| import torch | |
| from diffsynth.pipelines.flux_image_new import FluxImagePipeline, ModelConfig, ControlNetInput | |
| from PIL import Image | |
| pipe = FluxImagePipeline.from_pretrained( | |
| torch_dtype=torch.bfloat16, | |
| device="cuda", | |
| model_configs=[ | |
| ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="flux1-dev.safetensors"), | |
| ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder/model.safetensors"), | |
| ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder_2/"), | |
| ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors"), | |
| ModelConfig(model_id="ByteDance/InfiniteYou", origin_file_pattern="infu_flux_v1.0/aes_stage2/image_proj_model.bin"), | |
| ModelConfig(model_id="ByteDance/InfiniteYou", origin_file_pattern="infu_flux_v1.0/aes_stage2/InfuseNetModel/*.safetensors"), | |
| ], | |
| ) | |
| pipe.load_lora(pipe.dit, "models/train/FLUX.1-dev-InfiniteYou_lora/epoch-4.safetensors", alpha=1) | |
| image = pipe( | |
| prompt="a man with a red hat", | |
| controlnet_inputs=[ControlNetInput( | |
| image=Image.open("data/example_image_dataset/infiniteyou/image_1.jpg"), | |
| )], | |
| height=1024, width=1024, | |
| seed=0, rand_device="cuda", | |
| ) | |
| image.save("image_FLUX.1-dev-InfiniteYou_lora.jpg") | |