Crop Image

Extract a specific rectangular region from an image by specifying coordinates and dimensions.

Request Parameters

Response

Returns the cropped image in the specified or original format.

Example Request

    // example.sh
curl -X POST "https://oyyi.xyz/api/image/crop"   -H "accept: application/json" \
  -H "Content-Type: multipart/form-data" \
  -F "file=@image.jpg" \
  -F "x=100" \
  -F "y=100" \
  -F "width=500" \
  -F "height=300" \
  --output cropped.jpg
  

Example with Python

    // crop.py
import requests

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

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

data = {
    'x': 100,
    'y': 100,
    'width': 500,
    'height': 300
}

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

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

Example with JavaScript

    // crop.js
// Using fetch API
const formData = new FormData();
formData.append('file', fileInput.files[0]);
formData.append('x', '100');
formData.append('y', '100');
formData.append('width', '500');
formData.append('height', '300');

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

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

Coordinate System

(0,0)      (x,y)
  +----------+----------+
  |          |          |
  |          | Crop     |
  |          | Region   |
  +----------+----------+
  |          |          |
  |          |          |
  |          |          |
  +----------+----------+
                        (width-1, height-1)
      

Smart Cropping

How It Works

The crop endpoint extracts a rectangular region from an image:

1. Image Loading: The uploaded image is loaded into memory.
2. Coordinate Validation: The provided coordinates and dimensions are validated to ensure they fall within the image boundaries.
3. Smart Crop (Optional): If smart_crop is enabled, content-aware algorithms analyze the image to identify important features (faces, objects, etc.) and adjust the crop region accordingly.
4. Region Extraction: The specified rectangular region is extracted from the image.
5. Format Conversion: If an output_format is specified, the cropped image is converted to that format.
6. Quality Setting: For lossy formats (JPEG, WebP), the specified quality level is applied.

The result is a new image containing only the specified portion of the original image.

Boundary Handling

Error Responses

Notes

• The coordinate system starts at (0,0) in the top-left corner of the image.
• For precise cropping, it's helpful to know the dimensions of the original image beforehand. You can use the metadata endpoint to get this information.
• Smart cropping is useful for automatically focusing on the important parts of an image, such as faces in portraits or subjects in photographs.
• When cropping transparent images (PNG, WebP), the transparency is preserved in the output if the output format supports it.
• For animated GIFs, only the first frame will be cropped unless the output format is also GIF.
• The maximum file size allowed is 50MB.
• This operation preserves the alpha channel (transparency) if present in the original image and the output format supports it (PNG, WebP, GIF).

Use Cases

• Removing unwanted elements from the edges of an image
• Extracting a specific subject or region of interest
• Creating thumbnails focused on the most important part of an image
• Standardizing image aspect ratios for consistent layouts
• Preparing images for social media platforms with specific dimension requirements
• Removing metadata-containing borders from scanned documents
• Creating detail views of larger images
• Implementing image editing functionality in applications