cyberrealisticxlv211

stablediffusionapi
Texto a imagen

modelo de text-to-image basado en Diffusers y StableDiffusionXLPipeline que genera imágenes ultra-realistas.

Como usar

Uso del modelo:

import requests
import json

url = "https://modelslab.com/api/v6/images/text2img"

payload = json.dumps({
"key": "your_api_key",
"model_id": "cyberrealisticxlv211",
"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": "no",
"enhance_prompt": "yes",
"seed": None,
"guidance_scale": 7.5,
"multi_lingual": "no",
"panorama": "no",
"self_attention": "no",
"upscale": "no",
"embeddings": "embeddings_model_id",
"lora": "lora_model_id",
"webhook": None,
"track_id": None
})

headers = {
'Content-Type': 'application/json'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)

Funcionalidades

Generación de imágenes ultra-realistas
Escalabilidad a través de API de inferencia
Soporte para múltiples lenguajes de programación (PHP, Node, Java)
Parametros personalizables como prompt, negative_prompt, ancho, alto, etc.

Casos de uso

Generación de retratos ciberpunk ultrarrealistas
Creación de contenido visual para marketing
Diseño gráfico y arte digital