Image Enhancer

Overview

The Image Enhancer is a powerful AI tool that helps you improve the quality of your photos automatically. It can:

• Make blurry or low-quality images sharper and clearer
• Enhance colors and lighting to make your photos more vibrant
• Improve the overall detail and resolution of your images
• Fix common issues like noise and pixelation

Simply upload your image, and our AI will process it to create a higher quality version. Perfect for improving old photos, social media content, or any image that needs a quality boost!

API Reference

• URL: https://api.maxstudio.ai/image-enhancer
• Method: POST

API Parameters

⚠️ Important: When sending the base64 image, do not include the prefix (e.g., 'data:image/jpeg;base64,'). Send only the raw base64 string.

Header

Code Examples

// TypeScript implementation
interface Params {
  image: string;
}
async function ImageEnhancer(image: string): Promise<any> {
  try {
    const response = await fetch('https://api.maxstudio.ai/image-enhancer', {
      method: 'POST',
      headers: {
        'Content-Type': 'application/json'
      },
      body: JSON.stringify({
        image: image
      })
    });
    const jobId = await response.json();
    return jobId;
  } catch (error) {
    console.error('Error:', error);
    throw error;
  }
}

Success Response

{
  "jobId": "<job_id>"
}

Error Response Examples

// Rate Limit Error
{
  "status": 429,
  "error": "Rate limit exceeded. Please try again later."
}

// Insufficient Credits
{
  "status": 402,
  "error": "Insufficient credits. Please Buy credits."
}

// Invalid Input
{
  "status": 400,
  "error": "Image size must be less than 5MB"
}

Get Job Status

Header

To check the status of your job, use the following examples:

// TypeScript implementation
async function getJobStatus(jobId: string): Promise<any> {
  const url = `https://api.maxstudio.ai/image-enhancer/${jobId}`;
  try {
    const response = await axios.get(url);
    const jobId = await response.json();
    return jobId;
  } catch (error) {
    console.error('Error:', error);
    throw error;
  }
}

Job Status Reference

Output

{
  "status": "<status>",  // One of the status values from the table above
  "result": "<result>"   // Base64 encoded image data when status is 'completed'
}