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Food-Photography

Generated by Image Pipeline

This lora model is uploaded on imagepipeline.io

Model details - Please use this with realistic vision, it only really works with that.

  • use prompt, mine is "RAW photo, Spring Rolls, lora:foodphoto:1 foodphoto, dslr, soft lighting, high quality, film grain, Fujifilm XT"

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How to try this model ?

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

Get your API_KEY from imagepipeline.io. No payment required.

Coding in php javascript node etc ? Checkout our documentation

documentation

import requests  
import json  
  
url =  "https://imagepipeline.io/sd/text2image/v1/run"  
  
payload = json.dumps({  
"model_id":  "sd1.5",  
"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": "7ff920b9-9844-460c-8960-ebbf307ef4b7", 
"lora_weights":  "0.5" 
})  
  
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/sd/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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