kwaivgi/kling-v2.6-std/motion-control

gambar-ke-video

Kling v2.6 Std Motion Control API by Kuaishou

kwaivgi/kling-v2.6-std/motion-control

Motion-control

Kling 2.6 Standard Motion Control transfers motion from reference videos to animate still images. Upload a character image and a motion clip (dance, action, gesture), and the model extracts the movement to generate smooth, realistic video.

INPUT

Memuat konfigurasi parameter...

OUTPUT

Menunggu

Video yang dihasilkan akan muncul di sini

Konfigurasikan pengaturan Anda dan klik Jalankan untuk memulai

Permintaan Anda akan dikenakan biaya $0.06 per eksekusi. Dengan $10 Anda dapat menjalankan model ini sekitar 166 kali.

Berikut yang dapat Anda lakukan selanjutnya:

Seedance 2.0 Kling v3 Vidu Wan2.7

Parameter

Contoh kode
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": "kwaivgi/kling-v2.6-std/motion-control",
    "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()

Instalasi

Instal paket yang diperlukan untuk bahasa pemrograman Anda.

bash

pip install requests

Autentikasi

Semua permintaan API memerlukan autentikasi melalui API key. Anda bisa mendapatkan API key dari dasbor Atlas Cloud.

bash

export ATLASCLOUD_API_KEY="your-api-key-here"

HTTP Headers

python

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

Jaga keamanan API key Anda

Jangan pernah mengekspos API key Anda di kode sisi klien atau repositori publik. Gunakan variabel lingkungan atau proxy backend sebagai gantinya.

Kirim permintaan

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Kirim Permintaan

Kirim permintaan pembuatan asinkron. API mengembalikan prediction ID yang dapat Anda gunakan untuk memeriksa status dan mengambil hasil.

POST/api/v1/model/generateVideo

Isi Permintaan

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "kwaivgi/kling-v2.6-std/motion-control",
    "input": {
        "prompt": "A beautiful sunset over the ocean with gentle waves"
    }
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['id']}")
print(f"Status: {result['status']}")

Respons

{
  "id": "pred_abc123",
  "status": "processing",
  "model": "model-name",
  "created_at": "2025-01-01T00:00:00Z"
}

Periksa Status

Polling prediction endpoint untuk memeriksa status permintaan Anda saat ini.

GET/api/v1/model/prediction/{prediction_id}

Contoh Polling

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

Nilai Status

processingPermintaan masih diproses.

completedPembuatan selesai. Output tersedia.

succeededPembuatan berhasil. Output tersedia.

failedPembuatan gagal. Periksa field error.

Respons Selesai

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.mp4"
    ],
    "metrics": {
      "predict_time": 45.2
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

Unggah File

Unggah file ke penyimpanan Atlas Cloud dan dapatkan URL yang dapat Anda gunakan dalam permintaan API Anda. Gunakan multipart/form-data untuk mengunggah.

POST/api/v1/model/uploadMedia

Contoh Unggah

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

Respons

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Input Schema

Parameter berikut diterima di isi permintaan.

Total: 0Wajib: 0Opsional: 0

Tidak ada parameter yang tersedia.

Contoh Isi Permintaan

json

{
  "model": "kwaivgi/kling-v2.6-std/motion-control"
}

Output Schema

API mengembalikan respons prediction dengan URL output yang dihasilkan.

idstringrequired

Unique identifier for the prediction.

statusstringrequired

Current status of the prediction.

processingcompletedsucceededfailed

modelstringrequired

The model used for generation.

outputsarray[string]

Array of output URLs. Available when status is "completed".

errorstring

Error message if status is "failed".

metricsobject

Performance metrics.

predict_timenumber

Time taken for video generation in seconds.

created_atstringrequired

ISO 8601 timestamp when the prediction was created.

Format: date-time

completed_atstring

ISO 8601 timestamp when the prediction was completed.

Format: date-time

Contoh Respons

json

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.mp4"
  ],
  "metrics": {
    "predict_time": 45.2
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills mengintegrasikan 300+ model AI langsung ke asisten pengkodean AI Anda. Satu perintah untuk menginstal, lalu gunakan bahasa alami untuk menghasilkan gambar, video, dan mengobrol dengan LLM.

Klien yang Didukung

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ klien yang didukung

Instalasi

bash

npx skills add AtlasCloudAI/atlas-cloud-skills

Atur API Key

Dapatkan API key dari dasbor Atlas Cloud dan atur sebagai variabel lingkungan.

bash

export ATLASCLOUD_API_KEY="your-api-key-here"

Kemampuan

Setelah diinstal, Anda dapat menggunakan bahasa alami di asisten AI Anda untuk mengakses semua model Atlas Cloud.

Pembuatan GambarBuat gambar dengan model seperti Nano Banana 2, Z-Image, dan lainnya.

Pembuatan VideoBuat video dari teks atau gambar dengan Kling, Vidu, Veo, dll.

Obrolan LLMMengobrol dengan Qwen, DeepSeek, dan model bahasa besar lainnya.

Unggah MediaUnggah file lokal untuk pengeditan gambar dan alur kerja gambar-ke-video.

Pelajari lebih lanjut

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

Atlas Cloud MCP Server menghubungkan IDE Anda dengan 300+ model AI melalui Model Context Protocol. Berfungsi dengan klien apa pun yang kompatibel dengan MCP.

Klien yang Didukung

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ klien yang didukung

Instalasi

bash

npx -y atlascloud-mcp

Konfigurasi

Tambahkan konfigurasi berikut ke file pengaturan MCP di IDE Anda.

json

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

Alat yang Tersedia

atlas_generate_imageBuat gambar dari prompt teks.

atlas_generate_videoBuat video dari teks atau gambar.

atlas_chatMengobrol dengan model bahasa besar.

atlas_list_modelsJelajahi 300+ model AI yang tersedia.

atlas_quick_generatePembuatan konten satu langkah dengan pemilihan model otomatis.

atlas_upload_mediaUnggah file lokal untuk alur kerja API.

Pelajari lebih lanjut

github.com/AtlasCloudAI/mcp-server

Schema API

Schema tidak tersedia

Tidak ada contoh yang tersedia

Silakan masuk untuk melihat riwayat permintaan

Anda perlu masuk untuk mengakses riwayat permintaan model Anda.

Masuk

Kling V2.6 Standard Motion Control

Transfer motion from any video onto your character with Kling V2.6 Motion Control. Upload a reference image of your subject and a motion video — the model generates your character performing those exact movements. Perfect for dance videos, action sequences, and character animation.

Why It Looks Great

Precise motion transfer: Accurately maps movements from reference video to your character.
Character preservation: Maintains your subject's identity and appearance.
Audio retention: Option to keep the original video's sound.
Extended duration: Supports videos up to 30 seconds.
Orientation control: Specify character facing direction for better results.
Prompt Enhancer: Refine scene descriptions for enhanced output.

Parameters

Parameter	Required	Description
image	Yes	Reference image of your character/person.
video	Yes	Motion reference video to transfer movements from.
character_orientation	Yes	Direction character is facing (front, side, back).
prompt	No	Additional scene description or style guidance.
negative_prompt	No	Elements to avoid in the generated video.
keep_original_sound	No	Retain audio from the original motion video.

How to Use

Upload character image — a clear image of your subject.
Upload motion video — the video with movements to transfer.
Select character orientation — Generate the orientation of the characters in the video, which can be selected to match the image or the video.
Write prompt (optional) — add scene details or style guidance.
Add negative prompt (optional) — specify what to avoid.
Toggle audio — check to keep original video sound.
Run — click the button to generate.
Download — preview and save your video.

Pricing

Per 3-second billing based on video duration. Minimum 3 seconds, maximum 30 seconds.

Duration	Calculation	Cost
3 seconds (min)	3 ÷ 3 × $0.21	$0.21
6 seconds	6 ÷ 3 × $0.21	$0.42
10 seconds	10 ÷ 3 × $0.21	$0.70
15 seconds	15 ÷ 3 × $0.21	$1.05
30 seconds (max)	30 ÷ 3 × $0.21	$2.10

Best Use Cases

Dance Videos — Transfer choreography onto any character.
Action Sequences — Apply stunts and movements to your subjects.
Character Animation — Animate illustrated or AI-generated characters.
Content Creation — Create viral-ready videos with custom performers.
Virtual Influencers — Bring virtual characters to life with real motion.
Music Videos — Sync character movements to music performances.

Example Workflows

Upload anime character + dance video → Anime character performs the dance
Upload portrait photo + workout video → Person performs exercise routine
Upload mascot image + wave gesture → Mascot waves naturally
Upload product character + presentation motion → Animated product spokesperson

Character Orientation Guide

Orientation	When to Use
Front	Character facing camera directly
Side	Character in profile view
Back	Character facing away from camera

Pro Tips for Best Results

Use clear, well-lit character images with visible full body or upper body.
Match character orientation to their actual pose in the image.
Motion videos with clear, distinct movements work best.
Keep original sound for dance videos synced to music.
Use prompts to add environmental context or style details.
Shorter clips (3-10s) often produce more consistent results.

Notes

Minimum video duration is 3 seconds; maximum is 30 seconds.
If using URLs, ensure they are publicly accessible.
Processing time scales with video duration.
Best results come from motion videos with clear human movements.

More Models to Try

Kling V2.6 Pro Motion Control — Professional-grade motion transfer that maps movements from any reference video onto your character with superior quality and precision.
Wan 2.2 Animate — Transform static images into dynamic videos with AI-powered animation, bringing photos and illustrations to life with natural motion.
Wan 2.2 Fun Control — Creative pose and motion control for image-to-video generation, enabling playful character animations with customizable movements.