alibaba/wan-2.2/animate-mix

Imagem para Vídeo

The Wan video character swap model replaces the main character in a video with a character from an image. This model preserves the scene, lighting, and tone of the original video to ensure a seamless result.

Entrada

Carregando configuração de parâmetros...

Saída

Inativo

Os vídeos gerados serão exibidos aqui

Configure os parâmetros e clique em executar para começar a gerar

Cada execução custará 0.126. Com $10 você pode executar aproximadamente 79 vezes.

Você pode continuar com:

Upscale de Vídeo Estender Vídeo

Parâmetros

Exemplo de código
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": "alibaba/wan-2.2/animate-mix",
    "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()

Instalar

Instale o pacote necessário para a sua linguagem de programação.

bash

pip install requests

Autenticação

Todas as solicitações de API requerem autenticação por meio de uma chave de API. Você pode obter sua chave de API no painel do Atlas Cloud.

bash

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

Cabeçalhos HTTP

python

import os

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

Mantenha sua chave de API segura

Nunca exponha sua chave de API em código do lado do cliente ou repositórios públicos. Use variáveis de ambiente ou um proxy de backend.

Enviar uma solicitação

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())

Enviar uma solicitação

Envie uma solicitação de geração assíncrona. A API retorna um ID de predição que você pode usar para verificar o status e obter o resultado.

POST/api/v1/model/generateVideo

Corpo da solicitação

import requests

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

data = {
    "model": "alibaba/wan-2.2/animate-mix",
    "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']}")

Resposta

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

Verificar status

Consulte o endpoint de predição para verificar o status atual da sua solicitação.

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

Exemplo de 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)

Valores de status

processingA solicitação ainda está sendo processada.

completedA geração está completa. As saídas estão disponíveis.

succeededA geração foi bem-sucedida. As saídas estão disponíveis.

failedA geração falhou. Verifique o campo de erro.

Resposta concluída

{
  "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"
  }
}

Enviar arquivos

Envie arquivos para o armazenamento do Atlas Cloud e obtenha uma URL que pode ser usada nas suas solicitações de API. Use multipart/form-data para enviar.

POST/api/v1/model/uploadMedia

Exemplo de upload

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}")

Resposta

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

Schema de entrada

Os seguintes parâmetros são aceitos no corpo da solicitação.

Total: 0Obrigatório: 0Opcional: 0

Nenhum parâmetro disponível.

Exemplo de corpo da solicitação

json

{
  "model": "alibaba/wan-2.2/animate-mix"
}

Schema de saída

A API retorna uma resposta de predição com as URL de saída geradas.

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

Exemplo de resposta

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

O Atlas Cloud Skills integra mais de 300 modelos de IA diretamente no seu assistente de codificação com IA. Um comando para instalar e depois use linguagem natural para gerar imagens, vídeos e conversar com LLM.

Clientes compatíveis

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ clientes compatíveis

Instalar

bash

npx skills add AtlasCloudAI/atlas-cloud-skills

Configurar chave de API

Obtenha sua chave de API no painel do Atlas Cloud e defina-a como variável de ambiente.

bash

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

Funcionalidades

Após a instalação, você pode usar linguagem natural no seu assistente de IA para acessar todos os modelos do Atlas Cloud.

Geração de imagensGere imagens com modelos como Nano Banana 2, Z-Image e mais.

Criação de vídeosCrie vídeos a partir de texto ou imagens com Kling, Vidu, Veo, etc.

Chat com LLMConverse com Qwen, DeepSeek e outros modelos de linguagem de grande escala.

Upload de mídiaEnvie arquivos locais para fluxos de trabalho de edição de imagens e imagem para vídeo.

Saiba mais

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

O Atlas Cloud MCP Server conecta seu IDE com mais de 300 modelos de IA através do Model Context Protocol. Funciona com qualquer cliente compatível com MCP.

Clientes compatíveis

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ clientes compatíveis

Instalar

bash

npx -y atlascloud-mcp

Configuração

Adicione a seguinte configuração ao arquivo de configuração de MCP do seu IDE.

json

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

Ferramentas disponíveis

atlas_generate_imageGere imagens a partir de prompts de texto.

atlas_generate_videoCrie vídeos a partir de texto ou imagens.

atlas_chatConverse com modelos de linguagem de grande escala.

atlas_list_modelsExplore mais de 300 modelos de IA disponíveis.

atlas_quick_generateCriação de conteúdo em uma etapa com seleção automática de modelo.

atlas_upload_mediaEnvie arquivos locais para fluxos de trabalho de API.

Saiba mais

github.com/AtlasCloudAI/mcp-server

API Schema

Schema não disponível

Faça login para ver o histórico de solicitações

Você precisa fazer login para acessar o histórico de solicitações do modelo.

Fazer Login

Alibaba Wan 2.2 Animate Mix

An advanced, unified character animation and replacement model that transfers motion, expressions, and timing from a source clip while preserving the identity of a target character from a single reference image. Animate Mix is part of the Wan 2.2 Animate family and focuses on blending the target identity with source motion for coherent, high-quality video generation.

Overview

Purpose: Motion transfer and identity preservation from one image to a full video
Core capability: Mix mode fuses target appearance with source motion dynamics
Foundation: Built atop Wan2.2 innovations (e.g., MoE-driven diffusion, improved data, high-compression video)
Typical output: Smooth 24 fps video at up to 720p with holistic movement and expression replication
Use cases: Character animation, avatar replacement, lip-sync, dynamic explainer clips, social content

Key Features

One-image-to-video: Animate a character from a single, high-quality portrait or full-body image
Motion mix-in: Transfer pose, body motion, facial expressions, and timing from a source video
Identity retention: Preserve clothing, face, and hair of the target character while adopting motion
Holistic dynamics: Handles subtle micro-expressions, head motion, and body kinematics
Robustness: Works across varied camera motions and moderate occlusions with careful input selection
Motion + Identity Transfer: Applies actions and facial expressions from a reference video while preserving the target character’s face, hair, and clothing.
Dual Modes:
- Standard Mode (wan-std): Optimized for speed and cost; ideal for previews and basic outputs.
- Professional Mode (wan-pro): Smoother motion and higher fidelity for production use (higher time/cost).
Flexible Input Support: Handles wide image/video resolutions and aspect ratios for diverse pipelines.
Long Duration: Supports reference videos from 2 to 30 seconds.
Holistic Dynamics: Captures pose, micro‑expressions, head motion, and timing for coherent results.

Designed For

Content Creators: Identity-preserving avatar animation for social content.
Game Developers: Rapid prototyping of character motion with reference clips.
Marketing & Advertising: Transform static assets into dynamic character videos.
Animation Enthusiasts: Experiment with motion transfer and identity mixing.

Input Requirements

To achieve the best results, follow these guidelines:

Character Image

Content: One person, facing the camera, face fully visible and unobstructed; the subject should occupy a moderate portion of the frame.
Format: JPG, JPEG, PNG, BMP, WEBP.
Dimensions: Width and height between 200 and 4096 pixels.
Aspect Ratio: Between 1:3 and 3:1.
File Size: Max 5 MB.

Reference Video (Motion Source)

Content: One person with clearly visible face; stable framing improves motion transfer.
Format: MP4, AVI, MOV.
Duration: 2 to 30 seconds.
Dimensions: Width and height between 200 and 2048 pixels.
Aspect Ratio: Between 1:3 and 3:1.
File Size: Max 200 MB.
Recommendation: Higher resolution and frame rate yield better identity preservation and smoother motion.

Pricing

Billing is based on generated video duration and selected mode.

Billing Logic: Cost scales with video duration.
Mode Multiplier:
- Standard Mode: 1.0x base rate.
- Professional Mode: 1.5x base rate.
Service transitions to paid billing once the free quota is used; set up a payment method early to avoid interruptions.

How to Use

Upload Character Image: Provide a clear identity reference for the target character.
Upload Reference Video: Select a clip containing the desired motion and expressions.
Select Mode: Choose "Standard" (wan‑std) for speed or "Professional" (wan‑pro) for quality.
Generate: Submit to produce the identity‑preserving animated video.

Best Practices

Use high‑resolution, well‑lit images; avoid occlusions and heavy motion blur.
Choose a motion source with matching vibe (tempo, style, emotion) to your target.
Keep backgrounds simple to reduce artifacts and improve identity retention.
Prefer moderate motion complexity; extreme spins or strong occlusions may degrade quality.

Limitations

Identity drift may occur with occlusions, extreme camera motion, or low‑quality inputs.
Fast‑moving props or complex interactions can introduce artifacts and temporal instability.
Lip‑sync quality depends on clarity of the source clip and face visibility in the reference image.

Safety and Content

Respect privacy and consent when using identity transfer.
Follow platform policies and local regulations.
Avoid generating harmful or restricted content.

Version

Model: Alibaba Wan 2.2 Animate Mix
Family: Wan2.2 Animate (Move/Mix)
Technical context: Wan 2.2 with MoE‑driven video diffusion and improved training data