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| import os | |
| import gradio as gr | |
| from scepter.modules.utils.file_system import FS | |
| from huggingface_hub import hf_hub_download | |
| def resolve_hf_path(path): | |
| if isinstance(path, str) and path.startswith("hf://"): | |
| # The expected format is: hf://{repo_id}@{filename} | |
| parts = path[len("hf://"):].split("@") | |
| if len(parts) != 2: | |
| raise ValueError(f"Invalid HF URI format: {path}") | |
| repo_id = parts[0] | |
| filename = parts[1] | |
| print(f"Downloading {filename} from {repo_id} ...") | |
| local_path = hf_hub_download(repo_id=repo_id, filename=filename) | |
| return local_path | |
| return path | |
| os.environ["FLUX_FILL_PATH"] = "hf://black-forest-labs/[email protected]" | |
| os.environ["PORTRAIT_MODEL_PATH"] = "ms://iic/ACE_Plus@portrait/comfyui_portrait_lora64.safetensors" | |
| os.environ["SUBJECT_MODEL_PATH"] = "ms://iic/ACE_Plus@subject/comfyui_subject_lora16.safetensors" | |
| os.environ["LOCAL_MODEL_PATH"] = "ms://iic/ACE_Plus@local_editing/comfyui_local_lora16.safetensors" | |
| os.environ["ACE_PLUS_FFT_MODEL"] = "hf://ali-vilab/ACE_Plus@ace_plus_fft.safetensors" | |
| flux_full = resolve_hf_path(os.environ["FLUX_FILL_PATH"]) | |
| ace_plus_fft_model_path = resolve_hf_path(os.environ["ACE_PLUS_FFT_MODEL"]) | |
| # Update the environment variables with the resolved local file paths. | |
| os.environ["ACE_PLUS_FFT_MODEL"] = ace_plus_fft_model_path | |
| os.environ["FLUX_FILL_PATH"] = flux_full | |
| from inference.ace_plus_inference import ACEInference | |
| from scepter.modules.utils.config import Config | |
| from modules.flux import FluxMRModiACEPlus | |
| from inference.registry import INFERENCES | |
| config_path = os.path.join("config", "ace_plus_fft.yaml") | |
| cfg = Config(load=True, cfg_file=config_path) | |
| # Instantiate the ACEInference object. | |
| ace_infer = ACEInference(cfg) | |
| def face_swap_app(target_img, face_img): | |
| """ | |
| Swaps the face in the target image using the provided face image via ACE++. | |
| Parameters: | |
| target_img: The image in which you want to swap a face. | |
| face_img: The reference face image to insert. | |
| Returns: | |
| The output image after applying ACE++ face swapping. | |
| """ | |
| # For ACEInference, we pass: | |
| # - reference_image: the target image, | |
| # - edit_image: the new face image, | |
| # - edit_mask: set to None so the image processor will create it, | |
| # - prompt: "Face swap" instructs the model to perform face swapping. | |
| # Other parameters (output dimensions, sampler, etc.) are set here as desired. | |
| output_img, edit_image, change_image, mask, seed = ace_infer( | |
| reference_image=target_img, | |
| edit_image=face_img, | |
| edit_mask=None, # No manual mask provided; let ACE++ handle it | |
| prompt="Face swap", | |
| output_height=1024, | |
| output_width=1024, | |
| sampler='flow_euler', | |
| sample_steps=28, | |
| guide_scale=50, | |
| seed=-1 # Use a random seed if not specified | |
| ) | |
| return output_img | |
| # Create the Gradio interface. | |
| iface = gr.Interface( | |
| fn=face_swap_app, | |
| inputs=[ | |
| gr.Image(type="pil", label="Target Image"), | |
| gr.Image(type="pil", label="Face Image") | |
| ], | |
| outputs=gr.Image(type="pil", label="Swapped Face Output"), | |
| title="ACE++ Face Swap Demo", | |
| description="Upload a target image and a face image to swap the face using the ACE++ model." | |
| ) | |
| if __name__ == "__main__": | |
| iface.launch() |