Aidge Resource
Try for freeWorkplace
  • LATEST ADVANCEMENTS
    • Introducing Marco-MT: Bringing Translation to the Next Level with LLM
  • GETTING STARTED
    • Quick Start
    • Account and Authentication
    • Your First API Request
    • Test Your API Requests
    • Service Level Agreement
    • FAQ
  • API REFERENCE
    • E-commerce Information Translation
      • Marco Translator
        • Marco Translator API Reference
      • Image Translation
        • Image Translation Pro Version API Reference
        • Image Translation Pro Version Result API Call Description
        • Image Translation Standard Version API Reference
    • E-commerce Image Editing
      • Image Background Removal
        • Image Background Removal API Reference
      • Image Upscaling
        • Image Upscaling API Reference
      • Image Cropping
        • Image Cropping API Reference
      • Image Elements Removal
        • Image Elements Removal API Reference
      • Image Elements Detection
        • Image Elements Detection API Reference
    • E-commerce Virtual Model
      • Virtual Model Alternation
        • Virtual Model Alternation Submit API Reference
        • Virtual Model Alternation Result Query API Reference
      • Virtual TryOn
        • Virtual Try-on Submit API Reference
        • Virtual Try-On Query API Reference
        • General Model Library Reference
      • Hands&Feet Repair
        • Hands&Feet Repair Submit API Reference
        • Hands&Feet Repair Query API Reference
    • Editor Documentation
      • AI Model Editor
      • AI Image Editor
        • Image Workbench
        • Background Removal
        • Elements Removal
        • Image Translation
Powered by GitBook
On this page
  • Product Introduction
  • Use cases:
  • Product Introduction
  • Pricing
  • Quick Start

Was this helpful?

  1. API REFERENCE
  2. E-commerce Virtual Model

Hands&Feet Repair

Product Introduction

Provide AI-based restoration capabilities to address issues of limb distortions in model image generation, ensuring flawless images.

Use cases:

  • Further refinement of virtual try-on.

  • Further refinement of model alternation.

Product Introduction

  • Automatically identify hand and foot areas to achieve one-click repair.

  • Achieve seamless repair without altering the original clothing style.

Before

After

Pricing

To use the API, you are required to choose and purchase an API resource pack from us on a subscription basis. Each resource pack is valid for one calendar year upon successful purchase, and enables you to access the API up to the number of requests specified in the pack. No refunds can be provided.

  • If you need to purchase more QPS due to business requirements, please click here to contact us.

  • Resource packs cannot be used across different products. For example, if you need to use both product text translation and image translation, you must purchase separate resource packs for each.

The prices are as follows:

Capacity(images)

Unit Price(USD)

Maximum QPS

<=1,000

¥0.07 /image

1

1001-5000

¥0.05 /image

1

above 5000

¥0.03/image

1

Quick Start

1. Description of the API Stringing Process Involved

Step 1: Initiate Hand-foot Repair Task

  • Input Parameters: Image and Repair Information

  • API Call: Initiate the task through the Hand-foot Repair API

  • Output Parameters: Task ID

Step 2: Query Generated Results

  • Input Parameters: Task ID

  • API Call: Retrieve the repair results using the Hand-foot Repair Results Query API

  • Output Parameters:Hand-foot Repair Results

  1. Sample Request

IopClient client = new IopClient(url, appkey, appSecret);
IopRequest request = new IopRequest();
request.setApiName("/ai/hand-foot/repair");
request.addApiParameter("paramJson", "{\"area\":\"hand\",\"imageUrl\":\"http://aibz-aigc-record.oss-ap-southeast-1.aliyuncs.com/skin_repaint_result%2Faa0d0023ea46464ebff4cda31ffcc312_20250124144712.png?OSSAccessKeyId\\u003dLTAI5tAGoBnm5eYsnZ5E1zMr\\u0026Expires\\u003d2737701232\\u0026Signature\\u003dkFfey2VgD%2FCxUUqHgdMJwdQyeFQ%3D\",\"imgNum\":\"1\"}");
IopResponse response = client.execute(request);
System.out.println(response.getBody());
Thread.sleep(10);
  1. Sample Response

{
  "code": "0",
  "data": "{     \"usage\": 0,     \"result\": {       \"taskId\": \"31961aa1-763f-4b25-946d-c181be9bec12\"     }   }",
  "resCode": "200",
  "resMessage": "success",
  "request_id": "0ba2887315178178017221014"
}

PreviousGeneral Model Library ReferenceNextHands&Feet Repair Submit API Reference

Last updated 2 months ago

Was this helpful?