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Realistic-Stock-Photo

Generated on Image Pipeline

This checkpoint model is uploaded on imagepipeline.io

Model details - I trained a model and merge it a bit with version 1. I wanted to create a realistic skin texture without that typical glossy skin effect. A good prompt for this model is phone photo of ..... uploaded on snapchat Negative Prompt: (watermark:1.2), (text:1.2), (logo:1.2), (3d render:1.2), drawing, painting, crayon CFG scale is 3-5 for the prompt, minimum resolution is 1024x1024 obviously

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You can try using it locally or send an API call to test the output quality.

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import requests  
import json  
  
url =  "https://imagepipeline.io/sdxl/text2image/v1/run"  
  
payload = json.dumps({  
"model_id":  "c3b4f858-9c9e-4907-a1f5-f94e28d170ee",  
"prompt":  "ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner)), blue eyes, shaved side haircut, hyper detail, cinematic lighting, magic neon, dark red city, Canon EOS R3, nikon, f/1.4, ISO 200, 1/160s, 8K, RAW, unedited, symmetrical balance, in-frame, 8K",  
"negative_prompt":  "painting, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, ugly, blurry, bad anatomy, bad proportions, extra limbs, cloned face, skinny, glitchy, double torso, extra arms, extra hands, mangled fingers, missing lips, ugly face, distorted face, extra legs, anime",  
"width":  "512",  
"height":  "512",  
"samples":  "1",  
"num_inference_steps":  "30",  
"safety_checker":  false,   
"guidance_scale":  7.5,  
"multi_lingual":  "no",  
"embeddings":  "", 
"lora_models": "", 
"lora_weights":  "" 
})  
  
headers =  {  
'Content-Type':  'application/json',
'API-Key': 'your_api_key'
}  
  
response = requests.request("POST", url, headers=headers, data=payload)  
  
print(response.text)

}

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API Reference

Generate Image

  https://api.imagepipeline.io/sdxl/text2image/v1
Headers Type Description
API-Key str Get your API_KEY from imagepipeline.io
Content-Type str application/json - content type of the request body
Parameter Type Description
model_id str Your base model, find available lists in models page or upload your own
prompt str Text Prompt. Check our Prompt Guide for tips
num_inference_steps int [1-50] Noise is removed with each step, resulting in a higher-quality image over time. Ideal value 30-50 (without LCM)
guidance_scale float [1-20] Higher guidance scale prioritizes text prompt relevance but sacrifices image quality. Ideal value 7.5-12.5
lora_models str, array Pass the model_id(s) of LoRA models that can be found in models page
lora_weights str, array Strength of the LoRA effect

license: creativeml-openrail-m tags:

  • imagepipeline
  • imagepipeline.io
  • text-to-image
  • ultra-realistic pinned: false pipeline_tag: text-to-image

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