, {{style}}
      • flyover: 
        Drone camera flies low and fast over {{location_or_subject}}, tracking forward momentum, depth of field, {{style}}
      • top-down: 
        Perfect overhead bird's eye view of {{location_or_subject}}, drone looking straight down, minimal distortion, {{style}}
    • Append to all prompts: 
      DJI-quality drone footage, stabilized gimbal, no shake, cinematic color grade, photorealistic
    • Aspect ratio: 
      {{aspect_ratio}}
After generation, offer:
  • A different shot type variation
  • Adding wind/ambient audio via 
    mmaudio-v2-video-to-video
  • Upscaling via 
    ai-video-upscaler-pro
提交计划包含一个步骤：
  1. 航拍视频 — 如果提供了
    {{reference_image}}
    ，使用
    muapi video generate
    （model=
    veo3.1-image-to-video
    ）；否则使用
    muapi video generate
    （model=
    veo3.1-text-to-video
    ）。
    • 根据
      {{shot_type}}
      构建提示词：
      • reveal: 
        无人机相机从低空开始，缓慢上升并展示{{location_or_subject}}，广阔的全景航拍视角，{{style}}
      • orbit: 
        无人机相机以平滑的圆弧环绕{{location_or_subject}}，360度航拍旋转，{{style}}
      • flyover: 
        无人机相机低空快速飞越{{location_or_subject}}，保持向前追踪的动感，景深效果，{{style}}
      • top-down: 
        {{location_or_subject}}的完美垂直鸟瞰视角，无人机垂直向下拍摄，最小畸变，{{style}}
    • 所有提示词追加内容：
      DJI-quality drone footage, stabilized gimbal, no shake, cinematic color grade, photorealistic
    • 画面比例：
      {{aspect_ratio}}
生成完成后，提供以下选项：
  • 更换不同的镜头类型变体
  • 通过
    mmaudio-v2-video-to-video
    添加风声/环境音
  • 通过
    ai-video-upscaler-pro
    进行画质增强

Notes

注意事项

  • For architecture, emphasize "slow orbit to reveal full building facade".
  • For landscapes, use "magic hour lighting" for the best results.
  • veo3.1-text-to-video
    produces the best physics and camera motion for aerial scenes.
  • 对于建筑拍摄，强调“缓慢环绕以展示建筑完整立面”。
  • 对于景观拍摄，使用“magic hour lighting”以获得最佳效果。
  • veo3.1-text-to-video
    在航拍场景中能生成最逼真的物理效果和相机运动。

Trigger Keywords

触发关键词

drone
, 
aerial
, 
bird's eye
, 
flyover
, 
aerial shot
, 
drone footage
, 
top down
, 
overhead video
drone
, 
aerial
, 
bird's eye
, 
flyover
, 
aerial shot
, 
drone footage
, 
top down
, 
overhead video

Notes for the Executing Agent

执行代理注意事项

  • This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call 
    muapi
    CLI commands. Use 
    muapi auth configure
    first if 
    MUAPI_API_KEY
    is unset.
  • For model IDs without a CLI alias yet, fall back to the raw endpoint via 
    curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}'
    and poll with 
    muapi predict wait <request_id>
    .
  • Substitute 
    {{input_name}}
    placeholders with the user's actual inputs before issuing each call.
  • 本方案由LLM编排：阅读每个阶段，向用户收集缺失的输入，然后调用
    muapi
    CLI命令。如果未设置
    MUAPI_API_KEY
    ，请先使用
    muapi auth configure
    配置。
  • 对于尚未有CLI别名的模型ID，回退到原始端点，使用
    curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}'
    ，并通过
    muapi predict wait <request_id>
    轮询结果。
  • 在发出每个调用前，将
    {{input_name}}
    占位符替换为用户的实际输入。