alibaba/wan-2.7-pro/image-edit

gambar-ke-gambar

PRO

Wan 2.7 Pro Image-to-Image API by Alibaba

alibaba/wan-2.7-pro/image-edit

Image-edit

Edits and recomposes images with Wan 2.7 image pro using text instructions and multi-image references for higher quality outputs.

INPUT

Prompt *

Gambar *(0/9)

Anda dapat drag & drop file atau klik untuk mengunggah

MAX:9

Ukuran

Jumlah

Mode berpikir

Seed

OUTPUT

Menunggu

Gambar yang dihasilkan akan muncul di sini

Konfigurasikan pengaturan Anda dan klik Jalankan untuk memulai

Permintaan Anda akan dikenakan biaya $0.075 per eksekusi. Dengan $10 Anda dapat menjalankan model ini sekitar 133 kali.

Berikut yang dapat Anda lakukan selanjutnya:

Gambar ke Video Gambar ke Gambar

Parameter

Contoh kode
import requests
import time

# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "alibaba/wan-2.7-pro/image-edit",  # Required. Model name. options: alibaba/wan-2.7-pro/image-edit
    "prompt": "A beautiful landscape with mountains and lake",  # Required. Text instruction used to edit the image
    "images": [
        "https://example.com/image1.jpg"
    ],  # Required. Input images, each provided as a URL or Base64 string
    "size": "2K",  # Output image resolution. options: 1K | 2K
    "n": 1,  # Number of images to generate. (min: 1, max: 4)
    "thinking_mode": True,  # Whether to enable thinking mode for higher-quality image generation
    "seed": -1,  # Random seed for image generation. (min: -1, max: 2147483647)
    "enable_sync_mode": False,  # Whether to wait for generation to finish and return the final result directly in the response
    "enable_base64_output": False,  # Whether to return the generated image as a Base64 string instead of a URL
}

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"] == "completed":
            print("Generated image:", 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)

image_url = check_status()

Instalasi

Instal paket dependensi yang diperlukan.

pip install requests

Autentikasi

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

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

HTTP Headers

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/generateImage"
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/generateImage

Isi Permintaan

import requests

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

data = {
    "model": "alibaba/wan-2.7-pro/image-edit",
    "prompt": "A beautiful landscape with mountains and lake"
}

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

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

Respons

{
  "code": 200,
  "data": {
    "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.png"
    ],
    "metrics": {
      "predict_time": 8.3
    },
    "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: 9Wajib: 3Opsional: 6

modelstringrequired

Model name.

Default: "alibaba/wan-2.7-pro/image-edit"

alibaba/wan-2.7-pro/image-edit

promptstringrequired

Text instruction used to edit the image. Maximum length is 5000 characters.

imagesarray[string]required

Input images, each provided as a URL or Base64 string. The first image is treated as the primary input; subsequent images serve as references.

Min items: 1Max items: 9

sizestring

Output image resolution.

Default: "2K"

1K2K

ninteger

Number of images to generate.

Default: 1Min: 1Max: 4

thinking_modeboolean

Whether to enable thinking mode for higher-quality image generation.

Default: true

seedinteger

Random seed for image generation. Range: 0 to 2147483647. Use -1 for a random seed.

Default: -1Min: -1Max: 2147483647

enable_sync_modeboolean

Whether to wait for generation to finish and return the final result directly in the response.

Default: false

enable_base64_outputboolean

Whether to return the generated image as a Base64 string instead of a URL.

Default: false

Contoh Isi Permintaan

{
  "model": "alibaba/wan-2.7-pro/image-edit",
  "prompt": "A beautiful landscape",
  "images": [
    "https://example.com/file.jpg"
  ],
  "size": "2K",
  "n": 1,
  "thinking_mode": true,
  "seed": -1,
  "enable_sync_mode": false,
  "enable_base64_output": false
}

Output Schema

API mengembalikan respons prediction dengan URL output yang dihasilkan.

codeinteger

messagestring

dataunknown

Contoh Respons

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.png"
  ],
  "metrics": {
    "predict_time": 8.3
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills mengintegrasikan 400+ 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

npx skills add AtlasCloudAI/atlas-cloud-skills

Atur API Key

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

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 400+ 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

npx -y atlascloud-mcp

Konfigurasi

Tambahkan konfigurasi berikut ke file pengaturan MCP di IDE Anda.

{
  "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 400+ model AI yang tersedia.

atlas_quick_generatePembuatan konten satu langkah dengan pemilihan model terbaik otomatis.

atlas_upload_mediaUnggah file lokal untuk alur kerja API.

Pelajari lebih lanjut

github.com/AtlasCloudAI/mcp-server

Schema API

{
  "info": {
    "title": "AtlasCloud API",
    "version": "1.0.0",
    "description": "The AtlasCloud API."
  },
  "openapi": "3.0.0",
  "paths": {
    "/api/v1/model/generateImage": {
      "post": {
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "required": true,
            "schema": {
              "description": "Request ID",
              "type": "string"
            }
          }
        ],
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        }
      },
      "x-api-name": "model_result"
    }
  },
  "components": {
    "schemas": {
      "Input": {
        "type": "object",
        "properties": {
          "model": {
            "type": "string",
            "description": "Model name.",
            "default": "alibaba/wan-2.7-pro/image-edit",
            "enum": [
              "alibaba/wan-2.7-pro/image-edit"
            ]
          },
          "prompt": {
            "description": "Text instruction used to edit the image. Maximum length is 5000 characters.",
            "type": "string"
          },
          "images": {
            "description": "Input images, each provided as a URL or Base64 string. The first image is treated as the primary input; subsequent images serve as references.",
            "type": "array",
            "items": {
              "type": "string"
            },
            "minItems": 1,
            "maxItems": 9
          },
          "size": {
            "default": "2K",
            "description": "Output image resolution.",
            "enum": [
              "1K",
              "2K"
            ],
            "type": "string"
          },
          "n": {
            "default": 1,
            "minimum": 1,
            "maximum": 4,
            "description": "Number of images to generate.",
            "type": "integer"
          },
          "thinking_mode": {
            "default": true,
            "description": "Whether to enable thinking mode for higher-quality image generation.",
            "type": "boolean"
          },
          "seed": {
            "default": -1,
            "minimum": -1,
            "maximum": 2147483647,
            "description": "Random seed for image generation. Range: 0 to 2147483647. Use -1 for a random seed.",
            "type": "integer"
          },
          "enable_sync_mode": {
            "default": false,
            "description": "Whether to wait for generation to finish and return the final result directly in the response.",
            "disabled": true,
            "type": "boolean"
          },
          "enable_base64_output": {
            "default": false,
            "description": "Whether to return the generated image as a Base64 string instead of a URL.",
            "disabled": true,
            "type": "boolean"
          }
        },
        "required": [
          "model",
          "prompt",
          "images"
        ],
        "x-order-properties": [
          "model",
          "prompt",
          "images",
          "size",
          "n",
          "thinking_mode",
          "seed",
          "enable_sync_mode",
          "enable_base64_output"
        ]
      },
      "PredictionResponse": {
        "type": "object",
        "properties": {
          "code": {
            "type": "integer"
          },
          "message": {
            "type": "string"
          },
          "data": {
            "$ref": "#/components/schemas/PredictionData"
          }
        }
      },
      "PredictionData": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string",
            "description": "Unique ID of the generation task."
          },
          "model": {
            "type": "string",
            "description": "Model used for the generation."
          },
          "outputs": {
            "type": "array",
            "description": "Generated image results. Each item is an image URL, or a Base64 string when Base64 output is enabled.",
            "items": {
              "type": "string"
            }
          },
          "urls": {
            "type": "object",
            "properties": {
              "get": {
                "type": "string"
              }
            }
          },
          "has_nsfw_contents": {
            "type": "array",
            "items": {
              "type": "boolean"
            }
          },
          "status": {
            "type": "string",
            "description": "Current task status, such as created, processing, completed, unknown, or failed."
          },
          "created_at": {
            "type": "string",
            "format": "date-time"
          },
          "error": {
            "type": "string",
            "description": "Error message returned when the task fails."
          }
        }
      }
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ]
}

Template Prompt untuk LLM

# alibaba/wan-2.7-pro/image-edit

> Edits and recomposes images with Wan 2.7 image pro using text instructions and multi-image references for higher quality outputs.


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `alibaba/wan-2.7-pro/image-edit`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  Model name.
  - Default: `"alibaba/wan-2.7-pro/image-edit"`
  - Options: "alibaba/wan-2.7-pro/image-edit"

- **`prompt`** (`string`, _required_):
  Text instruction used to edit the image. Maximum length is 5000 characters.

- **`images`** (`array[string]`, _required_):
  Input images, each provided as a URL or Base64 string. The first image is treated as the primary input; subsequent images serve as references.
  - Min items: 1
  - Max items: 9

- **`size`** (`string`, _optional_):
  Output image resolution.
  - Default: `"2K"`
  - Options: "1K", "2K"

- **`n`** (`integer`, _optional_):
  Number of images to generate.
  - Default: `1`
  - Min: 1
  - Max: 4

- **`thinking_mode`** (`boolean`, _optional_):
  Whether to enable thinking mode for higher-quality image generation.
  - Default: `true`

- **`seed`** (`integer`, _optional_):
  Random seed for image generation. Range: 0 to 2147483647. Use -1 for a random seed.
  - Default: `-1`
  - Min: -1
  - Max: 2147483647

- **`enable_sync_mode`** (`boolean`, _optional_):
  Whether to wait for generation to finish and return the final result directly in the response.
  - Default: `false`

- **`enable_base64_output`** (`boolean`, _optional_):
  Whether to return the generated image as a Base64 string instead of a URL.
  - Default: `false`



**Required Parameters Example**:

```json
{
  "model": "alibaba/wan-2.7-pro/image-edit",
  "prompt": "",
  "images": [
    ""
  ]
}
```


**Full Example**:

```json
{
  "model": "alibaba/wan-2.7-pro/image-edit",
  "prompt": "",
  "images": [
    ""
  ],
  "size": "2K",
  "n": 1,
  "thinking_mode": true,
  "seed": -1,
  "enable_sync_mode": false,
  "enable_base64_output": false
}
```


### Output Schema

The API returns the following output format:


- **`code`** (`integer`, _optional_):

- **`message`** (`string`, _optional_):

- **`data`** (`string`, _optional_):



**Example Response**:

```json
{
  "code": 0,
  "message": "",
  "data": null
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "alibaba/wan-2.7-pro/image-edit",
  "prompt": "",
  "images": [
    ""
  ],
  "size": "2K",
  "n": 1,
  "thinking_mode": true,
  "seed": -1,
  "enable_sync_mode": false,
  "enable_base64_output": false
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/alibaba/wan-2.7-pro/image-edit)

Tidak ada contoh yang tersedia

Memuat...

Alibaba WAN 2.7 Pro Image Edit

Alibaba WAN 2.7 Pro Image Edit is the higher-fidelity image editing tier in the Wan 2.7 family. It is designed for instruction-guided edits and multi-image composition when output quality matters more than raw turnaround speed.

Why creators love it

Higher-quality edits: Better fit for texture transfer, material changes, and polished visual refinement.
Multi-image composition: Use one or more reference images alongside a text instruction.
Instruction-first workflow: Good for scene restyling, object replacement, and composition-guided editing.
Practical control surface: Supports flexible sizing, multiple variations, and consistent exploration with seed control.

Perfect for

Premium campaign and commercial design edits.
Product photography refinement and compositing.
Creative teams building polished before/after variations from source assets.
Professional creative teams that need stronger edit quality than the standard tier.

Recommended size guidance:

Prefer 1K or 2K for edit scenarios.
Even though the Pro family supports 4K for text-only generation, image-involved scenarios should stay on the lower supported sizes.

How to Use

Provide the source image and add extra references when needed.
Write a direct instruction describing the transformation you want.
Choose the target size, usually 1K or 2K.
Review the edited outputs and keep the version with the best balance of fidelity and polish.

Pro tips

Ask for one controlled edit at a time when you want stable, premium output.
Add more references only when they serve a clear visual purpose.

Wan 2.7 Pro Image-to-Image API by Alibaba

INPUT

OUTPUT

Parameter

Contoh kode

Instalasi

Autentikasi

HTTP Headers

Kirim permintaan

Kirim Permintaan

Isi Permintaan

Respons

Periksa Status

Contoh Polling

Nilai Status

Respons Selesai

Unggah File

Contoh Unggah

Respons

Input Schema

Contoh Isi Permintaan

Output Schema

Contoh Respons

Atlas Cloud Skills

Klien yang Didukung

Instalasi

Atur API Key

Kemampuan

MCP Server

Klien yang Didukung

Instalasi

Konfigurasi

Alat yang Tersedia

Schema API

Template Prompt untuk LLM

Alibaba WAN 2.7 Pro Image Edit

Why creators love it

Perfect for

How to Use

Pro tips

Jelajahi Model Serupa

Wan-2.7 Pro Text-to-image

Wan-2.7 Image-to-image

Wan-2.7 Text-to-image

Qwen Image 2.0 Pro Text-to-image

Qwen Image 2.0 Text-to-image

Qwen Image 2.0 Edit

Qwen Image 2.0 Pro Edit

Qwen-Image Edit Plus 20251215

Wan-2.6 Image-to-image

Qwen Image Edit

Qwen-Image Text-to-image Max

Qwen-Image Text-to-image Plus

Wan-2.5 Image Edit

Wan-2.5 Text-to-image

Qwen-Image Edit Plus

Qwen-Image Edit

Satu API untuk semua AI multimedia.

Join our Discord community

INPUT

OUTPUT

Parameter

Contoh kode

Instalasi

Autentikasi

HTTP Headers

Kirim permintaan

Kirim Permintaan

Isi Permintaan

Respons

Periksa Status

Contoh Polling

Nilai Status

Respons Selesai

Unggah File

Contoh Unggah

Respons

Input Schema

Contoh Isi Permintaan

Output Schema