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from diffusers import DiffusionPipeline as Pipe
import torch
class Generador:
def img_to_bytes(image) -> bytes:
import io
_imgByteArr = io.BytesIO()
image.save(_imgByteArr, format="png")
return _imgByteArr.getvalue()
def using_runway_sd_15(prompt:str)->bytes:
try:
_generador = Pipe.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16)
_generador.to("cuda")
_imagen = _generador(prompt).images[0]
_response = bytes(Generador.img_to_bytes(image=_imagen))
except Exception as e:
_response = bytes(str(e), 'utf-8')
finally:
return _response
def using_stability_sd_21(prompt:str)->bytes:
try:
_generador = Pipe.from_pretrained("stabilityai/stable-diffusion-2-1", torch_dtype=torch.float16)
_generador.to("cuda")
_imagen = _generador(prompt).images[0]
_response = bytes(Generador.img_to_bytes(image=_imagen))
except Exception as e:
_response = bytes(str(e), 'utf-8')
finally:
return _response
def using_realistic_v14(prompt:str)->bytes:
try:
_generador = Pipe.from_pretrained("SG161222/Realistic_Vision_V1.4", torch_dtype=torch.float16)
_generador.to("cuda")
_imagen = _generador(prompt).images[0]
_response = bytes(Generador.img_to_bytes(image=_imagen))
except Exception as e:
_response = bytes(str(e), 'utf-8')
finally:
return _response
def using_prompthero_openjourney(prompt:str)->bytes:
try:
_generador = Pipe.from_pretrained("prompthero/openjourney", torch_dtype=torch.float16)
_generador.to("cuda")
_imagen = _generador(prompt).images[0]
_response = bytes(Generador.img_to_bytes(image=_imagen))
except Exception as e:
print(e)
_response = bytes(str(e), 'utf-8')
finally:
return _response
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