API
If you're looking for an API, you can choose from your desired programming language.
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import requests
import base64
# Use this function to convert an image file from the filesystem to base64
def image_file_to_base64(image_path):
with open(image_path, 'rb') as f:
image_data = f.read()
return base64.b64encode(image_data).decode('utf-8')
# Use this function to fetch an image from a URL and convert it to base64
def image_url_to_base64(image_url):
response = requests.get(image_url)
image_data = response.content
return base64.b64encode(image_data).decode('utf-8')
api_key = "YOUR_API_KEY"
url = "https://api.segmind.com/v1/ssd-img2img"
# Request payload
data = {
"image": image_url_to_base64("https://segmind-sd-models.s3.amazonaws.com/outputs/ssd_img2img_input.jpeg"), # Or use image_file_to_base64("IMAGE_PATH")
"prompt": "photo of beautiful age 18 girl, pink hair, beautiful, close up, young, dslr, 8k, 4k, ultrarealistic, realistic, natural skin, textured skin",
"negative_prompt": "painting, drawing, sketch, cartoon, anime, manga, render, CG, 3d, watermark, signature, label, long neck",
"samples": 1,
"scheduler": "Euler a",
"num_inference_steps": 30,
"guidance_scale": 7.5,
"seed": 452361789,
"strength": 0.9,
"base64": False
}
headers = {'x-api-key': api_key}
response = requests.post(url, json=data, headers=headers)
print(response.content) # The response is the generated imageAttributes
Input Image
Prompt to render
Prompts to exclude, eg. 'bad anatomy, bad hands, missing fingers'
Number of samples to generate.
min : 1,
max : 4
Type of scheduler.
Allowed values:
Number of denoising steps.
min : 20,
max : 100
Scale for classifier-free guidance
min : 1,
max : 25
Seed for image generation.
min : -1,
max : 999999999999999
Scale for classifier-free guidance
min : 0,
max : 0.99
Base64 encoding of the output image.
To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.
PixelFlow allows you to use all these features
Unlock the full potential of generative AI with Segmind. Create stunning visuals and innovative designs with total creative control. Take advantage of powerful development tools to automate processes and models, elevating your creative workflow.
Segmented Creation Workflow
Gain greater control by dividing the creative process into distinct steps, refining each phase.
Customized Output
Customize at various stages, from initial generation to final adjustments, ensuring tailored creative outputs.
Layering Different Models
Integrate and utilize multiple models simultaneously, producing complex and polished creative results.
Workflow APIs
Deploy Pixelflows as APIs quickly, without server setup, ensuring scalability and efficiency.
Segmind Stable Diffusion 1B (SSD-1B) Img2Img
Segmind Stable Diffusion 1B (SSD-1B) Img2Img is a cutting-edge AI model that is reshaping the landscape of image-to-image transformations. Leveraging advanced machine learning techniques, SSD-1B excels at converting conceptual prompts into vivid visuals, refining images, and facilitating seamless image translations guided by nuanced text inputs. It stands as a pivotal tool for creatives, marketers, and software developers who are looking to break new ground in the realm of visual content creation.
At the core of SSD-1B Img2Img is a sophisticated algorithm adept at intricate visual content manipulation. With the ability to take an existing image and, through text-driven prompts, transform it into a new piece that resonates with the creator's intent, the modle shines in performing style transfers, enhancing details, and altering subjects while preserving the essence of the original image.
Advantages
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Text-Directed Transformation: Employs text prompts to direct the transformation process, aligning the output closely with the creator's objectives .
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Fluid Style Adaptation:Capably adjusts the style from one image to another, ensuring transitions are coherent and purposeful.
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Enhanced Detailing:Elevates the intricacies within images, enhancing definition and vibrancy.
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Expansive Creative Range: Provides a broad spectrum of creative possibilities, ranging from nuanced tweaks to complete conceptual overhauls.
Use Cases
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Creative Artwork: Enables artists to push the boundaries of their work, exploring new styles and themes effortlessly.
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Marketing Material: Assists marketers in crafting images that are in sync with brand stories, maintaining uniformity across all visual communications.
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Product Design: Allows designers to swiftly generate multiple product iterations, accelerating the design process.
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Entertainment Media: Supports content creators in the entertainment sector to adjust and refine visual elements to match dynamic narratives.
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Educational Tools: Aids educators in developing bespoke visual aids that enhance the learning experience for complex subjects.
Other Popular Models
sdxl-img2img
SDXL Img2Img is used for text-guided image-to-image translation. This model uses the weights from Stable Diffusion to generate new images from an input image using StableDiffusionImg2ImgPipeline from diffusers
sdxl-inpaint
This model is capable of generating photo-realistic images given any text input, with the extra capability of inpainting the pictures by using a mask
codeformer
CodeFormer is a robust face restoration algorithm for old photos or AI-generated faces.
sd2.1-faceswapper
Take a picture/gif and replace the face in it with a face of your choice. You only need one image of the desired face. No dataset, no training
