Invert Colors

Invert all colors in an image, creating a negative effect.

Request Parameters

Response

Returns the image with all colors inverted, in the same format as the input file.

Example Request

    curl -X POST "https://oyyi.xyz/api/image/invert"   -H "accept: application/json" \
  -H "Content-Type: multipart/form-data" \
  -F "file=@image.jpg" \
  --output inverted.jpg
  

Example with Python

    import requests

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

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

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

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

Example with JavaScript

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

fetch('https://oyyi.xyz/api/image/invert', {
  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 = 'inverted.jpg';
  a.click();

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

How It Works

The color inversion process works by subtracting each RGB color value from the maximum possible value (255). For each pixel:

R_new = 255 - R_original
G_new = 255 - G_original
B_new = 255 - B_original

This creates a negative effect where light areas become dark and dark areas become light, while colors are transformed to their complementary colors.

Error Responses

Notes

• The inversion applies to all color channels (RGB) but does not affect the alpha channel (transparency) if present.
• Inverting an already inverted image will restore it to its original colors.
• The maximum file size allowed is 10MB.
• This operation is particularly useful for creating artistic effects or improving the visibility of certain features.

Use Cases

• Creating artistic negative effects
• Improving visibility of low-contrast details
• Preparing images for specific scientific or medical analysis
• Creating high-contrast versions of images for accessibility purposes
• Generating complementary color schemes from existing images