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Recraft Creative Upscale

recraft-creative-upscale

Recraft Upscale specializes in enhancing image details and refining intricate elements. It goes beyond simply increasing resolution, adding depth by improving textures, fine details, and facial features.

Fast Inference
REST API
Try in ConsoleAPI DocsExamples

Model Information

Response Time~70 sec
StatusActive
Version
0.0.1
Updated26 days ago
API Reference
View Full Documentation

Prerequisites

  • Create an API Key from the Eachlabs Console
  • Install the required dependencies for your chosen language (e.g., requests for Python)

API Integration Steps

1. Create a Prediction

Send a POST request to create a new prediction. This will return a prediction ID that you'll use to check the result. The request should include your model inputs and API key.

import requests
import time


API_KEY = "YOUR_API_KEY"  # Replace with your API key
HEADERS = {
    "X-API-Key": API_KEY,
    "Content-Type": "application/json"
}


def create_prediction():
    response = requests.post(
        "https://api.eachlabs.ai/v1/prediction/",
        headers=HEADERS,
        json={
            "model": "recraft-creative-upscale",
            "version": "0.0.1",
            "input": {
  "image": "your_file.image/jpeg"
}
        }
    )
    prediction = response.json()
    
    if prediction["status"] != "success":
        raise Exception(f"Prediction failed: {prediction}")
    
    return prediction["predictionID"]

2. Get Prediction Result

Poll the prediction endpoint with the prediction ID until the result is ready. The API uses long-polling, so you'll need to repeatedly check until you receive a success status.

def get_prediction(prediction_id):
    while True:
        result = requests.get(
            f"https://api.eachlabs.ai/v1/prediction/{prediction_id}",
            headers=HEADERS
        ).json()
        
        if result["status"] == "success":
            return result
        elif result["status"] == "error":
            raise Exception(f"Prediction failed: {result}")
        
        time.sleep(1)  # Wait before polling again

3. Complete Example

Here's a complete example that puts it all together, including error handling and result processing. This shows how to create a prediction and wait for the result in a production environment.

try:
    # Create prediction
    prediction_id = create_prediction()
    print(f"Prediction created: {prediction_id}")
    
    # Get result
    result = get_prediction(prediction_id)
    print(f"Output URL: {result['output']}")
    print(f"Processing time: {result['metrics']['predict_time']}s")
except Exception as e:
    print(f"Error: {e}")

Additional Information

  • The API uses a two-step process: create prediction and poll for results
  • Response time: ~70 seconds
  • Rate limit: 60 requests/minute
  • Concurrent requests: 10 maximum
  • Use long-polling to check prediction status until completion

Overview

Recraft Creative Upscale is a model designed to enhance image resolution while preserving details and improving clarity. It is ideal for refining artwork, upscaling low-resolution images, and improving image quality without introducing excessive artifacts. This model ensures that images remain sharp and natural, making it particularly useful for creative projects that require high-quality visuals.

Technical Specifications

  • Input Type: Image
  • Output: High-resolution upscaled version of the input image.
  • Processing: AI-based upscaling using deep learning techniques.
  • Enhancement Focus: Detail preservation, clarity improvement, and artifact reduction.

Key Considerations

  • The Recraft Creative Upscale may not significantly enhance images that are extremely blurry or pixelated.
  • Upscaling performance varies depending on the input image’s original quality and resolution.
  • The Recraft Creative Upscale does not perform color correction or artistic modifications.
  • Overly compressed images with heavy artifacts may not yield optimal results.


Legal Information for Recraft CREATIVE UPSCALE

By using this model, you agree to:

Tips & Tricks

  • Use high-quality input images: Images with good contrast and sharpness produce the best upscaling results.
  • Avoid noisy images: Too much noise in an image may be amplified during upscaling.
  • Pre-process images if necessary: Slight sharpening or noise reduction before upscaling can enhance results.

Capabilities

  • Increases image resolution while maintaining sharpness.
  • Reduces pixelation and enhances fine details.
  • Preserves artistic integrity without adding unwanted artifacts.
  • Works well with digital artwork, photographs, and AI-generated images.

What can I use for?

  • Enhancing digital art to make it suitable for larger prints or displays.
  • Upscaling low-resolution images for better presentation in portfolios or social media.
  • Improving AI-generated images to refine textures and details.
  • Restoring old or compressed images by increasing clarity and reducing noise.

Things to be aware of

  • Upscale a hand-drawn sketch to refine line quality and remove pixelation.
  • Enhance an AI-generated image to make it more detailed and high-quality.
  • Improve the resolution of a digital painting to prepare it for large-scale printing.
  • Upscale a vintage photograph to restore details and improve clarity.

Limitations

  • Cannot generate missing details from highly pixelated images with Recraft.
  • May not effectively enhance very dark or low-contrast images.
  • Does not provide manual control over enhancement levels.
  • Fine textures may sometimes be over-smoothed or slightly altered.

Output Format: WEBP

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