DreamShaper-8 LCM API

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DreamShaper-8-lcm API unlocks the transformative power of advanced AI technology for high-quality AI art image generation and manipulation. Tailored for photorealism while preserving diversity, this API, fine-tuned on the SD1.5 base model, draws on diverse, high-resolution image datasets to ensure rich visual output. Through meticulous adjustment of model parameters and loss functions, DreamShaper-8-lcm API optimizes perceptual similarity, structural integrity, and color fidelity. Whether crafting lifelike scenes or exploring imaginative realms, developers can rely on this API to seamlessly integrate state-of-the-art image generation capabilities into their applications. Users of the DreamShaper-8-lcm API can embark on creative journeys confidently, leveraging its unmatched ability to imbue digital canvases with stunning realism and diversity, akin to the capabilities of the SD3 API. With the upcoming DreamShaper XL model, even more advanced AI models for image generation are on the horizon.

Input

POST https://gateway.appypie.com/dreamshaper/v1/getDreamshaperImageStream HTTP/1.1

Content-Type: application/json
Cache-Control: no-cache

{
    "prompt": "Image of Bird"
}

import urllib.request, json

try:
    url = "https://gateway.appypie.com/dreamshaper/v1/getDreamshaperImageStream"

    hdr ={
    # Request headers
    'Content-Type': 'application/json',
    'Cache-Control': 'no-cache',
    }

    # Request body
    data =  
    data = json.dumps(data)
    req = urllib.request.Request(url, headers=hdr, data = bytes(data.encode("utf-8")))

    req.get_method = lambda: 'POST'
    response = urllib.request.urlopen(req)
    print(response.getcode())
    print(response.read())
    except Exception as e:
    print(e)

// Request body
const body = {
    "prompt": "Image of Bird"
};

fetch('https://gateway.appypie.com/dreamshaper/v1/getDreamshaperImageStream', {
        method: 'POST',
        body: JSON.stringify(body),
        // Request headers
        headers: {
            'Content-Type': 'application/json',
            'Cache-Control': 'no-cache',}
    })
    .then(response => {
        console.log(response.status);
        console.log(response.text());
    })
    .catch(err => console.error(err));

curl -v -X POST "https://gateway.appypie.com/dreamshaper/v1/getDreamshaperImageStream" -H "Content-Type: application/json" -H "Cache-Control: no-cache" --data-raw "{
    \"prompt\": \"Image of Bird\"
}"

import java.io.BufferedReader;
import java.io.InputStreamReader;
import java.net.HttpURLConnection;
import java.net.URL;
import java.net.URLEncoder;
import java.util.HashMap;
import java.util.Map;
import java.io.UnsupportedEncodingException;
import java.io.DataInputStream;
import java.io.InputStream;
import java.io.FileInputStream;

public class HelloWorld {

  public static void main(String[] args) {
    try {
        String urlString = "https://gateway.appypie.com/dreamshaper/v1/getDreamshaperImageStream";
        URL url = new URL(urlString);
        HttpURLConnection connection = (HttpURLConnection) url.openConnection();

        //Request headers
    connection.setRequestProperty("Content-Type", "application/json");
    
    connection.setRequestProperty("Cache-Control", "no-cache");
    
        connection.setRequestMethod("POST");

        // Request body
        connection.setDoOutput(true);
        connection
            .getOutputStream()
            .write(
             "{ \"prompt\": \"Image of Bird\" }".getBytes()
             );
    
        int status = connection.getResponseCode();
        System.out.println(status);

        BufferedReader in = new BufferedReader(
            new InputStreamReader(connection.getInputStream())
        );
        String inputLine;
        StringBuffer content = new StringBuffer();
        while ((inputLine = in.readLine()) != null) {
            content.append(inputLine);
        }
        in.close();
        System.out.println(content);

        connection.disconnect();
    } catch (Exception ex) {
      System.out.print("exception:" + ex.getMessage());
    }
  }
}

$url = "https://gateway.appypie.com/dreamshaper/v1/getDreamshaperImageStream";
$curl = curl_init($url);

curl_setopt($curl, CURLOPT_CUSTOMREQUEST, "POST");
curl_setopt($curl, CURLOPT_URL, $url);
curl_setopt($curl, CURLOPT_RETURNTRANSFER, true);

# Request headers
$headers = array(
    'Content-Type: application/json',
    'Cache-Control: no-cache',);
curl_setopt($curl, CURLOPT_HTTPHEADER, $headers);

# Request body
$request_body = '{
    "prompt": "Image of Bird"
}';
curl_setopt($curl, CURLOPT_POSTFIELDS, $request_body);

$resp = curl_exec($curl);
curl_close($curl);
var_dump($resp);

Output

Try it out

DreamShaper-8 LCM API Documentation
API Parameters

The API POST-https://gateway.appypie.com/dreamshaper/v1/getDreamshaperImage takes the following parameters:

prompt

string, required

negative_prompt

string, optional

response_format

JavaScript Object Notation (JSON)

size

string, optional, default: 1024x1024

Integration and Implementation

To use the DreamShaper-8 LCM API, developers must make POST requests to the specified endpoint with the appropriate headers and request body. The request body should include the text prompt and any optional parameters such as negative prompts and image size.

Base URL

https://gateway.appypie.com/dreamshaper/v1/getDreamshaperImage

Endpoints

POST /getImage

This endpoint generates and modifies images based on the text prompts.

Request
- URL: https://endpoints.appypie.com/api-details#api=dreamshaper-8-lcm&operation=get-image-stream
- Method: POST
- Headers:
  - Content-Type: application/json
  - Cache-Control: no-cache
  - Ocp-Apim-Subscription-Key: {subscription_key}
- Body:
  JSON
```
{
  "prompt": "Image of Bird"
}
```

Responses

HTTP Status Codes:

200 OK: The request was successful, and the generated image is included in the response body.
400 Bad Request: The request must be corrected or include some arguments.
401 Unauthorized: The API key provided in the header is invalid.
500 Internal Server Error: An error occurred on the server while processing the request.

Sample Response:

JSON

{
  "status": 200,
  "content-type": "image/png",
  "content-length": "size_in_bytes",
  "image_data": "base64_encoded_image_data"
}

POST /Get image stream

This endpoint generates images based on the provided prompts.

Request

URL: https://gateway.appypie.com/dreamshaper/v1/getDreamshaperImage
Method: POST
Headers:
- Content-Type: application/json
- Cache-Control: no-cache
- Ocp-Apim-Subscription-Key: {subscription_key}

Body:

JSON

{
    "prompt": "image of bird",
    "System prompt": "You are supposed to be the best image generator."
}

Error Handling

The DreamShaper-8 LCM API provides comprehensive error handling to ensure smooth operation. Common status codes include:

Error Field Contract:

code: An integer that indicates the HTTP status code (e.g., 400, 401, 500).
message: A clear and concise description of what the error is about.
traceId: A unique identifier that can be used to trace the request in case of an issue.

Get Started with API

Overview of the DreamShaper-8 LCM Model

The DreamShaper-8 LCM API harnesses the power of advanced AI technology for high-quality AI art image generation and manipulation. This API is meticulously fine-tuned on the SD1.5 base model and draws on diverse, high-resolution image datasets to ensure rich visual output. Through precise adjustments of model parameters and loss functions, the DreamShaper-8 LCM API optimizes perceptual similarity, structural integrity, and color fidelity, making it a powerful tool for creating realistic images and diverse art styles.

The DreamShaper-8 LCM model is adept at generating both higher-resolution and lower-resolution images, catering to various user needs. It supports anime-style images and anime-style characters, enhancing its versatility. Developers can use this API to integrate state-of-the-art image generation capabilities into their applications seamlessly. The DreamShaper-8 LCM API also allows for customization of the caption style, enabling users to add context to their generated images effortlessly.

In addition to its core functionalities, the DreamShaper-8 LCM model includes Inpainting models and utilizes the Stable Diffusion Checkpoint to improve the quality and consistency of the output. These features make the DreamShaper-8 LCM API an indispensable tool for AI image generation. It supports advanced machine learning techniques and accepts text prompts to generate images, making it suitable for various applications. The API's checkpoint models and the Inpainting version further extend its capabilities, allowing for sophisticated image edits and refinements.

Users of the DreamShaper-8 LCM API can confidently embark on creative journeys, leveraging its unmatched ability to imbue digital canvases with stunning realism and diversity. As part of the Stability AI ecosystem, the DreamShaper-8 LCM model continues to evolve, with the upcoming DreamShaper XL model promising even more advanced AI techniques for image generation. Whether you need to create realistic images, explore various art styles, or generate anime-style characters, the DreamShaper-8 LCM API is your go-to solution for cutting-edge AI-powered artistry.

Use Cases of DreamShaper-8 LCM API

Text-to-Image Generation: The API can be used to generate high-quality images from text prompts, making it suitable for applications such as image description, image captioning, and image generation from text. This use case emphasizes the text-to-image generation capability, allowing users to create images based on detailed descriptions.
Image Manipulation: The API supports image manipulation tasks such as inpainting, which allows for the seamless removal of objects or regions from images. This feature is useful for applications like image editing, image restoration, and image enhancement, providing a high degree of control over the illustration style.
Stable Diffusion Animation: The DreamShaper-8 LCM API can be used to create animations with a stable diffusion effect, resulting in smooth and seamless transitions between frames. This feature is particularly useful for applications like video production, animation, and visual effects. The Realistic Vision technology ensures animations maintain high detail and photorealism.
Anime-Style Image Generation: The API can generate anime images with high detail and photorealism, making it suitable for applications like anime and manga creation, character design, and illustration. Leveraging the Anime model, users can achieve an authentic anime image look.
Realistic Image Generation: The API can generate realistic images with high photorealism and detail, making it suitable for applications like image generation for advertising, product visualization, and architectural visualization. This feature is part of the Key Features of the API, ensuring that Generative AI provides results that meet professional standards.
Image Generation for AI Models: The API can be used to generate images for training and testing AI models, making it suitable for applications like AI model development, AI model testing, and AI model deployment. This use case highlights the importance of high-quality image data for AI research and development.
Image Generation for Web Applications: The API can be used to generate images for web applications, making it suitable for applications like web design, web development, and web content creation. This includes generating images that can be placed at the bottom right of web pages for added visual appeal.
Image Generation for Mobile Applications: The API can be used to generate images for mobile applications, making it suitable for applications like mobile game development, mobile app development, and mobile content creation. Mobile developers can benefit from the exclusive tips provided by the API for optimizing images for mobile displays.
Image Generation for Virtual Reality (VR) and Augmented Reality (AR): The API can be used to generate images for VR and AR applications, making it suitable for applications like VR and AR development, VR and AR content creation, and VR and AR deployment. The Results of version updates ensure that the generated images are compatible with VR and AR environments.
Image Generation for Artificial Intelligence (AI) Research: The API can be used to generate images for AI research, making it suitable for applications like AI research, AI development, and AI deployment. Researchers can utilize the API for generating datasets and conducting experiments.