Apply Blur

Apply a Gaussian blur effect to images with adjustable intensity.

Request Parameters

Response

Returns the blurred image in the same format as the input file.

Example Request

    // example.sh
curl -X POST "https://oyyi.xyz/api/image/blur"   -H "accept: application/json" \
  -H "Content-Type: multipart/form-data" \
  -F "file=@image.jpg" \
  -F "intensity=5" \
  --output blurred.jpg
  

Example with Python

    // blur.py
import requests

url = "https://oyyi.xyz/api/image/blur"

files = {
    'file': open('image.jpg', 'rb')
}

data = {
    'intensity': 5
}

response = requests.post(url, files=files, data=data)

# Save the blurred image
with open('blurred.jpg', 'wb') as f:
    f.write(response.content)
  

Example with JavaScript

    // blur.js
// Using fetch API
const formData = new FormData();
formData.append('file', fileInput.files[0]);
formData.append('intensity', '5');

fetch('https://oyyi.xyz/api/image/blur', {
  method: 'POST',
  body: formData
})
.then(response => response.blob())
.then(blob => {
  // Create a URL for the blob
  const url = URL.createObjectURL(blob);

  // Create a link to download the image
  const a = document.createElement('a');
  a.href = url;
  a.download = 'blurred.jpg';
  a.click();

  // Clean up by revoking the URL
  URL.revokeObjectURL(url);
})
.catch(error => console.error('Error:', error));
  

Blur Methods

Blur Intensity Examples

How It Works

The blur effect works by averaging pixel values with their neighbors:

• Gaussian blur: Applies a weighted average where closer pixels have more influence than distant ones, based on a Gaussian distribution.
• Box blur: Applies a simple average of all pixels in a square area around each pixel.
• Median blur: Replaces each pixel with the median value of all pixels in a square area around it.

The intensity parameter controls the size of the area considered for each pixel. Higher values include more distant pixels, creating a stronger blur effect.

Error Responses

Notes

• The blur effect is applied to all color channels (RGB) but does not affect the alpha channel (transparency) if present.
• Higher intensity values will result in longer processing times, especially for large images.
• The maximum file size allowed is 10MB.
• Gaussian blur provides the most natural-looking results but is more computationally intensive than box blur.
• Median blur is particularly effective for removing salt-and-pepper noise from images.

Use Cases

• Softening backgrounds to make foreground subjects stand out
• Creating a depth-of-field effect
• Reducing noise in images
• Creating a dreamy or ethereal look
• Protecting sensitive information by blurring it out
• Preparing images for overlaying text or graphics