Imagen 3

imagen-3

Google's highest quality text-to-image model, Imagen-3 is capable of generating images with detail, rich lighting and beauty

Fast Inference

REST API

Try in Console API Docs Examples

Model Information

Response Time~15 sec

StatusActive

Version

0.0.1

Updated9 days ago

Live Demo

Average runtime: ~15 seconds

Input

Configure model parameters

Negative Prompt

Text prompt for what to discourage in the generated images

Enter your negative prompt

Prompt

Text prompt for image generation

A portrait of an Asian man with neon green lights in the background, shallow depth of field

aspect_ratio

An enumeration.

safety_filter_level

An enumeration.

Output

View generated results

Result

Preview, share or download your results with a single click.

Each execution costs $0.055 With $1 you can run this model about 18 times.

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": "imagen-3",
            "version": "0.0.1",
            "input": {
  "prompt": "your prompt here",
  "aspect_ratio": "1:1",
  "negative_prompt": "your negative prompt here",
  "safety_filter_level": "block_medium_and_above"
}
        }
    )
    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: ~15 seconds
Rate limit: 60 requests/minute
Concurrent requests: 10 maximum
Use long-polling to check prediction status until completion

Overview

Imagen 3 is a text-to-image generative model developed by Google Deepmind to produce high-quality images from textual descriptions. It excels in understanding natural language prompts and generating images with enhanced detail, lighting, and reduced artifacts. The Imagen 3 supports various artistic styles, ranging from photorealism to abstract art.

Technical Specifications

Architecture: Imagen 3 employs a latent diffusion model, enabling efficient and high-quality image generation from text prompts.
Training Data: The Imagen 3 is trained on a diverse dataset comprising various image styles and subjects, enhancing its ability to generate a wide range of visuals.
Resolution: Capable of producing images with high resolution, capturing fine details and textures.
Language Understanding: Enhanced natural language processing allows for better comprehension of complex prompts, resulting in more accurate image representations.

Key Considerations

Content Sensitivity: While the Imagen 3 includes safety filters, always review generated images to ensure they meet content standards, especially in sensitive contexts.

Prompt Specificity: Overly complex or ambiguous prompts may lead to unexpected results. Strive for clarity and specificity in your descriptions.

Legal Information for Imagen 3

By using this Imagen 3, you agree to:

Google DeepMind Privacy
Google DeepMind TERMS

Tips & Tricks

Optimizing Prompts for Imagen 3:

Clarity: Use clear and concise language to describe the desired image.
Detail: Incorporate specific details such as colors, lighting, and composition to guide Imagen 3.
Style Specification: Mention the desired artistic style (e.g., "watercolor painting," "digital art") to influence the output.

Negative Prompt Usage:

Exclusion: Clearly state elements to avoid in the negative_prompt to prevent their inclusion.
Testing: Experiment with different negative prompts to see their impact on the generated image.

Aspect Ratio Selection:

Purpose Alignment: Choose an aspect ratio that fits the intended use of the image (e.g., 16:9 for widescreen displays).
Consistency: Maintain consistent aspect ratios when generating images for a cohesive look.

Safety Filter Configuration:

Contextual Adjustment: Set the safety_filter_level based on the context and audience of the images.
Review: Even with filters, always review images to ensure appropriateness.

Capabilities

Diverse Style Generation: Produces images across various styles, including photorealistic, illustrative, and abstract art.

High-Resolution Output: Generates detailed images suitable for professional and creative use cases.

Natural Language Comprehension: Understands and interprets detailed textual descriptions to create corresponding visuals.

What can I use for?

Creative Design: Assists artists and designers in visualizing concepts and generating inspiration.

Marketing Materials: Generates visuals for advertising, social media, and promotional content.

Educational Resources: Creates illustrative content to support learning materials and presentations.

Things to be aware of

Style Exploration: Experiment with different artistic styles by specifying them in your prompts.

Detail Variation: Adjust the level of detail in prompts to see how Imagen 3 interprets and represents various complexities.

Negative Prompt Testing: Use the negative_prompt to refine images by excluding certain elements and observe the changes.

Limitations

Complex Scenes: Imagen 3 may struggle with highly complex scenes involving numerous interacting elements.

Text Generation: Rendering legible text within images can be challenging and may not always be accurate.

Abstract Concepts: Interpreting and visualizing highly abstract or conceptual prompts may lead to unpredictable results.

Output Format: PNG

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