atlascloud/image-upscaler

圖像工具

Image Upscaler API

atlascloud/image-upscaler

Image-upscaler

Increase image resolution up to 4x with texture-aware enhancement for print, ecommerce, or high-dpi screens.

輸入

圖片 *

可拖曳檔案至此，或點擊上傳

MAX:1

Outscale

Output format

輸出

閒置

生成的圖片將在這裡顯示

設定參數後點擊執行開始生成

每次執行將花費 $0.01。$10 可執行約 1000 次。

你可以繼續：

圖生影片圖生圖

參數

程式碼範例
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": "atlascloud/image-upscaler",  # Required. Model name. options: atlascloud/image-upscaler
    "image": "example_value",  # Required. Input image URL to upscale
    "outscale": 1,  # Output scale multiplier. (min: 1, max: 4)
    "output_format": "jpeg",  # Output image format. options: jpeg | png | webp | jpg
}

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()

安裝

安裝所需的相依套件。

pip install requests

驗證

所有 API 請求都需要透過 API Key 進行認證。您可以在 Atlas Cloud 控制台取得 API Key。

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

HTTP 標頭

import os

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

保護好您的 API Key

切勿在客戶端程式碼或公開儲存庫中暴露您的 API Key。請使用環境變數或後端代理。

提交請求

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())

提交請求

提交一個非同步生成請求。API 會傳回一個 prediction ID，您可以用它來檢查狀態與取得結果。

POST/api/v1/model/generateImage

請求主體

import requests

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

data = {
    "model": "atlascloud/image-upscaler",
    "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']}")

回應

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

檢查狀態

輪詢 prediction 端點以檢查請求的當前狀態。

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

輪詢範例

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)

狀態值

processing請求仍在處理中。

completed生成完成，輸出可用。

succeeded生成成功，輸出可用。

failed生成失敗，請檢查 error 欄位。

完成回應

{
  "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"
  }
}

上傳檔案

將檔案上傳到 Atlas Cloud 儲存空間，取得可在 API 請求中使用的 URL。使用 multipart/form-data 上傳。

POST/api/v1/model/uploadMedia

上傳範例

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}")

回應

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

Input Schema

以下參數在請求主體中被接受。

總計: 4必填: 2選填: 2

modelstringrequired

Model name.

Default: "atlascloud/image-upscaler"

atlascloud/image-upscaler

imagestringrequired

Input image URL to upscale.

outscalenumber

Output scale multiplier. Use 2.0 for standard upscaling and 4.0 for the maximum exposed scale.

Default: 1Min: 1Max: 4

output_formatstring

Output image format.

Default: "jpeg"

jpegpngwebpjpg

範例請求主體

{
  "model": "atlascloud/image-upscaler",
  "image": "example_image",
  "outscale": 1,
  "output_format": "jpeg"
}

Output Schema

API 傳回包含生成輸出 URL 的 prediction 回應。

created_atstring

ISO timestamp of when the request was created.

idstring

Unique identifier for the prediction.

modelstring

Model ID used for the prediction.

outputsarray

Array of URLs to the generated content. Empty when status is not completed.

statusstring

Status of the task: created, processing, completed, or failed.

範例回應

{
  "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 將 300+ AI 模型直接整合到您的 AI 程式碼助手中。一條命令安裝，即可用自然語言生成圖片、影片，以及與 LLM 對話。

支援的客戶端

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ 支援的客戶端

安裝

npx skills add AtlasCloudAI/atlas-cloud-skills

設定 API Key

從 Atlas Cloud 控制台取得 API Key，並將其設定為環境變數。

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

功能

安裝完成後，您可以在 AI 助手中使用自然語言存取所有 Atlas Cloud 模型。

圖片生成使用 Nano Banana 2、Z-Image 等模型生成圖片。

影片創作使用 Kling、Vidu、Veo 等從文字或圖片創建影片。

LLM 對話與 Qwen、DeepSeek 及其他大型語言模型對話。

媒體上傳上傳本機檔案用於圖片編輯和圖生影片工作流程。

MCP Server

Atlas Cloud MCP Server 透過 Model Context Protocol 將您的 IDE 與 300+ AI 模型連接。支援任何相容 MCP 的客戶端。

支援的客戶端

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ 支援的客戶端

安裝

npx -y atlascloud-mcp

設定

將以下設定新增到您的 IDE 的 MCP 設定檔中。

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

可用工具

atlas_generate_image根據文字提示生成圖片。

atlas_generate_video從文字或圖片創建影片。

atlas_chat與大型語言模型對話。

atlas_list_models瀏覽 300+ 可用 AI 模型。

atlas_quick_generate一步式內容創建，自動選擇最佳模型。

atlas_upload_media上傳本機檔案用於 API 工作流程。

了解更多

github.com/AtlasCloudAI/mcp-server

API Schema

{
  "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": {
        "properties": {
          "model": {
            "type": "string",
            "description": "Model name.",
            "default": "atlascloud/image-upscaler",
            "enum": [
              "atlascloud/image-upscaler"
            ]
          },
          "image": {
            "description": "Input image URL to upscale.",
            "type": "string",
            "x-format": "image"
          },
          "outscale": {
            "default": 1,
            "description": "Output scale multiplier. Use 2.0 for standard upscaling and 4.0 for the maximum exposed scale.",
            "maximum": 4,
            "minimum": 1,
            "type": "number",
            "x-ui-component": "slider"
          },
          "output_format": {
            "default": "jpeg",
            "description": "Output image format.",
            "enum": [
              "jpeg",
              "png",
              "webp",
              "jpg"
            ],
            "type": "string",
            "x-ui-component": "select"
          }
        },
        "required": [
          "model",
          "image"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "image",
          "outscale",
          "output_format"
        ]
      },
      "PredictionResponse": {
        "properties": {
          "created_at": {
            "description": "ISO timestamp of when the request was created.",
            "format": "date-time",
            "type": "string"
          },
          "has_nsfw_contents": {
            "description": "Array of boolean values indicating NSFW detection for each output.",
            "items": {
              "type": "boolean"
            },
            "type": "array"
          },
          "id": {
            "description": "Unique identifier for the prediction.",
            "type": "string"
          },
          "model": {
            "description": "Model ID used for the prediction.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated content. Empty when status is not completed.",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        },
        "type": "object"
      }
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ]
}

LLM 友善的提示詞範本

# atlascloud/image-upscaler

> Increase image resolution up to 4x with texture-aware enhancement for print, ecommerce, or high-dpi screens.


## 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**: `atlascloud/image-upscaler`


## 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: `"atlascloud/image-upscaler"`
  - Options: "atlascloud/image-upscaler"

- **`image`** (`string`, _required_):
  Input image URL to upscale.

- **`outscale`** (`number`, _optional_):
  Output scale multiplier. Use 2.0 for standard upscaling and 4.0 for the maximum exposed scale.
  - Default: `1`
  - Min: 1
  - Max: 4

- **`output_format`** (`string`, _optional_):
  Output image format.
  - Default: `"jpeg"`
  - Options: "jpeg", "png", "webp", "jpg"



**Required Parameters Example**:

```json
{
  "model": "atlascloud/image-upscaler",
  "image": ""
}
```


**Full Example**:

```json
{
  "model": "atlascloud/image-upscaler",
  "image": "",
  "outscale": 1,
  "output_format": "jpeg"
}
```


### Output Schema

The API returns the following output format:


- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created.

- **`has_nsfw_contents`** (`array[boolean]`, _optional_):
  Array of boolean values indicating NSFW detection for each output.

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated content. Empty when status is not completed.

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example Response**:

```json
{
  "created_at": "",
  "has_nsfw_contents": [],
  "id": "",
  "model": "",
  "outputs": [
    ""
  ],
  "status": "",
  "urls": {}
}
```


## 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": "atlascloud/image-upscaler",
  "image": "",
  "outscale": 1,
  "output_format": "jpeg"
}'

# 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/atlascloud/image-upscaler)

暫無可用範例

載入中...

Image Upscaler

Image Upscaler improves an existing image to a higher resolution while preserving the original content and composition. Provide an image URL, choose a scale, and receive an enhanced image URL.

Highlights

Image-to-image upscaling: Increase image resolution without changing the subject or layout.
Scale control: Choose an outscale value from 1.0 to 4.0.
Output format control: Generate jpeg, png, webp, or jpg outputs.
Fast sync backend: Requests route to the RealESRGAN sync backend through AtlasCloud Serverless.

Parameters

Parameter	Required	Description
`model`	Yes	Use `atlascloud/image-upscaler`.
`image`	Yes	Input image URL.
`outscale`	No	Output scale multiplier from `1.0` to `4.0`. Default: `1.0`; use `2.0` for a standard upscale test.
`output_format`	No	Output image format: `jpeg`, `png`, `webp`, or `jpg`. Default: `jpeg`.

Limits

The public API exposes the direct scale control only. Target-resolution, size, pixel-budget, base64 output, and seed fields are intentionally not exposed for this launch.

Use input images that are accessible by URL. Very large inputs may be rejected by the backend before processing.

Example Request

{
  "model": "atlascloud/image-upscaler",
  "image": "https://atlas-test-input.oss-us-west-1.aliyuncs.com/1024_square.png",
  "outscale": 2.0,
  "output_format": "png"
}

Pricing

Image Upscaler uses flat per-image billing.

Unit	Price
Per image	`$0.0100`

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Image Upscaler API

輸入

輸出

參數

程式碼範例

安裝

驗證

HTTP 標頭

提交請求

提交請求

請求主體

回應

檢查狀態

輪詢範例

狀態值

完成回應

上傳檔案

上傳範例

回應

Input Schema

範例請求主體

Output Schema

範例回應

Atlas Cloud Skills

支援的客戶端

安裝

設定 API Key

功能

MCP Server

支援的客戶端

安裝

設定

可用工具

API Schema

LLM 友善的提示詞範本

Image Upscaler

Highlights

Parameters

Limits

Example Request

Pricing

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Join our Discord community

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程式碼範例

安裝

驗證

HTTP 標頭

提交請求

提交請求

請求主體

回應

檢查狀態

輪詢範例

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完成回應

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範例回應