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from diffusers import DiffusionPipeline as Pipe
import torch
class Generador:
def using_runway_sd_15(prompt:str)->list:
try:
_generador = Pipe.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16)
_generador.to("cuda")
_imagen = _generador(prompt).images[0]
_response = list(_imagen.getdata())
except Exception as e:
_response = list(str(e))
finally:
return _response
def using_stability_sd_21(prompt:str)->list:
try:
_generador = Pipe.from_pretrained("stabilityai/stable-diffusion-2-1", torch_dtype=torch.float16)
_generador.to("cuda")
_imagen = _generador(prompt).images[0]
_response = list(_imagen.getdata())
except Exception as e:
_response = list(str(e))
finally:
return _response
def using_realistic_v14(prompt:str)->list:
try:
_generador = Pipe.from_pretrained("SG161222/Realistic_Vision_V1.4", torch_dtype=torch.float16)
_generador.to("cuda")
_imagen = _generador(prompt).images[0]
_response = list(_imagen.getdata())
except Exception as e:
_response = list(str(e))
finally:
return _response
def using_prompthero_openjourney(prompt:str)->list:
try:
_generador = Pipe.from_pretrained("prompthero/openjourney", torch_dtype=torch.float16)
_generador.to("cuda")
_imagen = _generador(prompt).images[0]
_response = list(_imagen.getdata())
except Exception as e:
_response = list(str(e))
finally:
return _response
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