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