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Style Changer by ByteDance

bytedance

ByteDance Image Stylization transforms images into stunning artworks with various artistic styles.

Partner Model
Fast Inference
REST API
Try in ConsoleAPI DocsExamples

Model Information

Response Time~5 sec
StatusActive
Version
0.0.1
Updated3 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": "bytedance",
            "version": "0.0.1",
            "input": {
  "style": "anime_style",
  "image_url": "your image url here"
}
        }
    )
    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: ~5 seconds
  • Rate limit: 60 requests/minute
  • Concurrent requests: 10 maximum
  • Use long-polling to check prediction status until completion

Overview

Style Changer by ByteDance image to image model is designed to transform an input image into a new version that follows a selected artistic or stylistic theme. By leveraging advanced image processing techniques, the model can generate a variety of styles, from realistic representations to highly stylized artistic interpretations. Users can provide an input image and choose from a diverse set of predefined styles to obtain a transformed output.

Technical Specifications

  • The Style Changer by ByteDance  supports a wide range of predefined artistic styles.
  • It utilizes an advanced image transformation algorithm to apply the selected style.
  • The transformation process maintains the structure of the original image while modifying textures and colors.
  • Outputs are generated with high fidelity and respect the chosen style parameters.
  • Processing times may vary based on image complexity and selected style.

Key Considerations

  • Some styles may introduce distortions that significantly alter facial features or object proportions.
  • Certain styles are more detailed and may take longer to process.
  • High-contrast images may result in exaggerated transformations depending on the selected style.
  • Some styles are more suitable for specific subjects (e.g., human portraits, landscapes, or objects).
  • If an image does not return the expected results, trying a different style may yield better outcomes.

Tips & Tricks

  • Style Selection:
    • 3D Gaming, Animated Movie: Best suited for characters and fantasy-based transformations.
    • Realistic Style: Maintains a lifelike appearance with slight enhancements.
    • Angel, Princess Style, Dreamy: Ideal for soft, ethereal aesthetics.
    • Anime Style, Japanese Comics, Exquisite Comic: Perfect for anime/manga-inspired results.
    • Cyber Machinery, Chinese Style: Suitable for futuristic or traditional cultural themes.
    • Ink Style, Monet’s Garden, New Monet Garden: Great for artistic and painterly transformations.
    • Ugly Clay, Cute Doll, Doll: Generates exaggerated, playful, or toy-like effects.
  • Image Selection:
    • Use well-lit and high-contrast images for better results.
    • Avoid backgrounds that are too busy or cluttered if the focus is on a single subject.
    • If applying a portrait transformation, ensure the face is clear and well-defined.

Capabilities

  • Style Changer by ByteDance generates high-quality stylized versions of input images.
  • Supports a wide range of artistic transformations.
  • Retains the original composition while altering the aesthetic style.
  • Provides quick and automated style transfer.
  • Suitable for creative projects, artistic experimentation, and digital content creation.

What can I use for?

  • Creating unique profile pictures with artistic styles.
  • Enhancing character designs with specific aesthetics.
  • Generating promotional visuals with customized themes.
  • Producing stylized art pieces for social media or digital portfolios.
  • Experimenting with different art styles for creative inspiration.

Things to be aware of

  • Test various styles to see which one complements the subject best.
  • Apply transformations to landscape photos for unique artistic effects.
  • Use portrait images with different styles to compare the variations in facial detail.
  • Style Changer by ByteDance combines generated images with additional editing for customized results.
  • Explore blending similar styles for a hybrid effect.

Limitations

  • The Style Changer by ByteDance may not always preserve fine details in the original image.
  • Some styles may introduce artifacts or unintended distortions.
  • Complex backgrounds may affect the quality of the stylization.
  • Not all styles work well with all types of images.
  • Style application may result in loss of certain textures or details from the original image.


Output Format:JPG

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