vmodel/Unblur
Image Unblur is an AI-based model designed to remove blur from images and restore clarity to blurry photos.
Input
in_path * image
Input low-quality image
num_steps enum
Number of sampling steps.
chopping_size enum
Chopping resolution
resize int
Reset the longest side of the image to this size (maintain aspect ratio)
Reset
Output
{
  "task_id": "d9zzvghifs95q8fkfd",
  "user_id": 1,
  "version": "55d15b370557b361940034c9f7fb7ede6442f74632be7c3594996fa31b920096",
  "error": null,
  "total_time": 5,
  "predict_time": 5,
  "logs": null,
  "output": [
    "https://data.vmodel.ai/data/model-example/vmodel/unblur/unblur_output.webp"
  ],
  "status": "succeeded",
  "create_at": 1746492954,
  "completed_at": 1746493015,
  "input": {
    "in_path": "https://data.vmodel.ai/data/model-example/vmodel/unblur/image_unblur.jpeg",
    "num_steps": 1,
    "chopping_size": 128
  }
}
Generated in: 5 seconds
Download
Examples
Model Example
Pricing
This model is priced based on a single task.
Output: $0.03986 / use or 25 uses / $1
Readme

Image Unblur API,AI-Powered Image Deblurring API

Overview

The Image Unblur API brings blurry or low-quality images back to life using advanced image restoration techniques. It sharpens details, enhances textures, and reduces blur, helping images look clearer and more natural.

Key Features & Capabilities

  • Advanced Deblurring: Effectively reduces motion blur, focus haze, and softness in low-quality images
  • Customizable Enhancement: Adjust sharpening strength based on the level of blur
  • Smart Resizing: Automatically resizes images while maintaining proportions and avoiding distortion
  • Quick & Efficient: Fast processing with lightweight performance and responsive API
  • Wide Format Support: Works with JPG, PNG, and WEBP files

How to Use the Image Unblur API

1. Prepare Source Image

  • Upload a blurry or soft image
  • Supported formats: JPG, JPEG, PNG, WEBP
  • Max image size: 2048×2048 pixels

2. Configure Unblur Settings

Parameter Type Description Default Options
in_path image Input low-quality image JPG, PNG, WEBP
num_steps enum Number of deblurring steps (higher = stronger deblur) 1 1, 2, 3, 4, 5
chopping_size enum Tiling resolution for internal processing 128 128, 256, 512
resize int Resize the longest side of the image to this pixel size (keep aspect ratio) 1024 Any positive integer

3. Retrieve Enhanced Image

  • The API returns a JSON response containing a URL to the deblurred high-resolution image

Use Cases

1. Old Photo Restoration and Portrait Recovery

“My grandfather's old photo was always blurry,now I can finally see what he really looked like.”

Family keepsakes like old photographs often become blurry over time due to age and the limitations of early cameras. With Image Unblur, we can bring back the facial details in these precious photos and breathe new life into old memories. The Image Unblur API is perfect for digital archiving, creating memory albums, or adding depth to family exhibits,helping us better preserve and cherish those invaluable moments.


2. E-commerce Product Image Enhancement

“After enhancing our product images, they looked much sharper on the homepage and significantly boosted customer clicks.”

On e-commerce platforms, poor image quality can reduce consumer trust. Using the Image Unblur API, you can quickly enhance product photo clarity and showcase finer details. This meets the high visual standards of platforms like Amazon or Shopify and not only draws more attention but also improves conversion rates effectively.


3. Social Media Profile Photo Enhancement

“My selfie was a little blurry, but after enhancing it, it looked sharp and natural on Instagram.”

Your profile picture is often the first impression you make on social media. Whether it's a selfie, casual lifestyle shot, or a formal headshot, Image Unblur can sharpen the image, highlight facial features, and define outlines. The enhanced image is perfect for platforms like LinkedIn, Instagram, or Twitter,helping you appear more professional and make a stronger impression.


Tips for Best Results

  • Use a higher num_steps value for images with severe blur
  • Don't enlarge blurry images before processing, deblurring works best at the original resolution
  • Avoid using highly pixelated or heavily compressed images. Results are best when objects, edges, or faces are still partially clear and recognizable