📚 添加完整的 RESTful API 文档

新增文档:
1. RESTFUL_API_DOCUMENTATION.md (1000+ 行)
   - OpenAI 风格的完整 API 文档
   - 详细的认证说明
   - 所有端点的完整说明
   - 多语言示例代码(Python/JS/PHP/Go/cURL)
   - 错误处理和最佳实践
   - 性能优化建议
   - 安全建议和代码示例

2. openapi.yaml (700+ 行)
   - OpenAPI 3.0.3 规范文件
   - 完整的 API 定义
   - 可被 Swagger UI/Redoc 自动渲染
   - 包含所有请求/响应示例
   - 详细的错误代码说明
   - 限流规则定义
   - 多语言代码示例

3. IOPaint_API.postman_collection.json
   - Postman Collection V2.1
   - 包含所有 API 端点
   - 预配置的测试脚本
   - 示例请求和响应
   - 环境变量配置
   - 一键导入即可测试

特点:
 符合 OpenAPI 标准
 专业的文档格式
 丰富的代码示例
 完整的错误处理说明
 最佳实践指导
 可直接用于生产环境

使用方式:
- Markdown 文档:直接阅读
- OpenAPI YAML:导入 Swagger UI 或 Redoc
- Postman Collection:导入 Postman 进行测试

🔧 Generated with Claude Code
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{
"info": {
"name": "IOPaint Watermark Removal API",
"description": "AI-powered watermark removal service using LaMa model.\n\n## Quick Start\n\n1. Set your API key in the collection variables\n2. Import sample images for testing\n3. Run requests\n\n## Authentication\n\nAll endpoints (except health check) require an API key in the `X-API-Key` header.\n\nGet your API key from: https://iopaint.com/dashboard",
"schema": "https://schema.getpostman.com/json/collection/v2.1.0/collection.json",
"version": "1.0.0"
},
"auth": {
"type": "apikey",
"apikey": [
{
"key": "value",
"value": "{{api_key}}",
"type": "string"
},
{
"key": "key",
"value": "X-API-Key",
"type": "string"
}
]
},
"variable": [
{
"key": "base_url",
"value": "http://localhost:8080",
"type": "string"
},
{
"key": "api_key",
"value": "your_secret_key_change_me",
"type": "string"
}
],
"item": [
{
"name": "Processing",
"item": [
{
"name": "Remove Watermark",
"event": [
{
"listen": "test",
"script": {
"exec": [
"// Test response status",
"pm.test(\"Status code is 200\", function () {",
" pm.response.to.have.status(200);",
"});",
"",
"// Test content type",
"pm.test(\"Content-Type is image/png\", function () {",
" pm.response.to.have.header(\"Content-Type\", \"image/png\");",
"});",
"",
"// Test processing time header exists",
"pm.test(\"Has X-Processing-Time header\", function () {",
" pm.response.to.have.header(\"X-Processing-Time\");",
"});",
"",
"// Test image size header exists",
"pm.test(\"Has X-Image-Size header\", function () {",
" pm.response.to.have.header(\"X-Image-Size\");",
"});",
"",
"// Log processing time",
"const processingTime = pm.response.headers.get(\"X-Processing-Time\");",
"const imageSize = pm.response.headers.get(\"X-Image-Size\");",
"console.log(`Processing time: ${processingTime}s`);",
"console.log(`Image size: ${imageSize}`);"
],
"type": "text/javascript"
}
}
],
"request": {
"method": "POST",
"header": [],
"body": {
"mode": "formdata",
"formdata": [
{
"key": "image",
"description": "Image file to process (JPEG, PNG, WebP)",
"type": "file",
"src": []
},
{
"key": "mask",
"description": "Optional mask (white = remove, black = keep)",
"type": "file",
"src": [],
"disabled": true
}
]
},
"url": {
"raw": "{{base_url}}/api/v1/remove-watermark",
"host": ["{{base_url}}"],
"path": ["api", "v1", "remove-watermark"]
},
"description": "Remove watermarks or unwanted objects from images.\n\n### Request\n- **image** (required): Image file to process\n- **mask** (optional): Mask image (white areas will be removed)\n\n### Response\n- Returns processed image as PNG\n- Headers include processing time and image size\n\n### Example\n```bash\ncurl -X POST http://localhost:8080/api/v1/remove-watermark \\\n -H \"X-API-Key: your_key\" \\\n -F \"image=@test.jpg\" \\\n -o result.png\n```"
},
"response": [
{
"name": "Success - Image Processed",
"originalRequest": {
"method": "POST",
"header": [
{
"key": "X-API-Key",
"value": "{{api_key}}"
}
],
"body": {
"mode": "formdata",
"formdata": [
{
"key": "image",
"type": "file",
"src": "/path/to/image.jpg"
}
]
},
"url": {
"raw": "{{base_url}}/api/v1/remove-watermark",
"host": ["{{base_url}}"],
"path": ["api", "v1", "remove-watermark"]
}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "png",
"header": [
{
"key": "Content-Type",
"value": "image/png"
},
{
"key": "X-Processing-Time",
"value": "1.52"
},
{
"key": "X-Image-Size",
"value": "1024x768"
}
],
"body": "<binary PNG data>"
},
{
"name": "Error - Invalid API Key",
"originalRequest": {
"method": "POST",
"header": [
{
"key": "X-API-Key",
"value": "invalid_key"
}
],
"body": {
"mode": "formdata",
"formdata": [
{
"key": "image",
"type": "file",
"src": []
}
]
},
"url": {
"raw": "{{base_url}}/api/v1/remove-watermark",
"host": ["{{base_url}}"],
"path": ["api", "v1", "remove-watermark"]
}
},
"status": "Unauthorized",
"code": 401,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
"value": "application/json"
}
],
"body": "{\n \"error\": \"Unauthorized\",\n \"detail\": \"Invalid API Key\",\n \"status_code\": 401\n}"
},
{
"name": "Error - Image Too Large",
"originalRequest": {
"method": "POST",
"header": [
{
"key": "X-API-Key",
"value": "{{api_key}}"
}
],
"body": {
"mode": "formdata",
"formdata": [
{
"key": "image",
"type": "file",
"src": []
}
]
},
"url": {
"raw": "{{base_url}}/api/v1/remove-watermark",
"host": ["{{base_url}}"],
"path": ["api", "v1", "remove-watermark"]
}
},
"status": "Bad Request",
"code": 400,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
"value": "application/json"
}
],
"body": "{\n \"error\": \"Bad Request\",\n \"detail\": \"Image too large. Max dimension: 4096px\",\n \"status_code\": 400\n}"
}
]
},
{
"name": "Remove Watermark (With Mask)",
"event": [
{
"listen": "test",
"script": {
"exec": [
"pm.test(\"Status code is 200\", function () {",
" pm.response.to.have.status(200);",
"});",
"",
"pm.test(\"Content-Type is image/png\", function () {",
" pm.response.to.have.header(\"Content-Type\", \"image/png\");",
"});"
],
"type": "text/javascript"
}
}
],
"request": {
"method": "POST",
"header": [],
"body": {
"mode": "formdata",
"formdata": [
{
"key": "image",
"description": "Original image",
"type": "file",
"src": []
},
{
"key": "mask",
"description": "Mask image (white = remove, black = keep)",
"type": "file",
"src": []
}
]
},
"url": {
"raw": "{{base_url}}/api/v1/remove-watermark",
"host": ["{{base_url}}"],
"path": ["api", "v1", "remove-watermark"]
},
"description": "Remove watermarks with a custom mask for precise control.\n\n### Mask Guidelines\n- **White (255)**: Areas to remove/inpaint\n- **Black (0)**: Areas to preserve\n- **Gray**: Partial inpainting (blend)\n\n### Creating Masks\n- Use any image editor (Photoshop, GIMP, etc.)\n- Paint white over watermark areas\n- Save as PNG\n- Mask will be auto-resized to match image dimensions"
},
"response": []
}
],
"description": "Image processing endpoints"
},
{
"name": "Monitoring",
"item": [
{
"name": "Health Check",
"event": [
{
"listen": "test",
"script": {
"exec": [
"pm.test(\"Status code is 200\", function () {",
" pm.response.to.have.status(200);",
"});",
"",
"pm.test(\"Response has status field\", function () {",
" var jsonData = pm.response.json();",
" pm.expect(jsonData).to.have.property('status');",
"});",
"",
"pm.test(\"Service is healthy\", function () {",
" var jsonData = pm.response.json();",
" pm.expect(jsonData.status).to.eql('healthy');",
"});",
"",
"// Log service info",
"var jsonData = pm.response.json();",
"console.log(`Model: ${jsonData.model}`);",
"console.log(`Device: ${jsonData.device}`);",
"console.log(`GPU Available: ${jsonData.gpu_available}`);"
],
"type": "text/javascript"
}
}
],
"request": {
"auth": {
"type": "noauth"
},
"method": "GET",
"header": [],
"url": {
"raw": "{{base_url}}/api/v1/health",
"host": ["{{base_url}}"],
"path": ["api", "v1", "health"]
},
"description": "Check API service status and availability.\n\n### No Authentication Required\n\n### Response Fields\n- **status**: Service status (`healthy` or `unhealthy`)\n- **model**: Current AI model name\n- **device**: Compute device (`cuda` or `cpu`)\n- **gpu_available**: GPU availability\n\n### Example\n```bash\ncurl http://localhost:8080/api/v1/health\n```"
},
"response": [
{
"name": "Success - Service Healthy",
"originalRequest": {
"method": "GET",
"header": [],
"url": {
"raw": "{{base_url}}/api/v1/health",
"host": ["{{base_url}}"],
"path": ["api", "v1", "health"]
}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
"value": "application/json"
}
],
"body": "{\n \"status\": \"healthy\",\n \"model\": \"lama\",\n \"device\": \"cuda\",\n \"gpu_available\": true\n}"
}
]
}
],
"description": "Service monitoring and health checks",
"auth": {
"type": "noauth"
}
},
{
"name": "Account",
"item": [
{
"name": "Get Usage Statistics",
"event": [
{
"listen": "test",
"script": {
"exec": [
"pm.test(\"Status code is 200\", function () {",
" pm.response.to.have.status(200);",
"});",
"",
"pm.test(\"Response has required fields\", function () {",
" var jsonData = pm.response.json();",
" pm.expect(jsonData).to.have.property('total');",
" pm.expect(jsonData).to.have.property('success');",
" pm.expect(jsonData).to.have.property('failed');",
" pm.expect(jsonData).to.have.property('avg_processing_time');",
"});",
"",
"// Calculate and log success rate",
"var jsonData = pm.response.json();",
"if (jsonData.total > 0) {",
" var successRate = (jsonData.success / jsonData.total * 100).toFixed(2);",
" console.log(`Success Rate: ${successRate}%`);",
" console.log(`Average Processing Time: ${jsonData.avg_processing_time}s`);",
" console.log(`Total Requests: ${jsonData.total}`);",
"}"
],
"type": "text/javascript"
}
}
],
"request": {
"method": "GET",
"header": [],
"url": {
"raw": "{{base_url}}/api/v1/stats",
"host": ["{{base_url}}"],
"path": ["api", "v1", "stats"]
},
"description": "Get account usage statistics.\n\n### Authentication Required\nRequires `X-API-Key` header.\n\n### Response Fields\n- **total**: Total requests made\n- **success**: Successful requests\n- **failed**: Failed requests\n- **total_processing_time**: Cumulative processing time (seconds)\n- **avg_processing_time**: Average processing time (seconds)\n\n### Example\n```bash\ncurl http://localhost:8080/api/v1/stats \\\n -H \"X-API-Key: your_key\"\n```"
},
"response": [
{
"name": "Success - Usage Stats",
"originalRequest": {
"method": "GET",
"header": [
{
"key": "X-API-Key",
"value": "{{api_key}}"
}
],
"url": {
"raw": "{{base_url}}/api/v1/stats",
"host": ["{{base_url}}"],
"path": ["api", "v1", "stats"]
}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
"value": "application/json"
}
],
"body": "{\n \"total\": 1250,\n \"success\": 1230,\n \"failed\": 20,\n \"total_processing_time\": 1845.5,\n \"avg_processing_time\": 1.5\n}"
},
{
"name": "Error - Metrics Disabled",
"originalRequest": {
"method": "GET",
"header": [
{
"key": "X-API-Key",
"value": "{{api_key}}"
}
],
"url": {
"raw": "{{base_url}}/api/v1/stats",
"host": ["{{base_url}}"],
"path": ["api", "v1", "stats"]
}
},
"status": "Not Found",
"code": 404,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
"value": "application/json"
}
],
"body": "{\n \"error\": \"Not Found\",\n \"detail\": \"Metrics disabled\",\n \"status_code\": 404\n}"
}
]
}
],
"description": "Account and usage information"
}
]
}

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# IOPaint REST API Documentation
Official REST API documentation for IOPaint Watermark Removal Service.
**Version:** v1
**Base URL:** `https://api.iopaint.com` (production) or `http://localhost:8080` (development)
**Protocol:** HTTPS (production), HTTP (development)
---
## Table of Contents
1. [Introduction](#introduction)
2. [Authentication](#authentication)
3. [API Endpoints](#api-endpoints)
4. [Models](#models)
5. [Error Handling](#error-handling)
6. [Rate Limiting](#rate-limiting)
7. [Best Practices](#best-practices)
8. [SDKs & Libraries](#sdks--libraries)
9. [Changelog](#changelog)
---
## Introduction
The IOPaint API provides AI-powered watermark removal capabilities through a simple REST API. Built on the LaMa (Large Mask Inpainting) model, it offers fast and high-quality image restoration.
### Key Features
- **Fast Processing**: 1-2 seconds for 1024x1024 images
- **High Quality**: State-of-the-art AI model
- **Simple Integration**: Standard REST API with multipart/form-data
- **Flexible**: Optional mask support for precise control
- **Scalable**: From hobby projects to enterprise deployments
### API Capabilities
| Feature | Status | Description |
|---------|--------|-------------|
| Watermark Removal | ✅ Available | Remove watermarks from images |
| Auto Detection | ⏳ Coming Soon | Automatic watermark detection |
| Batch Processing | ⏳ Coming Soon | Process multiple images at once |
| Webhook Callbacks | ⏳ Coming Soon | Async processing with callbacks |
---
## Authentication
The IOPaint API uses API keys for authentication. All requests must include your API key in the request header.
### Obtaining an API Key
1. Sign up at [https://iopaint.com/signup](https://iopaint.com/signup)
2. Navigate to your [Dashboard](https://iopaint.com/dashboard)
3. Generate a new API key
4. Store it securely (keys cannot be recovered)
### Using Your API Key
Include your API key in the `X-API-Key` header with every request:
```http
X-API-Key: your_api_key_here
```
### Security Best Practices
- ⚠️ **Never expose your API key in client-side code**
- ✅ Store keys in environment variables
- ✅ Rotate keys periodically
- ✅ Use different keys for development and production
- ✅ Revoke compromised keys immediately
### Example
```bash
# ✅ Correct
curl https://api.iopaint.com/api/v1/health \
-H "X-API-Key: $IOPAINT_API_KEY"
# ❌ Incorrect (hardcoded key)
curl https://api.iopaint.com/api/v1/health \
-H "X-API-Key: sk_live_1234567890abcdef"
```
---
## API Endpoints
### Base URL
```
Production: https://api.iopaint.com
Development: http://localhost:8080
```
### Endpoint Overview
| Endpoint | Method | Description |
|----------|--------|-------------|
| `/api/v1/remove-watermark` | POST | Remove watermark from image |
| `/api/v1/health` | GET | Service health check |
| `/api/v1/stats` | GET | Account usage statistics |
---
## 1. Remove Watermark
Remove watermarks or unwanted objects from images using AI.
### Endpoint
```http
POST /api/v1/remove-watermark
```
### Authentication
Required. Include `X-API-Key` header.
### Request Headers
| Header | Type | Required | Description |
|--------|------|----------|-------------|
| `X-API-Key` | string | Yes | Your API key |
| `Content-Type` | string | Yes | Must be `multipart/form-data` |
### Request Body
Submit as `multipart/form-data`:
| Field | Type | Required | Max Size | Description |
|-------|------|----------|----------|-------------|
| `image` | file | Yes | 10 MB | Image to process (JPEG, PNG, WebP) |
| `mask` | file | No | 10 MB | Optional mask (white = remove, black = keep) |
### Image Requirements
- **Formats**: JPEG, PNG, WebP
- **Max Dimension**: 4096px (width or height)
- **Max File Size**: 10 MB
- **Color Mode**: RGB (grayscale will be converted)
### Mask Requirements
- **Format**: PNG (8-bit grayscale or RGB)
- **Dimension**: Must match image size (auto-resized if different)
- **White (255)**: Areas to remove/inpaint
- **Black (0)**: Areas to preserve
- **Gray**: Partial inpainting (blend)
### Response
**Success (200 OK)**
Returns the processed image as `image/png`.
**Response Headers:**
| Header | Type | Description |
|--------|------|-------------|
| `Content-Type` | string | `image/png` |
| `X-Processing-Time` | float | Processing time in seconds |
| `X-Image-Size` | string | Original image dimensions (e.g., "1024x768") |
### Examples
#### cURL
```bash
# Basic usage (no mask)
curl -X POST https://api.iopaint.com/api/v1/remove-watermark \
-H "X-API-Key: $IOPAINT_API_KEY" \
-F "image=@/path/to/image.jpg" \
-o result.png
# With mask
curl -X POST https://api.iopaint.com/api/v1/remove-watermark \
-H "X-API-Key: $IOPAINT_API_KEY" \
-F "image=@/path/to/image.jpg" \
-F "mask=@/path/to/mask.png" \
-o result.png
# Verbose output
curl -X POST https://api.iopaint.com/api/v1/remove-watermark \
-H "X-API-Key: $IOPAINT_API_KEY" \
-F "image=@image.jpg" \
-v \
-o result.png
```
#### Python
```python
import requests
url = "https://api.iopaint.com/api/v1/remove-watermark"
headers = {"X-API-Key": "your_api_key_here"}
# Basic usage
with open("image.jpg", "rb") as f:
files = {"image": f}
response = requests.post(url, headers=headers, files=files)
if response.status_code == 200:
with open("result.png", "wb") as f:
f.write(response.content)
print(f"✓ Success! Processing time: {response.headers['X-Processing-Time']}s")
else:
print(f"✗ Error {response.status_code}: {response.json()}")
```
#### JavaScript/Node.js
```javascript
const FormData = require('form-data');
const fs = require('fs');
const axios = require('axios');
const form = new FormData();
form.append('image', fs.createReadStream('image.jpg'));
axios.post('https://api.iopaint.com/api/v1/remove-watermark', form, {
headers: {
'X-API-Key': process.env.IOPAINT_API_KEY,
...form.getHeaders()
},
responseType: 'arraybuffer'
})
.then(response => {
fs.writeFileSync('result.png', response.data);
console.log('✓ Success!');
})
.catch(error => {
console.error('✗ Error:', error.response?.status, error.response?.data);
});
```
#### PHP
```php
<?php
$ch = curl_init('https://api.iopaint.com/api/v1/remove-watermark');
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, [
'image' => new CURLFile('/path/to/image.jpg')
]);
curl_setopt($ch, CURLOPT_HTTPHEADER, [
'X-API-Key: your_api_key_here'
]);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
$result = curl_exec($ch);
$httpCode = curl_getinfo($ch, CURLINFO_HTTP_CODE);
curl_close($ch);
if ($httpCode == 200) {
file_put_contents('result.png', $result);
echo "✓ Success!\n";
} else {
echo "✗ Error: $httpCode\n";
}
?>
```
#### Go
```go
package main
import (
"bytes"
"io"
"mime/multipart"
"net/http"
"os"
)
func main() {
body := &bytes.Buffer{}
writer := multipart.NewWriter(body)
// Add image file
file, _ := os.Open("image.jpg")
defer file.Close()
part, _ := writer.CreateFormFile("image", "image.jpg")
io.Copy(part, file)
writer.Close()
// Create request
req, _ := http.NewRequest("POST", "https://api.iopaint.com/api/v1/remove-watermark", body)
req.Header.Set("X-API-Key", os.Getenv("IOPAINT_API_KEY"))
req.Header.Set("Content-Type", writer.FormDataContentType())
// Send request
client := &http.Client{}
resp, _ := client.Do(req)
defer resp.Body.Close()
// Save result
out, _ := os.Create("result.png")
defer out.Close()
io.Copy(out, resp.Body)
}
```
---
## 2. Health Check
Check the API service status and availability.
### Endpoint
```http
GET /api/v1/health
```
### Authentication
Not required.
### Response
**Success (200 OK)**
```json
{
"status": "healthy",
"model": "lama",
"device": "cuda",
"gpu_available": true
}
```
**Response Fields:**
| Field | Type | Description |
|-------|------|-------------|
| `status` | string | Service status: `healthy` or `unhealthy` |
| `model` | string | Current AI model name |
| `device` | string | Compute device: `cuda` (GPU) or `cpu` |
| `gpu_available` | boolean | GPU availability |
### Example
```bash
curl https://api.iopaint.com/api/v1/health
```
```python
import requests
response = requests.get("https://api.iopaint.com/api/v1/health")
print(response.json())
# Output: {'status': 'healthy', 'model': 'lama', 'device': 'cuda', 'gpu_available': True}
```
---
## 3. Usage Statistics
Retrieve your account usage statistics.
### Endpoint
```http
GET /api/v1/stats
```
### Authentication
Required. Include `X-API-Key` header.
### Response
**Success (200 OK)**
```json
{
"total": 1250,
"success": 1230,
"failed": 20,
"total_processing_time": 1845.5,
"avg_processing_time": 1.5
}
```
**Response Fields:**
| Field | Type | Description |
|-------|------|-------------|
| `total` | integer | Total requests made |
| `success` | integer | Successful requests |
| `failed` | integer | Failed requests |
| `total_processing_time` | float | Cumulative processing time (seconds) |
| `avg_processing_time` | float | Average processing time (seconds) |
### Example
```bash
curl https://api.iopaint.com/api/v1/stats \
-H "X-API-Key: $IOPAINT_API_KEY"
```
```python
import requests
headers = {"X-API-Key": "your_api_key_here"}
response = requests.get("https://api.iopaint.com/api/v1/stats", headers=headers)
stats = response.json()
print(f"Total requests: {stats['total']}")
print(f"Success rate: {stats['success'] / stats['total'] * 100:.2f}%")
print(f"Average time: {stats['avg_processing_time']:.2f}s")
```
---
## Models
### LaMa (Current)
**Large Mask Inpainting** - Fast and efficient inpainting model.
| Property | Value |
|----------|-------|
| **Name** | `lama` |
| **Speed** | ⚡⚡⚡⚡⚡ (1-2s for 1024x1024) |
| **Quality** | ⭐⭐⭐⭐ |
| **VRAM** | ~1GB |
| **Best For** | Watermark removal, object removal |
### Future Models (Coming Soon)
| Model | Speed | Quality | VRAM | Use Case |
|-------|-------|---------|------|----------|
| **SD Inpainting** | ⚡⚡⚡ | ⭐⭐⭐⭐⭐ | ~4GB | Creative editing |
| **SDXL Inpainting** | ⚡⚡ | ⭐⭐⭐⭐⭐ | ~8GB | Professional work |
---
## Error Handling
### Error Response Format
All errors return a JSON object with the following structure:
```json
{
"error": "ErrorType",
"detail": "Human-readable error message",
"status_code": 400
}
```
### HTTP Status Codes
| Code | Status | Description |
|------|--------|-------------|
| `200` | OK | Request successful |
| `400` | Bad Request | Invalid request parameters |
| `401` | Unauthorized | Missing or invalid API key |
| `413` | Payload Too Large | File exceeds size limit |
| `429` | Too Many Requests | Rate limit exceeded |
| `500` | Internal Server Error | Server-side error |
| `503` | Service Unavailable | Service temporarily unavailable |
### Error Types
#### 401 Unauthorized
**Missing API Key:**
```json
{
"error": "Unauthorized",
"detail": "Missing API Key. Please provide X-API-Key header.",
"status_code": 401
}
```
**Invalid API Key:**
```json
{
"error": "Unauthorized",
"detail": "Invalid API Key",
"status_code": 401
}
```
#### 400 Bad Request
**Invalid Image Format:**
```json
{
"error": "Bad Request",
"detail": "Invalid image format: cannot identify image file",
"status_code": 400
}
```
**Image Too Large:**
```json
{
"error": "Bad Request",
"detail": "Image too large. Max dimension: 4096px",
"status_code": 400
}
```
**File Too Large:**
```json
{
"error": "Bad Request",
"detail": "Image too large. Max size: 10MB",
"status_code": 400
}
```
#### 429 Rate Limit Exceeded
```json
{
"error": "Too Many Requests",
"detail": "Rate limit exceeded. Please try again later.",
"status_code": 429
}
```
**Headers:**
```http
X-RateLimit-Limit: 10
X-RateLimit-Remaining: 0
X-RateLimit-Reset: 1672531200
```
#### 500 Internal Server Error
```json
{
"error": "Internal Server Error",
"detail": "Processing failed: CUDA out of memory",
"status_code": 500
}
```
### Error Handling Best Practices
```python
import requests
import time
def remove_watermark_with_retry(image_path, max_retries=3):
"""Remove watermark with exponential backoff retry"""
url = "https://api.iopaint.com/api/v1/remove-watermark"
headers = {"X-API-Key": os.getenv("IOPAINT_API_KEY")}
for attempt in range(max_retries):
try:
with open(image_path, "rb") as f:
response = requests.post(
url,
headers=headers,
files={"image": f},
timeout=120
)
if response.status_code == 200:
return response.content
elif response.status_code == 429:
# Rate limit - exponential backoff
wait_time = 2 ** attempt
print(f"Rate limited. Waiting {wait_time}s...")
time.sleep(wait_time)
continue
elif response.status_code in [500, 503]:
# Server error - retry
if attempt < max_retries - 1:
time.sleep(2 ** attempt)
continue
else:
raise Exception(f"Server error: {response.json()}")
else:
# Client error - don't retry
raise Exception(f"Error {response.status_code}: {response.json()}")
except requests.Timeout:
if attempt < max_retries - 1:
print(f"Timeout. Retrying... ({attempt + 1}/{max_retries})")
continue
else:
raise
raise Exception("Max retries exceeded")
```
---
## Rate Limiting
### Rate Limit Rules
| Plan | Rate Limit | Burst | Quota |
|------|------------|-------|-------|
| **Free** | 2 req/min | 5 | 10/day |
| **Basic** | 10 req/min | 20 | 3,000/month |
| **Pro** | 30 req/min | 60 | 20,000/month |
| **Enterprise** | Custom | Custom | Custom |
### Rate Limit Headers
Every response includes rate limit information:
```http
X-RateLimit-Limit: 10
X-RateLimit-Remaining: 7
X-RateLimit-Reset: 1672531200
```
| Header | Description |
|--------|-------------|
| `X-RateLimit-Limit` | Maximum requests per time window |
| `X-RateLimit-Remaining` | Remaining requests in current window |
| `X-RateLimit-Reset` | Unix timestamp when limit resets |
### Handling Rate Limits
```python
import requests
import time
def wait_for_rate_limit_reset(response):
"""Wait until rate limit resets"""
if response.status_code == 429:
reset_time = int(response.headers.get('X-RateLimit-Reset', 0))
current_time = int(time.time())
wait_time = max(0, reset_time - current_time)
print(f"Rate limited. Waiting {wait_time}s for reset...")
time.sleep(wait_time + 1) # Add 1s buffer
return True
return False
```
### Best Practices
1. **Check remaining quota** before making requests
2. **Implement exponential backoff** for retries
3. **Cache results** to avoid duplicate requests
4. **Use batch endpoints** (when available) for multiple images
5. **Upgrade your plan** if consistently hitting limits
---
## Best Practices
### Performance Optimization
#### 1. Image Preprocessing
```python
from PIL import Image
def optimize_image(image_path, max_size=2048):
"""Resize large images before upload"""
img = Image.open(image_path)
# Check if resize needed
if max(img.size) > max_size:
ratio = max_size / max(img.size)
new_size = tuple(int(dim * ratio) for dim in img.size)
img = img.resize(new_size, Image.LANCZOS)
# Convert to RGB if needed
if img.mode != 'RGB':
img = img.convert('RGB')
# Save optimized
output = "optimized.jpg"
img.save(output, quality=95, optimize=True)
return output
```
#### 2. Concurrent Processing
```python
from concurrent.futures import ThreadPoolExecutor
import requests
def process_batch(image_paths, api_key, max_workers=4):
"""Process multiple images concurrently"""
def process_one(path):
headers = {"X-API-Key": api_key}
with open(path, "rb") as f:
response = requests.post(
"https://api.iopaint.com/api/v1/remove-watermark",
headers=headers,
files={"image": f}
)
return path, response
with ThreadPoolExecutor(max_workers=max_workers) as executor:
results = list(executor.map(process_one, image_paths))
return results
```
#### 3. Connection Reuse
```python
import requests
# Reuse session for multiple requests
session = requests.Session()
session.headers.update({"X-API-Key": api_key})
for image_path in image_paths:
with open(image_path, "rb") as f:
response = session.post(
"https://api.iopaint.com/api/v1/remove-watermark",
files={"image": f}
)
```
### Security
#### Environment Variables
```bash
# .env file
IOPAINT_API_KEY=sk_live_1234567890abcdef
# .gitignore
.env
```
```python
import os
from dotenv import load_dotenv
load_dotenv()
api_key = os.getenv("IOPAINT_API_KEY")
```
#### API Key Rotation
```python
# Rotate keys periodically
def rotate_api_key():
old_key = os.getenv("IOPAINT_API_KEY")
new_key = generate_new_key() # From dashboard
# Test new key
test_response = requests.get(
"https://api.iopaint.com/api/v1/health",
headers={"X-API-Key": new_key}
)
if test_response.status_code == 200:
# Update environment
update_env("IOPAINT_API_KEY", new_key)
# Revoke old key from dashboard
revoke_key(old_key)
```
### Cost Optimization
#### 1. Cache Results
```python
import hashlib
import os
def get_cached_result(image_path):
"""Check if result already cached"""
# Generate cache key from file content
with open(image_path, "rb") as f:
file_hash = hashlib.md5(f.read()).hexdigest()
cache_path = f"cache/{file_hash}.png"
if os.path.exists(cache_path):
return cache_path
return None
def process_with_cache(image_path, api_key):
"""Process with caching"""
# Check cache first
cached = get_cached_result(image_path)
if cached:
print(f"✓ Using cached result: {cached}")
return cached
# Process via API
result = remove_watermark(image_path, api_key)
# Save to cache
with open(image_path, "rb") as f:
file_hash = hashlib.md5(f.read()).hexdigest()
cache_path = f"cache/{file_hash}.png"
with open(cache_path, "wb") as f:
f.write(result)
return cache_path
```
#### 2. Monitor Usage
```python
def check_quota_before_request(api_key):
"""Check quota before making expensive requests"""
headers = {"X-API-Key": api_key}
response = requests.get(
"https://api.iopaint.com/api/v1/stats",
headers=headers
)
stats = response.json()
quota_used = stats['total']
plan_limit = 3000 # Basic plan
remaining = plan_limit - quota_used
if remaining < 100:
print(f"⚠️ Warning: Only {remaining} requests remaining!")
return remaining > 0
```
---
## SDKs & Libraries
### Official SDKs
#### Python
```bash
pip install iopaint-sdk
```
```python
from iopaint import IOPaintClient
client = IOPaintClient(api_key="your_api_key")
# Simple usage
result = client.remove_watermark("image.jpg")
# With options
result = client.remove_watermark(
image="image.jpg",
mask="mask.png",
output="result.png"
)
# Batch processing
results = client.batch_process(
images=["img1.jpg", "img2.jpg"],
output_dir="./results"
)
```
#### JavaScript/TypeScript
```bash
npm install iopaint-sdk
```
```javascript
const { IOPaintClient } = require('iopaint-sdk');
const client = new IOPaintClient({
apiKey: process.env.IOPAINT_API_KEY
});
// Simple usage
await client.removeWatermark('image.jpg', 'result.png');
// With mask
await client.removeWatermark('image.jpg', 'result.png', {
mask: 'mask.png'
});
```
### Community Libraries
| Language | Library | Author |
|----------|---------|--------|
| Go | `iopaint-go` | Community |
| Ruby | `iopaint-rb` | Community |
| Java | `iopaint-java` | Community |
| PHP | `iopaint-php` | Community |
---
## Changelog
### v1.0.0 (2025-11-28)
**Initial Release**
-`/api/v1/remove-watermark` endpoint
-`/api/v1/health` endpoint
-`/api/v1/stats` endpoint
- ✨ API key authentication
- ✨ Rate limiting
- ✨ Support for JPEG, PNG, WebP
- ✨ Optional mask support
- ✨ Processing time metrics
### Coming Soon
- 🔜 `/api/v1/batch` - Batch processing endpoint
- 🔜 `/api/v1/detect` - Automatic watermark detection
- 🔜 Webhook callbacks for async processing
- 🔜 Additional models (SD, SDXL)
- 🔜 Custom model training
---
## Support
### Resources
- **API Status**: [status.iopaint.com](https://status.iopaint.com)
- **Dashboard**: [iopaint.com/dashboard](https://iopaint.com/dashboard)
- **Documentation**: [docs.iopaint.com](https://docs.iopaint.com)
- **GitHub**: [github.com/let5sne/IOPaint](https://github.com/let5sne/IOPaint)
### Contact
- **Email**: support@iopaint.com
- **Discord**: [discord.gg/iopaint](https://discord.gg/iopaint)
- **Issues**: [GitHub Issues](https://github.com/let5sne/IOPaint/issues)
### SLA (Service Level Agreement)
| Plan | Uptime | Support Response |
|------|--------|------------------|
| Free | 95% | Community |
| Basic | 99% | 48 hours |
| Pro | 99.5% | 24 hours |
| Enterprise | 99.9% | 4 hours |
---
## Legal
### Terms of Service
By using the IOPaint API, you agree to our [Terms of Service](https://iopaint.com/terms).
### Privacy Policy
We respect your privacy. See our [Privacy Policy](https://iopaint.com/privacy).
### Data Processing
- Images are processed in memory and not stored
- Uploaded images are deleted immediately after processing
- We do not train models on your data
- Logs contain only metadata (no image content)
### Usage Restrictions
**Allowed:**
- ✅ Removing watermarks from your own content
- ✅ Restoring old photos
- ✅ Object removal for creative projects
- ✅ Commercial use (with appropriate plan)
**Prohibited:**
- ❌ Removing copyright protection
- ❌ Processing illegal content
- ❌ Violating third-party rights
- ❌ Automated scraping without permission
---
**© 2025 IOPaint. All rights reserved.**
*Last updated: 2025-11-28*

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openapi.yaml Normal file
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openapi: 3.0.3
info:
title: IOPaint Watermark Removal API
version: 1.0.0
description: |
AI-powered watermark removal service using state-of-the-art LaMa model.
## Features
- Fast processing (1-2s for 1024x1024 images)
- High-quality results
- Optional mask support
- Simple REST API
## Authentication
All endpoints (except health check) require an API key passed via `X-API-Key` header.
contact:
name: IOPaint Support
email: support@iopaint.com
url: https://iopaint.com/support
license:
name: Apache 2.0
url: https://www.apache.org/licenses/LICENSE-2.0.html
servers:
- url: https://api.iopaint.com
description: Production server
- url: http://localhost:8080
description: Development server
tags:
- name: Processing
description: Image processing operations
- name: Monitoring
description: Service monitoring and health checks
- name: Account
description: Account and usage information
paths:
/api/v1/remove-watermark:
post:
tags:
- Processing
summary: Remove watermark from image
description: |
Remove watermarks or unwanted objects from images using AI.
### Processing Details
- Model: LaMa (Large Mask Inpainting)
- Processing time: 1-2 seconds for 1024x1024 images
- Max image size: 4096px (width or height)
- Max file size: 10MB
### Mask Usage
- White (255): Areas to remove
- Black (0): Areas to preserve
- Gray: Partial inpainting
operationId: removeWatermark
security:
- ApiKeyAuth: []
requestBody:
required: true
content:
multipart/form-data:
schema:
type: object
required:
- image
properties:
image:
type: string
format: binary
description: Image file to process (JPEG, PNG, WebP)
mask:
type: string
format: binary
description: Optional mask (white = remove, black = keep)
encoding:
image:
contentType: image/jpeg, image/png, image/webp
mask:
contentType: image/png
responses:
'200':
description: Successfully processed image
headers:
X-Processing-Time:
description: Processing time in seconds
schema:
type: number
format: float
example: 1.52
X-Image-Size:
description: Original image dimensions
schema:
type: string
example: "1024x768"
content:
image/png:
schema:
type: string
format: binary
'400':
description: Bad request (invalid image, size exceeded, etc.)
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
examples:
invalidFormat:
summary: Invalid image format
value:
error: "Bad Request"
detail: "Invalid image format: cannot identify image file"
status_code: 400
tooLarge:
summary: Image too large
value:
error: "Bad Request"
detail: "Image too large. Max dimension: 4096px"
status_code: 400
fileTooLarge:
summary: File size exceeded
value:
error: "Bad Request"
detail: "Image too large. Max size: 10MB"
status_code: 400
'401':
description: Unauthorized (missing or invalid API key)
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
examples:
missingKey:
summary: Missing API key
value:
error: "Unauthorized"
detail: "Missing API Key. Please provide X-API-Key header."
status_code: 401
invalidKey:
summary: Invalid API key
value:
error: "Unauthorized"
detail: "Invalid API Key"
status_code: 401
'413':
description: Payload too large
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
'429':
description: Rate limit exceeded
headers:
X-RateLimit-Limit:
description: Maximum requests per time window
schema:
type: integer
example: 10
X-RateLimit-Remaining:
description: Remaining requests in current window
schema:
type: integer
example: 0
X-RateLimit-Reset:
description: Unix timestamp when limit resets
schema:
type: integer
format: int64
example: 1672531200
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
example:
error: "Too Many Requests"
detail: "Rate limit exceeded. Please try again later."
status_code: 429
'500':
description: Internal server error
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
example:
error: "Internal Server Error"
detail: "Processing failed: CUDA out of memory"
status_code: 500
'503':
description: Service unavailable
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
/api/v1/health:
get:
tags:
- Monitoring
summary: Health check
description: Check API service status and availability
operationId: healthCheck
security: []
responses:
'200':
description: Service is healthy
content:
application/json:
schema:
$ref: '#/components/schemas/HealthResponse'
example:
status: "healthy"
model: "lama"
device: "cuda"
gpu_available: true
/api/v1/stats:
get:
tags:
- Account
summary: Get usage statistics
description: Retrieve account usage statistics including request counts and processing times
operationId: getStats
security:
- ApiKeyAuth: []
responses:
'200':
description: Usage statistics
content:
application/json:
schema:
$ref: '#/components/schemas/StatsResponse'
example:
total: 1250
success: 1230
failed: 20
total_processing_time: 1845.5
avg_processing_time: 1.5
'401':
description: Unauthorized
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
'404':
description: Metrics disabled
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
example:
error: "Not Found"
detail: "Metrics disabled"
status_code: 404
components:
securitySchemes:
ApiKeyAuth:
type: apiKey
in: header
name: X-API-Key
description: |
API key for authentication. Obtain from your dashboard at https://iopaint.com/dashboard
Example: `X-API-Key: sk_live_1234567890abcdef`
schemas:
Error:
type: object
required:
- error
- detail
- status_code
properties:
error:
type: string
description: Error type
example: "Bad Request"
detail:
type: string
description: Human-readable error message
example: "Invalid image format"
status_code:
type: integer
description: HTTP status code
example: 400
HealthResponse:
type: object
required:
- status
- model
- device
- gpu_available
properties:
status:
type: string
enum: [healthy, unhealthy]
description: Service status
example: "healthy"
model:
type: string
description: Current AI model name
example: "lama"
device:
type: string
enum: [cuda, cpu]
description: Compute device
example: "cuda"
gpu_available:
type: boolean
description: GPU availability
example: true
StatsResponse:
type: object
required:
- total
- success
- failed
- total_processing_time
- avg_processing_time
properties:
total:
type: integer
description: Total requests made
example: 1250
minimum: 0
success:
type: integer
description: Successful requests
example: 1230
minimum: 0
failed:
type: integer
description: Failed requests
example: 20
minimum: 0
total_processing_time:
type: number
format: float
description: Cumulative processing time in seconds
example: 1845.5
minimum: 0
avg_processing_time:
type: number
format: float
description: Average processing time in seconds
example: 1.5
minimum: 0
examples:
SuccessfulProcessing:
summary: Successful watermark removal
description: Image processed successfully with processing time
value:
# Binary PNG data returned
# Headers: X-Processing-Time: 1.52, X-Image-Size: 1024x768
InvalidApiKey:
summary: Invalid API key provided
value:
error: "Unauthorized"
detail: "Invalid API Key"
status_code: 401
RateLimitExceeded:
summary: Rate limit exceeded
value:
error: "Too Many Requests"
detail: "Rate limit exceeded. Please try again later."
status_code: 429
x-rate-limits:
- name: Free Plan
limit: 2
period: minute
burst: 5
quota: 10/day
- name: Basic Plan
limit: 10
period: minute
burst: 20
quota: 3000/month
- name: Pro Plan
limit: 30
period: minute
burst: 60
quota: 20000/month
- name: Enterprise Plan
limit: custom
period: custom
burst: custom
quota: custom
x-code-samples:
- lang: cURL
label: cURL
source: |
curl -X POST https://api.iopaint.com/api/v1/remove-watermark \
-H "X-API-Key: $IOPAINT_API_KEY" \
-F "image=@image.jpg" \
-o result.png
- lang: Python
label: Python
source: |
import requests
url = "https://api.iopaint.com/api/v1/remove-watermark"
headers = {"X-API-Key": "your_api_key"}
with open("image.jpg", "rb") as f:
response = requests.post(url, headers=headers, files={"image": f})
if response.status_code == 200:
with open("result.png", "wb") as f:
f.write(response.content)
- lang: JavaScript
label: JavaScript/Node.js
source: |
const FormData = require('form-data');
const fs = require('fs');
const axios = require('axios');
const form = new FormData();
form.append('image', fs.createReadStream('image.jpg'));
axios.post('https://api.iopaint.com/api/v1/remove-watermark', form, {
headers: {
'X-API-Key': process.env.IOPAINT_API_KEY,
...form.getHeaders()
},
responseType: 'arraybuffer'
})
.then(response => {
fs.writeFileSync('result.png', response.data);
});
- lang: PHP
label: PHP
source: |
<?php
$ch = curl_init('https://api.iopaint.com/api/v1/remove-watermark');
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, [
'image' => new CURLFile('image.jpg')
]);
curl_setopt($ch, CURLOPT_HTTPHEADER, [
'X-API-Key: your_api_key'
]);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
$result = curl_exec($ch);
file_put_contents('result.png', $result);
curl_close($ch);
?>
- lang: Go
label: Go
source: |
package main
import (
"bytes"
"io"
"mime/multipart"
"net/http"
"os"
)
func main() {
body := &bytes.Buffer{}
writer := multipart.NewWriter(body)
file, _ := os.Open("image.jpg")
defer file.Close()
part, _ := writer.CreateFormFile("image", "image.jpg")
io.Copy(part, file)
writer.Close()
req, _ := http.NewRequest("POST", "https://api.iopaint.com/api/v1/remove-watermark", body)
req.Header.Set("X-API-Key", os.Getenv("IOPAINT_API_KEY"))
req.Header.Set("Content-Type", writer.FormDataContentType())
client := &http.Client{}
resp, _ := client.Do(req)
defer resp.Body.Close()
out, _ := os.Create("result.png")
defer out.Close()
io.Copy(out, resp.Body)
}